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Sample records for tensor imaging gdti

  1. The direct tensor solution and higher-order acquisition schemes for generalized diffusion tensor imaging

    NARCIS (Netherlands)

    Akkerman, Erik M.

    2010-01-01

    Both in diffusion tensor imaging (DTI) and in generalized diffusion tensor imaging (GDTI) the relation between the diffusion tensor and the measured apparent diffusion coefficients is given by a tensorial equation, which needs to be inverted in order to solve the diffusion tensor. The traditional

  2. Fast and Analytical EAP Approximation from a 4th-Order Tensor.

    Science.gov (United States)

    Ghosh, Aurobrata; Deriche, Rachid

    2012-01-01

    Generalized diffusion tensor imaging (GDTI) was developed to model complex apparent diffusivity coefficient (ADC) using higher-order tensors (HOTs) and to overcome the inherent single-peak shortcoming of DTI. However, the geometry of a complex ADC profile does not correspond to the underlying structure of fibers. This tissue geometry can be inferred from the shape of the ensemble average propagator (EAP). Though interesting methods for estimating a positive ADC using 4th-order diffusion tensors were developed, GDTI in general was overtaken by other approaches, for example, the orientation distribution function (ODF), since it is considerably difficult to recuperate the EAP from a HOT model of the ADC in GDTI. In this paper, we present a novel closed-form approximation of the EAP using Hermite polynomials from a modified HOT model of the original GDTI-ADC. Since the solution is analytical, it is fast, differentiable, and the approximation converges well to the true EAP. This method also makes the effort of computing a positive ADC worthwhile, since now both the ADC and the EAP can be used and have closed forms. We demonstrate our approach with 4th-order tensors on synthetic data and in vivo human data.

  3. Fast and Analytical EAP Approximation from a 4th-Order Tensor

    Directory of Open Access Journals (Sweden)

    Aurobrata Ghosh

    2012-01-01

    Full Text Available Generalized diffusion tensor imaging (GDTI was developed to model complex apparent diffusivity coefficient (ADC using higher-order tensors (HOTs and to overcome the inherent single-peak shortcoming of DTI. However, the geometry of a complex ADC profile does not correspond to the underlying structure of fibers. This tissue geometry can be inferred from the shape of the ensemble average propagator (EAP. Though interesting methods for estimating a positive ADC using 4th-order diffusion tensors were developed, GDTI in general was overtaken by other approaches, for example, the orientation distribution function (ODF, since it is considerably difficult to recuperate the EAP from a HOT model of the ADC in GDTI. In this paper, we present a novel closed-form approximation of the EAP using Hermite polynomials from a modified HOT model of the original GDTI-ADC. Since the solution is analytical, it is fast, differentiable, and the approximation converges well to the true EAP. This method also makes the effort of computing a positive ADC worthwhile, since now both the ADC and the EAP can be used and have closed forms. We demonstrate our approach with 4th-order tensors on synthetic data and in vivo human data.

  4. Diffusion tensor image registration using hybrid connectivity and tensor features.

    Science.gov (United States)

    Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

    2014-07-01

    Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. Copyright © 2013 Wiley Periodicals, Inc.

  5. Concatenated image completion via tensor augmentation and completion

    OpenAIRE

    Bengua, Johann A.; Tuan, Hoang D.; Phien, Ho N.; Do, Minh N.

    2016-01-01

    This paper proposes a novel framework called concatenated image completion via tensor augmentation and completion (ICTAC), which recovers missing entries of color images with high accuracy. Typical images are second- or third-order tensors (2D/3D) depending if they are grayscale or color, hence tensor completion algorithms are ideal for their recovery. The proposed framework performs image completion by concatenating copies of a single image that has missing entries into a third-order tensor,...

  6. Bayesian regularization of diffusion tensor images

    DEFF Research Database (Denmark)

    Frandsen, Jesper; Hobolth, Asger; Østergaard, Leif

    2007-01-01

    Diffusion tensor imaging (DTI) is a powerful tool in the study of the course of nerve fibre bundles in the human brain. Using DTI, the local fibre orientation in each image voxel can be described by a diffusion tensor which is constructed from local measurements of diffusion coefficients along...... several directions. The measured diffusion coefficients and thereby the diffusion tensors are subject to noise, leading to possibly flawed representations of the three dimensional fibre bundles. In this paper we develop a Bayesian procedure for regularizing the diffusion tensor field, fully utilizing...

  7. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading.

    Science.gov (United States)

    Inano, Rika; Oishi, Naoya; Kunieda, Takeharu; Arakawa, Yoshiki; Yamao, Yukihiro; Shibata, Sumiya; Kikuchi, Takayuki; Fukuyama, Hidenao; Miyamoto, Susumu

    2014-01-01

    Gliomas are the most common intra-axial primary brain tumour; therefore, predicting glioma grade would influence therapeutic strategies. Although several methods based on single or multiple parameters from diagnostic images exist, a definitive method for pre-operatively determining glioma grade remains unknown. We aimed to develop an unsupervised method using multiple parameters from pre-operative diffusion tensor images for obtaining a clustered image that could enable visual grading of gliomas. Fourteen patients with low-grade gliomas and 19 with high-grade gliomas underwent diffusion tensor imaging and three-dimensional T1-weighted magnetic resonance imaging before tumour resection. Seven features including diffusion-weighted imaging, fractional anisotropy, first eigenvalue, second eigenvalue, third eigenvalue, mean diffusivity and raw T2 signal with no diffusion weighting, were extracted as multiple parameters from diffusion tensor imaging. We developed a two-level clustering approach for a self-organizing map followed by the K-means algorithm to enable unsupervised clustering of a large number of input vectors with the seven features for the whole brain. The vectors were grouped by the self-organizing map as protoclusters, which were classified into the smaller number of clusters by K-means to make a voxel-based diffusion tensor-based clustered image. Furthermore, we also determined if the diffusion tensor-based clustered image was really helpful for predicting pre-operative glioma grade in a supervised manner. The ratio of each class in the diffusion tensor-based clustered images was calculated from the regions of interest manually traced on the diffusion tensor imaging space, and the common logarithmic ratio scales were calculated. We then applied support vector machine as a classifier for distinguishing between low- and high-grade gliomas. Consequently, the sensitivity, specificity, accuracy and area under the curve of receiver operating characteristic

  8. [An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].

    Science.gov (United States)

    Xu, Yonghong; Gao, Shangce; Hao, Xiaofei

    2016-04-01

    Diffusion tensor imaging(DTI)is a rapid development technology in recent years of magnetic resonance imaging.The diffusion tensor interpolation is a very important procedure in DTI image processing.The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy,but the method does not revise the size of tensors.The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation.Firstly,we decomposed diffusion tensors with the direction of tensors being represented by quaternion.Then we revised the size and direction of the tensor respectively according to different situations.Finally,we acquired the tensor of interpolation point by calculating the weighted average.We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data.The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy(FA)and the determinant of tensors,but also preserve the tensor anisotropy at the same time.In conclusion,the improved method provides a kind of important interpolation method for diffusion tensor image processing.

  9. Diffusion tensor imaging in spinal cord compression

    International Nuclear Information System (INIS)

    Wang, Wei; Qin, Wen; Hao, Nanxin; Wang, Yibin; Zong, Genlin

    2012-01-01

    Background Although diffusion tensor imaging has been successfully applied in brain research for decades, several main difficulties have hindered its extended utilization in spinal cord imaging. Purpose To assess the feasibility and clinical value of diffusion tensor imaging and tractography for evaluating chronic spinal cord compression. Material and Methods Single-shot spin-echo echo-planar DT sequences were scanned in 42 spinal cord compression patients and 49 healthy volunteers. The mean values of the apparent diffusion coefficient and fractional anisotropy were measured in region of interest at the cervical and lower thoracic spinal cord. The patients were divided into two groups according to the high signal on T2WI (the SCC-HI group and the SCC-nHI group for with or without high signal). A one-way ANOVA was used. Diffusion tensor tractography was used to visualize the morphological features of normal and impaired white matter. Results There were no statistically significant differences in the apparent diffusion coefficient and fractional anisotropy values between the different spinal cord segments of the normal subjects. All of the patients in the SCC-HI group had increased apparent diffusion coefficient values and decreased fractional anisotropy values at the lesion level compared to the normal controls. However, there were no statistically significant diffusion index differences between the SCC-nHI group and the normal controls. In the diffusion tensor imaging maps, the normal spinal cord sections were depicted as fiber tracts that were color-encoded to a cephalocaudal orientation. The diffusion tensor images were compressed to different degrees in all of the patients. Conclusion Diffusion tensor imaging and tractography are promising methods for visualizing spinal cord tracts and can provide additional information in clinical studies in spinal cord compression

  10. Tri-Clustered Tensor Completion for Social-Aware Image Tag Refinement.

    Science.gov (United States)

    Tang, Jinhui; Shu, Xiangbo; Qi, Guo-Jun; Li, Zechao; Wang, Meng; Yan, Shuicheng; Jain, Ramesh

    2017-08-01

    Social image tag refinement, which aims to improve tag quality by automatically completing the missing tags and rectifying the noise-corrupted ones, is an essential component for social image search. Conventional approaches mainly focus on exploring the visual and tag information, without considering the user information, which often reveals important hints on the (in)correct tags of social images. Towards this end, we propose a novel tri-clustered tensor completion framework to collaboratively explore these three kinds of information to improve the performance of social image tag refinement. Specifically, the inter-relations among users, images and tags are modeled by a tensor, and the intra-relations between users, images and tags are explored by three regularizations respectively. To address the challenges of the super-sparse and large-scale tensor factorization that demands expensive computing and memory cost, we propose a novel tri-clustering method to divide the tensor into a certain number of sub-tensors by simultaneously clustering users, images and tags into a bunch of tri-clusters. And then we investigate two strategies to complete these sub-tensors by considering (in)dependence between the sub-tensors. Experimental results on a real-world social image database demonstrate the superiority of the proposed method compared with the state-of-the-art methods.

  11. Diffusion tensor imaging tensor shape analysis for assessment of regional white matter differences.

    Science.gov (United States)

    Middleton, Dana M; Li, Jonathan Y; Lee, Hui J; Chen, Steven; Dickson, Patricia I; Ellinwood, N Matthew; White, Leonard E; Provenzale, James M

    2017-08-01

    Purpose The purpose of this study was to investigate a novel tensor shape plot analysis technique of diffusion tensor imaging data as a means to assess microstructural differences in brain tissue. We hypothesized that this technique could distinguish white matter regions with different microstructural compositions. Methods Three normal canines were euthanized at seven weeks old. Their brains were imaged using identical diffusion tensor imaging protocols on a 7T small-animal magnetic resonance imaging system. We examined two white matter regions, the internal capsule and the centrum semiovale, each subdivided into an anterior and posterior region. We placed 100 regions of interest in each of the four brain regions. Eigenvalues for each region of interest triangulated onto tensor shape plots as the weighted average of three shape metrics at the plot's vertices: CS, CL, and CP. Results The distribution of data on the plots for the internal capsule differed markedly from the centrum semiovale data, thus confirming our hypothesis. Furthermore, data for the internal capsule were distributed in a relatively tight cluster, possibly reflecting the compact and parallel nature of its fibers, while data for the centrum semiovale were more widely distributed, consistent with the less compact and often crossing pattern of its fibers. This indicates that the tensor shape plot technique can depict data in similar regions as being alike. Conclusion Tensor shape plots successfully depicted differences in tissue microstructure and reflected the microstructure of individual brain regions. This proof of principle study suggests that if our findings are reproduced in larger samples, including abnormal white matter states, the technique may be useful in assessment of white matter diseases.

  12. Motion Detection in Ultrasound Image-Sequences Using Tensor Voting

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    Inba, Masafumi; Yanagida, Hirotaka; Tamura, Yasutaka

    2008-05-01

    Motion detection in ultrasound image sequences using tensor voting is described. We have been developing an ultrasound imaging system adopting a combination of coded excitation and synthetic aperture focusing techniques. In our method, frame rate of the system at distance of 150 mm reaches 5000 frame/s. Sparse array and short duration coded ultrasound signals are used for high-speed data acquisition. However, many artifacts appear in the reconstructed image sequences because of the incompleteness of the transmitted code. To reduce the artifacts, we have examined the application of tensor voting to the imaging method which adopts both coded excitation and synthetic aperture techniques. In this study, the basis of applying tensor voting and the motion detection method to ultrasound images is derived. It was confirmed that velocity detection and feature enhancement are possible using tensor voting in the time and space of simulated ultrasound three-dimensional image sequences.

  13. Efficient Tensor Completion for Color Image and Video Recovery: Low-Rank Tensor Train.

    Science.gov (United States)

    Bengua, Johann A; Phien, Ho N; Tuan, Hoang Duong; Do, Minh N

    2017-05-01

    This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its definition from a well-balanced matricization scheme. Accordingly, new optimization formulations for tensor completion are proposed as well as two new algorithms for their solution. The first one called simple low-rank tensor completion via TT (SiLRTC-TT) is intimately related to minimizing a nuclear norm based on TT rank. The second one is from a multilinear matrix factorization model to approximate the TT rank of a tensor, and is called tensor completion by parallel matrix factorization via TT (TMac-TT). A tensor augmentation scheme of transforming a low-order tensor to higher orders is also proposed to enhance the effectiveness of SiLRTC-TT and TMac-TT. Simulation results for color image and video recovery show the clear advantage of our method over all other methods.

  14. Diffusion tensor and diffusion weighted imaging. Pictorial mathematics

    Energy Technology Data Exchange (ETDEWEB)

    Nakada, Tsutomu [California Univ., Davis, CA (United States)

    1995-06-01

    A new imaging algorithm for the treatment of a second order apparent diffusion tensor, D{sub app}{sup {xi}} is described. The method calls for only mathematics of images (pictorial mathematics) without necessity of eigenvalues/eigenvectors estimation. Nevertheless, it is capable of extracting properties of D{sub app}{sup {xi}} invariant to observation axes. While trace image is an example of images weighted by invariance of the tensor matrix, three dimensional anisotropy (3DAC) contrast represents the imaging method making use to anisotropic direction of tensor ellipsoid producing color coded contrast of exceptionally high anatomic resolution. Contrary to intuition, the processes require only a simple algorithm directly applicable to clinical magnetic resonance imaging (MRI). As a contrast method which precisely represents physical characteristics of a target tissue, invariant D{sub app}{sup {xi}} images produced by pictorial mathematics possess significant potential for a number of biological and clinical applications. (author).

  15. Tensor based structure estimation in multi-channel images

    DEFF Research Database (Denmark)

    Schou, Jesper; Dierking, Wolfgang; Skriver, Henning

    2000-01-01

    . In the second part tensors are used for representing the structure information. This approach has the advantage, that tensors can be averaged either spatially or by applying several images, and the resulting tensor provides information of the average strength as well as orientation of the structure...

  16. A tensor-based dictionary learning approach to tomographic image reconstruction

    DEFF Research Database (Denmark)

    Soltani, Sara; Kilmer, Misha E.; Hansen, Per Christian

    2016-01-01

    We consider tomographic reconstruction using priors in the form of a dictionary learned from training images. The reconstruction has two stages: first we construct a tensor dictionary prior from our training data, and then we pose the reconstruction problem in terms of recovering the expansion...... coefficients in that dictionary. Our approach differs from past approaches in that (a) we use a third-order tensor representation for our images and (b) we recast the reconstruction problem using the tensor formulation. The dictionary learning problem is presented as a non-negative tensor factorization problem...... with sparsity constraints. The reconstruction problem is formulated in a convex optimization framework by looking for a solution with a sparse representation in the tensor dictionary. Numerical results show that our tensor formulation leads to very sparse representations of both the training images...

  17. Unusual magnetic properties of rare-earth titanium oxides RTiO3: effect of the rare earth on the magnetic moment of titanium in Lasub(x)Ysub(1-x)Ti03 and GdTi03

    International Nuclear Information System (INIS)

    Greedan, J.E.; MacLean, D.A.

    1978-01-01

    The rare-earth orthotitanites, RTi0 3 are a relatively new series of materials with properties which are strongly dependent on the identity of the rare-earth ion. Low-temperature magnetization studies on the system Lasub(x)Ysub(1-x)Ti0 3 and the compound GdTi0 3 indicate that the magnitude of the Ti 3+ spontaneous moment depends on the average size of the rare-earth ion and on its magnetic moment. For most of the phases studied except GdTi0 3 the Ti 3+ moment is very much smaller than the 'spin only' value and is non-integral, yet semiconducting behaviour is simultaneously observed. (author)

  18. Tensor estimation for double-pulsed diffusional kurtosis imaging.

    Science.gov (United States)

    Shaw, Calvin B; Hui, Edward S; Helpern, Joseph A; Jensen, Jens H

    2017-07-01

    Double-pulsed diffusional kurtosis imaging (DP-DKI) represents the double diffusion encoding (DDE) MRI signal in terms of six-dimensional (6D) diffusion and kurtosis tensors. Here a method for estimating these tensors from experimental data is described. A standard numerical algorithm for tensor estimation from conventional (i.e. single diffusion encoding) diffusional kurtosis imaging (DKI) data is generalized to DP-DKI. This algorithm is based on a weighted least squares (WLS) fit of the signal model to the data combined with constraints designed to minimize unphysical parameter estimates. The numerical algorithm then takes the form of a quadratic programming problem. The principal change required to adapt the conventional DKI fitting algorithm to DP-DKI is replacing the three-dimensional diffusion and kurtosis tensors with the 6D tensors needed for DP-DKI. In this way, the 6D diffusion and kurtosis tensors for DP-DKI can be conveniently estimated from DDE data by using constrained WLS, providing a practical means for condensing DDE measurements into well-defined mathematical constructs that may be useful for interpreting and applying DDE MRI. Data from healthy volunteers for brain are used to demonstrate the DP-DKI tensor estimation algorithm. In particular, representative parametric maps of selected tensor-derived rotational invariants are presented. Copyright © 2017 John Wiley & Sons, Ltd.

  19. Tensor Fukunaga-Koontz transform for small target detection in infrared images

    Science.gov (United States)

    Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

    2016-09-01

    Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

  20. STRUCTURE TENSOR IMAGE FILTERING USING RIEMANNIAN L1 AND L∞ CENTER-OF-MASS

    Directory of Open Access Journals (Sweden)

    Jesus Angulo

    2014-06-01

    Full Text Available Structure tensor images are obtained by a Gaussian smoothing of the dyadic product of gradient image. These images give at each pixel a n×n symmetric positive definite matrix SPD(n, representing the local orientation and the edge information. Processing such images requires appropriate algorithms working on the Riemannian manifold on the SPD(n matrices. This contribution deals with structure tensor image filtering based on Lp geometric averaging. In particular, L1 center-of-mass (Riemannian median or Fermat-Weber point and L∞ center-of-mass (Riemannian circumcenter can be obtained for structure tensors using recently proposed algorithms. Our contribution in this paper is to study the interest of L1 and L∞ Riemannian estimators for structure tensor image processing. In particular, we compare both for two image analysis tasks: (i structure tensor image denoising; (ii anomaly detection in structure tensor images.

  1. Ultrasound elastic tensor imaging: comparison with MR diffusion tensor imaging in the myocardium

    Science.gov (United States)

    Lee, Wei-Ning; Larrat, Benoît; Pernot, Mathieu; Tanter, Mickaël

    2012-08-01

    We have previously proven the feasibility of ultrasound-based shear wave imaging (SWI) to non-invasively characterize myocardial fiber orientation in both in vitro porcine and in vivo ovine hearts. The SWI-estimated results were in good correlation with histology. In this study, we proposed a new and robust fiber angle estimation method through a tensor-based approach for SWI, coined together as elastic tensor imaging (ETI), and compared it with magnetic resonance diffusion tensor imaging (DTI), a current gold standard and extensively reported non-invasive imaging technique for mapping fiber architecture. Fresh porcine (n = 5) and ovine (n = 5) myocardial samples (20 × 20 × 30 mm3) were studied. ETI was firstly performed to generate shear waves and to acquire the wave events at ultrafast frame rate (8000 fps). A 2.8 MHz phased array probe (pitch = 0.28 mm), connected to a prototype ultrasound scanner, was mounted on a customized MRI-compatible rotation device, which allowed both the rotation of the probe from -90° to 90° at 5° increments and co-registration between two imaging modalities. Transmural shear wave speed at all propagation directions realized was firstly estimated. The fiber angles were determined from the shear wave speed map using the least-squares method and eigen decomposition. The test myocardial sample together with the rotation device was then placed inside a 7T MRI scanner. Diffusion was encoded in six directions. A total of 270 diffusion-weighted images (b = 1000 s mm-2, FOV = 30 mm, matrix size = 60 × 64, TR = 6 s, TE = 19 ms, 24 averages) and 45 B0 images were acquired in 14 h 30 min. The fiber structure was analyzed by the fiber-tracking module in software, MedINRIA. The fiber orientation in the overlapped myocardial region which both ETI and DTI accessed was therefore compared, thanks to the co-registered imaging system. Results from all ten samples showed good correlation (r2 = 0.81, p 0.05, unpaired, one-tailed t-test, N = 10). In

  2. X-ray strain tensor imaging: FEM simulation and experiments with a micro-CT.

    Science.gov (United States)

    Kim, Jae G; Park, So E; Lee, Soo Y

    2014-01-01

    In tissue elasticity imaging, measuring the strain tensor components is necessary to solve the inverse problem. However, it is impractical to measure all the tensor components in ultrasound or MRI elastography because of their anisotropic spatial resolution. The objective of this study is to compute 3D strain tensor maps from the 3D CT images of a tissue-mimicking phantom. We took 3D micro-CT images of the phantom twice with applying two different mechanical compressions to it. Applying the 3D image correlation technique to the CT images under different compression, we computed 3D displacement vectors and strain tensors at every pixel. To evaluate the accuracy of the strain tensor maps, we made a 3D FEM model of the phantom, and we computed strain tensor maps through FEM simulation. Experimentally obtained strain tensor maps showed similar patterns to the FEM-simulated ones in visual inspection. The correlation between the strain tensor maps obtained from the experiment and the FEM simulation ranges from 0.03 to 0.93. Even though the strain tensor maps suffer from high level noise, we expect the x-ray strain tensor imaging may find some biomedical applications such as malignant tissue characterization and stress analysis inside the tissues.

  3. Anisotropic Conductivity Tensor Imaging of In Vivo Canine Brain Using DT-MREIT.

    Science.gov (United States)

    Jeong, Woo Chul; Sajib, Saurav Z K; Katoch, Nitish; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je

    2017-01-01

    We present in vivo images of anisotropic electrical conductivity tensor distributions inside canine brains using diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT). The conductivity tensor is represented as a product of an ion mobility tensor and a scale factor of ion concentrations. Incorporating directional mobility information from water diffusion tensors, we developed a stable process to reconstruct anisotropic conductivity tensor images from measured magnetic flux density data using an MRI scanner. Devising a new image reconstruction algorithm, we reconstructed anisotropic conductivity tensor images of two canine brains with a pixel size of 1.25 mm. Though the reconstructed conductivity values matched well in general with those measured by using invasive probing methods, there were some discrepancies as well. The degree of white matter anisotropy was 2 to 4.5, which is smaller than previous findings of 5 to 10. The reconstructed conductivity value of the cerebrospinal fluid was about 1.3 S/m, which is smaller than previous measurements of about 1.8 S/m. Future studies of in vivo imaging experiments with disease models should follow this initial trial to validate clinical significance of DT-MREIT as a new diagnostic imaging modality. Applications in modeling and simulation studies of bioelectromagnetic phenomena including source imaging and electrical stimulation are also promising.

  4. Deep Into the Fibers! Postmortem Diffusion Tensor Imaging in Forensic Radiology.

    Science.gov (United States)

    Flach, Patricia Mildred; Schroth, Sarah; Schweitzer, Wolf; Ampanozi, Garyfalia; Slotboom, Johannes; Kiefer, Claus; Germerott, Tanja; Thali, Michael J; El-Koussy, Marwan

    2015-09-01

    In traumatic brain injury, diffusion-weighted and diffusion tensor imaging of the brain are essential techniques for determining the pathology sustained and the outcome. Postmortem cross-sectional imaging is an established adjunct to forensic autopsy in death investigation. The purpose of this prospective study was to evaluate postmortem diffusion tensor imaging in forensics for its feasibility, influencing factors and correlation to the cause of death compared with autopsy. Postmortem computed tomography, magnetic resonance imaging, and diffusion tensor imaging with fiber tracking were performed in 10 deceased subjects. The Likert scale grading of colored fractional anisotropy maps was correlated to the body temperature and intracranial pathology to assess the diagnostic feasibility of postmortem diffusion tensor imaging and fiber tracking. Optimal fiber tracking (>15,000 fiber tracts) was achieved with a body temperature at 10°C. Likert scale grading showed no linear correlation (P > 0.7) to fiber tract counts. No statistically significant correlation between total fiber count and postmortem interval could be observed (P = 0.122). Postmortem diffusion tensor imaging and fiber tracking allowed for radiological diagnosis in cases with shearing injuries but was impaired in cases with pneumencephalon and intracerebral mass hemorrhage. Postmortem diffusion tensor imaging with fiber tracking provides an exceptional in situ insight "deep into the fibers" of the brain with diagnostic benefit in traumatic brain injury and axonal injuries in the assessment of the underlying cause of death, considering influencing factors for optimal imaging technique.

  5. Susceptibility Tensor Imaging (STI) of the Brain

    Science.gov (United States)

    Li, Wei; Liu, Chunlei; Duong, Timothy Q.; van Zijl, Peter C.M.; Li, Xu

    2016-01-01

    Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility (MMS) and magnetic susceptibility anisotropy (MSA) can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping (QSM) to remove such dependence. Similar to diffusion tensor imaging (DTI), STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of susceptibility anisotropy in brain white matter is myelin. Another unique feature of susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. PMID:27120169

  6. X-linked adrenoleukodystrophy: correlation between Loes score and diffusion tensor imaging parameters.

    Science.gov (United States)

    Ono, Sergio Eiji; de Carvalho Neto, Arnolfo; Gasparetto, Emerson Leandro; Coelho, Luiz Otávio de Mattos; Escuissato, Dante Luiz; Bonfim, Carmem Maria Sales; Ribeiro, Lisandro Lima

    2014-01-01

    The present study was aimed at evaluating the correlation between diffusion tensor imaging parameters and Loes score as well as whether those parameters could indicate early structural alterations. Diffusion tensor imaging measurements were obtained in 30 studies of 14 patients with X-linked adrenoleukodystrophy and were correlated with Loes scores. A control group including 28 male patients was created to establish agematched diffusion tensor imaging measurements. Inter- and intraobserver statistical analyses were undertaken. Diffusion tensor imaging measurements presented strong Pearson correlation coefficients (r) of -0.86, 0.89, 0.89 and 0.84 for fractional anisotropy and mean, radial and axial diffusivities (p tensor measurements at early stage of the disease indicates that mean and radial diffusivities might be useful to predict the disease progression. Measurements of diffusion tensor parameters can be used as an adjunct to the Loes score, aiding in the monitoring of the disease and alerting for possible Loes score progression in the range of interest for therapeutic decisions.

  7. Validation of diffusion tensor MRI measurements of cardiac microstructure with structure tensor synchrotron radiation imaging.

    Science.gov (United States)

    Teh, Irvin; McClymont, Darryl; Zdora, Marie-Christine; Whittington, Hannah J; Davidoiu, Valentina; Lee, Jack; Lygate, Craig A; Rau, Christoph; Zanette, Irene; Schneider, Jürgen E

    2017-03-10

    Diffusion tensor imaging (DTI) is widely used to assess tissue microstructure non-invasively. Cardiac DTI enables inference of cell and sheetlet orientations, which are altered under pathological conditions. However, DTI is affected by many factors, therefore robust validation is critical. Existing histological validation is intrinsically flawed, since it requires further tissue processing leading to sample distortion, is routinely limited in field-of-view and requires reconstruction of three-dimensional volumes from two-dimensional images. In contrast, synchrotron radiation imaging (SRI) data enables imaging of the heart in 3D without further preparation following DTI. The objective of the study was to validate DTI measurements based on structure tensor analysis of SRI data. One isolated, fixed rat heart was imaged ex vivo with DTI and X-ray phase contrast SRI, and reconstructed at 100 μm and 3.6 μm isotropic resolution respectively. Structure tensors were determined from the SRI data and registered to the DTI data. Excellent agreement in helix angles (HA) and transverse angles (TA) was observed between the DTI and structure tensor synchrotron radiation imaging (STSRI) data, where HA DTI-STSRI  = -1.4° ± 23.2° and TA DTI-STSRI  = -1.4° ± 35.0° (mean ± 1.96 standard deviation across all voxels in the left ventricle). STSRI confirmed that the primary eigenvector of the diffusion tensor corresponds with the cardiomyocyte long-axis across the whole myocardium. We have used STSRI as a novel and high-resolution gold standard for the validation of DTI, allowing like-with-like comparison of three-dimensional tissue structures in the same intact heart free of distortion. This represents a critical step forward in independently verifying the structural basis and informing the interpretation of cardiac DTI data, thereby supporting the further development and adoption of DTI in structure-based electro-mechanical modelling and routine clinical

  8. Diffusion tensor imaging of the human skeletal muscle: contributions and applications

    International Nuclear Information System (INIS)

    Neji, Radhouene

    2010-01-01

    In this thesis, we present several techniques for the processing of diffusion tensor images. They span a wide range of tasks such as estimation and regularization, clustering and segmentation, as well as registration. The variational framework proposed for recovering a tensor field from noisy diffusion weighted images exploits the fact that diffusion data represent populations of fibers and therefore each tensor can be reconstructed using a weighted combination of tensors lying in its neighborhood. The segmentation approach operates both at the voxel and the fiber tract levels. It is based on the use of Mercer kernels over Gaussian diffusion probabilities to model tensor similarity and spatial interactions, allowing the definition of fiber metrics that combine information from spatial localization and diffusion tensors. Several clustering techniques can be subsequently used to segment tensor fields and fiber tractographies. Moreover, we show how to develop supervised extensions of these algorithms. The registration algorithm uses probability kernels in order to match moving and target images. The deformation consistency is assessed using the distortion induced in the distances between neighboring probabilities. Discrete optimization is used to seek an optimum of the defined objective function. The experimental validation is done over a dataset of manually segmented diffusion images of the lower leg muscle for healthy and diseased subjects. The results of the techniques developed throughout this thesis are promising. (author)

  9. Susceptibility tensor imaging (STI) of the brain.

    Science.gov (United States)

    Li, Wei; Liu, Chunlei; Duong, Timothy Q; van Zijl, Peter C M; Li, Xu

    2017-04-01

    Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility and magnetic susceptibility anisotropy can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping to remove such dependence. Similar to diffusion tensor imaging, STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of the susceptibility anisotropy in brain white matter is myelin. Another unique feature of the susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in the myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  10. A Review of Tensors and Tensor Signal Processing

    Science.gov (United States)

    Cammoun, L.; Castaño-Moraga, C. A.; Muñoz-Moreno, E.; Sosa-Cabrera, D.; Acar, B.; Rodriguez-Florido, M. A.; Brun, A.; Knutsson, H.; Thiran, J. P.

    Tensors have been broadly used in mathematics and physics, since they are a generalization of scalars or vectors and allow to represent more complex properties. In this chapter we present an overview of some tensor applications, especially those focused on the image processing field. From a mathematical point of view, a lot of work has been developed about tensor calculus, which obviously is more complex than scalar or vectorial calculus. Moreover, tensors can represent the metric of a vector space, which is very useful in the field of differential geometry. In physics, tensors have been used to describe several magnitudes, such as the strain or stress of materials. In solid mechanics, tensors are used to define the generalized Hooke’s law, where a fourth order tensor relates the strain and stress tensors. In fluid dynamics, the velocity gradient tensor provides information about the vorticity and the strain of the fluids. Also an electromagnetic tensor is defined, that simplifies the notation of the Maxwell equations. But tensors are not constrained to physics and mathematics. They have been used, for instance, in medical imaging, where we can highlight two applications: the diffusion tensor image, which represents how molecules diffuse inside the tissues and is broadly used for brain imaging; and the tensorial elastography, which computes the strain and vorticity tensor to analyze the tissues properties. Tensors have also been used in computer vision to provide information about the local structure or to define anisotropic image filters.

  11. Review of diffusion tensor imaging and its application in children

    Energy Technology Data Exchange (ETDEWEB)

    Vorona, Gregory A. [Children' s Hospital of Richmond at Virginia Commonwealth University, Department of Radiology, Richmond, VA (United States); Berman, Jeffrey I. [Children' s Hospital of Philadelphia, Department of Radiology, Philadelphia, PA (United States)

    2015-09-15

    Diffusion MRI is an imaging technique that uses the random motion of water to probe tissue microstructure. Diffusion tensor imaging (DTI) can quantitatively depict the organization and connectivity of white matter. Given the non-invasiveness of the technique, DTI has become a widely used tool for researchers and clinicians to examine the white matter of children. This review covers the basics of diffusion-weighted imaging and diffusion tensor imaging and discusses examples of their clinical application in children. (orig.)

  12. An Adaptive Spectrally Weighted Structure Tensor Applied to Tensor Anisotropic Nonlinear Diffusion for Hyperspectral Images

    Science.gov (United States)

    Marin Quintero, Maider J.

    2013-01-01

    The structure tensor for vector valued images is most often defined as the average of the scalar structure tensors in each band. The problem with this definition is the assumption that all bands provide the same amount of edge information giving them the same weights. As a result non-edge pixels can be reinforced and edges can be weakened…

  13. Diffusion Tensor Imaging-Based Research on Human White Matter Anatomy

    Directory of Open Access Journals (Sweden)

    Ming-guo Qiu

    2012-01-01

    Full Text Available The aim of this study is to investigate the white matter by the diffusion tensor imaging and the Chinese visible human dataset and to provide the 3D anatomical data of the corticospinal tract for the neurosurgical planning by studying the probabilistic maps and the reproducibility of the corticospinal tract. Diffusion tensor images and high-resolution T1-weighted images of 15 healthy volunteers were acquired; the DTI data were processed using DtiStudio and FSL software. The FA and color FA maps were compared with the sectional images of the Chinese visible human dataset. The probability maps of the corticospinal tract were generated as a quantitative measure of reproducibility for each voxel of the stereotaxic space. The fibers displayed by the diffusion tensor imaging were well consistent with the sectional images of the Chinese visible human dataset and the existing anatomical knowledge. The three-dimensional architecture of the white matter fibers could be clearly visualized on the diffusion tensor tractography. The diffusion tensor tractography can establish the 3D probability maps of the corticospinal tract, in which the degree of intersubject reproducibility of the corticospinal tract is consistent with the previous architectonic report. DTI is a reliable method of studying the fiber connectivity in human brain, but it is difficult to identify the tiny fibers. The probability maps are useful for evaluating and identifying the corticospinal tract in the DTI, providing anatomical information for the preoperative planning and improving the accuracy of surgical risk assessments preoperatively.

  14. Anisotropic conductivity tensor imaging in MREIT using directional diffusion rate of water molecules

    International Nuclear Information System (INIS)

    Kwon, Oh In; Jeong, Woo Chul; Sajib, Saurav Z K; Kim, Hyung Joong; Woo, Eung Je

    2014-01-01

    Magnetic resonance electrical impedance tomography (MREIT) is an emerging method to visualize electrical conductivity and/or current density images at low frequencies (below 1 KHz). Injecting currents into an imaging object, one component of the induced magnetic flux density is acquired using an MRI scanner for isotropic conductivity image reconstructions. Diffusion tensor MRI (DT-MRI) measures the intrinsic three-dimensional diffusion property of water molecules within a tissue. It characterizes the anisotropic water transport by the effective diffusion tensor. Combining the DT-MRI and MREIT techniques, we propose a novel direct method for absolute conductivity tensor image reconstructions based on a linear relationship between the water diffusion tensor and the electrical conductivity tensor. We first recover the projected current density, which is the best approximation of the internal current density one can obtain from the measured single component of the induced magnetic flux density. This enables us to estimate a scale factor between the diffusion tensor and the conductivity tensor. Combining these values at all pixels with the acquired diffusion tensor map, we can quantitatively recover the anisotropic conductivity tensor map. From numerical simulations and experimental verifications using a biological tissue phantom, we found that the new method overcomes the limitations of each method and successfully reconstructs both the direction and magnitude of the conductivity tensor for both the anisotropic and isotropic regions. (paper)

  15. Time-optimized high-resolution readout-segmented diffusion tensor imaging.

    Directory of Open Access Journals (Sweden)

    Gernot Reishofer

    Full Text Available Readout-segmented echo planar imaging with 2D navigator-based reacquisition is an uprising technique enabling the sampling of high-resolution diffusion images with reduced susceptibility artifacts. However, low signal from the small voxels and long scan times hamper the clinical applicability. Therefore, we introduce a regularization algorithm based on total variation that is applied directly on the entire diffusion tensor. The spatially varying regularization parameter is determined automatically dependent on spatial variations in signal-to-noise ratio thus, avoiding over- or under-regularization. Information about the noise distribution in the diffusion tensor is extracted from the diffusion weighted images by means of complex independent component analysis. Moreover, the combination of those features enables processing of the diffusion data absolutely user independent. Tractography from in vivo data and from a software phantom demonstrate the advantage of the spatially varying regularization compared to un-regularized data with respect to parameters relevant for fiber-tracking such as Mean Fiber Length, Track Count, Volume and Voxel Count. Specifically, for in vivo data findings suggest that tractography results from the regularized diffusion tensor based on one measurement (16 min generates results comparable to the un-regularized data with three averages (48 min. This significant reduction in scan time renders high resolution (1 × 1 × 2.5 mm(3 diffusion tensor imaging of the entire brain applicable in a clinical context.

  16. Visualization of Plant Fibres via Difusion Tensor Imaging

    Czech Academy of Sciences Publication Activity Database

    Gescheidtová, E.; Marcon, P.; Bartušek, Karel

    2011-01-01

    Roč. 7, č. 6 (2011), s. 543-546 ISSN 1931-7360 R&D Projects: GA ČR GAP102/11/0318 Institutional research plan: CEZ:AV0Z20650511 Keywords : plant fibres * difusion weighted imaging * difusion tensor imaging * MR imaging Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

  17. Tensors in image processing and computer vision

    CERN Document Server

    De Luis García, Rodrigo; Tao, Dacheng; Li, Xuelong

    2009-01-01

    Tensor signal processing is an emerging field with important applications to computer vision and image processing. This book presents the developments in this branch of signal processing, offering research and discussions by experts in the area. It is suitable for advanced students working in the area of computer vision and image processing.

  18. Spinal diffusion tensor imaging: a comprehensive review with emphasis on spinal cord anatomy and clinical applications.

    Science.gov (United States)

    Hendrix, Philipp; Griessenauer, Christoph J; Cohen-Adad, Julien; Rajasekaran, Shanmuganathan; Cauley, Keith A; Shoja, Mohammadali M; Pezeshk, Parham; Tubbs, R Shane

    2015-01-01

    Magnetic resonance imaging technology allows for in vivo visualization of fiber tracts of the central nervous system using diffusion-weighted imaging sequences and data processing referred to as "diffusion tensor imaging" and "diffusion tensor tractography." While protocols for high-fidelity diffusion tensor imaging of the brain are well established, the spinal cord has proven a more difficult target for diffusion tensor methods. Here, we review the current literature on spinal diffusion tensor imaging and tractography with special emphasis on neuroanatomical correlations and clinical applications. © 2014 Wiley Periodicals, Inc.

  19. Relationship between timed 25-foot walk and diffusion tensor imaging in multiple sclerosis.

    Science.gov (United States)

    Klineova, Sylvia; Farber, Rebecca; Saiote, Catarina; Farrell, Colleen; Delman, Bradley N; Tanenbaum, Lawrence N; Friedman, Joshua; Inglese, Matilde; Lublin, Fred D; Krieger, Stephen

    2016-01-01

    The majority of multiple sclerosis patients experience impaired walking ability, which impacts quality of life. Timed 25-foot walk is commonly used to gauge gait impairment but results can be broadly variable. Objective biological markers that correlate closely with patients' disability are needed. Diffusion tensor imaging, quantifying fiber tract integrity, might provide such information. In this project we analyzed relationships between timed 25-foot walk, conventional and diffusion tensor imaging magnetic resonance imaging markers. A cohort of gait impaired multiple sclerosis patients underwent brain and cervical spinal cord magnetic resonance imaging. Diffusion tensor imaging mean diffusivity and fractional anisotropy were measured on the brain corticospinal tracts and spinal restricted field of vision at C2/3. We analyzed relationships between baseline timed 25-foot walk, conventional and diffusion tensor imaging magnetic resonance imaging markers. Multivariate linear regression analysis showed a statistically significant association between several magnetic resonance imaging and diffusion tensor imaging metrics and timed 25-foot walk: brain mean diffusivity corticospinal tracts (p = 0.004), brain corticospinal tracts axial and radial diffusivity (P = 0.004 and 0.02), grey matter volume (p = 0.05), white matter volume (p = 0.03) and normalized brain volume (P = 0.01). The linear regression model containing mean diffusivity corticospinal tracts and controlled for gait assistance was the best fit model (p = 0.004). Our results suggest an association between diffusion tensor imaging metrics and gait impairment, evidenced by brain mean diffusivity corticospinal tracts and timed 25-foot walk.

  20. Joint eigenvector estimation from mutually anisotropic tensors improves susceptibility tensor imaging of the brain, kidney, and heart.

    Science.gov (United States)

    Dibb, Russell; Liu, Chunlei

    2017-06-01

    To develop a susceptibility-based MRI technique for probing microstructure and fiber architecture of magnetically anisotropic tissues-such as central nervous system white matter, renal tubules, and myocardial fibers-in three dimensions using susceptibility tensor imaging (STI) tools. STI can probe tissue microstructure, but is limited by reconstruction artifacts because of absent phase information outside the tissue and noise. STI accuracy may be improved by estimating a joint eigenvector from mutually anisotropic susceptibility and relaxation tensors. Gradient-recalled echo image data were simulated using a numerical phantom and acquired from the ex vivo mouse brain, kidney, and heart. Susceptibility tensor data were reconstructed using STI, regularized STI, and the proposed algorithm of mutually anisotropic and joint eigenvector STI (MAJESTI). Fiber map and tractography results from each technique were compared with diffusion tensor data. MAJESTI reduced the estimated susceptibility tensor orientation error by 30% in the phantom, 36% in brain white matter, 40% in the inner medulla of the kidney, and 45% in myocardium. This improved the continuity and consistency of susceptibility-based fiber tractography in each tissue. MAJESTI estimation of the susceptibility tensors yields lower orientation errors for susceptibility-based fiber mapping and tractography in the intact brain, kidney, and heart. Magn Reson Med 77:2331-2346, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  1. Higher-order tensors in diffusion imaging

    NARCIS (Netherlands)

    Schultz, T.; Fuster, A.; Ghosh, A.; Deriche, R.; Florack, L.M.J.; Lim, L.H.; Westin, C.-F.; Vilanova, A.; Burgeth, B.

    2014-01-01

    Diffusion imaging is a noninvasive tool for probing the microstructure of fibrous nerve and muscle tissue. Higher-order tensors provide a powerful mathematical language to model and analyze the large and complex data that is generated by its modern variants such as High Angular Resolution Diffusion

  2. Tensor Based Representation and Analysis of Diffusion-Weighted Magnetic Resonance Images

    Science.gov (United States)

    Barmpoutis, Angelos

    2009-01-01

    Cartesian tensor bases have been widely used to model spherical functions. In medical imaging, tensors of various orders can approximate the diffusivity function at each voxel of a diffusion-weighted MRI data set. This approximation produces tensor-valued datasets that contain information about the underlying local structure of the scanned tissue.…

  3. Adaptive distance learning scheme for diffusion tensor imaging using kernel target alignment

    NARCIS (Netherlands)

    Rodrigues, P.R.; Vilanova, A.; Twellmann, T.; Haar Romenij, ter B.M.; Alexander, D.; Gee, J.; Whitaker, R.

    2008-01-01

    In segmentation techniques for Diffusion Tensor Imaging (DTI) data, the similarity of diffusion tensors must be assessed for partitioning data into regions which are homogeneous in terms of tensor characteristics. Various distance measures have been proposed in literature for analysing the

  4. Data quality in diffusion tensor imaging studies of the preterm brain: a systematic review.

    Science.gov (United States)

    Pieterman, Kay; Plaisier, Annemarie; Govaert, Paul; Leemans, Alexander; Lequin, Maarten H; Dudink, Jeroen

    2015-08-01

    To study early neurodevelopment in preterm infants, evaluation of brain maturation and injury is increasingly performed using diffusion tensor imaging, for which the reliability of underlying data is paramount. To review the literature to evaluate acquisition and processing methodology in diffusion tensor imaging studies of preterm infants. We searched the Embase, Medline, Web of Science and Cochrane databases for relevant papers published between 2003 and 2013. The following keywords were included in our search: prematurity, neuroimaging, brain, and diffusion tensor imaging. We found 74 diffusion tensor imaging studies in preterm infants meeting our inclusion criteria. There was wide variation in acquisition and processing methodology, and we found incomplete reporting of these settings. Nineteen studies (26%) reported the use of neonatal hardware. Data quality assessment was not reported in 13 (18%) studies. Artefacts-correction and data-exclusion was not reported in 33 (45%) and 18 (24%) studies, respectively. Tensor estimation algorithms were reported in 56 (76%) studies but were often suboptimal. Diffusion tensor imaging acquisition and processing settings are incompletely described in current literature, vary considerably, and frequently do not meet the highest standards.

  5. A Riemannian scalar measure for diffusion tensor images

    NARCIS (Netherlands)

    Astola, L.J.; Fuster, A.; Florack, L.M.J.

    2010-01-01

    We study a well-known scalar quantity in Riemannian geometry, the Ricci scalar, in the context of Diffusion Tensor Imaging (DTI), which is an emerging non-invasive medical imaging modality. We derive a physical interpretation for the Ricci scalar and explore experimentally its significance in DTI.

  6. An introduction to diffusion tensor image analysis.

    Science.gov (United States)

    O'Donnell, Lauren J; Westin, Carl-Fredrik

    2011-04-01

    Diffusion tensor magnetic resonance imaging (DTI) is a relatively new technology that is popular for imaging the white matter of the brain. This article provides a basic and broad overview of DTI to enable the reader to develop an intuitive understanding of these types of data, and an awareness of their strengths and weaknesses. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. Volume illustration of muscle from diffusion tensor images.

    Science.gov (United States)

    Chen, Wei; Yan, Zhicheng; Zhang, Song; Crow, John Allen; Ebert, David S; McLaughlin, Ronald M; Mullins, Katie B; Cooper, Robert; Ding, Zi'ang; Liao, Jun

    2009-01-01

    Medical illustration has demonstrated its effectiveness to depict salient anatomical features while hiding the irrelevant details. Current solutions are ineffective for visualizing fibrous structures such as muscle, because typical datasets (CT or MRI) do not contain directional details. In this paper, we introduce a new muscle illustration approach that leverages diffusion tensor imaging (DTI) data and example-based texture synthesis techniques. Beginning with a volumetric diffusion tensor image, we reformulate it into a scalar field and an auxiliary guidance vector field to represent the structure and orientation of a muscle bundle. A muscle mask derived from the input diffusion tensor image is used to classify the muscle structure. The guidance vector field is further refined to remove noise and clarify structure. To simulate the internal appearance of the muscle, we propose a new two-dimensional example based solid texture synthesis algorithm that builds a solid texture constrained by the guidance vector field. Illustrating the constructed scalar field and solid texture efficiently highlights the global appearance of the muscle as well as the local shape and structure of the muscle fibers in an illustrative fashion. We have applied the proposed approach to five example datasets (four pig hearts and a pig leg), demonstrating plausible illustration and expressiveness.

  8. Data quality in diffusion tensor imaging studies of the preterm brain: a systematic review

    Energy Technology Data Exchange (ETDEWEB)

    Pieterman, Kay; Plaisier, Annemarie; Dudink, Jeroen [Erasmus Medical Center - Sophia, Division of Neonatology, Department of Pediatrics, dr. Molewaterplein 60, GJ, Rotterdam (Netherlands); Department of Radiology, Erasmus Medical Center, Rotterdam (Netherlands); Govaert, Paul [Erasmus Medical Center - Sophia, Division of Neonatology, Department of Pediatrics, dr. Molewaterplein 60, GJ, Rotterdam (Netherlands); Department of Pediatrics, Koningin Paola Children' s Hospital, Antwerp (Belgium); Leemans, Alexander [University Medical Center Utrecht, Image Sciences Institute, Utrecht (Netherlands); Lequin, Maarten H. [Department of Radiology, Erasmus Medical Center, Rotterdam (Netherlands)

    2015-08-15

    To study early neurodevelopment in preterm infants, evaluation of brain maturation and injury is increasingly performed using diffusion tensor imaging, for which the reliability of underlying data is paramount. To review the literature to evaluate acquisition and processing methodology in diffusion tensor imaging studies of preterm infants. We searched the Embase, Medline, Web of Science and Cochrane databases for relevant papers published between 2003 and 2013. The following keywords were included in our search: prematurity, neuroimaging, brain, and diffusion tensor imaging. We found 74 diffusion tensor imaging studies in preterm infants meeting our inclusion criteria. There was wide variation in acquisition and processing methodology, and we found incomplete reporting of these settings. Nineteen studies (26%) reported the use of neonatal hardware. Data quality assessment was not reported in 13 (18%) studies. Artefacts-correction and data-exclusion was not reported in 33 (45%) and 18 (24%) studies, respectively. Tensor estimation algorithms were reported in 56 (76%) studies but were often suboptimal. Diffusion tensor imaging acquisition and processing settings are incompletely described in current literature, vary considerably, and frequently do not meet the highest standards. (orig.)

  9. Data quality in diffusion tensor imaging studies of the preterm brain: a systematic review

    International Nuclear Information System (INIS)

    Pieterman, Kay; Plaisier, Annemarie; Dudink, Jeroen; Govaert, Paul; Leemans, Alexander; Lequin, Maarten H.

    2015-01-01

    To study early neurodevelopment in preterm infants, evaluation of brain maturation and injury is increasingly performed using diffusion tensor imaging, for which the reliability of underlying data is paramount. To review the literature to evaluate acquisition and processing methodology in diffusion tensor imaging studies of preterm infants. We searched the Embase, Medline, Web of Science and Cochrane databases for relevant papers published between 2003 and 2013. The following keywords were included in our search: prematurity, neuroimaging, brain, and diffusion tensor imaging. We found 74 diffusion tensor imaging studies in preterm infants meeting our inclusion criteria. There was wide variation in acquisition and processing methodology, and we found incomplete reporting of these settings. Nineteen studies (26%) reported the use of neonatal hardware. Data quality assessment was not reported in 13 (18%) studies. Artefacts-correction and data-exclusion was not reported in 33 (45%) and 18 (24%) studies, respectively. Tensor estimation algorithms were reported in 56 (76%) studies but were often suboptimal. Diffusion tensor imaging acquisition and processing settings are incompletely described in current literature, vary considerably, and frequently do not meet the highest standards. (orig.)

  10. Predicting patterns of glioma recurrence using diffusion tensor imaging

    International Nuclear Information System (INIS)

    Price, Stephen J.; Pickard, John D.; Jena, Rajesh; Burnet, Neil G.; Carpenter, T.A.; Gillard, Jonathan H.

    2007-01-01

    Although multimodality therapy for high-grade gliomas is making some improvement in outcome, most patients will still die from their disease within a short time. We need tools that allow treatments to be tailored to an individual. In this study we used diffusion tensor imaging (DTI), a technique sensitive to subtle disruption of white-matter tracts due to tumour infiltration, to see if it can be used to predict patterns of glioma recurrence. In this study we imaged 26 patients with gliomas using DTI. Patients were imaged after 2 years or on symptomatic tumour recurrence. The diffusion tensor was split into its isotropic (p) and anisotropic (q) components, and these were plotted on T 2 -weighted images to show the pattern of DTI abnormality. This was compared to the pattern of recurrence. Three DTI patterns could be identified: (a) a diffuse pattern of abnormality where p exceeded q in all directions and was associated with diffuse increase in tumour size; (b) a localised pattern of abnormality where the tumour recurred in one particular direction; and (c) a pattern of minimal abnormality seen in some patients with or without evidence of recurrence. Diffusion tensor imaging is able to predict patterns of tumour recurrence and may allow better individualisation of tumour management and stratification for randomised controlled trials. (orig.)

  11. Predicting patterns of glioma recurrence using diffusion tensor imaging

    Energy Technology Data Exchange (ETDEWEB)

    Price, Stephen J.; Pickard, John D. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Academic Neurosurgery Unit (United Kingdom); University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Wolfson Brain Imaging Centre, Department of Clinical Neurosciences (United Kingdom); Jena, Rajesh; Burnet, Neil G. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, University Department of Oncology (United Kingdom); Carpenter, T.A. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, Wolfson Brain Imaging Centre, Department of Clinical Neurosciences (United Kingdom); Gillard, Jonathan H. [University of Cambridge and Cambridge University Hospitals NHS Foundation Trust, Addenbrooke' s Hospital, University Department of Radiology (United Kingdom)

    2007-07-15

    Although multimodality therapy for high-grade gliomas is making some improvement in outcome, most patients will still die from their disease within a short time. We need tools that allow treatments to be tailored to an individual. In this study we used diffusion tensor imaging (DTI), a technique sensitive to subtle disruption of white-matter tracts due to tumour infiltration, to see if it can be used to predict patterns of glioma recurrence. In this study we imaged 26 patients with gliomas using DTI. Patients were imaged after 2 years or on symptomatic tumour recurrence. The diffusion tensor was split into its isotropic (p) and anisotropic (q) components, and these were plotted on T{sub 2}-weighted images to show the pattern of DTI abnormality. This was compared to the pattern of recurrence. Three DTI patterns could be identified: (a) a diffuse pattern of abnormality where p exceeded q in all directions and was associated with diffuse increase in tumour size; (b) a localised pattern of abnormality where the tumour recurred in one particular direction; and (c) a pattern of minimal abnormality seen in some patients with or without evidence of recurrence. Diffusion tensor imaging is able to predict patterns of tumour recurrence and may allow better individualisation of tumour management and stratification for randomised controlled trials. (orig.)

  12. Tensor Factorization for Low-Rank Tensor Completion.

    Science.gov (United States)

    Zhou, Pan; Lu, Canyi; Lin, Zhouchen; Zhang, Chao

    2018-03-01

    Recently, a tensor nuclear norm (TNN) based method was proposed to solve the tensor completion problem, which has achieved state-of-the-art performance on image and video inpainting tasks. However, it requires computing tensor singular value decomposition (t-SVD), which costs much computation and thus cannot efficiently handle tensor data, due to its natural large scale. Motivated by TNN, we propose a novel low-rank tensor factorization method for efficiently solving the 3-way tensor completion problem. Our method preserves the low-rank structure of a tensor by factorizing it into the product of two tensors of smaller sizes. In the optimization process, our method only needs to update two smaller tensors, which can be more efficiently conducted than computing t-SVD. Furthermore, we prove that the proposed alternating minimization algorithm can converge to a Karush-Kuhn-Tucker point. Experimental results on the synthetic data recovery, image and video inpainting tasks clearly demonstrate the superior performance and efficiency of our developed method over state-of-the-arts including the TNN and matricization methods.

  13. White matter injury in newborns with congenital heart disease: a diffusion tensor imaging study.

    Science.gov (United States)

    Mulkey, Sarah B; Ou, Xiawei; Ramakrishnaiah, Raghu H; Glasier, Charles M; Swearingen, Christopher J; Melguizo, Maria S; Yap, Vivien L; Schmitz, Michael L; Bhutta, Adnan T

    2014-09-01

    Brain injury is observed on cranial magnetic resonance imaging preoperatively in up to 50% of newborns with congenital heart disease. Newer imaging techniques such as diffusion tensor imaging provide sensitive measures of the white matter integrity. The objective of this study was to evaluate the diffusion tensor imaging analysis technique of tract-based spatial statistics in newborns with congenital heart disease. Term newborns with congenital heart disease who would require surgery at less than 1 month of age were prospectively enrolled (n = 19). Infants underwent preoperative and postoperative brain magnetic resonance imaging with diffusion tensor imaging. Tract-based spatial statistics, an objective whole-brain diffusion tensor imaging analysis technique, was used to determine differences in white matter fractional anisotropy between infant groups. Term control infants were also compared with congenital heart disease infants. Postmenstrual age was equivalent between congenital heart disease infant groups and between congenital heart disease and control infants. Ten infants had preoperative brain injury, either infarct or white matter injury, by conventional brain magnetic resonance imaging. The technique of tract-based spatial statistics showed significantly lower fractional anisotropy (P tensor imaging analysis technique that may have better sensitivity in detecting white matter injury compared with conventional brain magnetic resonance imaging in term newborns with congenital heart disease. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Homogeneity based segmentation and enhancement of Diffusion Tensor Images : a white matter processing framework

    NARCIS (Netherlands)

    Rodrigues, P.R.

    2011-01-01

    In diffusion magnetic resonance imaging (DMRI) the Brownian motion of the water molecules, within biological tissue, is measured through a series of images. In diffusion tensor imaging (DTI) this diffusion is represented using tensors. DTI describes, in a non-invasive way, the local anisotropy

  15. Diffusion tensor imaging of the nigrostriatal fibers in Parkinson's disease.

    Science.gov (United States)

    Zhang, Yu; Wu, I-Wei; Buckley, Shannon; Coffey, Christopher S; Foster, Eric; Mendick, Susan; Seibyl, John; Schuff, Norbert

    2015-08-01

    Parkinson's disease (PD) is histopathologically characterized by the loss of dopamine neurons in the substantia nigra pars compacta. The depletion of these neurons is thought to reduce the dopaminergic function of the nigrostriatal pathway, as well as the neural fibers that link the substantia nigra to the striatum (putamen and caudate), causing a dysregulation in striatal activity that ultimately leads to lack of movement control. Based on diffusion tensor imaging, visualizing this pathway and measuring alterations of the fiber integrity remain challenging. The objectives were to 1) develop a diffusion tensor tractography protocol for reliably tracking the nigrostriatal fibers on multicenter data; 2) test whether the integrities measured by diffusion tensor imaging of the nigrostriatal fibers are abnormal in PD; and 3) test whether abnormal integrities of the nigrostriatal fibers in PD patients are associated with the severity of motor disability and putaminal dopamine binding ratios. Diffusion tensor tractography was performed on 50 drug-naïve PD patients and 27 healthy control subjects from the international multicenter Parkinson's Progression Marker Initiative. Tractography consistently detected the nigrostriatal fibers, yielding reliable diffusion measures. Fractional anisotropy, along with radial and axial diffusivity of the nigrostriatal tract, showed systematic abnormalities in patients. In addition, variations in fractional anisotropy and radial diffusivity of the nigrostriatal tract were associated with the degree of motor deficits in PD patients. Taken together, the findings imply that the diffusion tensor imaging characteristic of the nigrostriatal tract is potentially an index for detecting and staging of early PD. © 2015 International Parkinson and Movement Disorder Society.

  16. Real-time object recognition in multidimensional images based on joined extended structural tensor and higher-order tensor decomposition methods

    Science.gov (United States)

    Cyganek, Boguslaw; Smolka, Bogdan

    2015-02-01

    In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.

  17. Real-time MR diffusion tensor and Q-ball imaging using Kalman filtering

    International Nuclear Information System (INIS)

    Poupon, C.; Roche, A.; Dubois, J.; Mangin, J.F.; Poupon, F.

    2008-01-01

    Diffusion magnetic resonance imaging (dMRI) has become an established research tool for the investigation of tissue structure and orientation. In this paper, we present a method for real-time processing of diffusion tensor and Q-ball imaging. The basic idea is to use Kalman filtering framework to fit either the linear tensor or Q-ball model. Because the Kalman filter is designed to be an incremental algorithm, it naturally enables updating the model estimate after the acquisition of any new diffusion-weighted volume. Processing diffusion models and maps during ongoing scans provides a new useful tool for clinicians, especially when it is not possible to predict how long a subject may remain still in the magnet. First, we introduce the general linear models corresponding to the two diffusion tensor and analytical Q-ball models of interest. Then, we present the Kalman filtering framework and we focus on the optimization of the diffusion orientation sets in order to speed up the convergence of the online processing. Last, we give some results on a healthy volunteer for the online tensor and the Q-ball model, and we make some comparisons with the conventional offline techniques used in the literature. We could achieve full real-time for diffusion tensor imaging and deferred time for Q-ball imaging, using a single workstation. (authors)

  18. Tensor voting for image correction by global and local intensity alignment.

    Science.gov (United States)

    Jia, Jiaya; Tang, Chi-Keung

    2005-01-01

    This paper presents a voting method to perform image correction by global and local intensity alignment. The key to our modeless approach is the estimation of global and local replacement functions by reducing the complex estimation problem to the robust 2D tensor voting in the corresponding voting spaces. No complicated model for replacement function (curve) is assumed. Subject to the monotonic constraint only, we vote for an optimal replacement function by propagating the curve smoothness constraint using a dense tensor field. Our method effectively infers missing curve segments and rejects image outliers. Applications using our tensor voting approach are proposed and described. The first application consists of image mosaicking of static scenes, where the voted replacement functions are used in our iterative registration algorithm for computing the best warping matrix. In the presence of occlusion, our replacement function can be employed to construct a visually acceptable mosaic by detecting occlusion which has large and piecewise constant color. Furthermore, by the simultaneous consideration of color matches and spatial constraints in the voting space, we perform image intensity compensation and high contrast image correction using our voting framework, when only two defective input images are given.

  19. Gaussian mixtures on tensor fields for segmentation: applications to medical imaging.

    Science.gov (United States)

    de Luis-García, Rodrigo; Westin, Carl-Fredrik; Alberola-López, Carlos

    2011-01-01

    In this paper, we introduce a new approach for tensor field segmentation based on the definition of mixtures of Gaussians on tensors as a statistical model. Working over the well-known Geodesic Active Regions segmentation framework, this scheme presents several interesting advantages. First, it yields a more flexible model than the use of a single Gaussian distribution, which enables the method to better adapt to the complexity of the data. Second, it can work directly on tensor-valued images or, through a parallel scheme that processes independently the intensity and the local structure tensor, on scalar textured images. Two different applications have been considered to show the suitability of the proposed method for medical imaging segmentation. First, we address DT-MRI segmentation on a dataset of 32 volumes, showing a successful segmentation of the corpus callosum and favourable comparisons with related approaches in the literature. Second, the segmentation of bones from hand radiographs is studied, and a complete automatic-semiautomatic approach has been developed that makes use of anatomical prior knowledge to produce accurate segmentation results. Copyright © 2010 Elsevier Ltd. All rights reserved.

  20. On Adapting the Tensor Voting Framework to Robust Color Image Denoising

    Science.gov (United States)

    Moreno, Rodrigo; Garcia, Miguel Angel; Puig, Domenec; Julià, Carme

    This paper presents an adaptation of the tensor voting framework for color image denoising, while preserving edges. Tensors are used in order to encode the CIELAB color channels, the uniformity and the edginess of image pixels. A specific voting process is proposed in order to propagate color from a pixel to its neighbors by considering the distance between pixels, the perceptual color difference (by using an optimized version of CIEDE2000), a uniformity measurement and the likelihood of the pixels being impulse noise. The original colors are corrected with those encoded by the tensors obtained after the voting process. Peak to noise ratios and visual inspection show that the proposed methodology has a better performance than state-of-the-art techniques.

  1. Comparison of Magnetic Susceptibility Tensor and Diffusion Tensor of the Brain.

    Science.gov (United States)

    Li, Wei; Liu, Chunlei

    2013-10-01

    Susceptibility tensor imaging (STI) provides a novel approach for noninvasive assessment of the white matter pathways of the brain. Using mouse brain ex vivo , we compared STI with diffusion tensor imaging (DTI), in terms of tensor values, principal tensor values, anisotropy values, and tensor orientations. Despite the completely different biophysical underpinnings, magnetic susceptibility tensors and diffusion tensors show many similarities in the tensor and principal tensor images, for example, the tensors perpendicular to the fiber direction have the highest gray-white matter contrast, and the largest principal tensor is along the fiber direction. Comparison to DTI fractional anisotropy, the susceptibility anisotropy provides much higher sensitivity to the chemical composition of the white matter, especially myelin. The high sensitivity can be further enhanced with the perfusion of ProHance, a gadolinium-based contrast agent. Regarding the tensor orientations, the direction of the largest principal susceptibility tensor agrees with that of diffusion tensors in major white matter fiber bundles. The STI fiber tractography can reconstruct the fiber pathways for the whole corpus callosum and for white matter fiber bundles that are in close contact but in different orientations. There are some differences between susceptibility and diffusion tensor orientations, which are likely due to the limitations in the current STI reconstruction. With the development of more accurate reconstruction methods, STI holds the promise for probing the white matter micro-architectures with more anatomical details and higher chemical sensitivity.

  2. Usefulness of Diffusion Tensor Imaging of White Matter in Alzheimer Disease and Vascular Dementia

    International Nuclear Information System (INIS)

    Sugihara, S.; Kinoshita, T.; Matsusue, E.; Fujii, S.; Ogawa, T.

    2004-01-01

    Purpose: To evaluate the usefulness of diffusion tensor imaging in detecting the water diffusivity caused by neuro pathological change in Alzheimer disease and vascular dementia. Material and Methods: Twenty patients with Alzheimer disease, 20 with vascular dementia, and 10 control subjects were examined. Diffusion tensor imaging applied diffusion gradient encoding in six non-collinear directions. Fractional anisotropy values were compared in the genu and splenium of the corpus callosum, and anterior and posterior white matter among the three groups. Results: In the patients with Alzheimer disease, fractional anisotropy values of the posterior white matter were significantly lower than those of controls. In patients with vascular dementia, fractional anisotropy values of the anterior white matter tended to be lower than those of the posterior white matter (P=0.07). Conclusion: Diffusion tensor imaging reflects the neuro pathological changes in the white matter, and may be useful in the diagnosis of Alzheimer disease and vascular dementia. Keywords: Alzheimer disease, .; diffusion tensor imaging, .; vascular dementia

  3. Image denoising using non linear diffusion tensors

    International Nuclear Information System (INIS)

    Benzarti, F.; Amiri, H.

    2011-01-01

    Image denoising is an important pre-processing step for many image analysis and computer vision system. It refers to the task of recovering a good estimate of the true image from a degraded observation without altering and changing useful structure in the image such as discontinuities and edges. In this paper, we propose a new approach for image denoising based on the combination of two non linear diffusion tensors. One allows diffusion along the orientation of greatest coherences, while the other allows diffusion along orthogonal directions. The idea is to track perfectly the local geometry of the degraded image and applying anisotropic diffusion mainly along the preferred structure direction. To illustrate the effective performance of our model, we present some experimental results on a test and real photographic color images.

  4. Tensor valuations and their applications in stochastic geometry and imaging

    CERN Document Server

    Kiderlen, Markus

    2017-01-01

    The purpose of this volume is to give an up-to-date introduction to tensor valuations and their applications. Starting with classical results concerning scalar-valued valuations on the families of convex bodies and convex polytopes, it proceeds to the modern theory of tensor valuations. Product and Fourier-type transforms are introduced and various integral formulae are derived. New and well-known results are presented, together with generalizations in several directions, including extensions to the non-Euclidean setting and to non-convex sets. A variety of applications of tensor valuations to models in stochastic geometry, to local stereology and to imaging are also discussed.

  5. Prediction of myelopathic level in cervical spondylotic myelopathy using diffusion tensor imaging.

    Science.gov (United States)

    Wang, Shu-Qiang; Li, Xiang; Cui, Jiao-Long; Li, Han-Xiong; Luk, Keith D K; Hu, Yong

    2015-06-01

    To investigate the use of a newly designed machine learning-based classifier in the automatic identification of myelopathic levels in cervical spondylotic myelopathy (CSM). In all, 58 normal volunteers and 16 subjects with CSM were recruited for diffusion tensor imaging (DTI) acquisition. The eigenvalues were extracted as the selected features from DTI images. Three classifiers, naive Bayesian, support vector machine, and support tensor machine, and fractional anisotropy (FA) were employed to identify myelopathic levels. The results were compared with clinical level diagnosis results and accuracy, sensitivity, and specificity were calculated to evaluate the performance of the developed classifiers. The accuracy by support tensor machine was the highest (93.62%) among the three classifiers. The support tensor machine also showed excellent capacity to identify true positives (sensitivity: 84.62%) and true negatives (specificity: 97.06%). The accuracy by FA value was the lowest (76%) in all the methods. The classifiers-based method using eigenvalues had a better performance in identifying the levels of CSM than the diagnosis using FA values. The support tensor machine was the best among three classifiers. © 2014 Wiley Periodicals, Inc.

  6. Diffusion tensor magnetic resonance imaging and fiber tractography of the sacral plexus in children with spina bifida

    DEFF Research Database (Denmark)

    Haakma, Wieke; Dik, Pieter; ten Haken, Bennie

    2014-01-01

    anatomical and microstructural properties of the sacral plexus of patients with spina bifida using diffusion tensor imaging and fiber tractography. MATERIALS AND METHODS: Ten patients 8 to 16 years old with spina bifida underwent diffusion tensor imaging on a 3 Tesla magnetic resonance imaging system...... diffusivity values at S1-S3 were significantly lower in patients. CONCLUSIONS: To our knowledge this 3 Tesla magnetic resonance imaging study showed for the first time sacral plexus asymmetry and disorganization in 10 patients with spina bifida using diffusion tensor imaging and fiber tractography...

  7. Novel region of interest interrogation technique for diffusion tensor imaging analysis in the canine brain.

    Science.gov (United States)

    Li, Jonathan Y; Middleton, Dana M; Chen, Steven; White, Leonard; Ellinwood, N Matthew; Dickson, Patricia; Vite, Charles; Bradbury, Allison; Provenzale, James M

    2017-08-01

    Purpose We describe a novel technique for measuring diffusion tensor imaging metrics in the canine brain. We hypothesized that a standard method for region of interest placement could be developed that is highly reproducible, with less than 10% difference in measurements between raters. Methods Two sets of canine brains (three seven-week-old full-brains and two 17-week-old single hemispheres) were scanned ex-vivo on a 7T small-animal magnetic resonance imaging system. Strict region of interest placement criteria were developed and then used by two raters to independently measure diffusion tensor imaging metrics within four different white-matter regions within each specimen. Average values of fractional anisotropy, radial diffusivity, and the three eigenvalues (λ1, λ2, and λ3) within each region in each specimen overall and within each individual image slice were compared between raters by calculating the percentage difference between raters for each metric. Results The mean percentage difference between raters for all diffusion tensor imaging metrics when pooled by each region and specimen was 1.44% (range: 0.01-5.17%). The mean percentage difference between raters for all diffusion tensor imaging metrics when compared by individual image slice was 2.23% (range: 0.75-4.58%) per hemisphere. Conclusion Our results indicate that the technique described is highly reproducible, even when applied to canine specimens of differing age, morphology, and image resolution. We propose this technique for future studies of diffusion tensor imaging analysis in canine brains and for cross-sectional and longitudinal studies of canine brain models of human central nervous system disease.

  8. Homogeneity based segmentation and enhancement of Diffusion Tensor Images : a white matter processing framework

    OpenAIRE

    Rodrigues, P.R.

    2011-01-01

    In diffusion magnetic resonance imaging (DMRI) the Brownian motion of the water molecules, within biological tissue, is measured through a series of images. In diffusion tensor imaging (DTI) this diffusion is represented using tensors. DTI describes, in a non-invasive way, the local anisotropy pattern enabling the reconstruction of the nervous fibers - dubbed tractography. DMRI constitutes a powerful tool to analyse the structure of the white matter within a voxel, but also to investigate the...

  9. Efficient tensor completion for color image and video recovery: Low-rank tensor train

    OpenAIRE

    Bengua, Johann A.; Phien, Ho N.; Tuan, Hoang D.; Do, Minh N.

    2016-01-01

    This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its definition from a well-balanced matricization scheme. Accordingly, new optimization formulations for tensor completion are proposed as well as two new algorithms for their solution. The first one called simple low-rank tensor completion via tensor tra...

  10. AGREEMENT BETWEEN THE WHITE MATTER CONNECTIVITY BASED ON THE TENSOR-BASED MORPHOMETRY AND THE VOLUMETRIC WHITE MATTER PARCELLATIONS BASED ON DIFFUSION TENSOR IMAGING

    OpenAIRE

    Kim, Seung-Goo; Lee, Hyekyoung; Chung, Moo K.; Hanson, Jamie L.; Avants, Brian B.; Gee, James C.; Davidson, Richard J.; Pollak, Seth D.

    2012-01-01

    We are interested in investigating white matter connectivity using a novel computational framework that does not use diffusion tensor imaging (DTI) but only uses T1-weighted magnetic resonance imaging. The proposed method relies on correlating Jacobian determinants across different voxels based on the tensor-based morphometry (TBM) framework. In this paper, we show agreement between the TBM-based white matter connectivity and the DTI-based white matter atlas. As an application, altered white ...

  11. Image processing tensor transform and discrete tomography with Matlab

    CERN Document Server

    Grigoryan, Artyom M

    2012-01-01

    Focusing on mathematical methods in computer tomography, Image Processing: Tensor Transform and Discrete Tomography with MATLAB(R) introduces novel approaches to help in solving the problem of image reconstruction on the Cartesian lattice. Specifically, it discusses methods of image processing along parallel rays to more quickly and accurately reconstruct images from a finite number of projections, thereby avoiding overradiation of the body during a computed tomography (CT) scan. The book presents several new ideas, concepts, and methods, many of which have not been published elsewhere. New co

  12. Diffusion-Weighted Imaging and Diffusion Tensor Imaging of Asymptomatic Lumbar Disc Herniation

    OpenAIRE

    Sakai, Toshinori; Miyagi, Ryo; Yamabe, Eiko; Fujinaga, Yasunari; Bhatia, Nitin N.; Yoshioka, Hiroshi

    2014-01-01

    Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) were performedon a healthy 31-year-old man with asymptomatic lumbar disc herniation. Althoughthe left S1 nerve root was obviously entrapped by a herniated mass, neither DWI nor DTI showed any significant findings for the nerve root. Decreased apparent diffusion coefficient (ADC) values and increased fractional anisotropy (FA) values were found. These results are contrary to those in previously published studies of symptomatic...

  13. Imaging Arterial Fibres Using Diffusion Tensor Imaging—Feasibility Study and Preliminary Results

    Directory of Open Access Journals (Sweden)

    Kerskens Christian

    2010-01-01

    Full Text Available Abstract MR diffusion tensor imaging (DTI was used to analyze the fibrous structure of aortic tissue. A fresh porcine aorta was imaged at 7T using a spin echo sequence with the following parameters: matrix 128 128 pixel; slice thickness 0.5 mm; interslice spacing 0.1 mm; number of slices 16; echo time 20.3 s; field of view 28 mm 28 mm. Eigenvectors from the diffusion tensor images were calculated for the central image slice and the averaged tensors and the eigenvector corresponding to the largest eigenvalue showed two distinct angles corresponding to near and to the transverse plane of the aorta. Fibre tractography within the aortic volume imaged confirmed that fibre angles were oriented helically with lead angles of and . The findings correspond to current histological and microscopy data on the fibrous structure of aortic tissue, and therefore the eigenvector maps and fibre tractography appear to reflect the alignment of the fibers in the aorta. In view of current efforts to develop noninvasive diagnostic tools for cardiovascular diseases, DTI may offer a technique to assess the structural properties of arterial tissue and hence any changes or degradation in arterial tissue.

  14. Spatial Mapping of Translational Diffusion Coefficients Using Diffusion Tensor Imaging: A Mathematical Description.

    Science.gov (United States)

    Shetty, Anil N; Chiang, Sharon; Maletic-Savatic, Mirjana; Kasprian, Gregor; Vannucci, Marina; Lee, Wesley

    2014-01-01

    In this article, we discuss the theoretical background for diffusion weighted imaging and diffusion tensor imaging. Molecular diffusion is a random process involving thermal Brownian motion. In biological tissues, the underlying microstructures restrict the diffusion of water molecules, making diffusion directionally dependent. Water diffusion in tissue is mathematically characterized by the diffusion tensor, the elements of which contain information about the magnitude and direction of diffusion and is a function of the coordinate system. Thus, it is possible to generate contrast in tissue based primarily on diffusion effects. Expressing diffusion in terms of the measured diffusion coefficient (eigenvalue) in any one direction can lead to errors. Nowhere is this more evident than in white matter, due to the preferential orientation of myelin fibers. The directional dependency is removed by diagonalization of the diffusion tensor, which then yields a set of three eigenvalues and eigenvectors, representing the magnitude and direction of the three orthogonal axes of the diffusion ellipsoid, respectively. For example, the eigenvalue corresponding to the eigenvector along the long axis of the fiber corresponds qualitatively to diffusion with least restriction. Determination of the principal values of the diffusion tensor and various anisotropic indices provides structural information. We review the use of diffusion measurements using the modified Stejskal-Tanner diffusion equation. The anisotropy is analyzed by decomposing the diffusion tensor based on symmetrical properties describing the geometry of diffusion tensor. We further describe diffusion tensor properties in visualizing fiber tract organization of the human brain.

  15. Combining voxel-based morphometry and diffusion tensor imaging to detect age-related brain changes.

    Science.gov (United States)

    Lehmbeck, Jan T; Brassen, Stefanie; Weber-Fahr, Wolfgang; Braus, Dieter F

    2006-04-03

    The present study combined optimized voxel-based morphometry and diffusion tensor imaging to detect age-related brain changes. We compared grey matter density maps (grey matter voxel-based morphometry) and white matter fractional anisotropy maps (diffusion tensor imaging-voxel-based morphometry) between two groups of 17 younger and 17 older women. Older women exhibited reduced white matter fractional anisotropy as well as decreased grey matter density most prominently in the frontal, limbic, parietal and temporal lobes. A discriminant analysis identified four frontal and limbic grey and white matter areas that separated the two groups most effectively. We conclude that grey matter voxel-based morphometry and diffusion tensor imaging voxel-based morphometry are well suited for the detection of age-related changes and their combination provides high accuracy when detecting the neural correlates of aging.

  16. AGREEMENT BETWEEN THE WHITE MATTER CONNECTIVITY BASED ON THE TENSOR-BASED MORPHOMETRY AND THE VOLUMETRIC WHITE MATTER PARCELLATIONS BASED ON DIFFUSION TENSOR IMAGING.

    Science.gov (United States)

    Kim, Seung-Goo; Lee, Hyekyoung; Chung, Moo K; Hanson, Jamie L; Avants, Brian B; Gee, James C; Davidson, Richard J; Pollak, Seth D

    2012-01-01

    We are interested in investigating white matter connectivity using a novel computational framework that does not use diffusion tensor imaging (DTI) but only uses T1-weighted magnetic resonance imaging. The proposed method relies on correlating Jacobian determinants across different voxels based on the tensor-based morphometry (TBM) framework. In this paper, we show agreement between the TBM-based white matter connectivity and the DTI-based white matter atlas. As an application, altered white matter connectivity in a clinical population is determined.

  17. Diffusion tensor imaging with direct cytopathological validation: characterisation of decorin treatment in experimental juvenile communicating hydrocephalus.

    Science.gov (United States)

    Aojula, Anuriti; Botfield, Hannah; McAllister, James Patterson; Gonzalez, Ana Maria; Abdullah, Osama; Logan, Ann; Sinclair, Alexandra

    2016-05-31

    In an effort to develop novel treatments for communicating hydrocephalus, we have shown previously that the transforming growth factor-β antagonist, decorin, inhibits subarachnoid fibrosis mediated ventriculomegaly; however decorin's ability to prevent cerebral cytopathology in communicating hydrocephalus has not been fully examined. Furthermore, the capacity for diffusion tensor imaging to act as a proxy measure of cerebral pathology in multiple sclerosis and spinal cord injury has recently been demonstrated. However, the use of diffusion tensor imaging to investigate cytopathological changes in communicating hydrocephalus is yet to occur. Hence, this study aimed to determine whether decorin treatment influences alterations in diffusion tensor imaging parameters and cytopathology in experimental communicating hydrocephalus. Moreover, the study also explored whether diffusion tensor imaging parameters correlate with cellular pathology in communicating hydrocephalus. Accordingly, communicating hydrocephalus was induced by injecting kaolin into the basal cisterns in 3-week old rats followed immediately by 14 days of continuous intraventricular delivery of either human recombinant decorin (n = 5) or vehicle (n = 6). Four rats remained as intact controls and a further four rats served as kaolin only controls. At 14-days post-kaolin, just prior to sacrifice, routine magnetic resonance imaging and magnetic resonance diffusion tensor imaging was conducted and the mean diffusivity, fractional anisotropy, radial and axial diffusivity of seven cerebral regions were assessed by voxel-based analysis in the corpus callosum, periventricular white matter, caudal internal capsule, CA1 hippocampus, and outer and inner parietal cortex. Myelin integrity, gliosis and aquaporin-4 levels were evaluated by post-mortem immunohistochemistry in the CA3 hippocampus and in the caudal brain of the same cerebral structures analysed by diffusion tensor imaging. Decorin significantly

  18. Data quality in diffusion tensor imaging studies of the preterm brain: a systematic review

    OpenAIRE

    Pieterman, Kay; Plaisier, Annemarie; Govaert, Paul; Leemans, Alexander; Lequin, Maarten H.; Dudink, Jeroen

    2015-01-01

    Background To study early neurodevelopment in preterm infants, evaluation of brain maturation and injury is increasingly performed using diffusion tensor imaging, for which the reliability of underlying data is paramount. Objective To review the literature to evaluate acquisition and processing methodology in diffusion tensor imaging studies of preterm infants. Materials and methods We searched the Embase, Medline, Web of Science and Cochrane databases for relevant papers published between 20...

  19. Imaging Arterial Fibres Using Diffusion Tensor Imaging—Feasibility Study and Preliminary Results

    Directory of Open Access Journals (Sweden)

    Ciaran K. Simms

    2010-01-01

    Full Text Available MR diffusion tensor imaging (DTI was used to analyze the fibrous structure of aortic tissue. A fresh porcine aorta was imaged at 7T using a spin echo sequence with the following parameters: matrix 128 × 128 pixel; slice thickness 0.5 mm; interslice spacing 0.1 mm; number of slices 16; echo time 20.3 s; field of view 28 mm × 28 mm. Eigenvectors from the diffusion tensor images were calculated for the central image slice and the averaged tensors and the eigenvector corresponding to the largest eigenvalue showed two distinct angles corresponding to near 0∘ and 180∘ to the transverse plane of the aorta. Fibre tractography within the aortic volume imaged confirmed that fibre angles were oriented helically with lead angles of 15±2.5∘ and 175±2.5∘. The findings correspond to current histological and microscopy data on the fibrous structure of aortic tissue, and therefore the eigenvector maps and fibre tractography appear to reflect the alignment of the fibers in the aorta. In view of current efforts to develop noninvasive diagnostic tools for cardiovascular diseases, DTI may offer a technique to assess the structural properties of arterial tissue and hence any changes or degradation in arterial tissue.

  20. Diffusion tensor imaging fiber tracking with reliable tracking orientation and flexible step size☆

    Science.gov (United States)

    Yao, Xufeng; Wang, Manning; Chen, Xinrong; Nie, Shengdong; Li, Zhexu; Xu, Xiaoping; Zhang, Xuelong; Song, Zhijian

    2013-01-01

    We propose a method of reliable tracking orientation and flexible step size fiber tracking. A new directional strategy was defined to select one optimal tracking orientation from each directional set, which was based on the single-tensor model and the two-tensor model. The directional set of planar voxels contained three tracking directions: two from the two-tensor model and one from the single-tensor model. The directional set of linear voxels contained only one principal vector. In addition, a flexible step size, rather than fixable step sizes, was implemented to improve the accuracy of fiber tracking. We used two sets of human data to assess the performance of our method; one was from a healthy volunteer and the other from a patient with low-grade glioma. Results verified that our method was superior to the single-tensor Fiber Assignment by Continuous Tracking and the two-tensor eXtended Streamline Tractography for showing detailed images of fiber bundles. PMID:25206444

  1. MR imaging and ultrasonographic findings of tensor fasciae suralis muscle: A case report

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Keun Ho; Shim, Jae Chan; Lee, Ghi Jai; Lee, Kyoung Eun; Kim, Ho Kyun; Suh, Jung Ho [Dept. of Radiology, Seoul Paik Hospital, Inje University College of Medicine, Seoul (Korea, Republic of)

    2015-10-15

    The tensor fasciae suralis muscle is a very rare anomalous muscle located in the popliteal region. This anatomic variation has been reported often through cadaver studies. However, there are only a few radiologic reports of this entity. We presented a case of tensor fasciae suralis muscle detected as an incidental finding in magnetic resonance imaging and ultrasound.

  2. A review of anisotropic conductivity models of brain white matter based on diffusion tensor imaging.

    Science.gov (United States)

    Wu, Zhanxiong; Liu, Yang; Hong, Ming; Yu, Xiaohui

    2018-06-01

    The conductivity of brain tissues is not only essential for electromagnetic source estimation (ESI), but also a key reflector of the brain functional changes. Different from the other brain tissues, the conductivity of whiter matter (WM) is highly anisotropic and a tensor is needed to describe it. The traditional electrical property imaging methods, such as electrical impedance tomography (EIT) and magnetic resonance electrical impedance tomography (MREIT), usually fail to image the anisotropic conductivity tensor of WM with high spatial resolution. The diffusion tensor imaging (DTI) is a newly developed technique that can fulfill this purpose. This paper reviews the existing anisotropic conductivity models of WM based on the DTI and discusses their advantages and disadvantages, as well as identifies opportunities for future research on this subject. It is crucial to obtain the linear conversion coefficient between the eigenvalues of anisotropic conductivity tensor and diffusion tensor, since they share the same eigenvectors. We conclude that the electrochemical model is suitable for ESI analysis because the conversion coefficient can be directly obtained from the concentration of ions in extracellular liquid and that the volume fraction model is appropriate to study the influence of WM structural changes on electrical conductivity. Graphical abstract ᅟ.

  3. Diffusion tensor imaging using multiple coils for mouse brain connectomics.

    Science.gov (United States)

    Nouls, John C; Badea, Alexandra; Anderson, Robert B J; Cofer, Gary P; Allan Johnson, G

    2018-04-19

    The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non-destructively and three-dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7-T preclinical scanner, we present a novel two-coil system in which each coil is shielded, placed off-isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal-to-noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil-dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two-coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade-offs between imaging throughput and connectivity

  4. Principles and implementation of diffusion-weighted and diffusion tensor imaging

    International Nuclear Information System (INIS)

    Roberts, Timothy P.L.; Schwartz, E.S.

    2007-01-01

    We review the physiological basis of diffusion-weighted imaging and discuss the implementation of diffusion-weighted imaging pulse sequences and the subsequent postprocessing to yield quantitative estimations of diffusion parameters. We also introduce the concept of directionality of ''apparent'' diffusion in vivo and the means of assessing such anisotropy quantitatively. This in turn leads to the methodological application of diffusion tensor imaging and the subsequent postprocessing, known as tractography. The following articles deal with the clinical applications enabled by such methodologies. (orig.)

  5. Retrospective correction of bias in diffusion tensor imaging arising from coil combination mode.

    Science.gov (United States)

    Sakaie, Ken; Lowe, Mark

    2017-04-01

    To quantify and retrospectively correct for systematic differences in diffusion tensor imaging (DTI) measurements due to differences in coil combination mode. Multi-channel coils are now standard among MRI systems. There are several options for combining signal from multiple coils during image reconstruction, including sum-of-squares (SOS) and adaptive combine (AC). This contribution examines the bias between SOS- and AC-derived measures of tissue microstructure and a strategy for limiting that bias. Five healthy subjects were scanned under an institutional review board-approved protocol. Each set of raw image data was reconstructed twice-once with SOS and once with AC. The diffusion tensor was calculated from SOS- and AC-derived data by two algorithms-standard log-linear least squares and an approach that accounts for the impact of coil combination on signal statistics. Systematic differences between SOS and AC in terms of tissue microstructure (axial diffusivity, radial diffusivity, mean diffusivity and fractional anisotropy) were evaluated on a voxel-by-voxel basis. SOS-based tissue microstructure values are systematically lower than AC-based measures throughout the brain in each subject when using the standard tensor calculation method. The difference between SOS and AC can be virtually eliminated by taking into account the signal statistics associated with coil combination. The impact of coil combination mode on diffusion tensor-based measures of tissue microstructure is statistically significant but can be corrected retrospectively. The ability to do so is expected to facilitate pooling of data among imaging protocols. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. Tensor eigenvalues and their applications

    CERN Document Server

    Qi, Liqun; Chen, Yannan

    2018-01-01

    This book offers an introduction to applications prompted by tensor analysis, especially by the spectral tensor theory developed in recent years. It covers applications of tensor eigenvalues in multilinear systems, exponential data fitting, tensor complementarity problems, and tensor eigenvalue complementarity problems. It also addresses higher-order diffusion tensor imaging, third-order symmetric and traceless tensors in liquid crystals, piezoelectric tensors, strong ellipticity for elasticity tensors, and higher-order tensors in quantum physics. This book is a valuable reference resource for researchers and graduate students who are interested in applications of tensor eigenvalues.

  7. Diffusion Tensor Imaging: Application to the Study of the Developing Brain

    Science.gov (United States)

    Cascio, Carissa J.; Gerig, Guido; Piven, Joseph

    2007-01-01

    Objective: To provide an overview of diffusion tensor imaging (DTI) and its application to the study of white matter in the developing brain in both healthy and clinical samples. Method: The development of DTI and its application to brain imaging of white matter tracts is discussed. Forty-eight studies using DTI to examine diffusion properties of…

  8. Susceptibility tensor imaging and tractography of collagen fibrils in the articular cartilage.

    Science.gov (United States)

    Wei, Hongjiang; Gibbs, Eric; Zhao, Peida; Wang, Nian; Cofer, Gary P; Zhang, Yuyao; Johnson, G Allan; Liu, Chunlei

    2017-11-01

    To investigate the B 0 orientation-dependent magnetic susceptibility of collagen fibrils within the articular cartilage and to determine whether susceptibility tensor imaging (STI) can detect the 3D collagen network within cartilage. Multiecho gradient echo datasets (100-μm isotropic resolution) were acquired from fixed porcine articular cartilage specimens at 9.4 T. The susceptibility tensor was calculated using phase images acquired at 12 or 15 different orientations relative to B 0 . The susceptibility anisotropy of the collagen fibril was quantified and diffusion tensor imaging (DTI) was compared against STI. 3D tractography was performed to visualize and track the collagen fibrils with DTI and STI. STI experiments showed the distinct and significant anisotropic magnetic susceptibility of collagen fibrils within the articular cartilage. STI can be used to measure and quantify susceptibility anisotropy maps. Furthermore, STI provides orientation information of the underlying collagen network via 3D tractography. The findings of this study demonstrate that STI can characterize the orientation variation of collagen fibrils where diffusion anisotropy fails. We believe that STI could serve as a sensitive and noninvasive marker to study the collagen fibrils microstructure. Magn Reson Med 78:1683-1690, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  9. Comparison of source moment tensor recovered by diffraction stacking migration and source time reversal imaging

    Science.gov (United States)

    Zhang, Q.; Zhang, W.

    2017-12-01

    Diffraction stacking migration is an automatic location methods and widely used in microseismic monitoring of the hydraulic fracturing. It utilizes the stacking of thousands waveform to enhance signal-to-noise ratio of weak events. For surface monitoring, the diffraction stacking method is suffered from polarity reverse among receivers due to radiation pattern of moment source. Joint determination of location and source mechanism has been proposed to overcome the polarity problem but needs significantly increased computational calculations. As an effective method to recover source moment tensor, time reversal imaging based on wave equation can locate microseismic event by using interferometry on the image to extract source position. However, the time reversal imaging is very time consuming compared to the diffraction stacking location because of wave-equation simulation.In this study, we compare the image from diffraction stacking and time reversal imaging to check if the diffraction stacking can obtain similar moment tensor as time reversal imaging. We found that image produced by taking the largest imaging value at each point along time axis does not exhibit the radiation pattern, while with the same level of calculation efficiency, the image produced for each trial origin time can generate radiation pattern similar to time reversal imaging procedure. Thus it is potential to locate the source position by the diffraction stacking method for general moment tensor sources.

  10. Diffusion tensor mode in imaging of intracranial epidermoid cysts: one step ahead of fractional anisotropy

    International Nuclear Information System (INIS)

    Jolapara, Milan; Kesavadas, Chandrasekharan; Saini, Jitender; Patro, Satya Narayan; Gupta, Arun Kumar; Kapilamoorthy, Tirur Raman; Bodhey, Narendra; Radhakrishnan, V.V.

    2009-01-01

    The signal characteristics of an epidermoid on T2-weighted imaging have been attributed to the presence of increased water content within the tumor. In this study, we explore the utility of diffusion tensor imaging (DTI) and diffusion tensor metrics (DTM) in knowing the microstructural anatomy of epidermoid cysts. DTI was performed in ten patients with epidermoid cysts. Directionally averaged mean diffusivity (D av ), exponential diffusion, and DTM-like fractional anisotropy (FA), diffusion tensor mode (mode), linear (CL), planar (CP), and spherical (CS) anisotropy were measured from the tumor as well as from the normal-looking white matter. Epidermoid cysts showed high FA. However, D av and exponential diffusion values did not show any restriction of diffusion. Diffusion tensor mode values were near -1, and CP values were high within the tumor. This suggested preferential diffusion of water molecules along a two-dimensional geometry (plane) in epidermoid cysts, which could be attributed to the parallel-layered arrangement of keratin filaments and flakes within these tumors. Thus, advanced imaging modalities like DTI with DTM can provide information regarding the microstructural anatomy of the epidermoid cysts. (orig.)

  11. Current and future diagnostic tools for traumatic brain injury: CT, conventional MRI, and diffusion tensor imaging.

    Science.gov (United States)

    Brody, David L; Mac Donald, Christine L; Shimony, Joshua S

    2015-01-01

    Brain imaging plays a key role in the assessment of traumatic brain injury. In this review, we present our perspectives on the use of computed tomography (CT), conventional magnetic resonance imaging (MRI), and newer advanced modalities such as diffusion tensor imaging. Specifically, we address assessment for immediately life-threatening intracranial lesions (noncontrast head CT), assessment of progression of intracranial lesions (noncontrast head CT), documenting intracranial abnormalities for medicolegal reasons (conventional MRI with blood-sensitive sequences), presurgical planning for post-traumatic epilepsy (high spatial resolution conventional MRI), early prognostic decision making (conventional MRI with diffusion-weighted imaging), prognostic assessment for rehabilitative planning (conventional MRI and possibly diffusion tensor imaging in the future), stratification of subjects and pharmacodynamic tracking of targeted therapies in clinical trials (specific MRI sequences or positron emission tomography (PET) ligands, e.g., diffusion tensor imaging for traumatic axonal injury). We would like to emphasize that all of these methods, especially the newer research approaches, require careful radiologic-pathologic validation for optimal interpretation. We have taken this approach in a mouse model of pericontusional traumatic axonal injury. We found that the extent of reduction in the diffusion tensor imaging parameter relative anisotropy directly correlated with the number of amyloid precursor protein (APP)-stained axonal varicosities (r(2)=0.81, p<0.0001, n=20 injured mice). Interestingly, however, the least severe contusional injuries did not result in APP-stained axonal varicosities, but did cause reduction in relative anisotropy. Clearly, both the imaging assessments and the pathologic assessments will require iterative refinement. © 2015 Elsevier B.V. All rights reserved.

  12. Experimental evaluation of electrical conductivity imaging of anisotropic brain tissues using a combination of diffusion tensor imaging and magnetic resonance electrical impedance tomography

    Energy Technology Data Exchange (ETDEWEB)

    Sajib, Saurav Z. K.; Jeong, Woo Chul; Oh, Tong In; Kim, Hyung Joong, E-mail: bmekim@khu.ac.kr, E-mail: ejwoo@khu.ac.kr; Woo, Eung Je, E-mail: bmekim@khu.ac.kr, E-mail: ejwoo@khu.ac.kr [Department of Biomedical Engineering, Kyung Hee University, Seoul 02447 (Korea, Republic of); Kyung, Eun Jung [Department of Pharmacology, Chung-Ang University, Seoul 06974 (Korea, Republic of); Kim, Hyun Bum [Department of East-West Medical Science, Kyung Hee University, Yongin 17104 (Korea, Republic of); Kwon, Oh In [Department of Mathematics, Konkuk University, Seoul 05029 (Korea, Republic of)

    2016-06-15

    Anisotropy of biological tissues is a low-frequency phenomenon that is associated with the function and structure of cell membranes. Imaging of anisotropic conductivity has potential for the analysis of interactions between electromagnetic fields and biological systems, such as the prediction of current pathways in electrical stimulation therapy. To improve application to the clinical environment, precise approaches are required to understand the exact responses inside the human body subjected to the stimulated currents. In this study, we experimentally evaluate the anisotropic conductivity tensor distribution of canine brain tissues, using a recently developed diffusion tensor-magnetic resonance electrical impedance tomography method. At low frequency, electrical conductivity of the biological tissues can be expressed as a product of the mobility and concentration of ions in the extracellular space. From diffusion tensor images of the brain, we can obtain directional information on diffusive movements of water molecules, which correspond to the mobility of ions. The position dependent scale factor, which provides information on ion concentration, was successfully calculated from the magnetic flux density, to obtain the equivalent conductivity tensor. By combining the information from both techniques, we can finally reconstruct the anisotropic conductivity tensor images of brain tissues. The reconstructed conductivity images better demonstrate the enhanced signal intensity in strongly anisotropic brain regions, compared with those resulting from previous methods using a global scale factor.

  13. Seamless warping of diffusion tensor fields

    DEFF Research Database (Denmark)

    Xu, Dongrong; Hao, Xuejun; Bansal, Ravi

    2008-01-01

    To warp diffusion tensor fields accurately, tensors must be reoriented in the space to which the tensors are warped based on both the local deformation field and the orientation of the underlying fibers in the original image. Existing algorithms for warping tensors typically use forward mapping...... of seams, including voxels in which the deformation is extensive. Backward mapping, however, cannot reorient tensors in the template space because information about the directional orientation of fiber tracts is contained in the original, unwarped imaging space only, and backward mapping alone cannot...... transfer that information to the template space. To combine the advantages of forward and backward mapping, we propose a novel method for the spatial normalization of diffusion tensor (DT) fields that uses a bijection (a bidirectional mapping with one-to-one correspondences between image spaces) to warp DT...

  14. Direct comparison of in vivo versus postmortem second-order motion-compensated cardiac diffusion tensor imaging.

    Science.gov (United States)

    Stoeck, Christian T; von Deuster, Constantin; Fleischmann, Thea; Lipiski, Miriam; Cesarovic, Nikola; Kozerke, Sebastian

    2018-04-01

    To directly compare in vivo versus postmortem second-order motion-compensated spin-echo diffusion tensor imaging of the porcine heart. Second-order motion-compensated spin-echo cardiac diffusion tensor imaging was performed during systolic contraction in vivo and repeated upon cardiac arrest by bariumchloride without repositioning of the study animal or replaning of imaging slices. In vivo and postmortem reproducibility was assessed by repeat measurements. Comparison of helix, transverse, and sheet (E2A) angulation as well as mean diffusivity and fractional anisotropy was performed. Intraclass correlation coefficients for repeated measurements (postmortem/in vivo) were 0.95/0.96 for helix, 0.70/0.66 for transverse, and 0.79/0.72 for E2A angulation; 0.83/0.72 for mean diffusivity; and 0.78/0.76 for fractional anisotropy. The corresponding 95% levels of agreement across the left ventricle were: helix 14 to 18°/12 to 15°, transverse 9 to 10°/10 to 11°, E2A 15 to 20°/16 to 18°. The 95% levels of agreement across the left ventricle for the comparison of postmortem versus in vivo were 20 to 22° for helix, 13 to 19° for transverse, and 24 to 31° for E2A angulation. Parameters derived from in vivo second-order motion-compensated spin-echo diffusion tensor imaging agreed well with postmortem imaging, indicating sufficient suppression of motion-induced signal distortions of in vivo cardiac diffusion tensor imaging. Magn Reson Med 79:2265-2276, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  15. 4.7-T diffusion tensor imaging of acute traumatic peripheral nerve injury.

    Science.gov (United States)

    Boyer, Richard B; Kelm, Nathaniel D; Riley, D Colton; Sexton, Kevin W; Pollins, Alonda C; Shack, R Bruce; Dortch, Richard D; Nanney, Lillian B; Does, Mark D; Thayer, Wesley P

    2015-09-01

    Diagnosis and management of peripheral nerve injury is complicated by the inability to assess microstructural features of injured nerve fibers via clinical examination and electrophysiology. Diffusion tensor imaging (DTI) has been shown to accurately detect nerve injury and regeneration in crush models of peripheral nerve injury, but no prior studies have been conducted on nerve transection, a surgical emergency that can lead to permanent weakness or paralysis. Acute sciatic nerve injuries were performed microsurgically to produce multiple grades of nerve transection in rats that were harvested 1 hour after surgery. High-resolution diffusion tensor images from ex vivo sciatic nerves were obtained using diffusion-weighted spin-echo acquisitions at 4.7 T. Fractional anisotropy was significantly reduced at the injury sites of transected rats compared with sham rats. Additionally, minor eigenvalues and radial diffusivity were profoundly elevated at all injury sites and were negatively correlated to the degree of injury. Diffusion tensor tractography showed discontinuities at all injury sites and significantly reduced continuous tract counts. These findings demonstrate that high-resolution DTI is a promising tool for acute diagnosis and grading of traumatic peripheral nerve injuries.

  16. Muscle changes detected with diffusion-tensor imaging after long-distance running.

    Science.gov (United States)

    Froeling, Martijn; Oudeman, Jos; Strijkers, Gustav J; Maas, Mario; Drost, Maarten R; Nicolay, Klaas; Nederveen, Aart J

    2015-02-01

    To develop a protocol for diffusion-tensor imaging (DTI) of the complete upper legs and to demonstrate feasibility of detection of subclinical sports-related muscle changes in athletes after strenuous exercise, which remain undetected by using conventional T2-weighted magnetic resonance (MR) imaging with fat suppression. The research was approved by the institutional ethics committee review board, and the volunteers provided written consent before the study. Five male amateur long-distance runners underwent an MR examination (DTI, T1-weighted MR imaging, and T2-weighted MR imaging with fat suppression) of both upper legs 1 week before, 2 days after, and 3 weeks after they participated in a marathon. The tensor eigenvalues (λ1, λ2, and λ3), the mean diffusivity, and the fractional anisotropy (FA) were derived from the DTI data. Data per muscle from the three time-points were compared by using a two-way mixed-design analysis of variance with a Bonferroni posthoc test. The DTI protocol allowed imaging of both complete upper legs with adequate signal-to-noise ratio and within a 20-minute imaging time. After the marathon, T2-weighted MR imaging revealed grade 1 muscle strains in nine of the 180 investigated muscles. The three eigenvalues, mean diffusivity, and FA were significantly increased (P DTI measurements of the upper legs was developed that fully included frequently injured muscles, such as hamstrings, in one single imaging session. This study also revealed changes in DTI parameters that over time were not revealed by qualitative T2-weighted MR imaging with fat suppression. © RSNA, 2014.

  17. Diffusion-tensor MR imaging of gray and white matter development during normal human brain maturation.

    Science.gov (United States)

    Mukherjee, Pratik; Miller, Jeffrey H; Shimony, Joshua S; Philip, Joseph V; Nehra, Deepika; Snyder, Abraham Z; Conturo, Thomas E; Neil, Jeffrey J; McKinstry, Robert C

    2002-10-01

    Conventional MR imaging findings of human brain development are thought to result from decreasing water content, increasing macromolecular concentration, and myelination. We use diffusion-tensor MR imaging to test theoretical models that incorporate hypotheses regarding how these maturational processes influence water diffusion in developing gray and white matter. Experimental data were derived from diffusion-tensor imaging of 167 participants, ages 31 gestational weeks to 11 postnatal years. An isotropic diffusion model was applied to the gray matter of the basal ganglia and thalamus. A model that assumes changes in the magnitude of diffusion while maintaining cylindrically symmetric anisotropy was applied to the white matter of the corpus callosum and internal capsule. Deviations of the diffusion tensor from the ideal model predictions, due to measurement noise, were estimated by using Monte Carlo simulations. Developing gray matter of the basal ganglia and developing white matter of the internal capsule and corpus callosum largely conformed to theory, with only small departures from model predictions in older children. However, data from the thalamus substantially diverged from predicted values, with progressively larger deviations from the model with increasing participant age. Changes in water diffusion during maturation of central gray and white matter structures can largely be explained by theoretical models incorporating simple assumptions regarding the influence of brain water content and myelination, although deviations from theory increase as the brain matures. Diffusion-tensor MR imaging is a powerful method for studying the process of brain development, with both scientific and clinical applications.

  18. Diffusion tensor imaging of occult injury of optic radiation following optic neuritis in multiple sclerosis.

    Science.gov (United States)

    Chen, Jiafeng; Zhu, Lijun; Li, He; Lu, Ziwen; Chen, Xin; Fang, Shaokuan

    2016-10-01

    Multiple sclerosis (MS) is easily detected by routine magnetic resonance imaging (MRI). However, it is not possible to detect early or occult lesions in MS by routine MRI, and this may explain the inconsistency between the severity of the lesions found by MRI and the degree of clinical disability of patients with MS. The present study included 10 patients with relapsing-remitting MS and 10 healthy volunteers. Each patient underwent routine 3.0 T MRI, diffusion tensor imaging (DTI), and diffusion tensor tractography (DTT). Optic nerve and optic radiation were analyzed by DTI and DTT. The fractional anisotropy (FA), mean diffusivity (MD), λ // , and λ ┴ values were measured. In the 10 patients with MS, 7 optic nerves were affected, and 13 optic nerves were not affected. Cranial MRI showed that optic nerve thickening and hyperintensity occurred in 2 patients with MS. In the directionally encoded color maps, a hypointensive green signal in the optic nerve was observed in 3 patients with MS. The FA values were significantly lower and the MD, λ // , and λ ┴ values were significantly higher in the affected and unaffected optic nerves and optic radiations in patients with MS in comparison with controls (P0.05). Diffusion tensor imaging is sensitive in the detection of occult injury of the optic nerve and optic radiation following optic neuritis. Diffusion tensor imaging may be a useful tool for the early diagnosis, treatment and management of MS.

  19. An introduction to visualization of diffusion tensor imaging and its applications

    NARCIS (Netherlands)

    Vilanova, A.; Zhang, S.; Kindlmann, G.; Laidlaw, D.H.; Weickert, J.; Hagen, H.

    2005-01-01

    Summary. Water diffusion is anisotropic in organized tissues such as white matter and muscle. Diffusion tensor imaging (DTI), a non-invasive MR technique, measures water self-diffusion rates and thus gives an indication of the underlying tissue microstructure. The diffusion rate is often expressed

  20. Generalized tensor-based morphometry of HIV/AIDS using multivariate statistics on deformation tensors.

    Science.gov (United States)

    Lepore, N; Brun, C; Chou, Y Y; Chiang, M C; Dutton, R A; Hayashi, K M; Luders, E; Lopez, O L; Aizenstein, H J; Toga, A W; Becker, J T; Thompson, P M

    2008-01-01

    This paper investigates the performance of a new multivariate method for tensor-based morphometry (TBM). Statistics on Riemannian manifolds are developed that exploit the full information in deformation tensor fields. In TBM, multiple brain images are warped to a common neuroanatomical template via 3-D nonlinear registration; the resulting deformation fields are analyzed statistically to identify group differences in anatomy. Rather than study the Jacobian determinant (volume expansion factor) of these deformations, as is common, we retain the full deformation tensors and apply a manifold version of Hotelling's $T(2) test to them, in a Log-Euclidean domain. In 2-D and 3-D magnetic resonance imaging (MRI) data from 26 HIV/AIDS patients and 14 matched healthy subjects, we compared multivariate tensor analysis versus univariate tests of simpler tensor-derived indices: the Jacobian determinant, the trace, geodesic anisotropy, and eigenvalues of the deformation tensor, and the angle of rotation of its eigenvectors. We detected consistent, but more extensive patterns of structural abnormalities, with multivariate tests on the full tensor manifold. Their improved power was established by analyzing cumulative p-value plots using false discovery rate (FDR) methods, appropriately controlling for false positives. This increased detection sensitivity may empower drug trials and large-scale studies of disease that use tensor-based morphometry.

  1. Diffusion Tensor Imaging Correlates of Reading Ability in Dysfluent and Non-Impaired Readers

    Science.gov (United States)

    Lebel, Catherine; Shaywitz, Bennett; Holahan, John; Shaywitz, Sally; Marchione, Karen; Beaulieu, Christian

    2013-01-01

    Many children and adults have specific reading disabilities; insight into the brain structure underlying these difficulties is evolving from imaging. Previous research highlights the left temporal-parietal white matter as important in reading, yet the degree of involvement of other areas remains unclear. Diffusion tensor imaging (DTI) and…

  2. TensorLy: Tensor Learning in Python

    NARCIS (Netherlands)

    Kossaifi, Jean; Panagakis, Yannis; Pantic, Maja

    2016-01-01

    Tensor methods are gaining increasing traction in machine learning. However, there are scant to no resources available to perform tensor learning and decomposition in Python. To answer this need we developed TensorLy. TensorLy is a state of the art general purpose library for tensor learning.

  3. Tensor-based Dictionary Learning for Spectral CT Reconstruction

    Science.gov (United States)

    Zhang, Yanbo; Wang, Ge

    2016-01-01

    Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628

  4. Tensor-Based Dictionary Learning for Spectral CT Reconstruction.

    Science.gov (United States)

    Zhang, Yanbo; Mou, Xuanqin; Wang, Ge; Yu, Hengyong

    2017-01-01

    Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods.

  5. Comparison of quality control software tools for diffusion tensor imaging.

    Science.gov (United States)

    Liu, Bilan; Zhu, Tong; Zhong, Jianhui

    2015-04-01

    Image quality of diffusion tensor imaging (DTI) is critical for image interpretation, diagnostic accuracy and efficiency. However, DTI is susceptible to numerous detrimental artifacts that may impair the reliability and validity of the obtained data. Although many quality control (QC) software tools are being developed and are widely used and each has its different tradeoffs, there is still no general agreement on an image quality control routine for DTIs, and the practical impact of these tradeoffs is not well studied. An objective comparison that identifies the pros and cons of each of the QC tools will be helpful for the users to make the best choice among tools for specific DTI applications. This study aims to quantitatively compare the effectiveness of three popular QC tools including DTI studio (Johns Hopkins University), DTIprep (University of North Carolina at Chapel Hill, University of Iowa and University of Utah) and TORTOISE (National Institute of Health). Both synthetic and in vivo human brain data were used to quantify adverse effects of major DTI artifacts to tensor calculation as well as the effectiveness of different QC tools in identifying and correcting these artifacts. The technical basis of each tool was discussed, and the ways in which particular techniques affect the output of each of the tools were analyzed. The different functions and I/O formats that three QC tools provide for building a general DTI processing pipeline and integration with other popular image processing tools were also discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Diffusion tensor imaging, white matter lesions, the corpus callosum, and gait in the elderly

    Science.gov (United States)

    Gait impairment is common in the elderly, especially affected by stroke and white matter hyper intensities found in conventional brain magnetic resonance imaging (MRI). Diffusion tensor imaging (DTI) is more sensitive to white matter damage than conventional MRI. The relationship between DTI measure...

  7. Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain.

    Science.gov (United States)

    Lanzafame, S; Giannelli, M; Garaci, F; Floris, R; Duggento, A; Guerrisi, M; Toschi, N

    2016-05-01

    An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate model- and algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter. The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value =0 and b-value =1000 s/mm(2) data while the DKI model was fitted to data comprising b-value =0, 1000 and 3000/2500 s/mm(2) [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition to MK/RK/AK maps, MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms. DKI-derived MD/FA/RD/AD and MO estimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK

  8. Shape anisotropy: tensor distance to anisotropy measure

    Science.gov (United States)

    Weldeselassie, Yonas T.; El-Hilo, Saba; Atkins, M. S.

    2011-03-01

    Fractional anisotropy, defined as the distance of a diffusion tensor from its closest isotropic tensor, has been extensively studied as quantitative anisotropy measure for diffusion tensor magnetic resonance images (DT-MRI). It has been used to reveal the white matter profile of brain images, as guiding feature for seeding and stopping in fiber tractography and for the diagnosis and assessment of degenerative brain diseases. Despite its extensive use in DT-MRI community, however, not much attention has been given to the mathematical correctness of its derivation from diffusion tensors which is achieved using Euclidean dot product in 9D space. But, recent progress in DT-MRI has shown that the space of diffusion tensors does not form a Euclidean vector space and thus Euclidean dot product is not appropriate for tensors. In this paper, we propose a novel and robust rotationally invariant diffusion anisotropy measure derived using the recently proposed Log-Euclidean and J-divergence tensor distance measures. An interesting finding of our work is that given a diffusion tensor, its closest isotropic tensor is different for different tensor distance metrics used. We demonstrate qualitatively that our new anisotropy measure reveals superior white matter profile of DT-MR brain images and analytically show that it has a higher signal to noise ratio than fractional anisotropy.

  9. Assessment of axonal degeneration in Alzheimer's disease with diffusion tensor MRI; Diffusion tensor imaging zur Erfassung axonaler Degeneration bei Morbus Alzheimer

    Energy Technology Data Exchange (ETDEWEB)

    Stahl, R. [Institut fuer Klinische Radiologie - Grosshadern, Klinikum der Universitaet Muenchen (Germany); Institut fuer Klinische Radiologie - Grosshadern, Klinikum der Universitaet Muenchen, Marchioninistr. 15, 81377, Muenchen (Germany); Dietrich, O.; Reiser, M.F.; Schoenberg, S.O. [Institut fuer Klinische Radiologie - Grosshadern, Klinikum der Universitaet Muenchen (Germany); Teipel, S.; Hampel, H. [Klinik fuer Psychiatrie und Psychotherapie, Klinikum der Universitaet Muenchen (Germany)

    2003-07-01

    Alzheimer disease (AD) causes cortical degeneration with subsequent degenerative changes of the white matter. The aim of this study was to investigate the extent of white matter tissue damage of patients with Alzheimer's disease in comparison with healthy subjects using diffusion tensor MRI (DTI). The value of integrated parallel imaging techniques (iPAT) for reduction of image distortion was assessed. We studied 9 patients with mild AD and 10 age and gender matched healthy controls. DTI brain scans were obtained on a 1.5 tesla system (Siemens Magnetom Sonata) using parallel imaging (iPAT) and an EPI diffusion sequence with TE/TR 71 ms/6000 ms. We used an 8-element head coil and a GRAPPA reconstruction algorithm with an acceleration factor of 2. From the tensor, the mean diffusivity (D), the fractional anisotropy (FA), and the relative anisotropy (RA) of several white matter regions were determined. FA was significantly lower (p <0,05) in the white matter of the genu of corpus callosum from patients with AD than in the corresponding regions from healthy controls. There was a trend observed for slightly higher ADC values in the AD group (p=0,06). No significant changes were observed in the regions of the splenium, internal capsule, pericallosal areas, frontal, temporal, parietal, and occipital lobe. The images obtained with iPAT contained substantially less susceptibility artefacts and were less distorted than images acquired with non-parallel imaging technique. DTI is a method with potential to assess early stages of white matter damage in vivo. The altered FA and ADC values in the genu of corpus callosum of patients with AD presumably reflect the microscopic white matter degeneration. Acquisition time can be reduced by iPAT methods with less image distortion from susceptibility artefacts resulting in a more accurate calculation of the diffusion tensor. (orig.) [German] Bei der Alzheimer-Erkrankung (AD) kommt es zur kortikalen Degeneration und sekundaer zu

  10. Diffusion Tensor Imaging of Heterotopia: Changes of Fractional Anisotropy during Radial Migration of Neurons

    Science.gov (United States)

    Kim, Jinna

    2010-01-01

    Purpose Diffusion tensor imaging provides better understanding of pathophysiology of congenital anomalies, involving central nervous system. This study was aimed to specify the pathogenetic mechanism of heterotopia, proved by diffusion tensor imaging, and establish new findings of heterotopia on fractional anisotropy maps. Materials and Methods Diffusion-weighted imaging data from 11 patients (M : F = 7 : 4, aged from 1 to 22 years, mean = 12.3 years) who visited the epilepsy clinic and received a routine seizure protocol MRI exam were retrospectively analyzed. Fractional anisotropy (FA) maps were generated from diffusion tensor imaging of 11 patients with heterotopia. Regions of interests (ROI) were placed in cerebral cortex, heterotopic gray matter and deep gray matter, including putamen. ANOVA analysis was performed for comparison of different gray matter tissues. Results Heterotopic gray matter showed signal intensities similar to normal gray matter on T1 and T2 weighted MRI. The measured FA of heterotopic gray matter was higher than that of cortical gray matter (0.236 ± 0.011 vs. 0.169 ± 0.015, p < 0.01, one way ANOVA), and slightly lower than that of deep gray matter (0.236 ± 0.011 vs. 0.259 ± 0.016, p < 0.01). Conclusion Increased FA of heterotopic gray matter suggests arrested neuron during radial migration and provides better understanding of neurodevelopment. PMID:20499428

  11. TensorLy: Tensor Learning in Python

    OpenAIRE

    Kossaifi, Jean; Panagakis, Yannis; Pantic, Maja

    2016-01-01

    Tensors are higher-order extensions of matrices. While matrix methods form the cornerstone of machine learning and data analysis, tensor methods have been gaining increasing traction. However, software support for tensor operations is not on the same footing. In order to bridge this gap, we have developed \\emph{TensorLy}, a high-level API for tensor methods and deep tensorized neural networks in Python. TensorLy aims to follow the same standards adopted by the main projects of the Python scie...

  12. A diffusion tensor imaging tractography algorithm based on Navier-Stokes fluid mechanics.

    Science.gov (United States)

    Hageman, Nathan S; Toga, Arthur W; Narr, Katherine L; Shattuck, David W

    2009-03-01

    We introduce a fluid mechanics based tractography method for estimating the most likely connection paths between points in diffusion tensor imaging (DTI) volumes. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow through the DTI image volume. We then estimate the most likely connection paths between points in the DTI volume using a metric derived from the fluid velocity vector field. We validate our algorithm using digital DTI phantoms based on a helical shape. Our method segmented the structure of the phantom with less distortion than was produced using implementations of heat-based partial differential equation (PDE) and streamline based methods. In addition, our method was able to successfully segment divergent and crossing fiber geometries, closely following the ideal path through a digital helical phantom in the presence of multiple crossing tracts. To assess the performance of our algorithm on anatomical data, we applied our method to DTI volumes from normal human subjects. Our method produced paths that were consistent with both known anatomy and directionally encoded color images of the DTI dataset.

  13. Changes in lumbosacral spinal nerve roots on diffusion tensor imaging in spinal stenosis

    OpenAIRE

    Zhong-jun Hou; Yong Huang; Zi-wen Fan; Xin-chun Li; Bing-yi Cao

    2015-01-01

    Lumbosacral degenerative disc disease is a common cause of lower back and leg pain. Conventional T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) scans are commonly used to image spinal cord degeneration. However, these modalities are unable to image the entire lumbosacral spinal nerve roots. Thus, in the present study, we assessed the potential of diffusion tensor imaging (DTI) for quantitative assessment of compressed lumbosacral spinal nerve roots. Subjects were 20 young healthy v...

  14. In-utero three dimension high resolution fetal brain diffusion tensor imaging.

    Science.gov (United States)

    Jiang, Shuzhou; Xue, Hui; Counsell, Serena; Anjari, Mustafa; Allsop, Joanna; Rutherford, Mary; Rueckert, Daniel; Hajnal, Joseph V

    2007-01-01

    We present a methodology to achieve 3D high resolution in-utero fetal brain DTI that shows excellent ADC as well as promising FA maps. After continuous DTI scanning to acquire a repeated series of parallel slices with 15 diffusion directions, image registration is used to realign the images to correct for fetal motion. Once aligned, the diffusion images are treated as irregularly sampled data where each voxel is associated with an appropriately rotated diffusion direction, and used to estimate the diffusion tensor on a regular grid. The method has been tested successful on eight fetuses and has been validated on adults imaged at 1.5T.

  15. Diffusion tensor imaging. Theory, sequence optimization and application in Alzheimer's disease

    International Nuclear Information System (INIS)

    Stieltjes, B.; Schlueter, M.; Hahn, H.K.; Wilhelm, T.; Essig, M.

    2003-01-01

    Diffusion tensor imaging (DTI) offers an in vivo view into the microarchitecture of the brain. Furthermore it allows a three-dimensional reconstruction of fiber tracts. We will discuss the principles of DTI and possibilities for sequence optimization. Finally we will give an overview of DTI and its application in Alzheimer's disease. (orig.) [de

  16. Sparse alignment for robust tensor learning.

    Science.gov (United States)

    Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Zhao, Cairong; Sun, Mingming

    2014-10-01

    Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods, L1- and L2-norms are introduced to enhance the robustness in the alignment step of the STA. The advantage of the proposed technique is that the difficulty in selecting the size of the local neighborhood can be avoided in the manifold learning based tensor feature extraction algorithms. Although STA is an unsupervised learning method, the sparsity encodes the discriminative information in the alignment step and provides the robustness of STA. Extensive experiments on the well-known image databases as well as action and hand gesture databases by encoding object images as tensors demonstrate that the proposed STA algorithm gives the most competitive performance when compared with the tensor-based unsupervised learning methods.

  17. Road detection in SAR images using a tensor voting algorithm

    Science.gov (United States)

    Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian

    2007-11-01

    In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.

  18. Determination of mouse skeletal muscle architecture using three dimensional diffusion tensor imaging

    NARCIS (Netherlands)

    Heemskerk, A.M.; Strijkers, G.J.; Vilanova, A.; Drost, M.R.; Nicolaij, K.

    2005-01-01

    Muscle architecture is the main determinant of the mechanical behavior of skeletal muscles. This study explored the feasibility of diffusion tensor imaging (DTI) and fiber tracking to noninvasively determine the in vivo three-dimensional (3D) architecture of skeletal muscle in mouse hind leg. In six

  19. Determination of mouse skeletal muscle architecture using three-dimensional diffusion tensor imaging

    NARCIS (Netherlands)

    Heemskerk, Anneriet M.; Strijkers, Gustav J.; Vilanova, Anna; Drost, Maarten R.; Nicolay, Klaas

    2005-01-01

    Muscle architecture is the main determinant of the mechanical behavior of skeletal muscles. This study explored the feasibility of diffusion tensor imaging (DTI) and fiber tracking to noninvasively determine the in vivo three-dimensional (3D) architecture of skeletal muscle in mouse hind leg. In six

  20. Diagnosis of Lumbar Foraminal Stenosis using Diffusion Tensor Imaging

    OpenAIRE

    Eguchi, Yawara; Ohtori, Seiji; Suzuki, Munetaka; Oikawa, Yasuhiro; Yamanaka, Hajime; Tamai, Hiroshi; Kobayashi, Tatsuya; Orita, Sumihisa; Yamauchi, Kazuyo; Suzuki, Miyako; Aoki, Yasuchika; Watanabe, Atsuya; Kanamoto, Hirohito; Takahashi, Kazuhisa

    2016-01-01

    Diagnosis of lumbar foraminal stenosis remains difficult. Here, we report on a case in which bilateral lumbar foraminal stenosis was difficult to diagnose, and in which diffusion tensor imaging (DTI) was useful. The patient was a 52-year-old woman with low back pain and pain in both legs that was dominant on the right. Right lumbosacral nerve compression due to a massive uterine myoma was apparent, but the leg pain continued after a myomectomy was performed. No abnormalities were observed dur...

  1. Harmonization of multi-site diffusion tensor imaging data.

    Science.gov (United States)

    Fortin, Jean-Philippe; Parker, Drew; Tunç, Birkan; Watanabe, Takanori; Elliott, Mark A; Ruparel, Kosha; Roalf, David R; Satterthwaite, Theodore D; Gur, Ruben C; Gur, Raquel E; Schultz, Robert T; Verma, Ragini; Shinohara, Russell T

    2017-11-01

    Diffusion tensor imaging (DTI) is a well-established magnetic resonance imaging (MRI) technique used for studying microstructural changes in the white matter. As with many other imaging modalities, DTI images suffer from technical between-scanner variation that hinders comparisons of images across imaging sites, scanners and over time. Using fractional anisotropy (FA) and mean diffusivity (MD) maps of 205 healthy participants acquired on two different scanners, we show that the DTI measurements are highly site-specific, highlighting the need of correcting for site effects before performing downstream statistical analyses. We first show evidence that combining DTI data from multiple sites, without harmonization, may be counter-productive and negatively impacts the inference. Then, we propose and compare several harmonization approaches for DTI data, and show that ComBat, a popular batch-effect correction tool used in genomics, performs best at modeling and removing the unwanted inter-site variability in FA and MD maps. Using age as a biological phenotype of interest, we show that ComBat both preserves biological variability and removes the unwanted variation introduced by site. Finally, we assess the different harmonization methods in the presence of different levels of confounding between site and age, in addition to test robustness to small sample size studies. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Application of diffusion tensor imaging in neurosurgery; Anwendung der Diffusions-Tensor-Bildgebung in der Neurochirurgie

    Energy Technology Data Exchange (ETDEWEB)

    Saur, R. [Sektion fuer Experimentelle Kernspinresonanz des ZNS, Abt. Neuroradiologie, Universitaetsklinikum Tuebingen (Germany); Augenklinik des Universitaetsklinikums Tuebingen (Germany); Klinik fuer Psychiatrie und Psychotherapie des Universitaetsklinikums Tuebingen (Germany); Gharabaghi, A. [Klinik fuer Neurochirurgie des Universitaetsklinikums Tuebingen (Germany); Erb, M. [Sektion fuer Experimentelle Kernspinresonanz des ZNS, Abt. Neuroradiologie, Universitaetsklinikum Tuebingen (Germany)

    2007-07-01

    Knowledge about integrity and location of fibre tracts arising from eloquent cortical areas is important to plan neurosurgical interventions and to allow maximization of resection of pathological tissue while preserving vital white matter tracts. Diffusion Tensor Imaging (DTI) is so far the only method to get preoperatively an impression of the individual complexity of nerve bundles. Thereby nerve fibres are not mapped directly. They are derived indirectly by analysis of the directional distribution of diffusion of water molecules which is influenced mainly by large fibre tracts. From acquisition to reconstruction and visualisation of the fibre tracts many representational stages and working steps have to be passed. Exact knowledge about problems of Diffusion Imaging is important for interpretation of the results. Particularly, brain tumor edema, intraoperative brain shift, MR-artefacts and limitations of the mathematical models and algorithms challenge DTI-developers and applicants. (orig.)

  3. Altered brain microstructure assessed by diffusion tensor imaging in patients with chronic pancreatitis

    DEFF Research Database (Denmark)

    Frøkjær, Jens Brøndum; Olesen, Søren Schou; Gram, Mikkel

    2011-01-01

    Objective In patients with painful chronic pancreatitis (CP) there is increasing evidence of abnormal pain processing in the central nervous system. Using magnetic resonance (MR) diffusion tensor imaging, brain microstructure in areas involved in processing of visceral pain was characterised...

  4. Feasibility of Diffusion Tensor Imaging for Assessing Functional Recovery in Rats with Olfactory Ensheathing Cell Transplantation After Contusive Spinal Cord Injury (SCI).

    Science.gov (United States)

    Gu, Mengchao; Gao, Zhengchao; Li, Xiaohui; Zhao, Feng; Guo, Lei; Liu, Jiantao; He, Xijing

    2017-06-17

    BACKGROUND Olfactory ensheathing cell transplantation is a promising treatment for spinal cord injury. Diffusion tensor imaging has been applied to assess various kinds of spinal cord injury. However, it has rarely been used to evaluate the beneficial effects of olfactory ensheathing cell transplantation. This study aimed to explore the feasibility of diffusion tensor imaging in the evaluation of functional recovery in rats with olfactory ensheathing cell transplantation after contusive spinal cord injury. MATERIAL AND METHODS Immunofluorescence staining was performed to determine the purity of olfactory ensheathing cells. Rats received cell transplantation at week 1 after injury. Basso, Beattie, and Bresnahan score was used to assess the functional recovery. Magnetic resonance imaging was applied weekly, including diffusion tensor imaging. Diffusion tensor tractography was reconstructed to visualize the repair process. RESULTS The results showed that olfactory ensheathing cell transplantation increased the functional and histological recovery and restrained the secondary injury process after the initial spinal cord injury. The fractional anisotropy values in rats with cell transplantation were significantly higher than those in the control group, while the apparent diffusion coefficient values were significantly lower. Basso, Beattie, and Bresnahan score was positively and linearly correlated with fractional anisotropy value, and it was negatively and linearly correlated with apparent diffusion coefficient value. CONCLUSIONS These findings suggest that diffusion tensor imaging parameters are sensitive biomarker indices for olfactory ensheathing cell transplantation interventions, and diffusion tensor imaging scan can reflect the functional recovery promoted by the olfactory ensheathing cell transplantation after contusive spinal cord injury.

  5. The relationship between functional magnetic resonance imaging activation, diffusion tensor imaging, and training effects.

    Science.gov (United States)

    Farrar, Danielle; Budson, Andrew E

    2017-04-01

    While the relationship between diffusion tensor imaging (DTI) measurements and training effects is explored by Voelker et al. (this issue), a cursory discussion of functional magnetic resonance imaging (fMRI) measurements categorizes increased activation with findings of greater white matter integrity. Evidence of the relationship between fMRI activation and white matter integrity is conflicting, as is the relationship between fMRI activation and training effects. An examination of the changes in fMRI activation in response to training is helpful, but the relationship between DTI and fMRI activation, particularly in the context of white matter changes, must be examined further before general conclusions can be drawn.

  6. Diagnosis of Lumbar Foraminal Stenosis using Diffusion Tensor Imaging.

    Science.gov (United States)

    Eguchi, Yawara; Ohtori, Seiji; Suzuki, Munetaka; Oikawa, Yasuhiro; Yamanaka, Hajime; Tamai, Hiroshi; Kobayashi, Tatsuya; Orita, Sumihisa; Yamauchi, Kazuyo; Suzuki, Miyako; Aoki, Yasuchika; Watanabe, Atsuya; Kanamoto, Hirohito; Takahashi, Kazuhisa

    2016-02-01

    Diagnosis of lumbar foraminal stenosis remains difficult. Here, we report on a case in which bilateral lumbar foraminal stenosis was difficult to diagnose, and in which diffusion tensor imaging (DTI) was useful. The patient was a 52-year-old woman with low back pain and pain in both legs that was dominant on the right. Right lumbosacral nerve compression due to a massive uterine myoma was apparent, but the leg pain continued after a myomectomy was performed. No abnormalities were observed during nerve conduction studies. Computed tomography and magnetic resonance imaging indicated bilateral L5 lumbar foraminal stenosis. DTI imaging was done. The extraforaminal values were decreased and tractography was interrupted in the foraminal region. Bilateral L5 vertebral foraminal stenosis was treated by transforaminal lumbar interbody fusion and the pain in both legs disappeared. The case indicates the value of DTI for diagnosing vertebral foraminal stenosis.

  7. Impact of Gradient Number and Voxel Size on Diffusion Tensor Imaging Tractography for Resective Brain Surgery

    NARCIS (Netherlands)

    Hoefnagels, Friso W. A.; de Witt Hamer, Philip C.; Pouwels, Petra J. W.; Barkhof, Frederik; Vandertop, W. Peter

    2017-01-01

    To explore quantitatively and qualitatively how the number of gradient directions (NGD) and spatial resolution (SR) affect diffusion tensor imaging (DTI) tractography in patients planned for brain tumor surgery, using routine clinical magnetic resonance imaging protocols. Of 67 patients with

  8. Diffusion tensor imaging for target volume definition in glioblastoma multiforme

    Energy Technology Data Exchange (ETDEWEB)

    Berberat, Jatta; Remonda, Luca [Cantonal Hospital, Department of Neuro-radiology, Aarau (Switzerland); McNamara, Jane; Rogers, Susanne [Cantonal Hospital, Department of Radiation Oncology, Aarau (Switzerland); Bodis, Stephan [Cantonal Hospital, Department of Radiation Oncology, Aarau (Switzerland); University Hospital, Department of Radiation Oncology, Zurich (Switzerland)

    2014-10-15

    Diffusion tensor imaging (DTI) is an MR-based technique that may better detect the peritumoural region than MRI. Our aim was to explore the feasibility of using DTI for target volume delineation in glioblastoma patients. MR tensor tracts and maps of the isotropic (p) and anisotropic (q) components of water diffusion were coregistered with CT in 13 glioblastoma patients. An in-house image processing program was used to analyse water diffusion in each voxel of interest in the region of the tumour. Tumour infiltration was mapped according to validated criteria and contralateral normal brain was used as an internal control. A clinical target volume (CTV) was generated based on the T{sub 1}-weighted image obtained using contrast agent (T{sub 1Gd}), tractography and the infiltration map. This was compared to a conventional T{sub 2}-weighted CTV (T{sub 2}-w CTV). Definition of a diffusion-based CTV that included the adjacent white matter tracts proved highly feasible. A statistically significant difference was detected between the DTI-CTV and T{sub 2}-w CTV volumes (p < 0.005, t = 3.480). As the DTI-CTVs were smaller than the T{sub 2}-w CTVs (tumour plus peritumoural oedema), the pq maps were not simply detecting oedema. Compared to the clinical planning target volume (PTV), the DTI-PTV showed a trend towards volume reduction. These diffusion-based volumes were smaller than conventional volumes, yet still included sites of tumour recurrence. Extending the CTV along the abnormal tensor tracts in order to preserve coverage of the likely routes of dissemination, whilst sparing uninvolved brain, is a rational approach to individualising radiotherapy planning for glioblastoma patients. (orig.) [German] Die Diffusions-Tensor-Bildgebung (DTI) ist eine MR-Technik, die dank der Erfassung des peritumoralen Bereichs eine Verbesserung bezueglich MRI bringt. Unser Ziel war die Pruefung der Machbarkeit der Verwendung der DTI fuer die Zielvolumenabgrenzung fuer Patienten mit

  9. Imaging of postthalamic visual fiber tracts by anisotropic diffusion weighted MRI and diffusion tensor imaging: principles and applications

    International Nuclear Information System (INIS)

    Reinges, Marcus H.T.; Schoth, Felix; Coenen, Volker A.; Krings, Timo

    2004-01-01

    Diffusion weighted MRI offers the possibility to study the course of the cerebral white matter tracts. In the present manuscript, the basics, the technique and the limitations of diffusion tensor imaging and anisotropic diffusion weighted MRI are presented and their applications in various neurological and neurosurgical diseases are discussed with special emphasis on the visual system. A special focus is laid on the combination of fiber tract imaging, anatomical imaging and functional MRI for presurgical planning and intraoperative neuronavigation of lesions near the visual system

  10. Mean template for tensor-based morphometry using deformation tensors.

    Science.gov (United States)

    Leporé, Natasha; Brun, Caroline; Pennec, Xavier; Chou, Yi-Yu; Lopez, Oscar L; Aizenstein, Howard J; Becker, James T; Toga, Arthur W; Thompson, Paul M

    2007-01-01

    Tensor-based morphometry (TBM) studies anatomical differences between brain images statistically, to identify regions that differ between groups, over time, or correlate with cognitive or clinical measures. Using a nonlinear registration algorithm, all images are mapped to a common space, and statistics are most commonly performed on the Jacobian determinant (local expansion factor) of the deformation fields. In, it was shown that the detection sensitivity of the standard TBM approach could be increased by using the full deformation tensors in a multivariate statistical analysis. Here we set out to improve the common space itself, by choosing the shape that minimizes a natural metric on the deformation tensors from that space to the population of control subjects. This method avoids statistical bias and should ease nonlinear registration of new subjects data to a template that is 'closest' to all subjects' anatomies. As deformation tensors are symmetric positive-definite matrices and do not form a vector space, all computations are performed in the log-Euclidean framework. The control brain B that is already the closest to 'average' is found. A gradient descent algorithm is then used to perform the minimization that iteratively deforms this template and obtains the mean shape. We apply our method to map the profile of anatomical differences in a dataset of 26 HIV/AIDS patients and 14 controls, via a log-Euclidean Hotelling's T2 test on the deformation tensors. These results are compared to the ones found using the 'best' control, B. Statistics on both shapes are evaluated using cumulative distribution functions of the p-values in maps of inter-group differences.

  11. Simultaneous analysis and quality assurance for diffusion tensor imaging.

    Directory of Open Access Journals (Sweden)

    Carolyn B Lauzon

    Full Text Available Diffusion tensor imaging (DTI enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio. However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70% while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA

  12. Diffusion tensor imaging correlates with lesion volume in cerebral hemisphere infarctions

    International Nuclear Information System (INIS)

    Rossi, Maija E; Jason, Eeva; Marchesotti, Silvia; Dastidar, Prasun; Ollikainen, Jyrki; Soimakallio, Seppo

    2010-01-01

    Both a large lesion volume and abnormalities in diffusion tensor imaging are independently associated with a poor prognosis after cerebral infarctions. Therefore, we assume that they are associated. This study assessed the associations between lesion volumes and diffusion tensor imaging in patients with a right-sided cerebral infarction. The lesion volumes of 33 patients (age 65.9 ± 8.7, 26 males and 7 females) were imaged using computed tomography (CT) in the acute phase (within 3-4 hours) and magnetic resonance imaging (MRI) in the chronic phase (follow-up at 12 months, with a range of 8-27 months). The chronic-phase fractional anisotropy (FA) and mean diffusivity (MD) values were measured at the site of the infarct and selected white matter tracts. Neurological tests in both the acute and chronic phases, and DTI lateralization were assessed with the Wilcoxon signed-rank test. The effects of thrombolytic therapy (n = 10) were assessed with the Mann-Whitney U test. The correlations between the measured parameters were analysed with Spearman's rho correlation. Bonferroni post-hoc correction was used to compensate for the familywise error rate in multiple comparisons. Several MD values in the right hemisphere correlated positively and FA values negatively with the lesion volumes. These correlations included both lesion area and healthy tissue. The results of the mini-mental state examination and the National Institutes of Health Stroke Scale also correlated with the lesion volume. A larger infarct volume is associated with more pronounced tissue modifications in the chronic stage as observed with the MD and FA alterations

  13. Motion-robust diffusion tensor acquisition at routine 3T magnetic resonance imaging

    International Nuclear Information System (INIS)

    Yasmin, Hasina; Abe, Osamu; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Kabasawa, Hiroyuki; Aoki, Shigeki

    2010-01-01

    We compared different acquisition and reconstruction methods in phantom and human studies in the clinical setting to validate our hypothesis that optimizing the k-space acquisition and reconstruction method could decrease motion artifacts. Diffusion tensor images of a water phantom were obtained with three table displacement magnitudes: 1 mm, 2 mm, and 3 mm. Images were reconstructed using homodyne and zero-fill reconstruction. Overscanning in 8- and 16-k y lines was tested. We performed visual assessment of the artifacts using reconstructed coronal images and analyzed them with Wilcoxon signed-ranks test both for phantom and human studies. Also, fractional anisotropy (FA) changes between acquisition methods were compared. Artifacts due to smaller displacement (1 and 2 mm) were significantly reduced in 16-k y overscan with zero filling. The Wilcoxon signed-ranks test showed significant differences (P<0.031 for reconstruction methods and P<0.016 for overscanning methods). FA changes were statistically significant (P<0.037; Student's t-test). The Wilcoxon signed-ranks test showed significant reductions (P<0.005) in the human study. Motion-induced artifacts can be reduced by optimizing acquisition and reconstruction methods. The techniques described in this study offer an effective method for robust estimation of diffusion tensor in the presence of motion-related artifactual data points. (author)

  14. Glioma grade assessment by using histogram analysis of diffusion tensor imaging-derived maps

    International Nuclear Information System (INIS)

    Jakab, Andras; Berenyi, Ervin; Molnar, Peter; Emri, Miklos

    2011-01-01

    Current endeavors in neuro-oncology include morphological validation of imaging methods by histology, including molecular and immunohistochemical techniques. Diffusion tensor imaging (DTI) is an up-to-date methodology of intracranial diagnostics that has gained importance in studies of neoplasia. Our aim was to assess the feasibility of discriminant analysis applied to histograms of preoperative diffusion tensor imaging-derived images for the prediction of glioma grade validated by histomorphology. Tumors of 40 consecutive patients included 13 grade II astrocytomas, seven oligoastrocytomas, six grade II oligodendrogliomas, three grade III oligoastrocytomas, and 11 glioblastoma multiformes. Preoperative DTI data comprised: unweighted (B 0 ) images, fractional anisotropy, longitudinal and radial diffusivity maps, directionally averaged diffusion-weighted imaging, and trace images. Sampling consisted of generating histograms for gross tumor volumes; 25 histogram bins per scalar map were calculated. The histogram bins that allowed the most precise determination of low-grade (LG) or high-grade (HG) classification were selected by multivariate discriminant analysis. Accuracy of the model was defined by the success rate of the leave-one-out cross-validation. Statistical descriptors of voxel value distribution did not differ between LG and HG tumors and did not allow classification. The histogram model had 88.5% specificity and 85.7% sensitivity in the separation of LG and HG gliomas; specificity was improved when cases with oligodendroglial components were omitted. Constructing histograms of preoperative radiological images over the tumor volume allows representation of the grade and enables discrimination of LG and HG gliomas which has been confirmed by histopathology. (orig.)

  15. The Value of Neurosurgical and Intraoperative Magnetic Resonance Imaging and Diffusion Tensor Imaging Tractography in Clinically Integrated Neuroanatomy Modules: A Cross-Sectional Study

    Science.gov (United States)

    Familiari, Giuseppe; Relucenti, Michela; Heyn, Rosemarie; Baldini, Rossella; D'Andrea, Giancarlo; Familiari, Pietro; Bozzao, Alessandro; Raco, Antonino

    2013-01-01

    Neuroanatomy is considered to be one of the most difficult anatomical subjects for students. To provide motivation and improve learning outcomes in this area, clinical cases and neurosurgical images from diffusion tensor imaging (DTI) tractographies produced using an intraoperative magnetic resonance imaging apparatus (MRI/DTI) were presented and…

  16. Probing white-matter microstructure with higher-order diffusion tensors and susceptibility tensor MRI

    Science.gov (United States)

    Liu, Chunlei; Murphy, Nicole E.; Li, Wei

    2012-01-01

    Diffusion MRI has become an invaluable tool for studying white matter microstructure and brain connectivity. The emergence of quantitative susceptibility mapping and susceptibility tensor imaging (STI) has provided another unique tool for assessing the structure of white matter. In the highly ordered white matter structure, diffusion MRI measures hindered water mobility induced by various tissue and cell membranes, while susceptibility sensitizes to the molecular composition and axonal arrangement. Integrating these two methods may produce new insights into the complex physiology of white matter. In this study, we investigated the relationship between diffusion and magnetic susceptibility in the white matter. Experiments were conducted on phantoms and human brains in vivo. Diffusion properties were quantified with the diffusion tensor model and also with the higher order tensor model based on the cumulant expansion. Frequency shift and susceptibility tensor were measured with quantitative susceptibility mapping and susceptibility tensor imaging. These diffusion and susceptibility quantities were compared and correlated in regions of single fiber bundles and regions of multiple fiber orientations. Relationships were established with similarities and differences identified. It is believed that diffusion MRI and susceptibility MRI provide complementary information of the microstructure of white matter. Together, they allow a more complete assessment of healthy and diseased brains. PMID:23507987

  17. Contemporary imaging of mild TBI: the journey toward diffusion tensor imaging to assess neuronal damage.

    Science.gov (United States)

    Fox, W Christopher; Park, Min S; Belverud, Shawn; Klugh, Arnett; Rivet, Dennis; Tomlin, Jeffrey M

    2013-04-01

    To follow the progression of neuroimaging as a means of non-invasive evaluation of mild traumatic brain injury (mTBI) in order to provide recommendations based on reproducible, defined imaging findings. A comprehensive literature review and analysis of contemporary published articles was performed to study the progression of neuroimaging findings as a non-invasive 'biomarker' for mTBI. Multiple imaging modalities exist to support the evaluation of patients with mTBI, including ultrasound (US), computed tomography (CT), single photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetic resonance imaging (MRI). These techniques continue to evolve with the development of fractional anisotropy (FA), fiber tractography (FT), and diffusion tensor imaging (DTI). Modern imaging techniques, when applied in the appropriate clinical setting, may serve as a valuable tool for diagnosis and management of patients with mTBI. An understanding of modern neuroanatomical imaging will enhance our ability to analyse injury and recognize the manifestations of mTBI.

  18. Mean magnetic susceptibility regularized susceptibility tensor imaging (MMSR-STI) for estimating orientations of white matter fibers in human brain.

    Science.gov (United States)

    Li, Xu; van Zijl, Peter C M

    2014-09-01

    An increasing number of studies show that magnetic susceptibility in white matter fibers is anisotropic and may be described by a tensor. However, the limited head rotation possible for in vivo human studies leads to an ill-conditioned inverse problem in susceptibility tensor imaging (STI). Here we suggest the combined use of limiting the susceptibility anisotropy to white matter and imposing morphology constraints on the mean magnetic susceptibility (MMS) for regularizing the STI inverse problem. The proposed MMS regularized STI (MMSR-STI) method was tested using computer simulations and in vivo human data collected at 3T. The fiber orientation estimated from both the STI and MMSR-STI methods was compared to that from diffusion tensor imaging (DTI). Computer simulations show that the MMSR-STI method provides a more accurate estimation of the susceptibility tensor than the conventional STI approach. Similarly, in vivo data show that use of the MMSR-STI method leads to a smaller difference between the fiber orientation estimated from STI and DTI for most selected white matter fibers. The proposed regularization strategy for STI can improve estimation of the susceptibility tensor in white matter. © 2014 Wiley Periodicals, Inc.

  19. Data quality in diffusion tensor imaging studies of the preterm brain : a systematic review

    NARCIS (Netherlands)

    Pieterman, Kay; Plaisier, Annemarie; Govaert, Paul; Leemans, A; Lequin, Maarten H.; Dudink, Jeroen

    BACKGROUND: To study early neurodevelopment in preterm infants, evaluation of brain maturation and injury is increasingly performed using diffusion tensor imaging, for which the reliability of underlying data is paramount. OBJECTIVE: To review the literature to evaluate acquisition and processing

  20. Dynamics of chaotic maps for modelling the multifractal spectrum of human brain Diffusion Tensor Images

    International Nuclear Information System (INIS)

    Provata, A.; Katsaloulis, P.; Verganelakis, D.A.

    2012-01-01

    Highlights: ► Calculation of human brain multifractal spectra. ► Calculations are based on Diffusion Tensor MRI Images. ► Spectra are modelled by coupled Ikeda map dynamics. ► Coupled lattice Ikeda maps model well only positive multifractal spectra. ► Appropriately modified coupled lattice Ikeda maps give correct spectra. - Abstract: The multifractal spectra of 3d Diffusion Tensor Images (DTI) obtained by magnetic resonance imaging of the human brain are studied. They are shown to deviate substantially from artificial brain images with the same white matter intensity. All spectra, obtained from 12 healthy subjects, show common characteristics indicating non-trivial moments of the intensity. To model the spectra the dynamics of the chaotic Ikeda map are used. The DTI multifractal spectra for positive q are best approximated by 3d coupled Ikeda maps in the fully developed chaotic regime. The coupling constants are as small as α = 0.01. These results reflect not only the white tissue non-trivial architectural complexity in the human brain, but also demonstrate the presence and importance of coupling between neuron axons. The architectural complexity is also mirrored by the deviations in the negative q-spectra, where the rare events dominate. To obtain a good agreement in the DTI negative q-spectrum of the brain with the Ikeda dynamics, it is enough to slightly modify the most rare events of the coupled Ikeda distributions. The representation of Diffusion Tensor Images with coupled Ikeda maps is not unique: similar conclusions are drawn when other chaotic maps (Tent, Logistic or Henon maps) are employed in the modelling of the neuron axons network.

  1. Combining Diffusion Tensor Metrics and DSC Perfusion Imaging: Can It Improve the Diagnostic Accuracy in Differentiating Tumefactive Demyelination from High-Grade Glioma?

    Science.gov (United States)

    Hiremath, S B; Muraleedharan, A; Kumar, S; Nagesh, C; Kesavadas, C; Abraham, M; Kapilamoorthy, T R; Thomas, B

    2017-04-01

    Tumefactive demyelinating lesions with atypical features can mimic high-grade gliomas on conventional imaging sequences. The aim of this study was to assess the role of conventional imaging, DTI metrics ( p:q tensor decomposition), and DSC perfusion in differentiating tumefactive demyelinating lesions and high-grade gliomas. Fourteen patients with tumefactive demyelinating lesions and 21 patients with high-grade gliomas underwent brain MR imaging with conventional, DTI, and DSC perfusion imaging. Imaging sequences were assessed for differentiation of the lesions. DTI metrics in the enhancing areas and perilesional hyperintensity were obtained by ROI analysis, and the relative CBV values in enhancing areas were calculated on DSC perfusion imaging. Conventional imaging sequences had a sensitivity of 80.9% and specificity of 57.1% in differentiating high-grade gliomas ( P = .049) from tumefactive demyelinating lesions. DTI metrics ( p : q tensor decomposition) and DSC perfusion demonstrated a statistically significant difference in the mean values of ADC, the isotropic component of the diffusion tensor, the anisotropic component of the diffusion tensor, the total magnitude of the diffusion tensor, and rCBV among enhancing portions in tumefactive demyelinating lesions and high-grade gliomas ( P ≤ .02), with the highest specificity for ADC, the anisotropic component of the diffusion tensor, and relative CBV (92.9%). Mean fractional anisotropy values showed no significant statistical difference between tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI and DSC parameters improved the diagnostic accuracy (area under the curve = 0.901). Addition of a heterogeneous enhancement pattern to DTI and DSC parameters improved it further (area under the curve = 0.966). The sensitivity increased from 71.4% to 85.7% after the addition of the enhancement pattern. DTI and DSC perfusion add profoundly to conventional imaging in differentiating tumefactive

  2. Use of diffusion tensor imaging to identify similarities and differences between cerebellar and Parkinsonism forms of multiple system atrophy

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Po-Shan [National Yang-Ming University, Department of Neurology, School of Medicine, Taipei (China); Taipei Veterans General Hospital, Neurological Institute, Taipei (China); Taipei Municipal Gan-Dau Hospital, Neurological Institute, Taipei (China); National Yang-Ming University, Institute of Brain Science, Taipei (China); Wu, Hsiu-Mei [National Yang-Ming University, Department of Neurology, School of Medicine, Taipei (China); Taipei Veterans General Hospital, Department of Radiology, Taipei (China); Lin, Ching-Po [National Yang-Ming University, Institute of Brain Science, Taipei (China); Soong, Bing-Wen [National Yang-Ming University, Department of Neurology, School of Medicine, Taipei (China); Taipei Veterans General Hospital, Neurological Institute, Taipei (China)

    2011-07-15

    We performed diffusion tensor imaging to determine if multiple system atrophy (MSA)-cerebellar (C) and MSA-Parkinsonism (P) show similar changes, as shown in pathological studies. Nineteen patients with MSA-C, 12 patients with MSA-P, 20 patients with Parkinson disease, and 20 healthy controls were evaluated with the use of voxel-based morphometry analysis of diffusion tensor imaging. There was an increase in apparent diffusion coefficient values in the middle cerebellar peduncles and cerebellum and a decrease in fractional anisotropy in the pyramidal tract, middle cerebellar peduncles, and white matter of the cerebellum in patients with MSA-C and MSA-P compared to the controls (P<0.001). In addition, isotropic diffusion-weighted image values were reduced in the cerebellar cortex and deep cerebellar nuclei in patients with MSA-C and increased in the basal ganglia in patients with MSA-P. These results indicate that despite their disparate clinical manifestations, patients with MSA-C and MSA-P share similar diffusion tensor imaging features in the infratentorial region. Further, the combination of FA, ADC and iDWI images can be used to distinguish between MSA (either form) and Parkinson disease, which has potential therapeutic implications. (orig.)

  3. Use of diffusion tensor imaging to identify similarities and differences between cerebellar and Parkinsonism forms of multiple system atrophy

    International Nuclear Information System (INIS)

    Wang, Po-Shan; Wu, Hsiu-Mei; Lin, Ching-Po; Soong, Bing-Wen

    2011-01-01

    We performed diffusion tensor imaging to determine if multiple system atrophy (MSA)-cerebellar (C) and MSA-Parkinsonism (P) show similar changes, as shown in pathological studies. Nineteen patients with MSA-C, 12 patients with MSA-P, 20 patients with Parkinson disease, and 20 healthy controls were evaluated with the use of voxel-based morphometry analysis of diffusion tensor imaging. There was an increase in apparent diffusion coefficient values in the middle cerebellar peduncles and cerebellum and a decrease in fractional anisotropy in the pyramidal tract, middle cerebellar peduncles, and white matter of the cerebellum in patients with MSA-C and MSA-P compared to the controls (P<0.001). In addition, isotropic diffusion-weighted image values were reduced in the cerebellar cortex and deep cerebellar nuclei in patients with MSA-C and increased in the basal ganglia in patients with MSA-P. These results indicate that despite their disparate clinical manifestations, patients with MSA-C and MSA-P share similar diffusion tensor imaging features in the infratentorial region. Further, the combination of FA, ADC and iDWI images can be used to distinguish between MSA (either form) and Parkinson disease, which has potential therapeutic implications. (orig.)

  4. Use of diffusion tensor imaging to identify similarities and differences between cerebellar and Parkinsonism forms of multiple system atrophy.

    Science.gov (United States)

    Wang, Po-Shan; Wu, Hsiu-Mei; Lin, Ching-Po; Soong, Bing-Wen

    2011-07-01

    We performed diffusion tensor imaging to determine if multiple system atrophy (MSA)-cerebellar (C) and MSA-Parkinsonism (P) show similar changes, as shown in pathological studies. Nineteen patients with MSA-C, 12 patients with MSA-P, 20 patients with Parkinson disease, and 20 healthy controls were evaluated with the use of voxel-based morphometry analysis of diffusion tensor imaging. There was an increase in apparent diffusion coefficient values in the middle cerebellar peduncles and cerebellum and a decrease in fractional anisotropy in the pyramidal tract, middle cerebellar peduncles, and white matter of the cerebellum in patients with MSA-C and MSA-P compared to the controls (P < 0.001). In addition, isotropic diffusion-weighted image values were reduced in the cerebellar cortex and deep cerebellar nuclei in patients with MSA-C and increased in the basal ganglia in patients with MSA-P. These results indicate that despite their disparate clinical manifestations, patients with MSA-C and MSA-P share similar diffusion tensor imaging features in the infratentorial region. Further, the combination of FA, ADC and iDWI images can be used to distinguish between MSA (either form) and Parkinson disease, which has potential therapeutic implications.

  5. Assessment of the Log-Euclidean Metric Performance in Diffusion Tensor Image Segmentation

    Directory of Open Access Journals (Sweden)

    Mostafa Charmi

    2010-06-01

    Full Text Available Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep impact on Diffusion Tensor Image (DTI segmentation results. The geodesic metric is the best distance measure since it yields high-quality segmentation results. However, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. The main goal of this paper is to assess the possible substitution of the geodesic metric with the Log-Euclidean one to reduce the computational cost of a statistical surface evolution algorithm. Materials and Methods: We incorporated the Log-Euclidean metric in the statistical surface evolution algorithm framework. To achieve this goal, the statistics and gradients of diffusion tensor images were defined using the Log-Euclidean metric. Numerical implementation of the segmentation algorithm was performed in the MATLAB software using the finite difference techniques. Results: In the statistical surface evolution framework, the Log-Euclidean metric was able to discriminate the torus and helix patterns in synthesis datasets and rat spinal cords in biological phantom datasets from the background better than the Euclidean and J-divergence metrics. In addition, similar results were obtained with the geodesic metric. However, the main advantage of the Log-Euclidean metric over the geodesic metric was the dramatic reduction of computational cost of the segmentation algorithm, at least by 70 times. Discussion and Conclusion: The qualitative and quantitative results have shown that the Log-Euclidean metric is a good substitute for the geodesic metric when using a statistical surface evolution algorithm in DTIs segmentation.

  6. Vessel Enhancement and Segmentation of 4D CT Lung Image Using Stick Tensor Voting

    Science.gov (United States)

    Cong, Tan; Hao, Yang; Jingli, Shi; Xuan, Yang

    2016-12-01

    Vessel enhancement and segmentation plays a significant role in medical image analysis. This paper proposes a novel vessel enhancement and segmentation method for 4D CT lung image using stick tensor voting algorithm, which focuses on addressing the vessel distortion issue of vessel enhancement diffusion (VED) method. Furthermore, the enhanced results are easily segmented using level-set segmentation. In our method, firstly, vessels are filtered using Frangi's filter to reduce intrapulmonary noises and extract rough blood vessels. Secondly, stick tensor voting algorithm is employed to estimate the correct direction along the vessel. Then the estimated direction along the vessel is used as the anisotropic diffusion direction of vessel in VED algorithm, which makes the intensity diffusion of points locating at the vessel wall be consistent with the directions of vessels and enhance the tubular features of vessels. Finally, vessels can be extracted from the enhanced image by applying level-set segmentation method. A number of experiments results show that our method outperforms traditional VED method in vessel enhancement and results in satisfied segmented vessels.

  7. Reducing surgical levels by paraspinal mapping and diffusion tensor imaging techniques in lumbar spinal stenosis

    OpenAIRE

    Chen, Hua-Biao; Wan, Qi; Xu, Qi-Feng; Chen, Yi; Bai, Bo

    2016-01-01

    Background Correlating symptoms and physical examination findings with surgical levels based on common imaging results is not reliable. In patients who have no concordance between radiological and clinical symptoms, the surgical levels determined by conventional magnetic resonance imaging (MRI) and neurogenic examination (NE) may lead to a more extensive surgery and significant complications. We aimed to confirm that whether the use of diffusion tensor imaging (DTI) and paraspinal mapping (PM...

  8. Tensor voting for robust color edge detection

    OpenAIRE

    Moreno, Rodrigo; García, Miguel Ángel; Puig, Domenec

    2014-01-01

    The final publication is available at Springer via http://dx.doi.org/10.1007/978-94-007-7584-8_9 This chapter proposes two robust color edge detection methods based on tensor voting. The first method is a direct adaptation of the classical tensor voting to color images where tensors are initialized with either the gradient or the local color structure tensor. The second method is based on an extension of tensor voting in which the encoding and voting processes are specifically tailored to ...

  9. The Disruption of Geniculocalcarine Tract in Occipital Neoplasm: A Diffusion Tensor Imaging Study

    Directory of Open Access Journals (Sweden)

    Yan Zhang

    2016-01-01

    Full Text Available Aim. Investigate the disruption of geniculocalcarine tract (GCT in different occipital neoplasm by diffusion tensor imaging (DTI. Methods. Thirty-two subjects (44.1 ± 3.6 years who had single occipital neoplasm (9 gliomas, 6 meningiomas, and 17 metastatic tumors with ipsilateral GCT involved and thirty healthy subjects (39.2 ± 3.3 years underwent conventional sequences scanning and diffusion tensor imaging by a 1.5T MR scanner. The diffusion-sensitive gradient direction is 13. Compare the fractional anisotropy (FA and mean diffusivity (MD values of healthy GCT with the corresponding values of GCT in peritumoral edema area. Perform diffusion tensor tractography (DTT on GCT by the line propagation technique in all subjects. Results. The FA values of GCT in peritumoral edema area decreased (P=0.001 while the MD values increased (P=0.002 when compared with healthy subjects. There was no difference in the FA values across tumor types (P=0.114 while the MD values of GCT in the metastatic tumor group were higher than the other groups (P=0.001. GCTs were infiltrated in all the 9 gliomas cases, with displacement in 2 cases and disruption in 7 cases. GCTs were displaced in 6 meningiomas cases. GCTs were displaced in all the 7 metastatic cases, with disruption in 7 cases. Conclusions. DTI represents valid markers for evaluating GCT’s disruption in occipital neoplasm. The disruption of GCT varies according to the properties of neoplasm.

  10. Real-time image-based B-mode ultrasound image simulation of needles using tensor-product interpolation.

    Science.gov (United States)

    Zhu, Mengchen; Salcudean, Septimiu E

    2011-07-01

    In this paper, we propose an interpolation-based method for simulating rigid needles in B-mode ultrasound images in real time. We parameterize the needle B-mode image as a function of needle position and orientation. We collect needle images under various spatial configurations in a water-tank using a needle guidance robot. Then we use multidimensional tensor-product interpolation to simulate images of needles with arbitrary poses and positions using collected images. After further processing, the interpolated needle and seed images are superimposed on top of phantom or tissue image backgrounds. The similarity between the simulated and the real images is measured using a correlation metric. A comparison is also performed with in vivo images obtained during prostate brachytherapy. Our results, carried out for both the convex (transverse plane) and linear (sagittal/para-sagittal plane) arrays of a trans-rectal transducer indicate that our interpolation method produces good results while requiring modest computing resources. The needle simulation method we present can be extended to the simulation of ultrasound images of other wire-like objects. In particular, we have shown that the proposed approach can be used to simulate brachytherapy seeds.

  11. Corticospinal tract degeneration and possible pathogenesis in ALS evaluated by MR diffusion tensor imaging

    DEFF Research Database (Denmark)

    Karlsborg, Merete; Rosenbaum, Sverre; Wiegell, Mette R.

    2004-01-01

    BACKGROUND: MR diffusion tensor imaging (DTI) appears to be a powerful method to investigate the neuronal and axonal fibre distribution in the human brain. Changes in diffusion characteristics of water molecules in the white matter can be estimated as the apparent diffusion coefficient (ADC...

  12. Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to Tensor Recovery.

    Science.gov (United States)

    Xie, Qi; Zhao, Qian; Meng, Deyu; Xu, Zongben

    2017-08-02

    It is well known that the sparsity/low-rank of a vector/matrix can be rationally measured by nonzero-entries-number ($l_0$ norm)/nonzero- singular-values-number (rank), respectively. However, data from real applications are often generated by the interaction of multiple factors, which obviously cannot be sufficiently represented by a vector/matrix, while a high order tensor is expected to provide more faithful representation to deliver the intrinsic structure underlying such data ensembles. Unlike the vector/matrix case, constructing a rational high order sparsity measure for tensor is a relatively harder task. To this aim, in this paper we propose a measure for tensor sparsity, called Kronecker-basis-representation based tensor sparsity measure (KBR briefly), which encodes both sparsity insights delivered by Tucker and CANDECOMP/PARAFAC (CP) low-rank decompositions for a general tensor. Then we study the KBR regularization minimization (KBRM) problem, and design an effective ADMM algorithm for solving it, where each involved parameter can be updated with closed-form equations. Such an efficient solver makes it possible to extend KBR to various tasks like tensor completion and tensor robust principal component analysis. A series of experiments, including multispectral image (MSI) denoising, MSI completion and background subtraction, substantiate the superiority of the proposed methods beyond state-of-the-arts.

  13. Studying Dynamic Myofiber Aggregate Reorientation in Dilated Cardiomyopathy Using In Vivo Magnetic Resonance Diffusion Tensor Imaging.

    Science.gov (United States)

    von Deuster, Constantin; Sammut, Eva; Asner, Liya; Nordsletten, David; Lamata, Pablo; Stoeck, Christian T; Kozerke, Sebastian; Razavi, Reza

    2016-10-01

    The objective of this study is to assess the dynamic alterations of myocardial microstructure and strain between diastole and systole in patients with dilated cardiomyopathy relative to healthy controls using the magnetic resonance diffusion tensor imaging, myocardial tagging, and biomechanical modeling. Dual heart-phase diffusion tensor imaging was successfully performed in 9 patients and 9 controls. Tagging data were acquired for the diffusion tensor strain correction and cardiac motion analysis. Mean diffusivity, fractional anisotropy, and myocyte aggregate orientations were compared between both cohorts. Cardiac function was assessed by left ventricular ejection fraction, torsion, and strain. Computational modeling was used to study the impact of cardiac shape on fiber reorientation and how fiber orientations affect strain. In patients with dilated cardiomyopathy, a more longitudinal orientation of diastolic myofiber aggregates was measured compared with controls. Although a significant steepening of helix angles (HAs) during contraction was found in the controls, consistent change in HAs during contraction was absent in patients. Left ventricular ejection fraction, cardiac torsion, and strain were significantly lower in the patients compared with controls. Computational modeling revealed that the dilated heart results in reduced HA changes compared with a normal heart. Reduced torsion was found to be exacerbated by steeper HAs. Diffusion tensor imaging revealed reduced reorientation of myofiber aggregates during cardiac contraction in patients with dilated cardiomyopathy relative to controls. Left ventricular remodeling seems to be an important factor in the changes to myocyte orientation. Steeper HAs are coupled with a worsening in strain and torsion. Overall, the findings provide new insights into the structural alterations in patients with dilated cardiomyopathy. © 2016 The Authors.

  14. The effects of noise over the complete space of diffusion tensor shape.

    Science.gov (United States)

    Gahm, Jin Kyu; Kindlmann, Gordon; Ennis, Daniel B

    2014-01-01

    Diffusion tensor magnetic resonance imaging (DT-MRI) is a technique used to quantify the microstructural organization of biological tissues. Multiple images are necessary to reconstruct the tensor data and each acquisition is subject to complex thermal noise. As such, measures of tensor invariants, which characterize components of tensor shape, derived from the tensor data will be biased from their true values. Previous work has examined this bias, but over a narrow range of tensor shape. Herein, we define the mathematics for constructing a tensor from tensor invariants, which permits an intuitive and principled means for building tensors with a complete range of tensor shape and salient microstructural properties. Thereafter, we use this development to evaluate by simulation the effects of noise on characterizing tensor shape over the complete space of tensor shape for three encoding schemes with different SNR and gradient directions. We also define a new framework for determining the distribution of the true values of tensor invariants given their measures, which provides guidance about the confidence the observer should have in the measures. Finally, we present the statistics of tensor invariant estimates over the complete space of tensor shape to demonstrate how the noise sensitivity of tensor invariants varies across the space of tensor shape as well as how the imaging protocol impacts measures of tensor invariants. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. 3D reconstruction of tensors and vectors

    International Nuclear Information System (INIS)

    Defrise, Michel; Gullberg, Grant T.

    2005-01-01

    Here we have developed formulations for the reconstruction of 3D tensor fields from planar (Radon) and line-integral (X-ray) projections of 3D vector and tensor fields. Much of the motivation for this work is the potential application of MRI to perform diffusion tensor tomography. The goal is to develop a theory for the reconstruction of both Radon planar and X-ray or line-integral projections because of the flexibility of MRI to obtain both of these type of projections in 3D. The development presented here for the linear tensor tomography problem provides insight into the structure of the nonlinear MRI diffusion tensor inverse problem. A particular application of tensor imaging in MRI is the potential application of cardiac diffusion tensor tomography for determining in vivo cardiac fiber structure. One difficulty in the cardiac application is the motion of the heart. This presents a need for developing future theory for tensor tomography in a motion field. This means developing a better understanding of the MRI signal for diffusion processes in a deforming media. The techniques developed may allow the application of MRI tensor tomography for the study of structure of fiber tracts in the brain, atherosclerotic plaque, and spine in addition to fiber structure in the heart. However, the relations presented are also applicable to other fields in medical imaging such as diffraction tomography using ultrasound. The mathematics presented can also be extended to exponential Radon transform of tensor fields and to other geometric acquisitions such as cone beam tomography of tensor fields

  16. Diffusion-weighted imaging and diffusion tensor imaging of asymptomatic lumbar disc herniation.

    Science.gov (United States)

    Sakai, Toshinori; Miyagi, Ryo; Yamabe, Eiko; Fujinaga, Yasunari; N Bhatia, Nitin; Yoshioka, Hiroshi

    2014-01-01

    Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) were performed on a healthy 31-year-old man with asymptomatic lumbar disc herniation. Although the left S1 nerve root was obviously entrapped by a herniated mass, neither DWI nor DTI showed any significant findings for the nerve root. Decreased apparent diffusion coefficient (ADC) values and increased fractional anisotropy (FA) values were found. These results are contrary to those in previously published studies of symptomatic patients, in which a combination of increased ADC and decreased FA seem to have a relationship with nerve injury and subsequent symptoms, such as leg pain or palsy. Our results seen in an asymptomatic subject suggest that the compressed nerve with no injury, such as edema, demyelination, or persistent axonal injury, may be indicated by a combination of decreased ADC and increased FA. ADC and FA could therefore be potential tools to elucidate the pathomechanism of radiculopathy.

  17. Dictionary-Based Tensor Canonical Polyadic Decomposition

    Science.gov (United States)

    Cohen, Jeremy Emile; Gillis, Nicolas

    2018-04-01

    To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed which enables high dimensional tensors dictionary-based canonical polyadic decomposition. The benefits of using a dictionary in tensor decomposition models are explored both in terms of parameter identifiability and estimation accuracy. Performances of the proposed algorithms are evaluated on the decomposition of simulated data and the unmixing of hyperspectral images.

  18. Diffusion tensor imaging and diffusion tensor imaging-fibre tractograph depict the mechanisms of Broca-like and Wernicke-like conduction aphasia.

    Science.gov (United States)

    Song, Xinjie; Dornbos, David; Lai, Zongli; Zhang, Yumei; Li, Tieshan; Chen, Hongyan; Yang, Zhonghua

    2011-06-01

    Conduction aphasia is usually considered a result of damage of the arcuate fasciculus, which is subjacent to the parietal portion of the supra-marginal gyrus and the upper part of the insula. It is important to stress that many features of conduction aphasia relate to a cortical deficit, more than a pure disconnection mechanism. In this study, we explore the mechanism of Broca-like and Wernicke-like conduction aphasia by using diffusion tensor imaging (DTI) and diffusion tensor imaging-fibre tractograph (DT-FT). We enrolled five Broca-like conduction aphasia cases, five Wernicke-like aphasia conduction cases and 10 healthy volunteers residing in Beijing and speaking Mandarin. All are right handed. We analyzed the arcuate fasciculus, Broca's areas and Wernicke's areas by DTI and measured fractional anisotrogy (FA). The results of left and right hemispheres were compared in both conduction aphasia cases and volunteers. Then the results of the conduction aphasia cases were compared with those of volunteers. The fibre construction of Broca's and Wernicke's areas was also compared by DTI-FT. The FA occupied by the identified connective pathways (Broca's area, Wernicke's area and the arcuate fasciculus) in the left hemisphere was larger than that in the right hemisphere in the control group (Paphasia cases, the FA of the left Broca's area was smaller than that of the right mirror side (PWernicke-like conduction aphasia patients, the FA of the left Wernicke's area was smaller than that of right mirror side (Paphasia results from not only arcuate fasciculus destruction, but also from disruption of the associated cortical areas. Along different segments of the arcuate fasciculus, the characteristics of language disorders of conduction aphasia were different. A lesion involving Broca's area and the anterior segments of the arcuate fasciculus would lead to Broca-like conduction aphasia, whereas a lesion involved Wernicke's area and posterior segments of the arcuate fasciculus

  19. Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging Based on a Riemannian Manifold Approach.

    Science.gov (United States)

    Baust, Maximilian; Weinmann, Andreas; Wieczorek, Matthias; Lasser, Tobias; Storath, Martin; Navab, Nassir

    2016-08-01

    In this paper, we consider combined TV denoising and diffusion tensor fitting in DTI using the affine-invariant Riemannian metric on the space of diffusion tensors. Instead of first fitting the diffusion tensors, and then denoising them, we define a suitable TV type energy functional which incorporates the measured DWIs (using an inverse problem setup) and which measures the nearness of neighboring tensors in the manifold. To approach this functional, we propose generalized forward- backward splitting algorithms which combine an explicit and several implicit steps performed on a decomposition of the functional. We validate the performance of the derived algorithms on synthetic and real DTI data. In particular, we work on real 3D data. To our knowledge, the present paper describes the first approach to TV regularization in a combined manifold and inverse problem setup.

  20. Changes of brain microstructure in patients with painful chronic pancreatitis assessed by diffusion tensor imaging

    DEFF Research Database (Denmark)

    Frøkjær, Jens Brøndum; Olesen, Søren Schou; Gram, Mikkel

    Objective In patients with painful chronic pancreatitis (CP) there is increasing evidence of abnormal pain processing in the central nervous system. Using magnetic resonance (MR) diffusion tensor imaging, brain microstructure in areas involved in processing of visceral pain was characterised...

  1. Glyph-Based Comparative Visualization for Diffusion Tensor Fields.

    Science.gov (United States)

    Zhang, Changgong; Schultz, Thomas; Lawonn, Kai; Eisemann, Elmar; Vilanova, Anna

    2016-01-01

    Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging modality that enables the in-vivo reconstruction and visualization of fibrous structures. To inspect the local and individual diffusion tensors, glyph-based visualizations are commonly used since they are able to effectively convey full aspects of the diffusion tensor. For several applications it is necessary to compare tensor fields, e.g., to study the effects of acquisition parameters, or to investigate the influence of pathologies on white matter structures. This comparison is commonly done by extracting scalar information out of the tensor fields and then comparing these scalar fields, which leads to a loss of information. If the glyph representation is kept, simple juxtaposition or superposition can be used. However, neither facilitates the identification and interpretation of the differences between the tensor fields. Inspired by the checkerboard style visualization and the superquadric tensor glyph, we design a new glyph to locally visualize differences between two diffusion tensors by combining juxtaposition and explicit encoding. Because tensor scale, anisotropy type, and orientation are related to anatomical information relevant for DTI applications, we focus on visualizing tensor differences in these three aspects. As demonstrated in a user study, our new glyph design allows users to efficiently and effectively identify the tensor differences. We also apply our new glyphs to investigate the differences between DTI datasets of the human brain in two different contexts using different b-values, and to compare datasets from a healthy and HIV-infected subject.

  2. Generalized Tensor-Based Morphometry of HIV/AIDS Using Multivariate Statistics on Deformation Tensors

    OpenAIRE

    Lepore, Natasha; Brun, Caroline; Chou, Yi-Yu; Chiang, Ming-Chang; Dutton, Rebecca A.; Hayashi, Kiralee M.; Luders, Eileen; Lopez, Oscar L.; Aizenstein, Howard J.; Toga, Arthur W.; Becker, James T.; Thompson, Paul M.

    2008-01-01

    This paper investigates the performance of a new multivariate method for tensor-based morphometry (TBM). Statistics on Riemannian manifolds are developed that exploit the full information in deformation tensor fields. In TBM, multiple brain images are warped to a common neuroanatomical template via 3-D nonlinear registration; the resulting deformation fields are analyzed statistically to identify group differences in anatomy. Rather than study the Jacobian determinant (volume expansion factor...

  3. Comparison of Turbo Spin Echo and Echo Planar Imaging for intravoxel incoherent motion and diffusion tensor imaging of the kidney at 3 Tesla

    Energy Technology Data Exchange (ETDEWEB)

    Hilbert, Fabian; Wech, Tobias; Neubauer, Henning; Veldhoen, Simon; Bley, Thorsten Alexander; Koestler, Herbert [Wuerzburg Univ. (Germany). Inst. fuer Diagnostische und Interventionelle Radiologie

    2017-10-01

    Echo Planar Imaging (EPI) is most commonly applied to acquire diffusion-weighted MR-images. EPI is able to capture an entire image in very short time, but is prone to distortions and artifacts. In diffusion-weighted EPI of the kidney severe distortions may occur due to intestinal gas. Turbo Spin Echo (TSE) is robust against distortions and artifacts, but needs more time to acquire an entire image compared to EPI. Therefore, TSE is more sensitive to motion during the readout. In this study we compare diffusion-weighted TSE and EPI of the human kidney with regard to intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI). Images were acquired with b-values between 0 and 750 s/mm{sup 2} with TSE and EPI. Distortions were observed with the EPI readout in all volunteers, while the TSE images were virtually distortion-free. Fractional anisotropy of the diffusion tensor was significantly lower for TSE than for EPI. All other parameters of DTI and IVIM were comparable for TSE and EPI. Especially the main diffusion directions yielded by TSE and EPI were similar. The results demonstrate that TSE is a worthwhile distortion-free alternative to EPI for diffusion-weighted imaging of the kidney at 3 Tesla.

  4. The role of diffusion tensor imaging in brain tumor surgery : A review of the literature

    NARCIS (Netherlands)

    Potgieser, Adriaan R. E.; Wagemakers, Michiel; van Hulzen, Arjen L. J.; de Jong, Bauke M.; Hoving, Eelco W.; Groen, Rob J. M.

    Diffusion tensor imaging (DTI) is a recent technique that utilizes diffusion of water molecules to make assumptions about white matter tract architecture of the brain. Early on, neurosurgeons recognized its potential value in neurosurgical planning, as it is the only technique that offers the

  5. Neuropsychological Correlates of Diffusion Tensor Imaging in Schizophrenia

    Science.gov (United States)

    Nestor, Paul G.; Kubicki, Marek; Gurrera, Ronald J.; Niznikiewicz, Margaret; Frumin, Melissa; McCarley, Robert W.; Shenton, Martha E.

    2009-01-01

    Patients with schizophrenia (n = 41) and healthy comparison participants (n = 46) completed neuropsychological measures of intelligence, memory, and executive function. A subset of each group also completed magnetic resonance diffusion tensor imaging (DTI) studies (fractional anisotropy and cross-sectional area) of the uncinate fasciculus (UF) and cingulate bundle (CB). Patients with schizophrenia showed reduced levels of functioning across all neuropsychological measures. In addition, selective neuropsychological–DTI relationships emerged. Among patients but not controls, lower levels of declarative–episodic verbal memory correlated with reduced left UF, whereas executive function errors related to performance monitoring correlated with reduced left CB. The data suggested abnormal DTI patterns linking declarative–episodic verbal memory deficits to the left UF and executive function deficits to the left CB among patients with schizophrenia. PMID:15506830

  6. Denoising human cardiac diffusion tensor magnetic resonance images using sparse representation combined with segmentation

    International Nuclear Information System (INIS)

    Bao, L J; Zhu, Y M; Liu, W Y; Pu, Z B; Magnin, I E; Croisille, P; Robini, M

    2009-01-01

    Cardiac diffusion tensor magnetic resonance imaging (DT-MRI) is noise sensitive, and the noise can induce numerous systematic errors in subsequent parameter calculations. This paper proposes a sparse representation-based method for denoising cardiac DT-MRI images. The method first generates a dictionary of multiple bases according to the features of the observed image. A segmentation algorithm based on nonstationary degree detector is then introduced to make the selection of atoms in the dictionary adapted to the image's features. The denoising is achieved by gradually approximating the underlying image using the atoms selected from the generated dictionary. The results on both simulated image and real cardiac DT-MRI images from ex vivo human hearts show that the proposed denoising method performs better than conventional denoising techniques by preserving image contrast and fine structures.

  7. An exploration into diffusion tensor imaging in the bovine ocular lens

    Directory of Open Access Journals (Sweden)

    Ehsan eVaghefi

    2013-03-01

    Full Text Available We describe our development of the diffusion tensor imaging modality for the bovine ocular lens. Diffusion gradients were added to a spin-echo pulse sequence and the relevant parameters of the sequence were refined to achieve good diffusion weighting in the lens tissue, which demonstrated heterogeneous regions of diffusive signal attenuation. Decay curves for b-value (loosely summarizes the strength of diffusion weighting and TE (determines the amount of MRI-obtained signal were used to estimate apparent diffusion coefficients (ADC and T2 in different lens regions. The ADCs varied by over an order of magnitude and revealed diffusive anisotropy in the lens. Up to 30 diffusion gradient directions, and 8 signal acquisition averages, were applied to lenses in culture in order to improve maps of diffusion tensor eigenvalues, equivalent to ADC, across the lens. From these maps, fractional anisotropy maps were calculated and compared to known spatial distributions of anisotropic molecular fluxes in the lens. This comparison suggested new hypotheses and experiments to quantitatively assess models of circulation in the avascular lens.

  8. Diffusion tensor imaging in inflammatory and neoplastic intramedullary spinal cord lesions: Focusing on fiber tracking

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyo Jin; Lee, Joon Woo; Lee, Eugene; Kim, Sung Gon; Kang, Yu Suhn; Ahn, Joong Mo; Kang, Heung Sik [Dept. of Radiology, Seoul National University Bundang Hospital, Seongnam (Korea, Republic of)

    2017-02-15

    Inflammatory and neoplastic intramedullary spinal cord lesions have overlapping clinical features, and it is occasionally difficult to distinguish one from the other on conventional magnetic resonance imaging. We aimed to compare diffusion tensor imaging findings between inflammatory and neoplastic intramedullary spinal cord lesions, with a specific focus on patterns of fiber tracking. Diffusion tensor imaging was performed in patients with either inflammatory or neoplastic intramedullary spinal cord lesions. The fiber tracking patterns (categorized as “intact,” “displaced,” or “interrupted”) were compared between these two groups. Eight patients were included in the study: 5 patients with pathologically or clinically confirmed inflammatory lesions and 3 patients with pathologically or clinically confirmed neoplastic lesions. Among the 5 patients with inflammatory lesions, 2 patients exhibited the displaced pattern and 3 patients exhibited the intact pattern. Among the 3 patients with neoplastic lesions, 1 patient exhibited the intact pattern, 1 patient exhibited the displaced pattern, and 1 patient exhibited the interrupted pattern. In this study, inflammatory and neoplastic intramedullary spinal cord lesions were not clearly differentiated by fiber tracking; both conditions can present with overlapping features such as displaced fibers. The exclusion of inflammatory conditions based on the presence of displaced fibers in fiber tracking images should be avoided.

  9. Regional Cerebral Disease Progression in Friedreich's Ataxia: A Longitudinal Diffusion Tensor Imaging Study.

    Science.gov (United States)

    Mascalchi, Mario; Toschi, Nicola; Giannelli, Marco; Ginestroni, Andrea; Della Nave, Riccardo; Tessa, Carlo; Piacentini, Silvia; Dotti, Maria Teresa; Aiello, Marco; Nicolai, Emanuele; Soricelli, Andrea; Salvi, Fabrizio; Diciotti, Stefano

    2016-01-01

    Imaging biomarkers of disease progression are desirable in inherited ataxias. MRI has demonstrated brain damage in Friedreich ataxia (FRDA) in form of regional atrophy of the medulla, peridentate cerebellar white matter (WM) and superior cerebellar peduncles (visible in T1-weighted images) and of change of microstructural characteristics of WM tracts of the brainstem, cerebellar peduncles, cerebellum, and supratentorial structures (visible through diffusion-weighted imaging). We explored the potential of brain MR morphometry and diffusion tensor imaging (DTI) to track the progression of neurodegeneration in FRDA. Eight patients (5F, 3M; age 13.4-41.2 years) and 8 healthy controls (2F, 6M; age 26.2-48.3 years) underwent 2 MRI examinations (mean 3.9 and 4.1 years apart, respectively) on the same 1.5T scanner. The protocol included 3D T1-weighted images and axial diffusion-weighted images (b-value 1,000 s/mm(2)) for calculating maps of fractional anisotropy, mean, axial and radial diffusivity, and mode of anisotropy. Tensor-based morphometry was used to investigate regional volume changes and tract-based spatial statistics was used to investigate microstructural changes in WM tracts. Longitudinal analyses showed no differences in regional volume changes but a significant difference in axial diffusivity changes in cerebral and corpus callosum WM of patients as compared to controls (mean longitudinal rate of change for axial diffusivity: -.02 × 10(-3) mm(2)/s/year in patients vs. .01 × 10(-3) mm(2)/s/year in controls). No correlation with number of triplets, disease duration, and worsening of the clinical deficit was observed. DTI can track brain microstructural changes in FRDA and can be considered a potential biomarker of disease progression. Copyright © 2015 by the American Society of Neuroimaging.

  10. Simultaneous multislice echo planar imaging with blipped controlled aliasing in parallel imaging results in higher acceleration: a promising technique for accelerated diffusion tensor imaging of skeletal muscle

    OpenAIRE

    Filli, Lukas; Piccirelli, Marco; Kenkel, David; Guggenberger, Roman; Andreisek, Gustav; Beck, Thomas; Runge, Val M; Boss, Andreas

    2015-01-01

    PURPOSE The aim of this study was to investigate the feasibility of accelerated diffusion tensor imaging (DTI) of skeletal muscle using echo planar imaging (EPI) applying simultaneous multislice excitation with a blipped controlled aliasing in parallel imaging results in higher acceleration unaliasing technique. MATERIALS AND METHODS After federal ethics board approval, the lower leg muscles of 8 healthy volunteers (mean [SD] age, 29.4 [2.9] years) were examined in a clinical 3-T magnetic ...

  11. Structural connectivity via the tensor-based morphometry

    OpenAIRE

    Kim, S.; Chung, M.; Hanson, J.; Avants, B.; Gee, J.; Davidson, R.; Pollak, S.

    2011-01-01

    The tensor-based morphometry (TBM) has been widely used in characterizing tissue volume difference between populations at voxel level. We present a novel computational framework for investigating the white matter connectivity using TBM. Unlike other diffusion tensor imaging (DTI) based white matter connectivity studies, we do not use DTI but only T1-weighted magnetic resonance imaging (MRI). To construct brain network graphs, we have developed a new data-driven approach called the ε-neighbor ...

  12. Retrospective Correction of Physiological Noise in DTI Using an Extended Tensor Model and Peripheral Measurements

    Science.gov (United States)

    Mohammadi, Siawoosh; Hutton, Chloe; Nagy, Zoltan; Josephs, Oliver; Weiskopf, Nikolaus

    2013-01-01

    Diffusion tensor imaging is widely used in research and clinical applications, but this modality is highly sensitive to artefacts. We developed an easy-to-implement extension of the original diffusion tensor model to account for physiological noise in diffusion tensor imaging using measures of peripheral physiology (pulse and respiration), the so-called extended tensor model. Within the framework of the extended tensor model two types of regressors, which respectively modeled small (linear) and strong (nonlinear) variations in the diffusion signal, were derived from peripheral measures. We tested the performance of four extended tensor models with different physiological noise regressors on nongated and gated diffusion tensor imaging data, and compared it to an established data-driven robust fitting method. In the brainstem and cerebellum the extended tensor models reduced the noise in the tensor-fit by up to 23% in accordance with previous studies on physiological noise. The extended tensor model addresses both large-amplitude outliers and small-amplitude signal-changes. The framework of the extended tensor model also facilitates further investigation into physiological noise in diffusion tensor imaging. The proposed extended tensor model can be readily combined with other artefact correction methods such as robust fitting and eddy current correction. PMID:22936599

  13. Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

    Science.gov (United States)

    Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

    2017-10-12

    Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

  14. White Matter Integrity in Asperger Syndrome: A Preliminary Diffusion Tensor Magnetic Resonance Imaging Study in Adults

    NARCIS (Netherlands)

    Bloemen, Oswald J. N.; Deeley, Quinton; Sundram, Fred; Daly, Eileen M.; Barker, Gareth J.; Jones, Derek K.; van Amelsvoort, Therese A. M. J.; Schmitz, Nicole; Robertson, Dene; Murphy, Kieran C.; Murphy, Declan G. M.

    2010-01-01

    Background: Autistic Spectrum Disorder (ASD), including Asperger syndrome and autism, is a highly genetic neurodevelopmental disorder. There is a consensus that ASD has a biological basis, and it has been proposed that it is a "connectivity" disorder. Diffusion Tensor Magnetic Resonance Imaging

  15. Methodological improvements in voxel-based analysis of diffusion tensor images: applications to study the impact of apolipoprotein E on white matter integrity.

    Science.gov (United States)

    Newlander, Shawn M; Chu, Alan; Sinha, Usha S; Lu, Po H; Bartzokis, George

    2014-02-01

    To identify regional differences in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) using customized preprocessing before voxel-based analysis (VBA) in 14 normal subjects with the specific genes that decrease (apolipoprotein [APO] E ε2) and that increase (APOE ε4) the risk of Alzheimer's disease. Diffusion tensor images (DTI) acquired at 1.5 Tesla were denoised with a total variation tensor regularization algorithm before affine and nonlinear registration to generate a common reference frame for the image volumes of all subjects. Anisotropic and isotropic smoothing with varying kernel sizes was applied to the aligned data before VBA to determine regional differences between cohorts segregated by allele status. VBA on the denoised tensor data identified regions of reduced FA in APOE ε4 compared with the APOE ε2 healthy older carriers. The most consistent results were obtained using the denoised tensor and anisotropic smoothing before statistical testing. In contrast, isotropic smoothing identified regional differences for small filter sizes alone, emphasizing that this method introduces bias in FA values for higher kernel sizes. Voxel-based DTI analysis can be performed on low signal to noise ratio images to detect subtle regional differences in cohorts using the proposed preprocessing techniques. Copyright © 2013 Wiley Periodicals, Inc.

  16. Global diffusion tensor imaging derived metrics differentiate glioblastoma multiforme vs. normal brains by using discriminant analysis: introduction of a novel whole-brain approach.

    Science.gov (United States)

    Roldan-Valadez, Ernesto; Rios, Camilo; Cortez-Conradis, David; Favila, Rafael; Moreno-Jimenez, Sergio

    2014-06-01

    Histological behavior of glioblastoma multiforme suggests it would benefit more from a global rather than regional evaluation. A global (whole-brain) calculation of diffusion tensor imaging (DTI) derived tensor metrics offers a valid method to detect the integrity of white matter structures without missing infiltrated brain areas not seen in conventional sequences. In this study we calculated a predictive model of brain infiltration in patients with glioblastoma using global tensor metrics. Retrospective, case and control study; 11 global DTI-derived tensor metrics were calculated in 27 patients with glioblastoma multiforme and 34 controls: mean diffusivity, fractional anisotropy, pure isotropic diffusion, pure anisotropic diffusion, the total magnitude of the diffusion tensor, linear tensor, planar tensor, spherical tensor, relative anisotropy, axial diffusivity and radial diffusivity. The multivariate discriminant analysis of these variables (including age) with a diagnostic test evaluation was performed. The simultaneous analysis of 732 measures from 12 continuous variables in 61 subjects revealed one discriminant model that significantly differentiated normal brains and brains with glioblastoma: Wilks' λ = 0.324, χ(2) (3) = 38.907, p tensor and linear tensor. These metrics might be clinically applied for diagnosis, follow-up, and the study of other neurological diseases.

  17. Spherical Tensor Calculus for Local Adaptive Filtering

    Science.gov (United States)

    Reisert, Marco; Burkhardt, Hans

    In 3D image processing tensors play an important role. While rank-1 and rank-2 tensors are well understood and commonly used, higher rank tensors are rare. This is probably due to their cumbersome rotation behavior which prevents a computationally efficient use. In this chapter we want to introduce the notion of a spherical tensor which is based on the irreducible representations of the 3D rotation group. In fact, any ordinary cartesian tensor can be decomposed into a sum of spherical tensors, while each spherical tensor has a quite simple rotation behavior. We introduce so called tensorial harmonics that provide an orthogonal basis for spherical tensor fields of any rank. It is just a generalization of the well known spherical harmonics. Additionally we propose a spherical derivative which connects spherical tensor fields of different degree by differentiation. Based on the proposed theory we present two applications. We propose an efficient algorithm for dense tensor voting in 3D, which makes use of tensorial harmonics decomposition of the tensor-valued voting field. In this way it is possible to perform tensor voting by linear-combinations of convolutions in an efficient way. Secondly, we propose an anisotropic smoothing filter that uses a local shape and orientation adaptive filter kernel which can be computed efficiently by the use spherical derivatives.

  18. Structural changes of central white matter tracts in Kennedy's disease - a diffusion tensor imaging and voxel-based morphometry study.

    Science.gov (United States)

    Pieper, C C; Konrad, C; Sommer, J; Teismann, I; Schiffbauer, H

    2013-05-01

    Spinobulbar muscular atrophy [Kennedy's disease (KD)] is a rare X-linked neurodegenerative disorder of mainly spinal and bulbar motoneurons. Recent studies suggest a multisystem character of this disease. The aim of this study was to identify and characterize structural changes of gray (GM) and white matter (WM) in the central nervous system. Whole-brain-based voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analyses were applied to MRI data of eight genetically proven patients with KD and compared with 16 healthy age-matched controls. Diffusion tensor imaging analysis showed not only decreased fractional anisotropy (FA) values in the brainstem, but also widespread changes in central WM tracts, whereas VBM analysis of the WM showed alterations primarily in the brainstem and cerebellum. There were no changes in GM volume. The FA value decrease in the brainstem correlated with the disease duration. Diffusion tensor imaging analysis revealed subtle changes of central WM tract integrity, while GM and WM volume remained unaffected. In our patient sample, KD had more extended effects than previously reported. These changes could either be attributed primarily to neurodegeneration or reflect secondary plastic changes due to atrophy of lower motor neurons and reorganization of cortical structures. © 2012 John Wiley & Sons A/S.

  19. Comparison between cerebral ischemia disease and multiple sclerosis by using MR diffusion tensor imaging

    International Nuclear Information System (INIS)

    Lou Xin; Cai Youquan; Ma Lin; Cai Jianming

    2007-01-01

    Objective: To assess the value of MR diffusion tensor imaging (DTI) in the differentiation between the patients with cerebral ischemia disease and multiple sclerosis. Methods: MR diffusion tensor imaging was performed in thirty-two patients with internal carotid artery stenosis ≥70% and eighteen patients with clinical diagnosed multiple sclerosis. Fractional anisotropy (FA) value of the germ, splenium, body of the corpus callosum, and the white matter of the frontal and occipital lobe were measured respectively, and independent-sample t-test statistical analysis was performed. Results: The FA value was decreased obviously in the anterior and posterior body and splenium of the corpus callosumin the MS patients compared with the ICA severe stenosis patients (0.67 ± 0.12 vs. 0.75 ± 0.05, t=3.443, P 0.05; 0.34 ± 0.08 vs. 0.34 ± 0.05, t=0.137, P> 0.05; 0.29 ± 0.06 vs. 0.40 ± 0.06, t=5.449, P>0.05). Conclusion: DTI can noninvasive detect the potential disorder of corpus callosum in vivo, thus providing useful information to differentiate the cerebral ischemia disease from multiple sclerosis. (authors)

  20. Diffusion tensor imaging in spinal cord injury

    International Nuclear Information System (INIS)

    Kamble, Ravindra B; Venkataramana, Neelam K; Naik, Arun L; Rao, Shailesh V

    2011-01-01

    To assess the feasibility of spinal tractography in patients of spinal cord injury vs a control group and to compare fractional anisotropy (FA) values between the groups. Diffusion tensor imaging (DTI) was performed in the spinal cord of 29 patients (18 patients and 11 controls). DTI was done in the cervical region if the cord injury was at the dorsal or lumbar region and in the conus region if cord injury was in the cervical or dorsal region. FA was calculated for the patients and the controls and the values were compared. The mean FA value was 0.550±0.09 in the control group and 0.367±0.14 in the patients; this difference was statistically significant (P=0.001). Spinal tractography is a feasible technique to assess the extent of spinal cord injury by FA, which is reduced in patients of spinal cord injury, suggesting possible Wallerian degeneration. In future, this technique may become a useful tool for assessing cord injury patients after stem cell therapy, with improvement in FA values indicating axonal regeneration

  1. Tract-Specific Analyses of Diffusion Tensor Imaging Show Widespread White Matter Compromise in Autism Spectrum Disorder

    Science.gov (United States)

    Shukla, Dinesh K.; Keehn, Brandon; Muller, Ralph-Axel

    2011-01-01

    Background: Previous diffusion tensor imaging (DTI) studies have shown white matter compromise in children and adults with autism spectrum disorder (ASD), which may relate to reduced connectivity and impaired function of distributed networks. However, tract-specific evidence remains limited in ASD. We applied tract-based spatial statistics (TBSS)…

  2. Tensor rank is not multiplicative under the tensor product

    NARCIS (Netherlands)

    M. Christandl (Matthias); A. K. Jensen (Asger Kjærulff); J. Zuiddam (Jeroen)

    2018-01-01

    textabstractThe tensor rank of a tensor t is the smallest number r such that t can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an ℓ-tensor. The tensor product of s and t is a (k+ℓ)-tensor. Tensor rank is sub-multiplicative under the tensor product. We revisit the

  3. Tensor rank is not multiplicative under the tensor product

    NARCIS (Netherlands)

    M. Christandl (Matthias); A. K. Jensen (Asger Kjærulff); J. Zuiddam (Jeroen)

    2017-01-01

    textabstractThe tensor rank of a tensor is the smallest number r such that the tensor can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an l-tensor. The tensor product of s and t is a (k + l)-tensor (not to be confused with the "tensor Kronecker product" used in

  4. Tensor rank is not multiplicative under the tensor product

    OpenAIRE

    Christandl, Matthias; Jensen, Asger Kjærulff; Zuiddam, Jeroen

    2017-01-01

    The tensor rank of a tensor t is the smallest number r such that t can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an l-tensor. The tensor product of s and t is a (k + l)-tensor. Tensor rank is sub-multiplicative under the tensor product. We revisit the connection between restrictions and degenerations. A result of our study is that tensor rank is not in general multiplicative under the tensor product. This answers a question of Draisma and Saptharishi. Specif...

  5. Tensor surgery and tensor rank

    NARCIS (Netherlands)

    M. Christandl (Matthias); J. Zuiddam (Jeroen)

    2018-01-01

    textabstractWe introduce a method for transforming low-order tensors into higher-order tensors and apply it to tensors defined by graphs and hypergraphs. The transformation proceeds according to a surgery-like procedure that splits vertices, creates and absorbs virtual edges and inserts new vertices

  6. Tensor surgery and tensor rank

    NARCIS (Netherlands)

    M. Christandl (Matthias); J. Zuiddam (Jeroen)

    2016-01-01

    textabstractWe introduce a method for transforming low-order tensors into higher-order tensors and apply it to tensors defined by graphs and hypergraphs. The transformation proceeds according to a surgery-like procedure that splits vertices, creates and absorbs virtual edges and inserts new

  7. T2-enhanced tensor diffusion trace-weighted image in the detection of hyper-acute cerebral infarction: Comparison with isotropic diffusion-weighted image

    International Nuclear Information System (INIS)

    Chou, M.-C.; Tzeng, W.-S.; Chung, H.-W.; Wang, C.-Y.; Liu, H.-S.; Juan, C.-J.; Lo, C.-P.; Hsueh, C.-J.; Chen, C.-Y.

    2010-01-01

    Background and purpose: Although isotropic diffusion-weighted imaging (isoDWI) is very sensitive to the detection of acute ischemic stroke, it may occasionally show diffusion negative result in hyper-acute stroke. We hypothesize that high diffusion contrast diffusion trace-weighted image with enhanced T2 may improve stroke lesion conspicuity. Methods: Five hyper acute stroke patients (M:F = 0:5, average age = 61.8 ± 20.5 y/o) and 16 acute stroke patients (M:F = 11:5, average age = 67.7 ± 12 y/o) were examined six-direction tensor DWIs at b = 707 s/mm 2 . Three different diffusion-weighted images, including isotropic (isoDWI), diffusion trace-weighted image (trDWI) and T2-enhanced diffusion trace-weighted image (T2E t rDWI), were generated. Normalized lesion-to-normal ratio (nLNR) and contrast-to-noise ratio (CNR) of three diffusion images were calculated from each patient and statistically compared. Results: The trDWI shows better nLNR than isoDWI on both hyper-acute and acute stroke lesions, whereas no significant improvement in CNR. Nevertheless, the T2E t rDWI has statistically superior CNR and nLNR than those of isoDWI and trDWI in both hyper-acute and acute stroke. Conclusions: We concluded that tensor diffusion trace-weighted image with T2 enhancement is more sensitive to stroke lesion detection, and can provide higher lesion conspicuity than the conventional isotropic DWI for early stroke lesion delineation without the need of high-b-value technique.

  8. Tensor rank is not multiplicative under the tensor product

    DEFF Research Database (Denmark)

    Christandl, Matthias; Jensen, Asger Kjærulff; Zuiddam, Jeroen

    2018-01-01

    The tensor rank of a tensor t is the smallest number r such that t can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an ℓ-tensor. The tensor product of s and t is a (k+ℓ)-tensor. Tensor rank is sub-multiplicative under the tensor product. We revisit the connection b...

  9. SU-E-I-93: Improved Imaging Quality for Multislice Helical CT Via Sparsity Regularized Iterative Image Reconstruction Method Based On Tensor Framelet

    International Nuclear Information System (INIS)

    Nam, H; Guo, M; Lee, K; Li, R; Xing, L; Gao, H

    2014-01-01

    Purpose: Inspired by compressive sensing, sparsity regularized iterative reconstruction method has been extensively studied. However, its utility pertinent to multislice helical 4D CT for radiotherapy with respect to imaging quality, dose, and time has not been thoroughly addressed. As the beginning of such an investigation, this work carries out the initial comparison of reconstructed imaging quality between sparsity regularized iterative method and analytic method through static phantom studies using a state-of-art 128-channel multi-slice Siemens helical CT scanner. Methods: In our iterative method, tensor framelet (TF) is chosen as the regularization method for its superior performance from total variation regularization in terms of reduced piecewise-constant artifacts and improved imaging quality that has been demonstrated in our prior work. On the other hand, X-ray transforms and its adjoints are computed on-the-fly through GPU implementation using our previous developed fast parallel algorithms with O(1) complexity per computing thread. For comparison, both FDK (approximate analytic method) and Katsevich algorithm (exact analytic method) are used for multislice helical CT image reconstruction. Results: The phantom experimental data with different imaging doses were acquired using a state-of-art 128-channel multi-slice Siemens helical CT scanner. The reconstructed image quality was compared between TF-based iterative method, FDK and Katsevich algorithm with the quantitative analysis for characterizing signal-to-noise ratio, image contrast, and spatial resolution of high-contrast and low-contrast objects. Conclusion: The experimental results suggest that our tensor framelet regularized iterative reconstruction algorithm improves the helical CT imaging quality from FDK and Katsevich algorithm for static experimental phantom studies that have been performed

  10. Autism Spectrum Disorder: Does Neuroimaging Support the DSM-5 Proposal for a Symptom Dyad? A Systematic Review of Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging Studies

    Science.gov (United States)

    Pina-Camacho, Laura; Villero, Sonia; Fraguas, David; Boada, Leticia; Janssen, Joost; Navas-Sanchez, Francisco J.; Mayoral, Maria; Llorente, Cloe; Arango, Celso; Parellada, Mara

    2012-01-01

    A systematic review of 208 studies comprising functional magnetic resonance imaging and diffusion tensor imaging data in patients with "autism spectrum disorder" (ASD) was conducted, in order to determine whether these data support the forthcoming DSM-5 proposal of a social communication and behavioral symptom dyad. Studies consistently reported…

  11. Diffusion tensor tractography of the brainstem pyramidal tract; A study on the optimal reduction factor in parallel imaging

    Energy Technology Data Exchange (ETDEWEB)

    Bae, Yun Jung; Park, Jong Bin; Kim, Jae Hyoung; Choi, Byung Se; Jung, Cheol Kyu [Dept. of of Radiology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam (Korea, Republic of)

    2016-08-15

    Parallel imaging mitigates susceptibility artifacts that can adversely affect diffusion tensor tractography (DTT) of the pons depending on the reduction (R) factor. We aimed to find the optimal R factor for DTT of the pons that would allow us to visualize the largest possible number of pyramidal tract fibers. Diffusion tensor imaging was performed on 10 healthy subjects at 3 Tesla based on single-shot echo-planar imaging using the following parameters: b value, 1000 s/mm{sup 2}; gradient direction, 15; voxel size, 2 × 2 × 2 mm{sup 3}; and R factors, 1, 2, 3, 4, and 5. DTT of the right and left pyramidal tracts in the pons was conducted in all subjects. Signal-to-noise ratio (SNR), image distortion, and the number of fibers in the tracts were compared across R factors. SNR, image distortion, and fiber number were significantly different according to R factor. Maximal SNR was achieved with an R factor of 2. Image distortion was minimal with an R factor of 5. The number of visible fibers was greatest with an R factor of 3. R factor 3 is optimal for DTT of the pontine pyramidal tract. A balanced consideration of SNR and image distortion, which do not have the same dependence on the R factor, is necessary for DTT of the pons.

  12. Distance Adaptive Tensor Discriminative Geometry Preserving Projection for Face Recognition

    Directory of Open Access Journals (Sweden)

    Ziqiang Wang

    2012-09-01

    Full Text Available There is a growing interest in dimensionality reduction techniques for face recognition, however, the traditional dimensionality reduction algorithms often transform the input face image data into vectors before embedding. Such vectorization often ignores the underlying data structure and leads to higher computational complexity. To effectively cope with these problems, a novel dimensionality reduction algorithm termed distance adaptive tensor discriminative geometry preserving projection (DATDGPP is proposed in this paper. The key idea of DATDGPP is as follows: first, the face image data are directly encoded in high-order tensor structure so that the relationships among the face image data can be preserved; second, the data-adaptive tensor distance is adopted to model the correlation among different coordinates of tensor data; third, the transformation matrix which can preserve discrimination and local geometry information is obtained by an iteration algorithm. Experimental results on three face databases show that the proposed algorithm outperforms other representative dimensionality reduction algorithms.

  13. Identification of ghost artifact using texture analysis in pediatric spinal cord diffusion tensor images.

    Science.gov (United States)

    Alizadeh, Mahdi; Conklin, Chris J; Middleton, Devon M; Shah, Pallav; Saksena, Sona; Krisa, Laura; Finsterbusch, Jürgen; Faro, Scott H; Mulcahey, M J; Mohamed, Feroze B

    2018-04-01

    Ghost artifacts are a major contributor to degradation of spinal cord diffusion tensor images. A multi-stage post-processing pipeline was designed, implemented and validated to automatically remove ghost artifacts arising from reduced field of view diffusion tensor imaging (DTI) of the pediatric spinal cord. A total of 12 pediatric subjects including 7 healthy subjects (mean age=11.34years) with no evidence of spinal cord injury or pathology and 5 patients (mean age=10.96years) with cervical spinal cord injury were studied. Ghost/true cords, labeled as region of interests (ROIs), in non-diffusion weighted b0 images were segmented automatically using mathematical morphological processing. Initially, 21 texture features were extracted from each segmented ROI including 5 first-order features based on the histogram of the image (mean, variance, skewness, kurtosis and entropy) and 16s-order feature vector elements, incorporating four statistical measures (contrast, correlation, homogeneity and energy) calculated from co-occurrence matrices in directions of 0°, 45°, 90° and 135°. Next, ten features with a high value of mutual information (MI) relative to the pre-defined target class and within the features were selected as final features which were input to a trained classifier (adaptive neuro-fuzzy interface system) to separate the true cord from the ghost cord. The implemented pipeline was successfully able to separate the ghost artifacts from true cord structures. The results obtained from the classifier showed a sensitivity of 91%, specificity of 79%, and accuracy of 84% in separating the true cord from ghost artifacts. The results show that the proposed method is promising for the automatic detection of ghost cords present in DTI images of the spinal cord. This step is crucial towards development of accurate, automatic DTI spinal cord post processing pipelines. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Diffusion tensor imaging of cingulum bundle and corpus callosum in schizophrenia vs. bipolar disorder.

    Science.gov (United States)

    Nenadić, Igor; Hoof, Anna; Dietzek, Maren; Langbein, Kerstin; Reichenbach, Jürgen R; Sauer, Heinrich; Güllmar, Daniel

    2017-08-30

    Both schizophrenia and bipolar disorder show abnormalities of white matter, as seen in diffusion tensor imaging (DTI) analyses of major brain fibre bundles. While studies in each of the two conditions have indicated possible overlap in anatomical location, there are few direct comparisons between the disorders. Also, it is unclear whether phenotypically similar subgroups (e.g. patients with bipolar disorder and psychotic features) might share white matter pathologies or be rather similar. Using region-of-interest (ROI) analysis of white matter with diffusion tensor imaging (DTI) at 3 T, we analysed fractional anisotropy (FA), radial diffusivity (RD), and apparent diffusion coefficient (ADC) of the corpus callosum and cingulum bundle in 33 schizophrenia patients, 17 euthymic (previously psychotic) bipolar disorder patients, and 36 healthy controls. ANOVA analysis showed significant main effects of group for RD and ADC (both elevated in schizophrenia). Across the corpus callosum ROIs, there was not group effect on FA, but for RD (elevated in schizophrenia, lower in bipolar disorder) and ADC (higher in schizophrenia, intermediate in bipolar disorder). Our findings show similarities and difference (some gradual) across regions of the two major fibre tracts implicated in these disorders, which would be consistent with a neurobiological overlap of similar clinical phenotypes. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  15. Diffusion tensor imaging of the cortical plate and subplate in very-low-birth-weight infants

    Energy Technology Data Exchange (ETDEWEB)

    Dudink, Jeroen; Govaert, Paul; Zwol, Arjen L. van; Conneman, Nikk; Goudoever, Johannes B. van [Erasmus MC-Sophia Children' s Hospital, Division of Neonatology, Department of Paediatrics, Rotterdam (Netherlands); Buijs, Jan [Maxima Medical Center, Division of Neonatology, Department of Paediatrics, Veldhoven (Netherlands); Lequin, Maarten [Erasmus MC-Sophia Children' s Hospital, Division of Paediatrics, Department of Radiology, Rotterdam, Zuid-holland (Netherlands)

    2010-08-15

    Many intervention studies in preterm infants aim to improve neurodevelopmental outcome, but short-term proxy outcome measurements are lacking. Cortical plate and subplate development could be such a marker. Our aim was to provide normal DTI reference values for the cortical plate and subplate of preterm infants. As part of an ongoing study we analysed diffusion tensor imaging (DTI) images of 19 preterm infants without evidence of injury on conventional MRI, with normal outcome (Bayley-II assessed at age 2), and scanned in the first 4 days of life. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values in the frontal and temporal subplate and cortical plate were measured in single and multiple voxel regions of interest (ROI) placed on predefined regions. Using single-voxel ROIs, statistically significant inverse correlation was found between gestational age (GA) and FA of the frontal (r = -0.5938, P = 0.0058) and temporal (r = -0.4912, P = 0.0327) cortical plate. ADC values had a significant positive correlation with GA in the frontal (r = 0.5427, P = 0.0164) and temporal (r = 0.5540, P = 0.0138) subplate. Diffusion tensor imaging allows in vivo exploration of the evolving cortical plate and subplate. We provide FA and ADC values of the subplate and cortical plate in very-low-birth-weight (VLBW) infants with normal developmental outcome that can be used as reference values. (orig.)

  16. Diffusion tensor imaging of the cortical plate and subplate in very-low-birth-weight infants

    International Nuclear Information System (INIS)

    Dudink, Jeroen; Govaert, Paul; Zwol, Arjen L. van; Conneman, Nikk; Goudoever, Johannes B. van; Buijs, Jan; Lequin, Maarten

    2010-01-01

    Many intervention studies in preterm infants aim to improve neurodevelopmental outcome, but short-term proxy outcome measurements are lacking. Cortical plate and subplate development could be such a marker. Our aim was to provide normal DTI reference values for the cortical plate and subplate of preterm infants. As part of an ongoing study we analysed diffusion tensor imaging (DTI) images of 19 preterm infants without evidence of injury on conventional MRI, with normal outcome (Bayley-II assessed at age 2), and scanned in the first 4 days of life. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values in the frontal and temporal subplate and cortical plate were measured in single and multiple voxel regions of interest (ROI) placed on predefined regions. Using single-voxel ROIs, statistically significant inverse correlation was found between gestational age (GA) and FA of the frontal (r = -0.5938, P = 0.0058) and temporal (r = -0.4912, P = 0.0327) cortical plate. ADC values had a significant positive correlation with GA in the frontal (r = 0.5427, P = 0.0164) and temporal (r = 0.5540, P = 0.0138) subplate. Diffusion tensor imaging allows in vivo exploration of the evolving cortical plate and subplate. We provide FA and ADC values of the subplate and cortical plate in very-low-birth-weight (VLBW) infants with normal developmental outcome that can be used as reference values. (orig.)

  17. Improved characterisation of stroke phenotype using sequential MR diffusion tensor imaging at 3 tesla

    International Nuclear Information System (INIS)

    Green, H.; Price, C.J.S.; Warburton, E; Pena, A.; Donovan, T.; Carpenter, T.A.; Pickard, J.D.; Gillard, J.H.

    2002-01-01

    Full text: MR diffusion weighted imaging (DWI) enables the identification of early ischemia in acute stroke. Recent advances in DWI allow the identification of anisotropic white matter tracts with diffusion tensor imaging (DTI).We used DTI to study patients with recent stroke in a high field MR system to establish the type of phenotypic abnormalities demonstrated and to determine whether DTI could produce an alternative tool that might be used in studies of clinical outcome and recovery. 25 patients with recent stroke were imaged at 3 Telsa. The extent of abnormality on the conventional and tensor images were compared. Regions of interest were drawn within the area of ischemia and in the contralateral hemisphere. The relative anisotropy index for these areas was calculated and compared. DTI studies were repeated in 11 patients at 1 week and 8 patients at 3 months. DTI was successfully performed in 21 patients. There were 21 men, mean age 58 years (range 25-86 years) imaged at a median of 1 day (range 6 hours to 14 days) from the known time of stroke onset. 19/21 patients demonstrated DWI changes on the b = 1000s/mm2 trace image. DTI imaging was initially normal in 6 patients. The abnormalities consisted of actual disruption of white matter tracts in 13 patients. Ansiotropy indices were reduced to 0.21 in the ischaemic areas compared with 0.34 in normal appearing contralateral white matter (p = 0.016). 2 patients demonstrated distortion of white matter tracts around ischemia induced mass effect. One patient without tract disruption initially had progressed to tract disruption when re-imaged six days from stroke onset. A further patient had distortion of white matter tracts around an infarct and had a good clinical outcome. DTI is able to quantify the extent of white matter tract disruption in acute stroke. The extent or lack of tract destruction may be prognostically important as it provides information that is not available with conventional diffusion or perfusion

  18. STRUCTURAL CONNECTIVITY VIA THE TENSOR-BASED MORPHOMETRY.

    Science.gov (United States)

    Kim, Seung-Goo; Chung, Moo K; Hanson, Jamie L; Avants, Brian B; Gee, James C; Davidson, Richard J; Pollak, Seth D

    2011-01-01

    The tensor-based morphometry (TBM) has been widely used in characterizing tissue volume difference between populations at voxel level. We present a novel computational framework for investigating the white matter connectivity using TBM. Unlike other diffusion tensor imaging (DTI) based white matter connectivity studies, we do not use DTI but only T1-weighted magnetic resonance imaging (MRI). To construct brain network graphs, we have developed a new data-driven approach called the ε -neighbor method that does not need any predetermined parcellation. The proposed pipeline is applied in detecting the topological alteration of the white matter connectivity in maltreated children.

  19. Preliminary diffusion tensor imaging studies in limb-girdle muscular dystrophies

    Science.gov (United States)

    Hidalgo-Tobon, S.; Hernandez-Salazar, G.; Vargas-Cañas, S.; Marrufo-Melendez, O.; Solis-Najera, S.; Taboada-Barajas, J.; Rodriguez, A. O.; Delgado-Hernandez, R.

    2012-10-01

    Limb-girdle muscular dystrophies (LGMD) are a group of autosomal dominantly or recessively inherited muscular dystrophies that also present with primary proximal (limb-girdle) muscle weakness. This type of dystrophy involves the shoulder and pelvic girdles, distinct phenotypic or clinical characteristics are recognized. Imaging experiments were conducted on a 1.5T GE scanner (General Electric Medical Systems. Milwaukee. USA), using a combination of two eight-channel coil array. Diffusion Tensor Imaging (DTI) data were acquired using a SE-EPI sequence, diffusion weighted gradients were applied along 30 non-collinear directions with a b-value=550 s/mm2. The connective tissue content does not appear to have a significant effect on the directionality of the diffusion, as assessed by fractional anisotropy. The fibers of the Sartorius muscle and gracilis showed decreased number of tracts, secondary to fatty infiltration and replacement of connective tissue and muscle mass loss characteristic of the underlying pathology. Our results demonstrated the utility of non-invasive MRI techniques to characterize the muscle pathology, through quantitative and qualitative methods such as the FA values and tractrography.

  20. Diffusion tensor MRI and fiber tractography of the sacral plexus in children with spina bifida

    DEFF Research Database (Denmark)

    Haakma, Wieke; Dik, Pieter; ten Haken, Bennie

    2014-01-01

    anatomical and microstructural properties of the sacral plexus of patients with spina bifida using diffusion tensor imaging and fiber tractography. MATERIALS AND METHODS: Ten patients 8 to 16 years old with spina bifida underwent diffusion tensor imaging on a 3 Tesla magnetic resonance imaging system...... diffusivity values at S1-S3 were significantly lower in patients. CONCLUSIONS: To our knowledge this 3 Tesla magnetic resonance imaging study showed for the first time sacral plexus asymmetry and disorganization in 10 patients with spina bifida using diffusion tensor imaging and fiber tractography...

  1. Peritumoral edema of meningiomas and metastatic brain tumors: differences in diffusion characteristics evaluated with diffusion-tensor MR imaging

    International Nuclear Information System (INIS)

    Toh, Cheng-Hong; Wong, Alex M.-C; Wong, Ho-Fai; Wan, Yung-Liang; Wei, Kuo-Chen; Ng, Shu-Hang

    2007-01-01

    We prospectively compared the fractional anisotropy (FA) and mean diffusivity (MD) of the peritumoral edema of meningiomas and metastatic brain tumors with diffusion-tensor magnetic resonance (MR) imaging. The study protocol was approved by the local ethics committee, and written informed consent was obtained. Preoperative diffusion-tensor MR imaging was performed in 15 patients with meningiomas and 11 patients with metastatic brain tumors. Regions of interest (ROI) were placed in the peritumoral edema and normal-appearing white matter (NAWM) of the contralateral hemisphere to measure the FA and MD. The FA and MD ratios were calculated for each ROI in relation to the NAWM of the contralateral hemisphere. Changes in peritumoral MD and FA, in terms of primary values and ratios, were compared using a two-sample t-test; P -3 mm 2 /s) of the peritumoral edema for metastases and meningiomas, respectively, were 0.902 ± 0.057 and 0.820 ± 0.094, the mean MD ratios were 220.3 ± 22.6 and 193.1 ± 23.4, the mean FA values were 0.146 ± 0.026 and 0.199 ± 0.052, and the mean FA ratios were 32.3 ± 5.9 and 46.0 ± 12.1. All the values were significantly different between metastases and meningiomas (MD values P 0.016, MD ratios P = 0.006, FA values P = 0.005, FA ratios P = 0.002). The peritumoral edema of metastatic brain tumors and meningiomas show different MD and FA on diffusion-tensor MR imaging. (orig.)

  2. Peritumoral edema of meningiomas and metastatic brain tumors: differences in diffusion characteristics evaluated with diffusion-tensor MR imaging

    Energy Technology Data Exchange (ETDEWEB)

    Toh, Cheng-Hong; Wong, Alex M.-C; Wong, Ho-Fai; Wan, Yung-Liang [Chang Gung Memorial Hospital, Department of Medical Imaging and Intervention, Tao-Yuan (China); Chang Gung University, School of Medicine and Medical Technology, Tao-Yuan (China); Wei, Kuo-Chen [Chang Gung Memorial Hospital, Department of Neurosurgery, Tao-Yuan (China); Chang Gung University, School of Medicine and Medical Technology, Tao-Yuan (China); Ng, Shu-Hang [Chang Gung Memorial Hospital, Department of Medical Imaging and Intervention, Tao-Yuan (China); Chang Gung University, School of Medicine and Medical Technology, Tao-Yuan (China); Chang Gung Memorial Hospital, Molecular Image Center, Tao-Yuan (China)

    2007-06-15

    We prospectively compared the fractional anisotropy (FA) and mean diffusivity (MD) of the peritumoral edema of meningiomas and metastatic brain tumors with diffusion-tensor magnetic resonance (MR) imaging. The study protocol was approved by the local ethics committee, and written informed consent was obtained. Preoperative diffusion-tensor MR imaging was performed in 15 patients with meningiomas and 11 patients with metastatic brain tumors. Regions of interest (ROI) were placed in the peritumoral edema and normal-appearing white matter (NAWM) of the contralateral hemisphere to measure the FA and MD. The FA and MD ratios were calculated for each ROI in relation to the NAWM of the contralateral hemisphere. Changes in peritumoral MD and FA, in terms of primary values and ratios, were compared using a two-sample t-test; P < 0.05 was taken as indicating statistical significance. The mean MD values (x 10{sup -3} mm{sup 2}/s) of the peritumoral edema for metastases and meningiomas, respectively, were 0.902 {+-} 0.057 and 0.820 {+-} 0.094, the mean MD ratios were 220.3 {+-} 22.6 and 193.1 {+-} 23.4, the mean FA values were 0.146 {+-} 0.026 and 0.199 {+-} 0.052, and the mean FA ratios were 32.3 {+-} 5.9 and 46.0 {+-} 12.1. All the values were significantly different between metastases and meningiomas (MD values P = 0.016, MD ratios P = 0.006, FA values P = 0.005, FA ratios P = 0.002). The peritumoral edema of metastatic brain tumors and meningiomas show different MD and FA on diffusion-tensor MR imaging. (orig.)

  3. Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer’s disease cases

    OpenAIRE

    Taoka, Toshiaki; Masutani, Yoshitaka; Kawai, Hisashi; Nakane, Toshiki; Matsuoka, Kiwamu; Yasuno, Fumihiko; Kishimoto, Toshifumi; Naganawa, Shinji

    2017-01-01

    Purpose: The activity of the glymphatic system is impaired in animal models of Alzheimer’s disease (AD). We evaluated the activity of the human glymphatic system in cases of AD with a diffusion-based technique called diffusion tensor image analysis along the perivascular space (DTI-ALPS). Materials and methods: Diffusion tensor images were acquired to calculate diffusivities in the x, y, and z axes of the plane of the lateral ventricle body in 31 patients. We evaluated the diffusivity along t...

  4. Tensor gauge condition and tensor field decomposition

    Science.gov (United States)

    Zhu, Ben-Chao; Chen, Xiang-Song

    2015-10-01

    We discuss various proposals of separating a tensor field into pure-gauge and gauge-invariant components. Such tensor field decomposition is intimately related to the effort of identifying the real gravitational degrees of freedom out of the metric tensor in Einstein’s general relativity. We show that as for a vector field, the tensor field decomposition has exact correspondence to and can be derived from the gauge-fixing approach. The complication for the tensor field, however, is that there are infinitely many complete gauge conditions in contrast to the uniqueness of Coulomb gauge for a vector field. The cause of such complication, as we reveal, is the emergence of a peculiar gauge-invariant pure-gauge construction for any gauge field of spin ≥ 2. We make an extensive exploration of the complete tensor gauge conditions and their corresponding tensor field decompositions, regarding mathematical structures, equations of motion for the fields and nonlinear properties. Apparently, no single choice is superior in all aspects, due to an awkward fact that no gauge-fixing can reduce a tensor field to be purely dynamical (i.e. transverse and traceless), as can the Coulomb gauge in a vector case.

  5. Tensor spherical harmonics and tensor multipoles. II. Minkowski space

    International Nuclear Information System (INIS)

    Daumens, M.; Minnaert, P.

    1976-01-01

    The bases of tensor spherical harmonics and of tensor multipoles discussed in the preceding paper are generalized in the Hilbert space of Minkowski tensor fields. The transformation properties of the tensor multipoles under Lorentz transformation lead to the notion of irreducible tensor multipoles. We show that the usual 4-vector multipoles are themselves irreducible, and we build the irreducible tensor multipoles of the second order. We also give their relations with the symmetric tensor multipoles defined by Zerilli for application to the gravitational radiation

  6. Diffusion tensor imaging of the brainstem in children with achondroplasia.

    Science.gov (United States)

    Bosemani, Thangamadhan; Orman, Gunes; Carson, Kathryn A; Meoded, Avner; Huisman, Thierry A G M; Poretti, Andrea

    2014-11-01

    The aims of this study were to compare, using diffusion tensor imaging (DTI) of the brainstem, microstructural integrity of the white matter in children with achondroplasia and age-matched participants and to correlate the severity of craniocervical junction (CCJ) narrowing and neurological findings with DTI scalars in children with achondroplasia. This study also aimed to assess the potential role of fibroblast growth factor receptor type 3 on white matter microstructure. Diffusion tensor imaging was performed using a 1.5T magnetic resonance scanner and balanced pairs of diffusion gradients along 20 non-collinear directions. Measurements were obtained from regions of interest, sampled in each pontine corticospinal tract (CST), medial lemniscus, and middle cerebellar peduncle, as well as in the lower brainstem and centrum semiovale, for fractional anisotropy and for mean, axial, and radial diffusivity. In addition, a severity score for achondroplasia was assessed by measuring CCJ narrowing. Eight patients with achondroplasia (seven males, one female; mean age 5y 6mo, range 1y 1mo-15y 1mo) and eight age- and sex-matched comparison participants (mean age 5y 2mo, range 1y 1mo-14y 11mo) were included in this study. Fractional anisotropy was lower and mean diffusivity and radial diffusivity were higher in the lower brainstem of patients with achondroplasia than in age-matched comparison participants. The CST and middle cerebellar peduncle of the participants showed increases in mean, axial, and radial diffusivity. Fractional anisotropy in the lower brainstem was negatively correlated with the degree of CCJ narrowing. No differences in the DTI metrics of the centrum semiovale were observed between the two groups. The reduction in fractional anisotropy and increase in diffusivities in the lower brainstem of participants with achondroplasia may reflect secondary encephalomalacic degeneration and cavitation of the affected white matter tracts as shown by histology. In

  7. Linear Invariant Tensor Interpolation Applied to Cardiac Diffusion Tensor MRI

    Science.gov (United States)

    Gahm, Jin Kyu; Wisniewski, Nicholas; Kindlmann, Gordon; Kung, Geoffrey L.; Klug, William S.; Garfinkel, Alan; Ennis, Daniel B.

    2015-01-01

    Purpose Various methods exist for interpolating diffusion tensor fields, but none of them linearly interpolate tensor shape attributes. Linear interpolation is expected not to introduce spurious changes in tensor shape. Methods Herein we define a new linear invariant (LI) tensor interpolation method that linearly interpolates components of tensor shape (tensor invariants) and recapitulates the interpolated tensor from the linearly interpolated tensor invariants and the eigenvectors of a linearly interpolated tensor. The LI tensor interpolation method is compared to the Euclidean (EU), affine-invariant Riemannian (AI), log-Euclidean (LE) and geodesic-loxodrome (GL) interpolation methods using both a synthetic tensor field and three experimentally measured cardiac DT-MRI datasets. Results EU, AI, and LE introduce significant microstructural bias, which can be avoided through the use of GL or LI. Conclusion GL introduces the least microstructural bias, but LI tensor interpolation performs very similarly and at substantially reduced computational cost. PMID:23286085

  8. Diffusion Tensor Imaging of Normal-Appearing White Matter as Biomarker for Radiation-Induced Late Delayed Cognitive Decline

    International Nuclear Information System (INIS)

    Chapman, Christopher H.; Nagesh, Vijaya; Sundgren, Pia C.; Buchtel, Henry; Chenevert, Thomas L.; Junck, Larry; Lawrence, Theodore S.; Tsien, Christina I.; Cao, Yue

    2012-01-01

    Purpose: To determine whether early assessment of cerebral white matter degradation can predict late delayed cognitive decline after radiotherapy (RT). Methods and Materials: Ten patients undergoing conformal fractionated brain RT participated in a prospective diffusion tensor magnetic resonance imaging study. Magnetic resonance imaging studies were acquired before RT, at 3 and 6 weeks during RT, and 10, 30, and 78 weeks after starting RT. The diffusivity variables in the parahippocampal cingulum bundle and temporal lobe white matter were computed. A quality-of-life survey and neurocognitive function tests were administered before and after RT at the magnetic resonance imaging follow-up visits. Results: In both structures, longitudinal diffusivity (λ ‖ ) decreased and perpendicular diffusivity (λ ⊥ ) increased after RT, with early changes correlating to later changes (p ⊥ at 3 weeks, and patients with >50% of cingula volume receiving >12 Gy had a greater increase in λ ⊥ at 3 and 6 weeks (p ‖ (30 weeks, p ‖ changes predicted for post-RT changes in verbal recall scores (3 and 6 weeks, p < .05). The neurocognitive test scores correlated significantly with the quality-of-life survey results. Conclusions: The correlation between early diffusivity changes in the parahippocampal cingulum and the late decline in verbal recall suggests that diffusion tensor imaging might be useful as a biomarker for predicting late delayed cognitive decline.

  9. Structural changes in Parkinson's disease: voxel-based morphometry and diffusion tensor imaging analyses based on 123I-MIBG uptake.

    Science.gov (United States)

    Kikuchi, Kazufumi; Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Somehara, Ryo; Kamei, Ryotaro; Baba, Shingo; Yamaguchi, Hiroo; Kira, Jun-Ichi; Honda, Hiroshi

    2017-12-01

    Patients with Parkinson's disease (PD) may exhibit symptoms of sympathetic dysfunction that can be measured using 123 I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy. We investigated the relationship between microstructural brain changes and 123 I-MIBG uptake in patients with PD using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analyses. This retrospective study included 24 patients with PD who underwent 3 T magnetic resonance imaging and 123 I-MIBG scintigraphy. They were divided into two groups: 12 MIBG-positive and 12 MIBG-negative cases (10 men and 14 women; age range: 60-81 years, corrected for gender and age). The heart/mediastinum count (H/M) ratio was calculated on anterior planar 123 I-MIBG images obtained 4 h post-injection. VBM and DTI were performed to detect structural differences between these two groups. Patients with low H/M ratio had significantly reduced brain volume at the right inferior frontal gyrus (uncorrected p  90). Patients with low H/M ratios also exhibited significantly lower fractional anisotropy than those with high H/M ratios (p based morphometry can detect grey matter changes in Parkinson's disease. • Diffusion tensor imaging can detect white matter changes in Parkinson's disease.

  10. Delineating Neural Structures of Developmental Human Brains with Diffusion Tensor Imaging

    Directory of Open Access Journals (Sweden)

    Hao Huang

    2010-01-01

    Full Text Available The human brain anatomy is characterized by dramatic structural changes during fetal development. It is extraordinarily complex and yet its origin is a simple tubular structure. Revealing detailed anatomy at different stages of brain development not only aids in understanding this highly ordered process, but also provides clues to detect abnormalities caused by genetic or environmental factors. However, anatomical studies of human brain development during the fetal period are surprisingly scarce and histology-based atlases have become available only recently. Diffusion tensor imaging (DTI measures water diffusion to delineate the underlying neural structures. The high contrasts derived from DTI can be used to establish the brain atlas. With DTI tractography, coherent neural structures, such as white matter tracts, can be three-dimensionally reconstructed. The primary eigenvector of the diffusion tensor can be further explored to characterize microstructures in the cerebral wall of the developmental brains. In this mini-review, the application of DTI in order to reveal the structures of developmental fetal brains has been reviewed in the above-mentioned aspects. The fetal brain DTI provides a unique insight for delineating the neural structures in both macroscopic and microscopic levels. The resultant DTI database will provide structural guidance for the developmental study of human fetal brains in basic neuroscience, and reference standards for diagnostic radiology of premature newborns.

  11. Longitudinal study on diffusion tensor imaging and diffusion tensor tractography following spinal cord contusion injury in rats.

    Science.gov (United States)

    Zhao, Can; Rao, Jia-Sheng; Pei, Xiao-Jiao; Lei, Jian-Feng; Wang, Zhan-Jing; Yang, Zhao-Yang; Li, Xiao-Guang

    2016-06-01

    Diffusion tensor imaging (DTI) as a potential technology has been used in spinal cord injury (SCI) studies, but the longitudinal evaluation of DTI parameters after SCI, and the correlation between DTI parameters and locomotor outcomes need to be defined. Adult Wistar rats (n = 6) underwent traumatic thoracic cord contusion by an NYU impactor. DTI and Basso-Beattie-Bresnahan datasets were collected pre-SCI and 1, 3, 7, 14, and 84 days post-SCI. Diffusion tensor tractography (DTT) of the spinal cord was also generated. Fractional anisotropy (FA) and connection rate of fibers at the injury epicenter and at 5 mm rostral/caudal to the epicenter were calculated. The variations of these parameters after SCI were observed by one-way analysis of variance and the correlations between these parameters and motor function were explored by Pearson's correlation. FA at the epicenter decreased most remarkably on day 1 post-SCI (from 0.780 ± 0.012 to 0.330 ± 0.015), and continued to decrease slightly by day 3 post-SCI (0.313 ± 0.015), while other parameters decreased significantly over the first 3 days after SCI. DTT showed residual fibers concentrated on ventral and ventrolateral sides of the cord. Moreover, FA at the epicenter exhibited the strongest correlation (r = 0.887, p = 0.000) with the locomotion performance. FA was sensitive to degeneration in white matter and DTT could directly reflect the distribution of the residual white matter. Moreover, days 1 to 3 post-SCI may be the optimal time window for SCI examination and therapy.

  12. Neurite density imaging versus imaging of microscopic anisotropy in diffusion MRI: A model comparison using spherical tensor encoding.

    Science.gov (United States)

    Lampinen, Björn; Szczepankiewicz, Filip; Mårtensson, Johan; van Westen, Danielle; Sundgren, Pia C; Nilsson, Markus

    2017-02-15

    In diffusion MRI (dMRI), microscopic diffusion anisotropy can be obscured by orientation dispersion. Separation of these properties is of high importance, since it could allow dMRI to non-invasively probe elongated structures such as neurites (axons and dendrites). However, conventional dMRI, based on single diffusion encoding (SDE), entangles microscopic anisotropy and orientation dispersion with intra-voxel variance in isotropic diffusivity. SDE-based methods for estimating microscopic anisotropy, such as the neurite orientation dispersion and density imaging (NODDI) method, must thus rely on model assumptions to disentangle these features. An alternative approach is to directly quantify microscopic anisotropy by the use of variable shape of the b-tensor. Along those lines, we here present the 'constrained diffusional variance decomposition' (CODIVIDE) method, which jointly analyzes data acquired with diffusion encoding applied in a single direction at a time (linear tensor encoding, LTE) and in all directions (spherical tensor encoding, STE). We then contrast the two approaches by comparing neurite density estimated using NODDI with microscopic anisotropy estimated using CODIVIDE. Data were acquired in healthy volunteers and in glioma patients. NODDI and CODIVIDE differed the most in gray matter and in gliomas, where NODDI detected a neurite fraction higher than expected from the level of microscopic diffusion anisotropy found with CODIVIDE. The discrepancies could be explained by the NODDI tortuosity assumption, which enforces a connection between the neurite density and the mean diffusivity of tissue. Our results suggest that this assumption is invalid, which leads to a NODDI neurite density that is inconsistent between LTE and STE data. Using simulations, we demonstrate that the NODDI assumptions result in parameter bias that precludes the use of NODDI to map neurite density. With CODIVIDE, we found high levels of microscopic anisotropy in white matter

  13. Assessment of diffusion tensor image quality across sites and vendors using the American College of Radiology head phantom.

    Science.gov (United States)

    Wang, Zhiyue J; Seo, Youngseob; Babcock, Evelyn; Huang, Hao; Bluml, Stefan; Wisnowski, Jessica; Holshouser, Barbara; Panigrahy, Ashok; Shaw, Dennis W W; Altman, Nolan; McColl, Roderick W; Rollins, Nancy K

    2016-05-08

    The purpose of this study was to explore the feasibility of assessing quality of diffusion tensor imaging (DTI) from multiple sites and vendors using American College of Radiology (ACR) phantom. Participating sites (Siemens (n = 2), GE (n= 2), and Philips (n = 4)) reached consensus on parameters for DTI and used the widely available ACR phantom. Tensor data were processed at one site. B0 and eddy current distortions were assessed using grid line displacement on phantom Slice 5; signal-to-noise ratio (SNR) was measured at the center and periphery of the b = 0 image; fractional anisotropy (FA) and mean diffusivity (MD) were assessed using phantom Slice 7. Variations of acquisition parameters and deviations from specified sequence parameters were recorded. Nonlinear grid line distortion was higher with linear shimming and could be corrected using the 2nd order shimming. Following image registration, eddy current distortion was consistently smaller than acquisi-tion voxel size. SNR was consistently higher in the image periphery than center by a factor of 1.3-2.0. ROI-based FA ranged from 0.007 to 0.024. ROI-based MD ranged from 1.90 × 10-3 to 2.33 × 10-3 mm2/s (median = 2.04 × 10-3 mm2/s). Two sites had image void artifacts. The ACR phantom can be used to compare key qual-ity measures of diffusion images acquired from multiple vendors at multiple sites.

  14. Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging.

    Science.gov (United States)

    Genova, Helen M; Rajagopalan, Venkateswaran; Deluca, John; Das, Abhijit; Binder, Allison; Arjunan, Aparna; Chiaravalloti, Nancy; Wylie, Glenn

    2013-01-01

    The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS), looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI) was used to examine where in the brain BOLD activity covaried with "state" fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI) was used to examine where in the brain white matter damage correlated with increased "trait" fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS) completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a "fatigue-network" in MS.

  15. Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging.

    Directory of Open Access Journals (Sweden)

    Helen M Genova

    Full Text Available The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS, looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI was used to examine where in the brain BOLD activity covaried with "state" fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI was used to examine where in the brain white matter damage correlated with increased "trait" fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a "fatigue-network" in MS.

  16. Love songs, bird brains and diffusion tensor imaging.

    Science.gov (United States)

    De Groof, Geert; Van der Linden, Annemie

    2010-08-01

    The song control system of songbirds displays a remarkable seasonal neuroplasticity in species in which song output also changes seasonally. Thus far, this song control system has been extensively analyzed by histological and electrophysiological methods. However, these approaches do not provide a global view of the brain and/or do not allow repeated measurements, which are necessary to establish causal correlations between alterations in neural substrate and behavior. Research has primarily been focused on the song nuclei themselves, largely neglecting their interconnections and other brain regions involved in seasonally changing behavior. In this review, we introduce and explore the song control system of songbirds as a natural model for brain plasticity. At the same time, we point out the added value of the songbird brain model for in vivo diffusion tensor techniques and its derivatives. A compilation of the diffusion tensor imaging (DTI) data obtained thus far in this system demonstrates the usefulness of this in vivo method for studying brain plasticity. In particular, it is shown to be a perfect tool for long-term studies of morphological and cellular changes of specific brain circuits in different endocrine/photoperiod conditions. The method has been successfully applied to obtain quantitative measurements of seasonal changes of fiber tracts and nuclei from the song control system. In addition, outside the song control system, changes have been discerned in the optic chiasm and in an interhemispheric connection. DTI allows the detection of seasonal changes in a region analogous to the mammalian secondary auditory cortex and in regions of the 'social behavior network', an interconnected group of structures that controls multiple social behaviors, including aggression and courtship. DTI allows the demonstration, for the first time, that the songbird brain in its entirety exhibits an extreme seasonal plasticity which is not merely limited to the song control

  17. TENSOR MODELING BASED FOR AIRBORNE LiDAR DATA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    N. Li

    2016-06-01

    Full Text Available Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed. First, multiple features are extracted from raw LiDAR point cloud, and raster LiDAR images are derived by accumulating features or the “raw” data attributes. Then, the feature rasters of LiDAR data are stored as a tensor, and tensor decomposition is used to select component features. This tensor representation could keep the initial spatial structure and insure the consideration of the neighborhood. Based on a small number of component features a k nearest neighborhood classification is applied.

  18. Spatial Mapping of Structural and Connectional Imaging Data for the Developing Human Brain with Diffusion Tensor Imaging

    Science.gov (United States)

    Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao

    2014-01-01

    During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302

  19. Spatial mapping of structural and connectional imaging data for the developing human brain with diffusion tensor imaging.

    Science.gov (United States)

    Ouyang, Austin; Jeon, Tina; Sunkin, Susan M; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S; Huang, Hao

    2015-02-01

    During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Diffusion tensor imaging of partial intractable epilepsy

    International Nuclear Information System (INIS)

    Dumas de la Roque, Anne; Oppenheim, Catherine; Rodrigo, Sebastian; Meder, Jean-Francois; Chassoux, Francine; Devaux, Bertrand; Beuvon, Frederic; Daumas-Duport, Catherine

    2005-01-01

    Our aim was to assess the value of diffusion tensor imaging (DTI) in patients with partial intractable epilepsy. We used DTI (25 non-collinear directions) in 15 patients with a cortical lesion on conventional MRI. Fractional anisotropy (FA) was measured in the internal capsule, and in the normal-appearing white matter (WM), adjacent tothe lesion, and away from the lesion, at a set distance of 2-3 cm. In each patient, increased or decreased FA measurements were those that varied from mirror values using an arbitrary 10% threshold. Over the whole population, ipsi- and contralateral FA measurements were also compared using a Wilcoxon test (p<0.05). Over the whole population, FA was significantly reduced in the WM adjacent to and away from the lesion, whilst being normal in the internal capsule. FA was reduced by more than 10% in the WM adjacent to and distant from the lesion in 13 and 12 patients respectively. For nine of the ten patients for whom the surgical resection encompassed the limits of the lesion on conventional MRI, histological data showed WM alterations (gliosis, axonal loss, abnormal cells). DTI often reveals WM abnormalities that are undetected on conventional MRI in patients with partial intractable epilepsy. (orig.)

  1. Changes in lumbosacral spinal nerve roots on diffusion tensor imaging in spinal stenosis

    Directory of Open Access Journals (Sweden)

    Zhong-jun Hou

    2015-01-01

    Full Text Available Lumbosacral degenerative disc disease is a common cause of lower back and leg pain. Conventional T1-weighted imaging (T1WI and T2-weighted imaging (T2WI scans are commonly used to image spinal cord degeneration. However, these modalities are unable to image the entire lumbosacral spinal nerve roots. Thus, in the present study, we assessed the potential of diffusion tensor imaging (DTI for quantitative assessment of compressed lumbosacral spinal nerve roots. Subjects were 20 young healthy volunteers and 31 patients with lumbosacral stenosis. T2WI showed that the residual dural sac area was less than two-thirds that of the corresponding normal area in patients from L 3 to S 1 stenosis. On T1WI and T2WI, 74 lumbosacral spinal nerve roots from 31 patients showed compression changes. DTI showed thinning and distortion in 36 lumbosacral spinal nerve roots (49% and abruption in 17 lumbosacral spinal nerve roots (23%. Moreover, fractional anisotropy values were reduced in the lumbosacral spinal nerve roots of patients with lumbosacral stenosis. These findings suggest that DTI can objectively and quantitatively evaluate the severity of lumbosacral spinal nerve root compression.

  2. Changes in lumbosacral spinal nerve roots on diffusion tensor imaging in spinal stenosis.

    Science.gov (United States)

    Hou, Zhong-Jun; Huang, Yong; Fan, Zi-Wen; Li, Xin-Chun; Cao, Bing-Yi

    2015-11-01

    Lumbosacral degenerative disc disease is a common cause of lower back and leg pain. Conventional T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) scans are commonly used to image spinal cord degeneration. However, these modalities are unable to image the entire lumbosacral spinal nerve roots. Thus, in the present study, we assessed the potential of diffusion tensor imaging (DTI) for quantitative assessment of compressed lumbosacral spinal nerve roots. Subjects were 20 young healthy volunteers and 31 patients with lumbosacral stenosis. T2WI showed that the residual dural sac area was less than two-thirds that of the corresponding normal area in patients from L3 to S1 stenosis. On T1WI and T2WI, 74 lumbosacral spinal nerve roots from 31 patients showed compression changes. DTI showed thinning and distortion in 36 lumbosacral spinal nerve roots (49%) and abruption in 17 lumbosacral spinal nerve roots (23%). Moreover, fractional anisotropy values were reduced in the lumbosacral spinal nerve roots of patients with lumbosacral stenosis. These findings suggest that DTI can objectively and quantitatively evaluate the severity of lumbosacral spinal nerve root compression.

  3. Diffusion tensor imaging of the normal prostate at 3 Tesla

    International Nuclear Information System (INIS)

    Guerses, Bengi; Kabakci, Neslihan; Kovanlikaya, Arzu; Firat, Zeynep; Bayram, Ali; Kovanlikaya, Ilhami; Ulud, Aziz M.

    2008-01-01

    The aim of this study was to assess the feasibility of diffusion tensor imaging (DTI) of the prostate and to determine normative fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of healthy prostate with a 3-Tesla magnetic resonance imaging (MRI) system. Thirty volunteers with a mean age of 28 (25-35) years were scanned with a 3-Tesla MRI (Intera Achieva; Philips, The Netherlands) system using a six-channel phased array coil. Initially, T2-weighted turbo spin-echo (TSE) axial images of the prostate were obtained. In two subjects, a millimetric hypointense signal change was detected in the peripheral zones on T2-weighted TSE images. These two subjects were excluded from the study. DTI with single-shot echo-planar imaging (ssEPI) was performed in the remaining 28 subjects. ADC and FA values were measured using the manufacturer supplied software by positioning 9-pixel ROIs on each zone. Differences between parameters of the central and peripheral zones were assessed. Mean ADC value of the central (1.220 ± 0.271 x 10 -3 mm 2 /s) was found to be significantly lower when compared with the peripheral gland (1.610 ± 0.347 x 10 -3 mm 2 /s) (P < 0.01). Mean FA of the central gland was significantly higher (0.26), compared with the peripheral gland (0.16) (P < 0.01). This study shows the feasibility of prostate DTI with a 3-Tesla MR system and the normative FA and ADC values of peripheral and central zones of the normal prostate. The results are compatible with the microstructural organization of the gland. (orig.)

  4. Current contribution of diffusion tensor imaging in the evaluation of diffuse axonal injury

    Directory of Open Access Journals (Sweden)

    Daphine Centola Grassi

    Full Text Available ABSTRACT Traumatic brain injury (TBI is the number one cause of death and morbidity among young adults. Moreover, survivors are frequently left with functional disabilities during the most productive years of their lives. One main aspect of TBI pathology is diffuse axonal injury, which is increasingly recognized due to its presence in 40% to 50% of all cases that require hospital admission. Diffuse axonal injury is defined as widespread axonal damage and is characterized by complete axotomy and secondary reactions due to overall axonopathy. These changes can be seen in neuroimaging studies as hemorrhagic focal areas and diffuse edema. However, the diffuse axonal injury findings are frequently under-recognized in conventional neuroimaging studies. In such scenarios, diffuse tensor imaging (DTI plays an important role because it provides further information on white matter integrity that is not obtained with standard magnetic resonance imaging sequences. Extensive reviews concerning the physics of DTI and its use in the context of TBI patients have been published, but these issues are still hazy for many allied-health professionals. Herein, we aim to review the current contribution of diverse state-of-the-art DTI analytical methods to the understanding of diffuse axonal injury pathophysiology and prognosis, to serve as a quick reference for those interested in planning new studies and who are involved in the care of TBI victims. For this purpose, a comprehensive search in Pubmed was performed using the following keywords: “traumatic brain injury”, “diffuse axonal injury”, and “diffusion tensor imaging”.

  5. Quantitative evaluation of normal lumbosacral plexus nerve by using diffusion tensor imaging

    International Nuclear Information System (INIS)

    Shi Yin; Wang Chuanbing; Liu Wei; Zong Min; Sa Rina; Shi Haibin; Wang Dehang

    2014-01-01

    Objective: To observe the lumbosacral plexus nerves by diffusion tensor tractography (DTT) and quantitatively evaluate them by using diffusion tensor imaging (DTI) in healthy volunteers. Methods: A total of 60 healthy volunteers (30 males and 30 females) underwent DTI scanning. Mean FA values of the lumbosacral plexus nerves (both sides of lumbar roots L3 to S1, proximal and distal to the lumbar foraminal zone) were quantified. Differences among various segments of lumbar nerve roots were compared with ANOVA test and SNK test. Differences between two sides of the lumbar nerve roots at the same lumbar segment were compared with paired-samples t test. Differences between the proximal and the distal nerve to the the lumbar foraminal zone at the same lumbar segment were compared with paired-samples t test. The lumbosacral plexus nerve was visualized with tractography. Results: (1) The lumbosacral plexus nerve was clearly visualized with tractography. (2) Mean FA values of the lumbar nerve roots L3 to S1 were as followings: proximal to the left lumbar foraminal zone 0.202 ± 0.021, 0.201 ± 0.026, 0.201 ± 0.027, 0.191 ±0.016, distal to the left lumbar foraminal zone 0.222 ± 0.034, 0.250 ± 0.028, 0.203 ± 0.026, 0.183 ± 0.020, proximal to the right lumbar foraminal zone 0.200 ± 0.023, 0.202 ± 0.023, 0.205 ± 0.027, 0.191 ± 0.017, distal to the right lumbar foraminal zone 0.225 ± 0.032, 0.247 ± 0.027, 0.205 ± 0.033, 0.183 ± 0.021. Mean FA values were significantly different between the proximal nerve to the distal nerve in lumbar nerve roots L3, L4, S1 (t=-9.114-2.366, P<0.05), but not significantly different in L5 (P>0.05). Differences were not found between the right and left side nerves at the same lumbar segment (P>0.05). (3) The whole length of the lumbar roots nerve L3 to S1 can be visualized clearly by using DTT. Conclusions: Diffusion tensor imaging and tractography can show and provide quantitative information of human lumbosacral plexus nerves. DTI

  6. A voxel-based morphometry and diffusion tensor imaging analysis of asymptomatic Parkinson's disease-related G2019S LRRK2 mutation carriers.

    Science.gov (United States)

    Thaler, Avner; Artzi, Moran; Mirelman, Anat; Jacob, Yael; Helmich, Rick C; van Nuenen, Bart F L; Gurevich, Tanya; Orr-Urtreger, Avi; Marder, Karen; Bressman, Susan; Bloem, Bastiaan R; Hendler, Talma; Giladi, Nir; Ben Bashat, Dafna

    2014-05-01

    Patients with Parkinson's disease have reduced gray matter volume and fractional anisotropy in both cortical and sub-cortical structures, yet changes in the pre-motor phase of the disease are unknown. A comprehensive imaging study using voxel-based morphometry and diffusion tensor imaging tract-based spatial statistics analysis was performed on 64 Ashkenazi Jewish asymptomatic first degree relatives of patients with Parkinson's disease (30 mutation carriers), who carry the G2019S mutation in the leucine-rich repeat kinase 2 (LRRK2) gene. No between-group differences in gray matter volume could be noted in either whole-brain or volume-of-interest analysis. Diffusion tensor imaging analysis did not identify group differences in white matter areas, and volume-of-interest analysis identified no differences in diffusivity parameters in Parkinson's disease-related structures. G2019S carriers do not manifest changes in gray matter volume or diffusivity parameters in Parkinson's disease-related structures prior to the appearance of motor symptoms. © 2014 International Parkinson and Movement Disorder Society.

  7. Arcuate fasciculus laterality by diffusion tensor imaging correlates with language laterality by functional MRI in preadolescent children.

    Science.gov (United States)

    Sreedharan, Ruma Madhu; Menon, Amitha C; James, Jija S; Kesavadas, Chandrasekharan; Thomas, Sanjeev V

    2015-03-01

    Language lateralization is unique to humans. Functional MRI (fMRI) and diffusion tensor imaging (DTI) enable the study of language areas and white matter fibers involved in language, respectively. The objective of this study was to correlate arcuate fasciculus (AF) laterality by diffusion tensor imaging with that by fMRI in preadolescent children which has not yet been reported. Ten children between 8 and 12 years were subjected to fMRI and DTI imaging using Siemens 1.5 T MRI. Two language fMRI paradigms--visual verb generation and word pair task--were used. Analysis was done using SPM8 software. In DTI, the fiber volume of the arcuate fasciculus (AFV) and fractional anisotropy (FA) was measured. The fMRI Laterality Index (fMRI-LI) and DTI Laterality Index (DTI-LI) were calculated and their correlation assessed using the Pearson Correlation Index. Of ten children, mean age 10.6 years, eight showed left lateralization while bilateral language lateralization was seen in two. AFV by DTI was more on the left side in seven of the eight children who had left lateralization by fMRI. DTI could not trace the AF in one child. Of the two with bilateral language lateralization on fMRI, one showed larger AFV on the right side while the other did not show any asymmetry. There was a significant correlation (p laterality in children with a high degree of correlation between the two imaging modalities.

  8. Mid-callosal plane determination using preferred directions from diffusion tensor images

    Science.gov (United States)

    Costa, André L.; Rittner, Letícia; Lotufo, Roberto A.; Appenzeller, Simone

    2015-03-01

    The corpus callosum is the major brain structure responsible for inter{hemispheric communication between neurons. Many studies seek to relate corpus callosum attributes to patient characteristics, cerebral diseases and psychological disorders. Most of those studies rely on 2D analysis of the corpus callosum in the mid-sagittal plane. However, it is common to find conflicting results among studies, once many ignore methodological issues and define the mid-sagittal plane based on precary or invalid criteria with respect to the corpus callosum. In this work we propose a novel method to determine the mid-callosal plane using the corpus callosum internal preferred diffusion directions obtained from diffusion tensor images. This plane is analogous to the mid-sagittal plane, but intended to serve exclusively as the corpus callosum reference. Our method elucidates the great potential the directional information of the corpus callosum fibers have to indicate its own referential. Results from experiments with five image pairs from distinct subjects, obtained under the same conditions, demonstrate the method effectiveness to find the corpus callosum symmetric axis relative to the axial plane.

  9. Diffusion tensor MR microscopy of tissues with low diffusional anisotropy.

    Science.gov (United States)

    Bajd, Franci; Mattea, Carlos; Stapf, Siegfried; Sersa, Igor

    2016-06-01

    Diffusion tensor imaging exploits preferential diffusional motion of water molecules residing within tissue compartments for assessment of tissue structural anisotropy. However, instrumentation and post-processing errors play an important role in determination of diffusion tensor elements. In the study, several experimental factors affecting accuracy of diffusion tensor determination were analyzed. Effects of signal-to-noise ratio and configuration of the applied diffusion-sensitizing gradients on fractional anisotropy bias were analyzed by means of numerical simulations. In addition, diffusion tensor magnetic resonance microscopy experiments were performed on a tap water phantom and bovine articular cartilage-on-bone samples to verify the simulation results. In both, the simulations and the experiments, the multivariate linear regression of the diffusion-tensor analysis yielded overestimated fractional anisotropy with low SNRs and with low numbers of applied diffusion-sensitizing gradients. An increase of the apparent fractional anisotropy due to unfavorable experimental conditions can be overcome by applying a larger number of diffusion sensitizing gradients with small values of the condition number of the transformation matrix. This is in particular relevant in magnetic resonance microscopy, where imaging gradients are high and the signal-to-noise ratio is low.

  10. Diffusion Tensor Imaging Correlates with Short-Term Myelopathy Outcome in Patients with Cervical Spondylotic Myelopathy.

    Science.gov (United States)

    Vedantam, Aditya; Rao, Avinash; Kurpad, Shekar N; Jirjis, Michael B; Eckardt, Gerald; Schmit, Brian D; Wang, Marjorie C

    2017-01-01

    To determine if spinal cord diffusion tensor imaging indexes correlate with short-term clinical outcome in patients undergoing elective cervical spine surgery for cervical spondylotic myelopathy (CSM). A prospective consecutive cohort study was performed in patients undergoing elective cervical spine surgery for CSM. After obtaining informed consent, patients with CSM underwent preoperative T2-weighted magnetic resonance imaging and diffusion tensor imaging of the cervical spine. Fractional anisotropy (FA) values at the level of maximum cord compression and at the noncompressed C1-2 level were calculated on axial images. We recorded the modified Japanese Orthopaedic Association (mJOA) scale, Neck Disability Index, and Short Form-36 physical functioning subscale scores for all patients preoperatively and 3 months postoperatively. Statistical analysis was performed to identify correlations between FA and clinical outcome scores. The study included 27 patients (mean age 54.5 years ± 1.9, 12 men). The mean postoperative changes in mJOA scale, Neck Disability Index, and Short Form-36 physical functioning subscale scores were 0.9 ± 0.3, -6.0 ± 1.9, and 3.4 ± 1.9. The mean FA at the level of maximum compression was significantly lower than the mean FA at the C1-2 level (0.5 vs. 0.55, P = 0.01). FA was significantly correlated with change in mJOA scale score (Pearson r = -0.42, P = 0.02). FA was significantly correlated with the preoperative mJOA scale score (Pearson r = 0.65, P < 0.001). Preoperative FA at the level of maximum cord compression significantly correlates with the 3-month change in mJOA scale score among patients with CSM. FA was also significantly associated with preoperative mJOA scale score and is a potential biomarker for spinal cord dysfunction in CSM. Published by Elsevier Inc.

  11. Reconstruction of white matter fibre tracts using diffusion kurtosis tensor imaging at 1.5T: Pre-surgical planning in patients with gliomas.

    Science.gov (United States)

    Leote, Joao; Nunes, Rita G; Cerqueira, Luis; Loução, Ricardo; Ferreira, Hugo A

    2018-01-01

    Tractography studies for pre-surgical planning of primary brain tumors is typically done using diffusion tensor imaging (DTI), which cannot resolve crossing, kissing or highly angulated fibres. Tractography based on the estimation of the diffusion kurtosis (DK) tensor was recently demonstrated to enable tackling these limitations. However, its use in the clinical context at low 1.5T field has not yet been reported. To evaluate if the estimation of whole-brain tractography using the DK tensor is feasible for pre-surgical investigation of patients with brain tumors at 1.5T. Eight healthy subjects and 3 patients with brain tumors were scanned at 1.5T using a 12-channel head coil. Diffusion-weighted images were acquired with repetition/echo times of 5800/107 ms, 82 × 82 resolution, 3 × 3 × 3 mm 3 voxel size, b-values of 0, 1000, 2000 s/mm 2 and 64 gradient sensitising directions. Whole-brain tractography was estimated using the DK tensor and corticospinal tracts (CST) were isolated using regions-of-interest placed at the cerebral peduncles and motor gyrus. Tract size, DK metrics and CST deviation index (highest curvature point) were compared between healthy subjects and patients. Tract sizes did not differ between groups. The CST deviation index was significantly higher in patients compared to healthy subjects. Fractional anisotropy was significantly lower in patients, with higher mean kurtosis asymmetry index at the highest curvature point in patients. Corticospinal fibre bundles estimated using DK tensor in a 1.5T scanner presented similar properties in patients with brain gliomas as those reported in the literature using DTI-based tractography.

  12. Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination.

    Science.gov (United States)

    Zhao, Qibin; Zhang, Liqing; Cichocki, Andrzej

    2015-09-01

    CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithms require the tensor rank to be manually specified, however, the determination of tensor rank remains a challenging problem especially for CP rank . In addition, existing approaches do not take into account uncertainty information of latent factors, as well as missing entries. To address these issues, we formulate CP factorization using a hierarchical probabilistic model and employ a fully Bayesian treatment by incorporating a sparsity-inducing prior over multiple latent factors and the appropriate hyperpriors over all hyperparameters, resulting in automatic rank determination. To learn the model, we develop an efficient deterministic Bayesian inference algorithm, which scales linearly with data size. Our method is characterized as a tuning parameter-free approach, which can effectively infer underlying multilinear factors with a low-rank constraint, while also providing predictive distributions over missing entries. Extensive simulations on synthetic data illustrate the intrinsic capability of our method to recover the ground-truth of CP rank and prevent the overfitting problem, even when a large amount of entries are missing. Moreover, the results from real-world applications, including image inpainting and facial image synthesis, demonstrate that our method outperforms state-of-the-art approaches for both tensor factorization and tensor completion in terms of predictive performance.

  13. Corticospinal tract degeneration and possible pathogenesis in ALS evaluated by MR diffusion tensor imaging

    DEFF Research Database (Denmark)

    Karlsborg, Merete; Rosenbaum, Sverre; Wiegell, Mette R.

    2004-01-01

    BACKGROUND: MR diffusion tensor imaging (DTI) appears to be a powerful method to investigate the neuronal and axonal fibre distribution in the human brain. Changes in diffusion characteristics of water molecules in the white matter can be estimated as the apparent diffusion coefficient (ADC...... significance. ADC was unchanged at the level of the corona radiata. FA was significantly reduced at the lowest level (pons), only tended to be reduced in the internal capsule, but was also unchanged in the corona radiata. CONCLUSIONS: Segmentation of the CST into three regions supports the hypothesis...

  14. Microstructural changes in thickened corpus callosum in children: contribution of magnetic resonance diffusion tensor imaging

    Energy Technology Data Exchange (ETDEWEB)

    Merlini, Laura; Anooshiravani, Mehrak; Kanavaki, Aikaterini; Hanquinet, Sylviane [University of Geneva Children' s Hospital, Pediatric Radiology Unit, Geneva (Switzerland)

    2015-06-15

    Thickened corpus callosum is a rare finding and its pathophysiology is not well known. An anomalous supracallosal bundle has been depicted by fiber tracking in some cases but no diffusion tensor imaging metrics of thickened corpus callosum have been reported. To use diffusion tensor imaging (DTI) in cases of thickened corpus callosum to help in understanding its clinical significance. During a 7-year period five children (ages 6 months to 15 years) with thickened corpus callosum were studied. We determined DTI metrics of fractional anisotropy (FA), mean diffusivity, and axial (λ1) and radial (λ2, λ3) diffusivity and performed 3-D fiber tracking reconstruction of the thickened corpus callosum. We compared our results with data from the literature and 24 age-matched controls. Brain abnormalities were seen in all cases. All children had at least three measurements of corpus callosum thickness above the 97th percentile according to age. In all children 3-D fiber tracking showed an anomalous supracallosal bundle and statistically significant decrease in FA (P = 0.003) and λ1 (P = 0.001) of the corpus callosum compared with controls, but no significant difference in mean diffusivity and radial diffusivity. Thickened corpus callosum was associated with abnormal bundles, suggesting underlying axonal guidance abnormality. DTI metrics suggested abnormal fiber compactness and density, which may be associated with alterations in cognition. (orig.)

  15. Diffusion tensor MR imaging in neurofibromatosis type 1: expanding the knowledge of microstructural brain abnormalities

    International Nuclear Information System (INIS)

    Ferraz-Filho, Jose R.L.; Muniz, Marcos P.; Souza, Antonio S.; Rocha, Antonio J. da; Goloni-Bertollo, Eny M.; Pavarino-Bertelli, Erika C.

    2012-01-01

    Neurofibromatosis type 1 (NF1) is a hereditary disease with a dominant autosomal pattern. In children and adolescents, it is frequently associated with the appearance of T2-weighted hyperintensities in the brain's white matter. MRI with diffusion tensor imaging (DTI) is used to detect white matter abnormalities by measuring fractional anisotropy (FA). This study employed DTI to evaluate the relationship between FA patterns and the findings of T2 sequences, with the aim of improving our understanding of anatomical changes and microstructural brain abnormalities in individuals with NF1. Forty-four individuals with NF1 and 20 control subjects were evaluated. The comparative analysis of FA between NF1 and control groups was based on four predetermined anatomical regions of the brain hemispheres (basal ganglia, cerebellum, pons, thalamus) and related the presence or absence of T2-weighted hyperintensities in the brain, which are called unidentified bright objects (UBOs). The FA values between the groups demonstrated statistically significant differences (P ≤ 0.05) for the cerebellum and thalamus in patients with NF1, independent of the occurrence of UBOs. Diffusion tensor MR imaging confirms the influence of UBOs in the decrease of FA values in this series of patients with NF1. Additionally, this technique allows the characterization of microstructural abnormalities even in some brain regions that appear normal in conventional MR sequences. (orig.)

  16. Comparison of two global digital algorithms for Minkowski tensor estimation

    DEFF Research Database (Denmark)

    The geometry of real world objects can be described by Minkowski tensors. Algorithms have been suggested to approximate Minkowski tensors if only a binary image of the object is available. This paper presents implementations of two such algorithms. The theoretical convergence properties...... are confirmed by simulations on test sets, and recommendations for input arguments of the algorithms are given. For increasing resolutions, we obtain more accurate estimators for the Minkowski tensors. Digitisations of more complicated objects are shown to require higher resolutions....

  17. Killing tensors and conformal Killing tensors from conformal Killing vectors

    International Nuclear Information System (INIS)

    Rani, Raffaele; Edgar, S Brian; Barnes, Alan

    2003-01-01

    Koutras has proposed some methods to construct reducible proper conformal Killing tensors and Killing tensors (which are, in general, irreducible) when a pair of orthogonal conformal Killing vectors exist in a given space. We give the completely general result demonstrating that this severe restriction of orthogonality is unnecessary. In addition, we correct and extend some results concerning Killing tensors constructed from a single conformal Killing vector. A number of examples demonstrate that it is possible to construct a much larger class of reducible proper conformal Killing tensors and Killing tensors than permitted by the Koutras algorithms. In particular, by showing that all conformal Killing tensors are reducible in conformally flat spaces, we have a method of constructing all conformal Killing tensors, and hence all the Killing tensors (which will in general be irreducible) of conformally flat spaces using their conformal Killing vectors

  18. Tensors for physics

    CERN Document Server

    Hess, Siegfried

    2015-01-01

    This book presents the science of tensors in a didactic way. The various types and ranks of tensors and the physical basis is presented. Cartesian Tensors are needed for the description of directional phenomena in many branches of physics and for the characterization the anisotropy of material properties. The first sections of the book provide an introduction to the vector and tensor algebra and analysis, with applications to physics,  at undergraduate level. Second rank tensors, in particular their symmetries, are discussed in detail. Differentiation and integration of fields, including generalizations of the Stokes law and the Gauss theorem, are treated. The physics relevant for the applications in mechanics, quantum mechanics, electrodynamics and hydrodynamics is presented. The second part of the book is devoted to  tensors of any rank, at graduate level.  Special topics are irreducible, i.e. symmetric traceless tensors, isotropic tensors, multipole potential tensors, spin tensors, integration and spin-...

  19. Altered Development of White Matter in Youth at High Familial Risk for Bipolar Disorder: A Diffusion Tensor Imaging Study

    Science.gov (United States)

    Versace, Amelia; Ladouceur, Cecile D.; Romero, Soledad; Birmaher, Boris; Axelson, David A.; Kupfer, David J.; Phillips, Mary L.

    2010-01-01

    Objective: To study white matter (WM) development in youth at high familial risk for bipolar disorder (BD). WM alterations are reported in youth and adults with BD. WM undergoes important maturational changes in adolescence. Age-related changes in WM microstructure using diffusion tensor imaging with tract-based spatial statistics in healthy…

  20. Diffusion tensor imaging and voxel based morphometry study in amyotrophic lateral sclerosis: relationships with motor disability

    OpenAIRE

    Thivard, Lionel; Pradat, Pierre‐François; Lehéricy, Stéphane; Lacomblez, Lucette; Dormont, Didier; Chiras, Jacques; Benali, Habib; Meininger, Vincent

    2007-01-01

    International audience; The aim of this study was to investigate the extent of cortical and subcortical lesions in amyotrophic lateral sclerosis (ALS) using, in combination, voxel based diffusion tensor imaging (DTI) and voxel based morphometry (VBM). We included 15 patients with definite or probable ALS and 25 healthy volunteers. Patients were assessed using the revised ALS Functional Rating Scale (ALSFRS-R). In patients, reduced fractional anisotropy was found in bilateral corticospinal tra...

  1. Analysis of the diffusion tensor imaging parameters of a normal cervical spinal cord in a healthy population.

    Science.gov (United States)

    Wei, Liang-Feng; Wang, Shou-Sen; Zheng, Zhao-Cong; Tian, Jun; Xue, Liang

    2017-05-01

    Diffusion tensor imaging (DTI) shows great advantage in the diagnosis of brain diseases, including cervical spinal cord (CSC) disease. This study aims to obtain the normal values of the DTI parameters for a healthy population and to establish a baseline for CSC disease diagnosis using DTI. A total of 36 healthy adults were subjected to magnetic resonance imaging (MRI) for the entire CSC using the Siemens 3.0 T MR System. Sagittal DTI acquisition was carried out with a single-shot spin-echo echo-planar imaging (EPI) sequence along 12 non-collinear directions. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were determined at different cervical levels using a region of interest (ROI) method, following which they were correlated with parameters, like age and sex. Further, diffusion tensor tracking (DTT) was carried out to reconstruct the white matter fiber bundles of the CSC. The full and complete fiber bundle structure of a normal CSC was confirmed in both the T2-weighted and DTI images. The FA and ADC values were significantly negatively correlated with each other and showed strongly negative and positive correlations with age, respectively, but not with sex. Additionally, there was no significant difference between the FA and the ADC values at different cervical levels. The DTI technique can act as an important supplement to the conventional MRI technique for CSC observation. Moreover, the FA and ADC values can be used as sensitive parameters in the DTI study on the CSC by taking the effects of age into consideration.

  2. Quantification of diffusion tensor imaging in normal white matter maturation of early childhood using an automated processing pipeline.

    Science.gov (United States)

    Loh, K B; Ramli, N; Tan, L K; Roziah, M; Rahmat, K; Ariffin, H

    2012-07-01

    The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas. Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction. DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued. DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data. Diffusion tensor imaging outperforms conventional MRI in depicting white matter maturation. • DTI will become an important clinical tool for diagnosing paediatric neurological diseases. • DTI appears especially helpful for developmental abnormalities, tumours and white matter disease. • An automated processing pipeline assists quantitative analysis of high throughput DTI data.

  3. A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity.

    Science.gov (United States)

    Zhu, Yingying; Zhu, Xiaofeng; Kim, Minjeong; Yan, Jin; Wu, Guorong

    2017-06-01

    Functional connectivity (FC) has been widely investigated in many imaging-based neuroscience and clinical studies. Since functional Magnetic Resonance Image (MRI) signal is just an indirect reflection of brain activity, it is difficult to accurately quantify the FC strength only based on signal correlation. To address this limitation, we propose a learning-based tensor model to derive high sensitivity and specificity connectome biomarkers at the individual level from resting-state fMRI images. First, we propose a learning-based approach to estimate the intrinsic functional connectivity. In addition to the low level region-to-region signal correlation, latent module-to-module connection is also estimated and used to provide high level heuristics for measuring connectivity strength. Furthermore, sparsity constraint is employed to automatically remove the spurious connections, thus alleviating the issue of searching for optimal threshold. Second, we integrate our learning-based approach with the sliding-window technique to further reveal the dynamics of functional connectivity. Specifically, we stack the functional connectivity matrix within each sliding window and form a 3D tensor where the third dimension denotes for time. Then we obtain dynamic functional connectivity (dFC) for each individual subject by simultaneously estimating the within-sliding-window functional connectivity and characterizing the across-sliding-window temporal dynamics. Third, in order to enhance the robustness of the connectome patterns extracted from dFC, we extend the individual-based 3D tensors to a population-based 4D tensor (with the fourth dimension stands for the training subjects) and learn the statistics of connectome patterns via 4D tensor analysis. Since our 4D tensor model jointly (1) optimizes dFC for each training subject and (2) captures the principle connectome patterns, our statistical model gains more statistical power of representing new subject than current state

  4. The 1/ N Expansion of Tensor Models with Two Symmetric Tensors

    Science.gov (United States)

    Gurau, Razvan

    2018-06-01

    It is well known that tensor models for a tensor with no symmetry admit a 1/ N expansion dominated by melonic graphs. This result relies crucially on identifying jackets, which are globally defined ribbon graphs embedded in the tensor graph. In contrast, no result of this kind has so far been established for symmetric tensors because global jackets do not exist. In this paper we introduce a new approach to the 1/ N expansion in tensor models adapted to symmetric tensors. In particular we do not use any global structure like the jackets. We prove that, for any rank D, a tensor model with two symmetric tensors and interactions the complete graph K D+1 admits a 1/ N expansion dominated by melonic graphs.

  5. 3D structure tensor analysis of light microscopy data for validating diffusion MRI.

    Science.gov (United States)

    Khan, Ahmad Raza; Cornea, Anda; Leigland, Lindsey A; Kohama, Steven G; Jespersen, Sune Nørhøj; Kroenke, Christopher D

    2015-05-01

    Diffusion magnetic resonance imaging (d-MRI) is a powerful non-invasive and non-destructive technique for characterizing brain tissue on the microscopic scale. However, the lack of validation of d-MRI by independent experimental means poses an obstacle to accurate interpretation of data acquired using this method. Recently, structure tensor analysis has been applied to light microscopy images, and this technique holds promise to be a powerful validation strategy for d-MRI. Advantages of this approach include its similarity to d-MRI in terms of averaging the effects of a large number of cellular structures, and its simplicity, which enables it to be implemented in a high-throughput manner. However, a drawback of previous implementations of this technique arises from it being restricted to 2D. As a result, structure tensor analyses have been limited to tissue sectioned in a direction orthogonal to the direction of interest. Here we describe the analytical framework for extending structure tensor analysis to 3D, and utilize the results to analyze serial image "stacks" acquired with confocal microscopy of rhesus macaque hippocampal tissue. Implementation of 3D structure tensor procedures requires removal of sources of anisotropy introduced in tissue preparation and confocal imaging. This is accomplished with image processing steps to mitigate the effects of anisotropic tissue shrinkage, and the effects of anisotropy in the point spread function (PSF). In order to address the latter confound, we describe procedures for measuring the dependence of PSF anisotropy on distance from the microscope objective within tissue. Prior to microscopy, ex vivo d-MRI measurements performed on the hippocampal tissue revealed three regions of tissue with mutually orthogonal directions of least restricted diffusion that correspond to CA1, alveus and inferior longitudinal fasciculus. We demonstrate the ability of 3D structure tensor analysis to identify structure tensor orientations that

  6. OPERATOR NORM INEQUALITIES BETWEEN TENSOR UNFOLDINGS ON THE PARTITION LATTICE.

    Science.gov (United States)

    Wang, Miaoyan; Duc, Khanh Dao; Fischer, Jonathan; Song, Yun S

    2017-05-01

    Interest in higher-order tensors has recently surged in data-intensive fields, with a wide range of applications including image processing, blind source separation, community detection, and feature extraction. A common paradigm in tensor-related algorithms advocates unfolding (or flattening) the tensor into a matrix and applying classical methods developed for matrices. Despite the popularity of such techniques, how the functional properties of a tensor changes upon unfolding is currently not well understood. In contrast to the body of existing work which has focused almost exclusively on matricizations, we here consider all possible unfoldings of an order- k tensor, which are in one-to-one correspondence with the set of partitions of {1, …, k }. We derive general inequalities between the l p -norms of arbitrary unfoldings defined on the partition lattice. In particular, we demonstrate how the spectral norm ( p = 2) of a tensor is bounded by that of its unfoldings, and obtain an improved upper bound on the ratio of the Frobenius norm to the spectral norm of an arbitrary tensor. For specially-structured tensors satisfying a generalized definition of orthogonal decomposability, we prove that the spectral norm remains invariant under specific subsets of unfolding operations.

  7. White Matter Compromise of Callosal and Subcortical Fiber Tracts in Children with Autism Spectrum Disorder: A Diffusion Tensor Imaging Study

    Science.gov (United States)

    Shukla, Dinesh K.; Keehn, Brandon; Lincoln, Alan J.; Muller, Ralph-Axel

    2010-01-01

    Objective: Autism spectrum disorder (ASD) is increasingly viewed as a disorder of functional networks, highlighting the importance of investigating white matter and interregional connectivity. We used diffusion tensor imaging (DTI) to examine white matter integrity for the whole brain and for corpus callosum, internal capsule, and middle…

  8. Diffusion tensor imaging and tractography in clinical neuro sciences

    International Nuclear Information System (INIS)

    Zarei, M.; Johansen-Berg, H.; Matthews, P.M.

    2003-01-01

    Rapidly evolving MR technology has allowed better understanding of structure and function of the human brain. Diffusion weighted MRI was developed two decades ago and it is now well established in diagnosis of acute ischaemia in patients with stroke. Diffusion tensor MRI uses the same principles but takes a step further allowing US to measure magnitude of the diffusion along different directions. This lead to the development of diffusion tensor tractography, a technique by which major neural pathways in the living brain can be visualized. There is a growing interest in exploring possible use of these techniques in clinical neurology and psychiatry. This article aims to review the principles of this technique and recent discoveries which may help US to better understand neurological and psychiatric disorders

  9. Inference of segmented color and texture description by tensor voting.

    Science.gov (United States)

    Jia, Jiaya; Tang, Chi-Keung

    2004-06-01

    A robust synthesis method is proposed to automatically infer missing color and texture information from a damaged 2D image by (N)D tensor voting (N > 3). The same approach is generalized to range and 3D data in the presence of occlusion, missing data and noise. Our method translates texture information into an adaptive (N)D tensor, followed by a voting process that infers noniteratively the optimal color values in the (N)D texture space. A two-step method is proposed. First, we perform segmentation based on insufficient geometry, color, and texture information in the input, and extrapolate partitioning boundaries by either 2D or 3D tensor voting to generate a complete segmentation for the input. Missing colors are synthesized using (N)D tensor voting in each segment. Different feature scales in the input are automatically adapted by our tensor scale analysis. Results on a variety of difficult inputs demonstrate the effectiveness of our tensor voting approach.

  10. Diffusion tensor magnetic resonance imaging of the breast: a pilot study

    International Nuclear Information System (INIS)

    Baltzer, Pascal A.T.; Schaefer, Anja; Dietzel, Matthias; Kaiser, Werner A.; Graessel, David; Gajda, Mieczyslaw; Camara, Oumar

    2011-01-01

    Diffusion-weighted MR imaging has shown diagnostic value for differential diagnosis of breast lesions. Diffusion tensor imaging (DTI) adds information about tissue microstructure by addressing diffusion direction. We have examined the diagnostic application of DTI of the breast. A total of 59 patients (71 lesions: 54 malignant, 17 benign) successfully underwent prospective echo planar imaging-DTI (EPI-DTI) (1.5 T). First, diffusion direction both of parenchyma as well as lesions was assessed on parametric maps. Subsequently, apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values were measured. Statistics included univariate (Mann-Whitney U test, receiver operating analysis) and multivariate (logistic regression analysis, LRA) tests. Main diffusion direction of parenchyma was anterior-posterior in the majority of cases (66.1%), whereas lesions (benign, malignant) showed no predominant diffusion direction in the majority of cases (23.9%). ADC values showed highest differences between benign and malignant lesions (P < 0.001) with resulting area under the curve (AUC) of 0.899. FA values were lower in benign (interquartile range, IR, 0.14-0.24) compared to malignant lesions (IR 0.21-0.35, P < 0.002) with an AUC of 0.751-0.770. Following LRA, FA did not prove to have incremental value for differential diagnosis over ADC values. Microanatomical differences between benign and malignant breast lesions as well as breast parenchyma can be visualized by using DTI. (orig.)

  11. Migration transformation of two-dimensional magnetic vector and tensor fields

    DEFF Research Database (Denmark)

    Zhdanov, Michael; Cai, Hongzhu; Wilson, Glenn

    2012-01-01

    We introduce a new method of rapid interpretation of magnetic vector and tensor field data, based on ideas of potential field migration which extends the general principles of seismic and electromagnetic migration to potential fields. 2-D potential field migration represents a direct integral...... to the downward continuation of a well-behaved analytical function. We present case studies for imaging of SQUID-based magnetic tensor data acquired over a magnetite skarn at Tallawang, Australia. The results obtained from magnetic tensor field migration agree very well with both Euler deconvolution and the known...

  12. An efficient method for tensor voting using steerable filters

    NARCIS (Netherlands)

    Franken, E.M.; Almsick, van M.A.; Rongen, P.M.J.; Florack, L.M.J.; Haar Romenij, ter B.M.; Leonardis, A.; Bischof, H; Pinz, A.

    2006-01-01

    In many image analysis applications there is a need to extract curves in noisy images. To achieve a more robust extraction, one can exploit correlations of oriented features over a spatial context in the image. Tensor voting is an existing technique to extract features in this way. In this paper, we

  13. Brain diffusion tensor MRI in systematic lupus erythematosus: A systematic review.

    Science.gov (United States)

    Costallat, Beatriz Lavras; Ferreira, Daniel Miranda; Lapa, Aline Tamires; Rittner, Letícia; Costallat, Lilian Tereza Lavras; Appenzeller, Simone

    2018-01-01

    Diffusion tensor imaging (DTI) maps the brain's microstructure by measuring fractional anisotropy (FA) and mean diffusivity (MD). This systematic review describes brain diffusion tensor Magnetic resonance imaging (MRI) studies in systemic lupus erythematosus (SLE).The literature was reviewed following the PRISMA guidelines and using the terms "lupus", "systemic lupus erythematosus", "SLE", "diffusion tensor imaging", "DTI", "white matter" (WM), "microstructural damage", "tractography", and "fractional anisotropy"; the search included articles published in English from January 2007 to April 2017. The subjects included in the study were selected according to the ACR criteria and included 195 SLE patients with neuropsychiatric manifestation (NPSLE), 299 without neuropsychiatric manifestation (non-NPSLE), and 423 healthy controls (HC). Most studies identified significantly reduced FA and increased MD values in several WM regions of both NPSLE and non-NPSLE patients compared to HC. Subclinical microstructural changes were observed in either regional areas or the entire brain in both the non-NPSLE and NPSLE groups. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Impact of time-of-day on diffusivity measures of brain tissue derived from diffusion tensor imaging.

    Science.gov (United States)

    Thomas, Cibu; Sadeghi, Neda; Nayak, Amrita; Trefler, Aaron; Sarlls, Joelle; Baker, Chris I; Pierpaoli, Carlo

    2018-06-01

    Diurnal fluctuations in MRI measures of structural and functional properties of the brain have been reported recently. These fluctuations may have a physiological origin, since they have been detected using different MRI modalities, and cannot be explained by factors that are typically known to confound MRI measures. While preliminary evidence suggests that measures of structural properties of the brain based on diffusion tensor imaging (DTI) fluctuate as a function of time-of-day (TOD), the underlying mechanism has not been investigated. Here, we used a longitudinal within-subjects design to investigate the impact of time-of-day on DTI measures. In addition to using the conventional monoexponential tensor model to assess TOD-related fluctuations, we used a dual compartment tensor model that allowed us to directly assess if any change in DTI measures is due to an increase in CSF/free-water volume fraction or due to an increase in water diffusivity within the parenchyma. Our results show that Trace or mean diffusivity, as measured using the conventional monoexponential tensor model tends to increase systematically from morning to afternoon scans at the interface of grey matter/CSF, most prominently in the major fissures and the sulci of the brain. Interestingly, in a recent study of the glymphatic system, these same regions were found to show late enhancement after intrathecal injection of a CSF contrast agent. The increase in Trace also impacts DTI measures of diffusivity such as radial and axial diffusivity, but does not affect fractional anisotropy. The dual compartment analysis revealed that the increase in diffusivity measures from PM to AM was driven by an increase in the volume fraction of CSF-like free-water. Taken together, our findings provide important insight into the likely physiological origins of diurnal fluctuations in MRI measurements of structural properties of the brain. Published by Elsevier Inc.

  15. Diffusion tensor imaging of brain white matter in Huntington gene mutation individuals

    Directory of Open Access Journals (Sweden)

    Roberta Arb Saba

    Full Text Available ABSTRACT Objective To evaluate the role of the involvement of white matter tracts in huntingtin gene mutation patients as a potential biomarker of the progression of the disease. Methods We evaluated 34 participants (11 symptomatic huntingtin gene mutation, 12 presymptomatic huntingtin gene mutation, and 11 controls. We performed brain magnetic resonance imaging to assess white matter integrity using diffusion tensor imaging, with measurement of fractional anisotropy. Results We observed a significant decrease of fractional anisotropy in the cortical spinal tracts, corona radiate, corpus callosum, external capsule, thalamic radiations, superior and inferior longitudinal fasciculus, and inferior frontal-occipital fasciculus in the Huntington disease group compared to the control and presymptomatic groups. Reduction of fractional anisotropy is indicative of a degenerative process and axonal loss. There was no statistically significant difference between the presymptomatic and control groups. Conclusion White matter integrity is affected in huntingtin gene mutation symptomatic individuals, but other studies with larger samples are required to assess its usefulness in the progression of the neurodegenerative process.

  16. Determination of mouse skeletal muscle architecture using three-dimensional diffusion tensor imaging.

    Science.gov (United States)

    Heemskerk, Anneriet M; Strijkers, Gustav J; Vilanova, Anna; Drost, Maarten R; Nicolay, Klaas

    2005-06-01

    Muscle architecture is the main determinant of the mechanical behavior of skeletal muscles. This study explored the feasibility of diffusion tensor imaging (DTI) and fiber tracking to noninvasively determine the in vivo three-dimensional (3D) architecture of skeletal muscle in mouse hind leg. In six mice, the hindlimb was imaged with a diffusion-weighted (DW) 3D fast spin-echo (FSE) sequence followed by the acquisition of an exercise-induced, T(2)-enhanced data set. The data showed the expected fiber organization, from which the physiological cross-sectional area (PCSA), fiber length, and pennation angle for the tibialis anterior (TA) were obtained. The values of these parameters ranged from 5.4-9.1 mm(2), 5.8-7.8 mm, and 21-24 degrees , respectively, which is in agreement with values obtained previously with the use of invasive methods. This study shows that 3D DT acquisition and fiber tracking is feasible for the skeletal muscle of mice, and thus enables the quantitative determination of muscle architecture.

  17. LOW AND MEAN RADIATION DOSES IMPACT ON THE CEREBRAL TRACTS STRUCTURE OF THE CHERNOBYL ACCIDENT LIQUIDATORS IN THE REMOTE PERIOD (BASED ON ROUTINE AND DIFFUSION-TENSOR MAGNETIC RESONANCE IMAGING DATA

    Directory of Open Access Journals (Sweden)

    I. M. Levashkina

    2017-01-01

    Full Text Available To evaluate correlation between brain structural damages and radiation exposure level for the Chernobyl nuclear power plant accident liquidators, routine and diffusion tensor magnetic resonance imaging methods are efficient to visualize and evaluate those damages; it is also important to compare magnetic resonance imaging data of liquidators with results, received for people of the same age and the same stage of cerebral vascular disease (the discirculatory encephalopathy of I and II stage, but who did not participate in the Chernobyl accident liquidation and did not suffer from other liquidation factors and radiation catastrophe aftermaths. As a result, the Chernobyl accident liquidators group (49 subjects and group of control (50 subjects were examined with routine magnetic resonance imaging methods and standard protocols. In addition, the innovative method of diffusion tensor magnetic resonance imaging was applied to examine 11 cerebral tracts, bilaterally (22 tracts in both hemispheres for every subject of the research. It was for the first time when diffusion tensor magnetic resonance imaging was applied to conduct visual analysis of polymorphic brain changes for the Chernobyl accident liquidators and special research conducted to find correlation between fractional anisotropy coefficient and radiation exposure for these patients. The results of diffusion tensor magnetic resonance imaging indicated no statistically significant (p > 0,05 difference in the level of cerebral morphological changes and between average fraction anisotropy coefficient value in any cerebral tract for both sub-groups of liquidators with different level of irradiation: 28 subjects, who were exposed by low and very low radiation doses (0–100 micro-Sv, sub-group A and 21 subjects, who were exposed by mean radiation doses (100–1000 micro-Sv, sub-group B. However, comparing diffusion tensor magnetic resonance imaging results of control group and liquidators group

  18. Neuroanatomical correlates of tinnitus revealed by cortical thickness analysis and diffusion tensor imaging

    Energy Technology Data Exchange (ETDEWEB)

    Aldhafeeri, Faten M [The University of Liverpool, Department of Medical Imaging, School of Health Sciences, Liverpool (United Kingdom); King Khalid General Hospital, Ministry of Health, Radiology Department, Hafral-batin (Saudi Arabia); Mackenzie, Ian; Kay, Tony [Aintree University Hospitals NHS Foundation Trust, Liverpool (United Kingdom); Alghamdi, Jamaan [The University of Liverpool, Department of Medical Imaging, School of Health Sciences, Liverpool (United Kingdom); King Abdul Aziz University, Physics Department, Faculty of Sciences, Jeddah (Saudi Arabia); Sluming, Vanessa [The University of Liverpool, Department of Medical Imaging, School of Health Sciences, Liverpool (United Kingdom); Magnetic Resonance and Image Analysis Research Centre, Liverpool (United Kingdom)

    2012-08-15

    Tinnitus is a poorly understood auditory perception of sound in the absence of external stimuli. Convergent evidence proposes that tinnitus perception involves brain structural alterations as part of its pathophysiology. The aim of this study is to investigate the structural brain changes that might be associated with tinnitus-related stress and negative emotions. Using high-resolution magnetic resonance imaging and diffusion tensor imaging, we investigated grey matter and white matter (WM) alterations by estimating cortical thickness measures, fractional anisotropy and mean diffusivity in 14 tinnitus subjects and 14 age- and sex-matched non-tinnitus subjects. Significant cortical thickness reductions were found in the prefrontal cortex (PFC), temporal lobe and limbic system in tinnitus subjects compared to non-tinnitus subjects. Tinnitus sufferers were found to have disrupted WM integrity in tracts involving connectivity of the PFC, temporal lobe, thalamus and limbic system. Our results suggest that such neural changes may represent neural origins for tinnitus or consequences of tinnitus and its associations. (orig.)

  19. Neuroanatomical correlates of tinnitus revealed by cortical thickness analysis and diffusion tensor imaging

    International Nuclear Information System (INIS)

    Aldhafeeri, Faten M.; Mackenzie, Ian; Kay, Tony; Alghamdi, Jamaan; Sluming, Vanessa

    2012-01-01

    Tinnitus is a poorly understood auditory perception of sound in the absence of external stimuli. Convergent evidence proposes that tinnitus perception involves brain structural alterations as part of its pathophysiology. The aim of this study is to investigate the structural brain changes that might be associated with tinnitus-related stress and negative emotions. Using high-resolution magnetic resonance imaging and diffusion tensor imaging, we investigated grey matter and white matter (WM) alterations by estimating cortical thickness measures, fractional anisotropy and mean diffusivity in 14 tinnitus subjects and 14 age- and sex-matched non-tinnitus subjects. Significant cortical thickness reductions were found in the prefrontal cortex (PFC), temporal lobe and limbic system in tinnitus subjects compared to non-tinnitus subjects. Tinnitus sufferers were found to have disrupted WM integrity in tracts involving connectivity of the PFC, temporal lobe, thalamus and limbic system. Our results suggest that such neural changes may represent neural origins for tinnitus or consequences of tinnitus and its associations. (orig.)

  20. Measurement of mean rotation and strain-rate tensors by using stereoscopic PIV

    DEFF Research Database (Denmark)

    Özcan, Oktay; Meyer, Knud Erik; Larsen, Poul Scheel

    2005-01-01

    A technique is described for measuring the mean velocity gradient (rate-of-displacement) tensor by using a conventional stereoscopic particle image velocimetry (SPIV) system. Planar measurement of the mean vorticity vector, rate-of-rotation and rate-of-strain tensors and the production of turbule...

  1. Diffusion tensor imaging--arcuate fasciculus and the importance for the neurosurgeon.

    Science.gov (United States)

    Hana, Ardian; Dooms, Georges; Boecher-Schwarz, Hans; Hertel, Frank

    2015-05-01

    Tumors in eloquent areas of the brain like Broca or Wernicke might have disastrous consequences for patients. We intended to visualize the arcuate fasciculus (AF) and to demonstrate his relation with the corticospinal tract and the visual pathway using diffusion tensor imaging (DTI). We depicted between 2012 and 2014 the AF in 71 patients. Men and women of all ages were included. Eleven patients had postoperative controls also. We used a 3DT1-sequence for the navigation. Furthermore T2- and DTI-sequences were performed. The FOV was 200 × 200 mm(2), slice thickness 2mm, and an acquisition matrix of 96 × 96 yielding nearly isotropic voxels of 2 × 2 × 2 mm. 3-Tesla-MRI was carried out strictly axial using 32 gradient directions and one b0-image. We used Echo-Planar-Imaging (EPI) and ASSET parallel imaging with an acceleration factor of 2. b-Value was 800 s/mm(2). Additional scanning time was less than 9 min. AF was portrayed in 63 patients bilaterally. In one glioblastoma patient it was impossible to visualize the left AF and in seven other patients we could not portray the right one. The lesions affected AF by disrupting or displacing the fibers. DTI might be a useful tool to portray AF. It is time-saving and can be used to preserve morbidity in patients with lesions in eloquent brain areas. It might give deeper insights of the white matter and the reorganization of AF-fibers postoperatively. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Surface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder.

    Science.gov (United States)

    Landin-Romero, Ramón; Canales-Rodríguez, Erick J; Kumfor, Fiona; Moreno-Alcázar, Ana; Madre, Mercè; Maristany, Teresa; Pomarol-Clotet, Edith; Amann, Benedikt L

    2017-01-01

    The profile of grey matter abnormalities and related white-matter pathology in schizoaffective disorder has only been studied to a limited extent. The aim of this study was to identify grey- and white-matter abnormalities in patients with schizoaffective disorder using complementary structural imaging techniques. Forty-five patients meeting Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition criteria and Research Diagnostic Criteria for schizoaffective disorder and 45 matched healthy controls underwent structural-T1 and diffusion magnetic resonance imaging to enable surface-based brain morphometry and diffusion tensor imaging analyses. Analyses were conducted to determine group differences in cortical volume, cortical thickness and surface area, as well as in fractional anisotropy and mean diffusivity. At a threshold of p = 0.05 corrected, all measures revealed significant differences between patients and controls at the group level. Spatial overlap of abnormalities was observed across the various structural neuroimaging measures. In grey matter, patients with schizoaffective disorder showed abnormalities in the frontal and temporal lobes, striatum, fusiform, cuneus, precuneus, lingual and limbic regions. White-matter abnormalities were identified in tracts connecting these areas, including the corpus callosum, superior and inferior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus and cingulum bundle. The spatial overlap of abnormalities across the different imaging techniques suggests widespread and consistent brain pathology in schizoaffective disorder. The abnormalities were mainly detected in areas that have commonly been reported to be abnormal in schizophrenia, and to some extent in bipolar disorder, which may explain the clinical and aetiological overlap in these disorders.

  3. A preliminary diffusional kurtosis imaging study of Parkinson disease: comparison with conventional diffusion tensor imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kamagata, Koji; Kamiya, Kouhei; Suzuki, Michimasa; Hori, Masaaki; Yoshida, Mariko; Aoki, Shigeki [Juntendo University School of Medicine, Department of Radiology, Bunkyo-ku, Tokyo (Japan); Tomiyama, Hiroyuki; Hatano, Taku; Motoi, Yumiko; Hattori, Nobutaka [Juntendo University School of Medicine, Department of Neurology, Tokyo (Japan); Abe, Osamu [Nihon University School of Medicine, Department of Radiology, Tokyo (Japan); Shimoji, Keigo [National Center of Neurology and Psychiatry Hospital, Department of Radiology, Tokyo (Japan)

    2014-03-15

    Diffusional kurtosis imaging (DKI) is a more sensitive technique than conventional diffusion tensor imaging (DTI) for assessing tissue microstructure. In particular, it quantifies the microstructural integrity of white matter, even in the presence of crossing fibers. The aim of this preliminary study was to compare how DKI and DTI show white matter alterations in Parkinson disease (PD). DKI scans were obtained with a 3-T magnetic resonance imager from 12 patients with PD and 10 healthy controls matched by age and sex. Tract-based spatial statistics were used to compare the mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) maps of the PD patient group and the control group. In addition, a region-of-interest analysis was performed for the area of the posterior corona radiata and superior longitudinal fasciculus (SLF) fiber crossing. FA values in the frontal white matter were significantly lower in PD patients than in healthy controls. Reductions in MK occurred more extensively throughout the brain: in addition to frontal white matter, MK was lower in the parietal, occipital, and right temporal white matter. The MK value of the area of the posterior corona radiata and SLF fiber crossing was also lower in the PD group. DKI detects changes in the cerebral white matter of PD patients more sensitively than conventional DTI. In addition, DKI is useful for evaluating crossing fibers. By providing a sensitive index of brain pathology in PD, DKI may enable improved monitoring of disease progression. (orig.)

  4. The energy–momentum tensor(s in classical gauge theories

    Directory of Open Access Journals (Sweden)

    Daniel N. Blaschke

    2016-11-01

    Full Text Available We give an introduction to, and review of, the energy–momentum tensors in classical gauge field theories in Minkowski space, and to some extent also in curved space–time. For the canonical energy–momentum tensor of non-Abelian gauge fields and of matter fields coupled to such fields, we present a new and simple improvement procedure based on gauge invariance for constructing a gauge invariant, symmetric energy–momentum tensor. The relationship with the Einstein–Hilbert tensor following from the coupling to a gravitational field is also discussed.

  5. New MRI Markers for Alzheimer's Disease: A Meta-Analysis of Diffusion Tensor Imaging and a Comparison with Medial Temporal Lobe Measurements

    NARCIS (Netherlands)

    Clerx, L.; Visser, P.J.; Verhey, F.; Aalten, P.

    2012-01-01

    The aim of the present study is to evaluate the diagnostic value of diffusion tensor imaging (DTI) for early Alzheimer's disease (AD) in comparison to widely accepted medial temporal lobe (MTL) atrophy measurements. A systematic literature research was performed into DTI and MTL atrophy in AD and

  6. Diffusion tensor imaging of the spinal cord: a review Imagen de difusión tensora de la médula espinal: una revisión Imagem da medula espinal por tensor de difusão

    Directory of Open Access Journals (Sweden)

    Aditya Vedantam

    2013-01-01

    Full Text Available Diffusion tensor imaging (DTI is a magnetic resonance technique capable of measuring the magnitude and direction of water molecule diffusion in various tissues. The use of DTI is being expanded to evaluate a variety of spinal cord disorders both for prognostication and to guide therapy. The purpose of this article is to review the literature on spinal cord DTI in both animal models and humans in different neurosurgical conditions. DTI of the spinal cord shows promise in traumatic spinal cord injury, cervical spondylotic myelopathy, and intramedullary tumors. However, scanning protocols and image processing need to be refined and standardized.La técnica de imagen por difusión tensora (DTI, Diffusion tensor imaging es una técnica de resonancia magnética que mide la magnitud y dirección de la difusión de moléculas de agua en varios tejidos. El uso de DTI se ha expandido para evaluar una variedad de disturbios de la columna vertebral tanto para pronóstico como para orientación de la terapia. La finalidad de este artículo es revisar la literatura sobre DTI de la médula espinal tanto en modelos animales como en humanos en diferentes condiciones neuroquirúrgicas. La DTI de la médula espinal se muestra promisora en las lesiones traumáticas de la médula, en la mielopatía espondilótica cervical y en los tumores intramedulares. Sin embargo, los protocolos de barrido y el procesamiento de imágenes necesitan ser refinados y estandarizados.O exame por imagem de ressonância magnética utilizando a técnica de tensores de difusão (DTI, Diffusion tensor imaging consegue medir a magnitude e direção da difusão de moléculas de água em vários tecidos. A DTI está começando a ser usada para avaliar uma série de patologias da medula espinal, tanto para prognósticos como para orientar o tratamento. O presente artigo revisa a literatura sobre DTI da medula espinhal, em modelos animais e humanos, em diferentes condições neurocirúrgicas. A

  7. MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.

    Science.gov (United States)

    Prasath, V B S; Pelapur, R; Glinskii, O V; Glinsky, V V; Huxley, V H; Palaniappan, K

    2015-04-01

    Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.

  8. Long-term effects of radiation therapy on white matter of the corpus callosum: a diffusion tensor imaging study in children

    Energy Technology Data Exchange (ETDEWEB)

    Makola, Monwabisi [University of Cincinnati, College of Medicine, Cincinnati, OH (United States); Douglas Ris, M. [Texas Children' s Hospital, Department of Pediatrics, Baylor College of Medicine, Houston, TX (United States); Mahone, E.M. [Kennedy Krieger Institute, Department of Neuropsychology, Baltimore, MD (United States); Johns Hopkins University School of Medicine, Department of Psychiatry and Behavioral Sciences, Baltimore, MD (United States); Yeates, Keith Owen [University of Calgary, Department of Psychology, Alberta Children' s Hospital Research Institute, Hotchkiss Brain Institute, Calgary, AB (Canada); Cecil, Kim M. [Imaging Research Center, Cincinnati Children' s Hospital Medical Center, Cincinnati, OH (United States); University of Cincinnati College of Medicine, Department of Radiology, Cincinnati, OH (United States); University of Cincinnati College of Medicine, Department of Pediatrics, Cincinnati, OH (United States); University of Cincinnati College of Medicine, Neuroscience Graduate Program, Cincinnati, OH (United States); University of Cincinnati College of Medicine, Department of Environmental Health, Cincinnati, OH (United States)

    2017-12-15

    Despite improving survival rates, children are at risk for long-term cognitive and behavioral difficulties following the diagnosis and treatment of a brain tumor. Surgery, chemotherapy and radiation therapy have all been shown to impact the developing brain, especially the white matter. The purpose of this study was to determine the long-term effects of radiation therapy on white matter integrity, as measured by diffusion tensor imaging, in pediatric brain tumor patients 2 years after the end of radiation treatment, while controlling for surgical interventions. We evaluated diffusion tensor imaging performed at two time points: a baseline 3 to 12 months after surgery and a follow-up approximately 2 years later in pediatric brain tumor patients. A region of interest analysis was performed within three regions of the corpus callosum. Diffusion tensor metrics were determined for participants (n=22) who underwent surgical tumor resection and radiation therapy and demographically matched with participants (n=22) who received surgical tumor resection only. Analysis revealed that 2 years after treatment, the radiation treated group exhibited significantly lower fractional anisotropy and significantly higher radial diffusivity within the body of the corpus callosum compared to the group that did not receive radiation. The findings indicate that pediatric brain tumor patients treated with radiation therapy may be at greater risk of experiencing long-term damage to the body of the corpus callosum than those treated with surgery alone. (orig.)

  9. Long-term effects of radiation therapy on white matter of the corpus callosum: a diffusion tensor imaging study in children

    International Nuclear Information System (INIS)

    Makola, Monwabisi; Douglas Ris, M.; Mahone, E.M.; Yeates, Keith Owen; Cecil, Kim M.

    2017-01-01

    Despite improving survival rates, children are at risk for long-term cognitive and behavioral difficulties following the diagnosis and treatment of a brain tumor. Surgery, chemotherapy and radiation therapy have all been shown to impact the developing brain, especially the white matter. The purpose of this study was to determine the long-term effects of radiation therapy on white matter integrity, as measured by diffusion tensor imaging, in pediatric brain tumor patients 2 years after the end of radiation treatment, while controlling for surgical interventions. We evaluated diffusion tensor imaging performed at two time points: a baseline 3 to 12 months after surgery and a follow-up approximately 2 years later in pediatric brain tumor patients. A region of interest analysis was performed within three regions of the corpus callosum. Diffusion tensor metrics were determined for participants (n=22) who underwent surgical tumor resection and radiation therapy and demographically matched with participants (n=22) who received surgical tumor resection only. Analysis revealed that 2 years after treatment, the radiation treated group exhibited significantly lower fractional anisotropy and significantly higher radial diffusivity within the body of the corpus callosum compared to the group that did not receive radiation. The findings indicate that pediatric brain tumor patients treated with radiation therapy may be at greater risk of experiencing long-term damage to the body of the corpus callosum than those treated with surgery alone. (orig.)

  10. Diffusion tensor magnetic resonance imaging for hand and foot fibers location at the corona radiata: comparison with two lesion studies

    Directory of Open Access Journals (Sweden)

    Dong-Hoon eLee

    2014-09-01

    Full Text Available The corticospinal tract is the motor pathway in the human brain, and corona radiata is an important location to diagnose stroke. We detected hand and foot motor fiber tracts in the corona radiata to investigate accurate locations using diffusion tensor imaging and functional imaging. Ten right-handed normal volunteers participated in this study. We used a probabilistic tracking algorithm, a brain normalization method, and functional imaging results to set out ROIs. Moreover, our results were compared to previous results of lesion studies to confirm their accuracy and usefulness. The location measurements were performed in two index types; anteriority index on the basis of the anterior and posterior location of lateral ventricle, laterality index on the basis of the left and right location. The anteriority indices were 56.40/43.2 (hand/foot at the upper CR and lower CR 40.72/30.90 at the lower CR. The measurements of anteriority and laterality of motor fibers were represented as anteriority index 0.40/0.31 and laterality index 0.60/0.47 (hand/foot. Our results showed that the hand and foot fibers were in good agreements with previous lesion studies. This study and approaches can be used as a standard for diffusion tensor image combined with lesion location studies in patients who need rehabilitation or follow up.

  11. The tensor distribution function.

    Science.gov (United States)

    Leow, A D; Zhu, S; Zhan, L; McMahon, K; de Zubicaray, G I; Meredith, M; Wright, M J; Toga, A W; Thompson, P M

    2009-01-01

    Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of six directions, second-order tensors (represented by three-by-three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high-angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues.

  12. Diffusion Tensor Imaging for the Differentiation of Microangiopathy, Infarction and Perfusion-Diffusion Mismatch Lesions

    International Nuclear Information System (INIS)

    Ha, Dong Ho; Choi, Sun Seob; Kang, Myong Jin; Lee, Jin Hwa; Yoon, Seong Kuk; Nam, Kyung Jin

    2009-01-01

    This study was designed to evaluate the usefulness of diffusion tensor imaging (DTI) and the DTI indices for differentiating between microangiopathy lesions, acute infarction lesions and perfusion-diffusion mismatch areas. DTI was performed in 35 patients with the use of a 1.5 Tesla MRI system. The MRI parameters were as follows: a spin echo EPI sequence with a bvalue = 1000 s/mm 2 , 25 diffusion directions, a repetition time of 8400 msec, an echo time of 75 msec, a matrix size of 128 x 128, a FOV of 22 cm and a 4 mm slice thickness. From the diffusion tensor images, the apparent diffusion coefficient (ADC), fractional anisotropy (FA), volume ratio (VR), relative anisotropy (RA), anisotropy index (AI), exponential ADC (eADC) and magnitude diffusion coefficient (MDC) were measured for the contra-lateral normal area (28 cases), the microangiopathy lesions (10 cases), the infarction lesions (17 cases) and the perfusion-diffusion mismatch area (8 cases). As compared to the normal area, the microangiopathy lesions showed increased ADC and MDC values and decreased FA, VR, RA, AI and eADC values. The infarction lesions showed increased VR, RA and eADC values, a normal FA, a decreased AI and decreased ADC and MDC values. The mismatch area showed a similar pattern as that for the microangiopathy lesions; however, the differences were not prominent, with an increase of the ADC and MDC values and a decrease of FA, VR, RA, AI and eADC values. The DTI indices could have a role in making the differential diagnosis of microangiopathy, acute infarction and perfusion-diffusion mismatch lesions

  13. Tensor completion and low-n-rank tensor recovery via convex optimization

    International Nuclear Information System (INIS)

    Gandy, Silvia; Yamada, Isao; Recht, Benjamin

    2011-01-01

    In this paper we consider sparsity on a tensor level, as given by the n-rank of a tensor. In an important sparse-vector approximation problem (compressed sensing) and the low-rank matrix recovery problem, using a convex relaxation technique proved to be a valuable solution strategy. Here, we will adapt these techniques to the tensor setting. We use the n-rank of a tensor as a sparsity measure and consider the low-n-rank tensor recovery problem, i.e. the problem of finding the tensor of the lowest n-rank that fulfills some linear constraints. We introduce a tractable convex relaxation of the n-rank and propose efficient algorithms to solve the low-n-rank tensor recovery problem numerically. The algorithms are based on the Douglas–Rachford splitting technique and its dual variant, the alternating direction method of multipliers

  14. Tensor and non-tensor tractography for the assessment of the corticospinal tract of children with motor disorders: a comparative study.

    Science.gov (United States)

    Stefanou, Maria-Ioanna; Lumsden, Daniel E; Ashmore, Jonathan; Ashkan, Keyoumars; Lin, Jean-Pierre; Charles-Edwards, Geoffrey

    2016-10-01

    Non-invasive measures of corticospinal tract (CST) integrity may help to guide clinical interventions, particularly in children and young people (CAYP) with motor disorders. We compared diffusion tensor imaging (DTI) metrics extracted from the CST generated by tensor and non-tensor based tractography algorithms. For a group of 25 CAYP undergoing clinical evaluation, the CST was reconstructed using (1) deterministic tensor-based tractography algorithm, (2) probabilistic tensor-based, and (3) constrained spherical deconvolution (CSD)-derived tractography algorithms. Choice of tractography algorithm significantly altered the results of tracking. Larger tracts were consistently defined with CSD, with differences in FA but not MD values for tracts to the pre- or post-central gyrus. Differences between deterministic and probabilistic tensor-based algorithms were minimal. Non-tensor reconstructed tracts appeared to be more anatomically representative. Examining metrics along the tract, difference in FA values appeared to be greatest in voxels with predominantly single-fibre orientations. Less pronounced differences were seen outwith of these regions. With an increasing interest in the applications of tractography analysis at all stages of movement disorder surgery, it is important that clinicians remain alert to the consequences of choice of tractography algorithm on subsequently generated tracts, including differences in volumes, anatomical reconstruction, and DTI metrics, the latter of which will have global as well as more regional effects. Tract-wide analysis of DTI based metrics is of limited utility, and a more segmental approach to analysis may be appropriate, particularly if disruption to a focal region of a white matter pathway is anticipated.

  15. Clinical feasibility of simultaneous multi-slice imaging with blipped-CAIPI for diffusion-weighted imaging and diffusion-tensor imaging of the brain.

    Science.gov (United States)

    Yokota, Hajime; Sakai, Koji; Tazoe, Jun; Goto, Mariko; Imai, Hiroshi; Teramukai, Satoshi; Yamada, Kei

    2017-12-01

    Background Simultaneous multi-slice (SMS) imaging is starting to be used in clinical situation, although evidence of clinical feasibility is scanty. Purpose To prospectively assess the clinical feasibility of SMS diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI) with blipped-controlled aliasing in parallel imaging for brain lesions. Material and Methods The institutional review board approved this study. This study included 156 hyperintense lesions on DWI from 32 patients. A slice acceleration factor of 2 was applied for SMS scans, which allowed shortening of the scan time by 41.3%. The signal-to-noise ratio (SNR) was calculated for brain tissue of a selected slice. The contrast-to-noise ratio (CNR), apparent diffusion coefficient (ADC), and fractional anisotropy (FA) were calculated in 36 hyperintense lesions with a diameter of three pixels or more. Visual assessment was performed for all 156 lesions. Tractography of the corticospinal tract of 29 patients was evaluated. The number of tracts and averaged tract length were used for quantitative analysis, and visual assessment was evaluated by grading. Results The SMS scan showed no bias and acceptable 95% limits of agreement compared to conventional scans in SNR, CNR, and ADC on Bland-Altman analyses. Only FA of the lesions was higher in the SMS scan by 9% ( P = 0.016), whereas FA of the surrounding tissues was similar. Quantitative analysis of tractography showed similar values. Visual assessment of DWI hyperintense lesions and tractography also resulted in comparable evaluation. Conclusion SMS imaging was clinically feasible for imaging quality and quantitative values compared with conventional DWI and DTI.

  16. Tensor Transpose and Its Properties

    OpenAIRE

    Pan, Ran

    2014-01-01

    Tensor transpose is a higher order generalization of matrix transpose. In this paper, we use permutations and symmetry group to define? the tensor transpose. Then we discuss the classification and composition of tensor transposes. Properties of tensor transpose are studied in relation to tensor multiplication, tensor eigenvalues, tensor decompositions and tensor rank.

  17. Stimulated echo diffusion tensor imaging and SPAIR T2 -weighted imaging in chronic exertional compartment syndrome of the lower leg muscles.

    Science.gov (United States)

    Sigmund, Eric E; Sui, Dabang; Ukpebor, Obehi; Baete, Steven; Fieremans, Els; Babb, James S; Mechlin, Michael; Liu, Kecheng; Kwon, Jane; McGorty, KellyAnne; Hodnett, Philip A; Bencardino, Jenny

    2013-11-01

    To evaluate the performance of diffusion tensor imaging (DTI) in the evaluation of chronic exertional compartment syndrome (CECS) as compared to T2 -weighted (T2w) imaging. Using an Institutional Review Board (IRB)-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant protocol, spectral adiabatic inversion recovery (SPAIR) T2w imaging and stimulated echo DTI were applied to eight healthy volunteers and 14 suspected CECS patients before and after exertion. Longitudinal and transverse diffusion eigenvalues, mean diffusivity (MD), and fractional anisotropy (FA) were measured in seven calf muscle compartments, which in patients were classified by their response on T2w: normal (20% change). Mixed model analysis of variance compared subject groups and compartments in terms of response factors (post/pre-exercise ratios) of DTI parameters. All diffusivities significantly increased (P DTI shows promise as an ancillary imaging method in the diagnosis and understanding of the pathophysiology in CECS. Future studies may explore its utility in predicting response to treatment. Copyright © 2013 Wiley Periodicals, Inc.

  18. In vivo assessment of peripheral nerve regeneration by diffusion tensor imaging.

    Science.gov (United States)

    Morisaki, Shinsuke; Kawai, Yuko; Umeda, Masahiro; Nishi, Mayumi; Oda, Ryo; Fujiwara, Hiroyoshi; Yamada, Kei; Higuchi, Toshihiro; Tanaka, Chuzo; Kawata, Mitsuhiro; Kubo, Toshikazu

    2011-03-01

    To evaluate the sensitivity of diffusion tensor imaging (DTI) in assessing peripheral nerve regeneration in vivo. We assessed the changes in the DTI parameters and histological analyses after nerve injury to examine degeneration and regeneration in the rat sciatic nerves. For magnetic resonance imaging (MRI), 16 rats were randomly divided into two groups: group P (permanently crushed; n = 7) and group T (temporally crushed; n = 9). Serial MRI of the right leg was performed before the operation, and then performed at the timepoints of 1, 2, 3, and 4 weeks after the crush injury. The changes in fractional anisotropy (FA), axial diffusivity (λ(∥)), and radial diffusivity (λ(⟂)) were quantified. For histological analyses, the number of axons and the myelinated axon areas were quantified. Decreased FA and increased λ(⟂) were observed in the degenerative phase, and increased FA and decreased λ(⟂) were observed in the regenerative phase. The changes in FA and λ(⟂) were strongly correlated with histological changes, including axonal and myelin regeneration. DTI parameters, especially λ(⟂) , can be good indicators for peripheral nerve regeneration and can be applied as noninvasive diagnostic tools for a variety of neurological diseases. Copyright © 2011 Wiley-Liss, Inc.

  19. Diffusion tensor imaging differentiates vascular parkinsonism from parkinsonian syndromes of degenerative origin in elderly subjects

    Energy Technology Data Exchange (ETDEWEB)

    Deverdun, Jérémy [Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier (France); Laboratoire Charles Coulomb, CNRS UMR 5221 - Université Montpellier II, Montpellier (France); I2FH, Institut d’Imagerie Fonctionnelle Humaine, Hôpital Gui de Chauliac, CHRU de, Montpellier (France); Menjot de Champfleur, Sophie [Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier (France); Clinique du Parc, Castelnau-le-Lez (France); Cabello-Aguilar, Simon [Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier (France); I2FH, Institut d’Imagerie Fonctionnelle Humaine, Hôpital Gui de Chauliac, CHRU de, Montpellier (France); Maury, Florence [Department of Neurology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier (France); Molino, François [Laboratoire Charles Coulomb, CNRS UMR 5221 - Université Montpellier II, Montpellier (France); Institut de Génomique Fonctionnelle, UMR 5203 - INSERM U661 - Université Montpellier II - Université, Montpellier I (France); Charif, Mahmoud [Department of Neurology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier (France); Leboucq, Nicolas [Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier (France); Ayrignac, Xavier; Labauge, Pierre [Department of Neurology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier (France); and others

    2014-11-15

    Background and Purpose: The etiologic diagnosis of parkinsonian syndromes is of particular importance when considering syndromes of vascular or degenerative origin. The purpose of this study is to find differences in the white-matter architecture between those two groups in elderly patients. Materials and Methods: Thirty-five patients were prospectively included (multiple-system atrophy, n = 5; Parkinson's disease, n = 15; progressive supranuclear palsy, n = 9; vascular parkinsonism, n = 6), with a mean age of 76 years. Patients with multiple-system atrophy, progressive supranuclear palsy and Parkinson's disease were grouped as having parkinsonian syndromes of degenerative origin. Brain MRIs included diffusion tensor imaging. Fractional anisotropy and mean-diffusivity maps were spatially normalized, and group analyses between parkinsonian syndromes of degenerative origin and vascular parkinsonism were performed using a voxel-based approach. Results: Statistical parametric-mapping analysis of diffusion tensor imaging data showed decreased fractional anisotropy value in internal capsules bilaterally in patients with vascular parkinsonism compared to parkinsonian syndromes of degenerative origin (p = 0.001) and showed a lower mean diffusivity in the white matter of the left superior parietal lobule (p = 0.01). Fractional anisotropy values were found decreased in the middle cerebellar peduncles in multiple-system atrophy compared to Parkinson's disease and progressive supranuclear palsy. The mean diffusivity was increased in those regions for these subgroups. Conclusion: Clinically defined vascular parkinsonism was associated with decreased fractional anisotropy in the deep white matter (internal capsules) compared to parkinsonian syndromes of degenerative origin. These findings are consistent with previously published neuropathological data.

  20. Diffusion tensor imaging differentiates vascular parkinsonism from parkinsonian syndromes of degenerative origin in elderly subjects

    International Nuclear Information System (INIS)

    Deverdun, Jérémy; Menjot de Champfleur, Sophie; Cabello-Aguilar, Simon; Maury, Florence; Molino, François; Charif, Mahmoud; Leboucq, Nicolas; Ayrignac, Xavier; Labauge, Pierre

    2014-01-01

    Background and Purpose: The etiologic diagnosis of parkinsonian syndromes is of particular importance when considering syndromes of vascular or degenerative origin. The purpose of this study is to find differences in the white-matter architecture between those two groups in elderly patients. Materials and Methods: Thirty-five patients were prospectively included (multiple-system atrophy, n = 5; Parkinson's disease, n = 15; progressive supranuclear palsy, n = 9; vascular parkinsonism, n = 6), with a mean age of 76 years. Patients with multiple-system atrophy, progressive supranuclear palsy and Parkinson's disease were grouped as having parkinsonian syndromes of degenerative origin. Brain MRIs included diffusion tensor imaging. Fractional anisotropy and mean-diffusivity maps were spatially normalized, and group analyses between parkinsonian syndromes of degenerative origin and vascular parkinsonism were performed using a voxel-based approach. Results: Statistical parametric-mapping analysis of diffusion tensor imaging data showed decreased fractional anisotropy value in internal capsules bilaterally in patients with vascular parkinsonism compared to parkinsonian syndromes of degenerative origin (p = 0.001) and showed a lower mean diffusivity in the white matter of the left superior parietal lobule (p = 0.01). Fractional anisotropy values were found decreased in the middle cerebellar peduncles in multiple-system atrophy compared to Parkinson's disease and progressive supranuclear palsy. The mean diffusivity was increased in those regions for these subgroups. Conclusion: Clinically defined vascular parkinsonism was associated with decreased fractional anisotropy in the deep white matter (internal capsules) compared to parkinsonian syndromes of degenerative origin. These findings are consistent with previously published neuropathological data

  1. Semi-Supervised Tensor-Based Graph Embedding Learning and Its Application to Visual Discriminant Tracking.

    Science.gov (United States)

    Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen

    2017-01-01

    An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.

  2. Longitudinal diffusion tensor imaging in amyotrophic lateral sclerosis

    Directory of Open Access Journals (Sweden)

    Keil Carsten

    2012-11-01

    Full Text Available Abstract Background Amyotrophic lateral sclerosis (ALS is a fatal neurodegenerative disorder, caused by progressive loss of motor neurons. Changes are widespread in the subcortical white matter in ALS. Diffusion tensor imaging (DTI detects pathological changes in white matter fibres in vivo, based on alterations in the degree (diffusivity, ADC and directedness (fractional anisotropy, FA of proton movement. Methods 24 patients with ALS and 24 age-matched controls received 1.5T DTI. FA and ADC were analyzed using statistical parametric mapping. In 15 of the 24 ALS patients, a second DTI was obtained after 6 months. Results Decreased FA in the corticospinal tract (CST and frontal areas confirm existing results. With a direct comparison of baseline and follow-up dataset, the progression of upper motor neuron degeneration, reflected in FA decrease, could be captured along the CST and in frontal areas. The involvement of cerebellum in the pathology of ALS, as suspected from functional MRI studies, could be confirmed by a reduced FA (culmen, declive. These structural changes correlated well with disease duration, ALSFRS-R, and physical and executive functions. Conclusion DTI detects changes that are regarded as prominent features of ALS and thus, shows promise in its function as a biomarker. Using the technique herein, we could demonstrate DTI changes at follow-up which correlated well with clinical progression.

  3. Arcuate fasciculus laterality by diffusion tensor imaging correlates with language laterality by functional MRI in preadolescent children

    International Nuclear Information System (INIS)

    Sreedharan, Ruma Madhu; Menon, Amitha C.; Thomas, Sanjeev V.; James, Jija S.; Kesavadas, Chandrasekharan

    2015-01-01

    Language lateralization is unique to humans. Functional MRI (fMRI) and diffusion tensor imaging (DTI) enable the study of language areas and white matter fibers involved in language, respectively. The objective of this study was to correlate arcuate fasciculus (AF) laterality by diffusion tensor imaging with that by fMRI in preadolescent children which has not yet been reported. Ten children between 8 and 12 years were subjected to fMRI and DTI imaging using Siemens 1.5 T MRI. Two language fMRI paradigms - visual verb generation and word pair task - were used. Analysis was done using SPM8 software. In DTI, the fiber volume of the arcuate fasciculus (AFV) and fractional anisotropy (FA) was measured. The fMRI Laterality Index (fMRI-LI) and DTI Laterality Index (DTI-LI) were calculated and their correlation assessed using the Pearson Correlation Index. Of ten children, mean age 10.6 years, eight showed left lateralization while bilateral language lateralization was seen in two. AFV by DTI was more on the left side in seven of the eight children who had left lateralization by fMRI. DTI could not trace the AF in one child. Of the two with bilateral language lateralization on fMRI, one showed larger AFV on the right side while the other did not show any asymmetry. There was a significant correlation (p < 0.02) between fMRI-LI and DTI-LI. Group mean of AFV by DTI was higher on the left side (2659.89 ± 654.75 mm 3 ) as compared to the right (1824.11 ± 582.81 mm 3 ) (p < 0.01). Like fMRI, DTI also reveals language laterality in children with a high degree of correlation between the two imaging modalities. (orig.)

  4. Arcuate fasciculus laterality by diffusion tensor imaging correlates with language laterality by functional MRI in preadolescent children

    Energy Technology Data Exchange (ETDEWEB)

    Sreedharan, Ruma Madhu [Government Medical College Hospital, Department of Radiology, Trivandrum, Kerala (India); Menon, Amitha C.; Thomas, Sanjeev V. [Sree Chitra, Thirunal Institute for Medical Sciences and Technology, Department of Neurology, Thiruvananthapuram, Kerala (India); James, Jija S.; Kesavadas, Chandrasekharan [SCTIMST, Department of Imaging Science and Interventional Radiology, Trivandrum, Kerala (India)

    2015-03-01

    Language lateralization is unique to humans. Functional MRI (fMRI) and diffusion tensor imaging (DTI) enable the study of language areas and white matter fibers involved in language, respectively. The objective of this study was to correlate arcuate fasciculus (AF) laterality by diffusion tensor imaging with that by fMRI in preadolescent children which has not yet been reported. Ten children between 8 and 12 years were subjected to fMRI and DTI imaging using Siemens 1.5 T MRI. Two language fMRI paradigms - visual verb generation and word pair task - were used. Analysis was done using SPM8 software. In DTI, the fiber volume of the arcuate fasciculus (AFV) and fractional anisotropy (FA) was measured. The fMRI Laterality Index (fMRI-LI) and DTI Laterality Index (DTI-LI) were calculated and their correlation assessed using the Pearson Correlation Index. Of ten children, mean age 10.6 years, eight showed left lateralization while bilateral language lateralization was seen in two. AFV by DTI was more on the left side in seven of the eight children who had left lateralization by fMRI. DTI could not trace the AF in one child. Of the two with bilateral language lateralization on fMRI, one showed larger AFV on the right side while the other did not show any asymmetry. There was a significant correlation (p < 0.02) between fMRI-LI and DTI-LI. Group mean of AFV by DTI was higher on the left side (2659.89 ± 654.75 mm{sup 3}) as compared to the right (1824.11 ± 582.81 mm{sup 3}) (p < 0.01). Like fMRI, DTI also reveals language laterality in children with a high degree of correlation between the two imaging modalities. (orig.)

  5. Microstructural changes of whole brain in patients with comitant strabismus: evidence from a diffusion tensor imaging study

    Directory of Open Access Journals (Sweden)

    Huang X

    2016-08-01

    Full Text Available Xin Huang,1,2,* Hai-Jun Li,3,* Ying Zhang,1 De-Chang Peng,3 Pei-Hong Hu,1 Yu-Lin Zhong,1 Fu-Qing Zhou,3 Yi Shao1 1Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, 2Department of Ophthalmology, The First People’s Hospital of Jiujiang City, Jiujiang, 3Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China*These authors contributed equally to this work Objective: The aim of this study was to investigate the fractional anisotropy (FA and mean diffusivity (MD using a diffusion tensor imaging technique and whole-brain voxel-based analysis in patients with comitant strabismus.Patients and methods: A total of 19 (nine males and ten females patients with comitant strabismus and 19 age-, sex-, and education-matched healthy controls (HCs underwent magnetic resonance imaging examination. Imaging data were analyzed using two-sample t-tests to identify group differences in FA and MD values. Patients with comitant strabismus were distinguishable from HCs by receiver operating characteristic curves.Results: Compared with HCs, patients with comitant strabismus exhibited significantly decreased FA values in the brain regions of the left superior temporal gyrus and increased values in the bilateral medial frontal gyrus, right globus pallidus/brainstem, and bilateral precuneus. Meanwhile, MD value was significantly reduced in the brain regions of the bilateral cerebellum posterior lobe and left middle frontal gyrus but increased in the brain regions of the right middle frontal gyrus and left anterior cingulate.Conclusion: These results suggest significant brain abnormalities in comitant strabismus, which may underlie the pathologic mechanisms of fusion defects and ocular motility disorders in patients with comitant strabismus. Keywords: comitant strabismus, diffusion tensor imaging, mean diffusivity, fractional anisotropy, resting state

  6. Abnormal Corpus Callosum Connectivity, Socio-Communicative Deficits, and Motor Deficits in Children with Autism Spectrum Disorder: A Diffusion Tensor Imaging Study

    Science.gov (United States)

    Hanaie, Ryuzo; Mohri, Ikuko; Kagitani-Shimono, Kuriko; Tachibana, Masaya; Matsuzaki, Junko; Watanabe, Yoshiyuki; Fujita, Norihiko; Taniike, Masako

    2014-01-01

    In addition to social and communicative deficits, many studies have reported motor deficits in autism spectrum disorder (ASD). This study investigated the macro and microstructural properties of the corpus callosum (CC) of 18 children with ASD and 12 typically developing controls using diffusion tensor imaging tractography. We aimed to explore…

  7. The tensor rank of tensor product of two three-qubit W states is eight

    OpenAIRE

    Chen, Lin; Friedland, Shmuel

    2017-01-01

    We show that the tensor rank of tensor product of two three-qubit W states is not less than eight. Combining this result with the recent result of M. Christandl, A. K. Jensen, and J. Zuiddam that the tensor rank of tensor product of two three-qubit W states is at most eight, we deduce that the tensor rank of tensor product of two three-qubit W states is eight. We also construct the upper bound of the tensor rank of tensor product of many three-qubit W states.

  8. Diffusion Tensor Imaging Evaluation of Neural Network Development in Patients Undergoing Therapeutic Repetitive Transcranial Magnetic Stimulation following Stroke

    Directory of Open Access Journals (Sweden)

    Naoki Yamada

    2018-01-01

    Full Text Available We aimed to investigate plastic changes in cerebral white matter structures using diffusion tensor imaging following a 15-day stroke rehabilitation program. We compared the detection of cerebral plasticity between generalized fractional anisotropy (GFA, a novel tool for investigating white matter structures, and fractional anisotropy (FA. Low-frequency repetitive transcranial magnetic stimulation (LF-rTMS of 2400 pulses applied to the nonlesional hemisphere and 240 min intensive occupation therapy (OT daily over 15 days. Motor function was evaluated using the Fugl-Meyer assessment (FMA and Wolf Motor Function Test (WMFT. Patients underwent diffusion tensor magnetic resonance imaging (MRI on admission and discharge, from which bilateral FA and GFA values in Brodmann area (BA 4 and BA6 were calculated. Motor function improved following treatment (p<0.001. Treatment increased GFA values for both the lesioned and nonlesioned BA4 (p<0.05, p<0.001, resp.. Changes in GFA value for BA4 of the lesioned hemisphere were significantly inversely correlated with changes in WMFT scores (R2=0.363, p<0.05. Our findings indicate that the GFA may have a potentially more useful ability than FA to detect changes in white matter structures in areas of fiber intersection for any such future investigations.

  9. Predictability of motor outcome according to the time of diffusion tensor imaging in patients with cerebral infarct

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Yong Hyun [Yeungnam College of Science and Technology, Department of Physical Therapy, Taegu (Korea, Republic of); Jeoung, Yong Jae [Yeungnam University, Department of Physical Medicine and Rehabilitation, College of Medicine, Taegu (Korea, Republic of); Lee, Jun [Yeungnam University, Department of Neurology, College of Medicine, Taegu (Korea, Republic of); Son, Su Min; Jang, Sung Ho [Yeungnam University 317-1, Department of Physical Medicine and Rehabilitation, College of Medicine, Taegu (Korea, Republic of); Kim, Saeyoon [Yeungnam University, Department of Pediatrics, College of Medicine, Taegu (Korea, Republic of); Kim, Chulseung [Medical Devices Clinical Trial Center of Yeungnam University Hospital, Taegu (Korea, Republic of)

    2012-07-15

    Predictability of diffusion tensor imaging tractography (DTT) for motor outcome can differ according to the time of DTT. We attempted to compare the predictability for motor outcome according to the time of diffusion tensor imaging (DTI) by analyzing the corticospinal tract (CST) integrity on DTT in patients with corona radiata (CR) infarct. Seventy-one consecutive hemiparetic patients with CR infarct were recruited. Motor function of the affected extremities was measured twice: at onset and at 6 months from onset. According to the time of DTI, patients were classified into two groups: the early scanning group (ES group) within 14 days since stroke onset; and the late scanning group (LS group) 15-28 days. Motor outcome was compared with the CST integrity on DTT. Motor prognosis was predicted from scan time of DTI and the CST integrity on DTT in the logistic regression model. According to separate regression analysis, the CST integrity of the late group was found to predict MI score (OR = 14.000, 95% CI = 3.194-61.362, p < 0.05), whereas the CST integrity of the early group was not found to predict MI score. In terms of both positive and negative predictabilities, we found that predictability of DTT for motor outcome was better in patients who were scanned later (15-28 days after onset) than in patients who were scanned earlier (1-14 days after onset). (orig.)

  10. Predictability of motor outcome according to the time of diffusion tensor imaging in patients with cerebral infarct

    International Nuclear Information System (INIS)

    Kwon, Yong Hyun; Jeoung, Yong Jae; Lee, Jun; Son, Su Min; Jang, Sung Ho; Kim, Saeyoon; Kim, Chulseung

    2012-01-01

    Predictability of diffusion tensor imaging tractography (DTT) for motor outcome can differ according to the time of DTT. We attempted to compare the predictability for motor outcome according to the time of diffusion tensor imaging (DTI) by analyzing the corticospinal tract (CST) integrity on DTT in patients with corona radiata (CR) infarct. Seventy-one consecutive hemiparetic patients with CR infarct were recruited. Motor function of the affected extremities was measured twice: at onset and at 6 months from onset. According to the time of DTI, patients were classified into two groups: the early scanning group (ES group) within 14 days since stroke onset; and the late scanning group (LS group) 15-28 days. Motor outcome was compared with the CST integrity on DTT. Motor prognosis was predicted from scan time of DTI and the CST integrity on DTT in the logistic regression model. According to separate regression analysis, the CST integrity of the late group was found to predict MI score (OR = 14.000, 95% CI = 3.194-61.362, p < 0.05), whereas the CST integrity of the early group was not found to predict MI score. In terms of both positive and negative predictabilities, we found that predictability of DTT for motor outcome was better in patients who were scanned later (15-28 days after onset) than in patients who were scanned earlier (1-14 days after onset). (orig.)

  11. Bowen-York tensors

    International Nuclear Information System (INIS)

    Beig, Robert; Krammer, Werner

    2004-01-01

    For a conformally flat 3-space, we derive a family of linear second-order partial differential operators which sends vectors into trace-free, symmetric 2-tensors. These maps, which are parametrized by conformal Killing vectors on the 3-space, are such that the divergence of the resulting tensor field depends only on the divergence of the original vector field. In particular, these maps send source-free electric fields into TT tensors. Moreover, if the original vector field is the Coulomb field on R 3 {0}, the resulting tensor fields on R 3 {0} are nothing but the family of TT tensors originally written by Bowen and York

  12. Interactive Volume Rendering of Diffusion Tensor Data

    Energy Technology Data Exchange (ETDEWEB)

    Hlawitschka, Mario; Weber, Gunther; Anwander, Alfred; Carmichael, Owen; Hamann, Bernd; Scheuermann, Gerik

    2007-03-30

    As 3D volumetric images of the human body become an increasingly crucial source of information for the diagnosis and treatment of a broad variety of medical conditions, advanced techniques that allow clinicians to efficiently and clearly visualize volumetric images become increasingly important. Interaction has proven to be a key concept in analysis of medical images because static images of 3D data are prone to artifacts and misunderstanding of depth. Furthermore, fading out clinically irrelevant aspects of the image while preserving contextual anatomical landmarks helps medical doctors to focus on important parts of the images without becoming disoriented. Our goal was to develop a tool that unifies interactive manipulation and context preserving visualization of medical images with a special focus on diffusion tensor imaging (DTI) data. At each image voxel, DTI provides a 3 x 3 tensor whose entries represent the 3D statistical properties of water diffusion locally. Water motion that is preferential to specific spatial directions suggests structural organization of the underlying biological tissue; in particular, in the human brain, the naturally occuring diffusion of water in the axon portion of neurons is predominantly anisotropic along the longitudinal direction of the elongated, fiber-like axons [MMM+02]. This property has made DTI an emerging source of information about the structural integrity of axons and axonal connectivity between brain regions, both of which are thought to be disrupted in a broad range of medical disorders including multiple sclerosis, cerebrovascular disease, and autism [Mos02, FCI+01, JLH+99, BGKM+04, BJB+03].

  13. Diffusion tensor imaging in children and adolescents with tuberous sclerosis

    Energy Technology Data Exchange (ETDEWEB)

    Karadag, Demet [Institute of Diagnostic and Interventional Radiology, Friedrich Schiller University, Department of Paediatric Radiology, Jena (Germany); Kirikkale Yuksek Ihtisas Hospital, Department of Radiology, Kirirkale (Turkey); Mentzel, Hans-J.; Loebel, Ulrike; Reichenbach, Juergen R.; Kaiser, Werner A. [Institute of Diagnostic and Interventional Radiology, Friedrich Schiller University, Department of Paediatric Radiology, Jena (Germany); Guellmar, Daniel [Institute of Diagnostic and Interventional Radiology, Friedrich Schiller University, Department of Paediatric Radiology, Jena (Germany); Friedrich Schiller University, Biomagnetic Centre, Clinic of Neurology, Jena (Germany); Rating, Tina; Brandl, Ulrich [Friedrich Schiller University, Department of Paediatric Neurology, Jena (Germany)

    2005-10-01

    Tuberous sclerosis (TS) is characterised by benign hamartomatous lesions in many organs. Diffusion tensor imaging (DTI) can detect microstructural changes in pathological processes. To determine apparent diffusion coefficient (ADC) and fractional anisotropy (FA) maps in children with TS and to investigate the diffusion properties in cortical tubers, white-matter lesions, perilesional white matter, and contralateral normal-appearing white matter, and to compare the results with ADC and FA maps of normal age- and sex-matched volunteers. Seven children and adolescents (age range 2-20 years) suffering from TS were included. MRI was performed on a 1.5-T scanner using a transmit/receive coil with T1-W and T2-W spin-echo and FLAIR sequences. DT images were acquired by using a single-shot echo-planar pulse sequence. Diffusion gradients were applied in six different directions with a b value of 1,000 s/mm{sup 2}. ADC was higher in cortical tubers than in the corresponding cortical location of controls. ADC values were higher and FA values were lower in white-matter lesions and perilesional white matter than in both the contralateral normal-appearing white matter of patients and in controls. There were no significant differences for both ADC and FA values in the normal-appearing white matter of patients with TS compared to controls. DTI provides important information about cortical tubers, white-matter abnormalities, and perilesional white matter in patients with TS. (orig.)

  14. Correlation between pennation angle and image quality of skeletal muscle fibre tractography using deterministic diffusion tensor imaging.

    Science.gov (United States)

    Okamoto, Yoshikazu; Okamoto, Toru; Yuka, Kujiraoka; Hirano, Yuji; Isobe, Tomonori; Minami, Manabu

    2012-12-01

    The aim of this study was to ascertain whether a correlation existed between muscle pennation angle and the ability to successfully perform tractography of the lower leg muscle fibres with deterministic diffusion tensor imaging (DTI) in normal volunteers. Fourteen volunteers aged 20-39 (mean 28.2 years old) were recruited. All volunteers were scanned using DTI, and six fibre tractographs were constructed from one lower leg of each volunteer, and the 'fibre density' was calculated in each of the tractographs. The pennation angle is the angle formed by the muscle fibre and the aponeurosis. The average pennation angle (AVPA) and standard deviation of the pennation angle (SDPA) were also measured for each muscle by ultrasonography in the same region as the MRI scan. For all 84 tractography images, the correlation coefficient between the fibre density and AVPA or SDPA was calculated. Fibre density and AVPA showed a moderate negative correlation (R = -0.72), and fibre density and SDPA showed a weak negative correlation (R = -0.47). With respect to comparisons within each muscle, AVPA and fibre density showed a moderate negative correlation in the gastrocnemius lateralis muscle (R = -0.57). Our data suggest that a larger, more variable pennation angle resulted in worse skeletal muscle tractography using deterministic DTI. © 2012 The Authors. Journal of Medical Imaging and Radiation Oncology © 2012 The Royal Australian and New Zealand College of Radiologists.

  15. Brain involvement in patients with inflammatory bowel disease: a voxel-based morphometry and diffusion tensor imaging study.

    Science.gov (United States)

    Zikou, Anastasia K; Kosmidou, Maria; Astrakas, Loukas G; Tzarouchi, Loukia C; Tsianos, Epameinondas; Argyropoulou, Maria I

    2014-10-01

    To investigate structural brain changes in inflammatory bowel disease (IBD). Brain magnetic resonance imaging (MRI) was performed on 18 IBD patients (aged 45.16 ± 14.71 years) and 20 aged-matched control subjects. The imaging protocol consisted of a sagittal-FLAIR, a T1-weighted high-resolution three-dimensional spoiled gradient-echo sequence, and a multisession spin-echo echo-planar diffusion-weighted sequence. Differences between patients and controls in brain volume and diffusion indices were evaluated using the voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) methods, respectively. The presence of white-matter hyperintensities (WMHIs) was evaluated on FLAIR images. VBM revealed decreased grey matter (GM) volume in patients in the fusiform and the inferior temporal gyrus bilaterally, the right precentral gyrus, the right supplementary motor area, the right middle frontal gyrus and the left superior parietal gyrus (p tensor imaging detects microstructural brain abnormalities in IBD. • Voxel based morphometry reveals brain atrophy in IBD.

  16. Measuring Fractional Anisotropy of the Corpus Callosum Using Diffusion Tensor Imaging: Mid-Sagittal versus Axial Imaging Planes

    International Nuclear Information System (INIS)

    Kim, Eung Yeop; Park, Hae Jeong; Kim, Dong Hyun; Lee, Seung Koo; Kim, Jin Na

    2008-01-01

    Many diffusion tensor imaging (DTI) studies of the corpus callosum (CC) have been performed with a relatively thick slice thickness in the axial plane, which may result in underestimating the fractional anisotropy (FA) of the CC due to a partial volume effect. We hypothesized that the FA of the CC can be more accurately measured by using mid-sagittal DTI. We compared the FA values of the CC between the axial and mid-sagittal DTI. Fourteen healthy volunteers underwent MRI at 3.0 T. DTI was performed in both the mid-sagittal and axial planes. One 5-mm mid-sagittal image and twenty-five 2-mm axial images were obtained for the CC. The five regions of interest (ROIs) that included the prefrontal (I), premotor and supplementary motor (II), motor (III), sensory (IV) and parietal, temporal and occipital regions (V) were drawn along the border of the CC on each sagittal FA map. The FA values obtained from each region were compared between the two sagittal maps. The FA values of all the regions, except for region V, were significantly increased on the mid-sagittal imaging. The FA values in region IV were significantly underestimated on the mid-sagittal image from the axial imaging, compared with those in the regions I and V (p = 0.037 and p = 0.001, respectively). The FA values of the CC were significantly higher on the midsagittal DTI than those on the axial DTI in regions I-IV, and particularly in the region IV. Mid-sagittal DTI may provide more accurate FA values of the CC than can the axial DTI, and mid-sagittal DTI may be more desirable for studies that compare between patients and healthy subjects

  17. Harmonic d-tensors

    Energy Technology Data Exchange (ETDEWEB)

    Hohmann, Manuel [Physikalisches Institut, Universitaet Tartu (Estonia)

    2016-07-01

    Tensor harmonics are a useful mathematical tool for finding solutions to differential equations which transform under a particular representation of the rotation group SO(3). In order to make use of this tool also in the setting of Finsler geometry, where the objects of relevance are d-tensors instead of tensors, we construct a set of d-tensor harmonics for both SO(3) and SO(4) symmetries and show how these can be used for calculations in Finsler geometry and gravity.

  18. From stochastic completion fields to tensor voting

    NARCIS (Netherlands)

    Almsick, van M.A.; Duits, R.; Franken, E.M.; Haar Romenij, ter B.M.; Olsen, O.F.; Florack, L.M.J.; Kuijper, A.

    2005-01-01

    Several image processing algorithms imitate the lateral interaction of neurons in the visual striate cortex V1 to account for the correlations along contours and lines. Here we focus on two methodologies: tensor voting by Guy and Medioni, and stochastic completion fields by Mumford, Williams and

  19. Current density tensors

    Science.gov (United States)

    Lazzeretti, Paolo

    2018-04-01

    It is shown that nonsymmetric second-rank current density tensors, related to the current densities induced by magnetic fields and nuclear magnetic dipole moments, are fundamental properties of a molecule. Together with magnetizability, nuclear magnetic shielding, and nuclear spin-spin coupling, they completely characterize its response to magnetic perturbations. Gauge invariance, resolution into isotropic, deviatoric, and antisymmetric parts, and contributions of current density tensors to magnetic properties are discussed. The components of the second-rank tensor properties are rationalized via relationships explicitly connecting them to the direction of the induced current density vectors and to the components of the current density tensors. The contribution of the deviatoric part to the average value of magnetizability, nuclear shielding, and nuclear spin-spin coupling, uniquely determined by the antisymmetric part of current density tensors, vanishes identically. The physical meaning of isotropic and anisotropic invariants of current density tensors has been investigated, and the connection between anisotropy magnitude and electron delocalization has been discussed.

  20. Road Network Extraction from VHR Satellite Images Using Context Aware Object Feature Integration and Tensor Voting

    Directory of Open Access Journals (Sweden)

    Mehdi Maboudi

    2016-08-01

    Full Text Available Road networks are very important features in geospatial databases. Even though high-resolution optical satellite images have already been acquired for more than a decade, tools for automated extraction of road networks from these images are still rare. One consequence of this is the need for manual interaction which, in turn, is time and cost intensive. In this paper, a multi-stage approach is proposed which integrates structural, spectral, textural, as well as contextual information of objects to extract road networks from very high resolution satellite images. Highlights of the approach are a novel linearity index employed for the discrimination of elongated road segments from other objects and customized tensor voting which is utilized to fill missing parts of the network. Experiments are carried out with different datasets. Comparison of the achieved results with the results of seven state-of-the-art methods demonstrated the efficiency of the proposed approach.

  1. Embryo Cell Membranes Reconstruction by Tensor Voting

    OpenAIRE

    Michelin , Gaël; Guignard , Léo; Fiuza , Ulla-Maj; Malandain , Grégoire

    2014-01-01

    International audience; Image-based studies of developing organs or embryos produce a huge quantity of data. To handle such high-throughput experimental protocols, automated computer-assisted methods are highly desirable. This article aims at designing an efficient cell segmentation method from microscopic images. The proposed approach is twofold: first, cell membranes are enhanced or extracted by the means of structure-based filters, and then perceptual grouping (i.e. tensor voting) allows t...

  2. Diurnal microstructural variations in healthy adult brain revealed by diffusion tensor imaging.

    Directory of Open Access Journals (Sweden)

    Chunxiang Jiang

    Full Text Available Biorhythm is a fundamental property of human physiology. Changes in the extracellular space induced by cell swelling in response to the neural activity enable the in vivo characterization of cerebral microstructure by measuring the water diffusivity using diffusion tensor imaging (DTI. To study the diurnal microstructural alterations of human brain, fifteen right-handed healthy adult subjects were recruited for DTI studies in two repeated sessions (8∶30 AM and 8∶30 PM within a 24-hour interval. Fractional anisotropy (FA, apparent diffusion coefficient (ADC, axial (λ// and radial diffusivity (λ⊥ were compared pixel by pixel between the sessions for each subject. Significant increased morning measurements in FA, ADC, λ// and λ⊥ were seen in a wide range of brain areas involving frontal, parietal, temporal and occipital lobes. Prominent evening dominant λ⊥ (18.58% was detected in the right inferior temporal and ventral fusiform gyri. AM-PM variation of λ⊥ was substantially left side hemisphere dominant (p<0.05, while no hemispheric preference was observed for the same analysis for ADC (p = 0.77, λ// (p = 0.08 or FA (p = 0.25. The percentage change of ADC, λ//, λ⊥, and FA were 1.59%, 2.15%, 1.20% and 2.84%, respectively, for brain areas without diurnal diffusivity contrast. Microstructural variations may function as the substrates of the phasic neural activities in correspondence to the environment adaptation in a light-dark cycle. This research provided a baseline for researches in neuroscience, sleep medicine, psychological and psychiatric disorders, and necessitates that diurnal effect should be taken into account in following up studies using diffusion tensor quantities.

  3. Six dimensional X-ray Tensor Tomography with a compact laboratory setup

    Science.gov (United States)

    Sharma, Y.; Wieczorek, M.; Schaff, F.; Seyyedi, S.; Prade, F.; Pfeiffer, F.; Lasser, T.

    2016-09-01

    Attenuation based X-ray micro computed tomography (XCT) provides three-dimensional images with micrometer resolution. However, there is a trade-off between the smallest size of the structures that can be resolved and the measurable sample size. In this letter, we present an imaging method using a compact laboratory setup that reveals information about micrometer-sized structures within samples that are several orders of magnitudes larger. We combine the anisotropic dark-field signal obtained in a grating interferometer and advanced tomographic reconstruction methods to reconstruct a six dimensional scattering tensor at every spatial location in three dimensions. The scattering tensor, thus obtained, encodes information about the orientation of micron-sized structures such as fibres in composite materials or dentinal tubules in human teeth. The sparse acquisition schemes presented in this letter enable the measurement of the full scattering tensor at every spatial location and can be easily incorporated in a practical, commercially feasible laboratory setup using conventional X-ray tubes, thus allowing for widespread industrial applications.

  4. Diffusion tensor optical coherence tomography

    Science.gov (United States)

    Marks, Daniel L.; Blackmon, Richard L.; Oldenburg, Amy L.

    2018-01-01

    In situ measurements of diffusive particle transport provide insight into tissue architecture, drug delivery, and cellular function. Analogous to diffusion-tensor magnetic resonance imaging (DT-MRI), where the anisotropic diffusion of water molecules is mapped on the millimeter scale to elucidate the fibrous structure of tissue, here we propose diffusion-tensor optical coherence tomography (DT-OCT) for measuring directional diffusivity and flow of optically scattering particles within tissue. Because DT-OCT is sensitive to the sub-resolution motion of Brownian particles as they are constrained by tissue macromolecules, it has the potential to quantify nanoporous anisotropic tissue structure at micrometer resolution as relevant to extracellular matrices, neurons, and capillaries. Here we derive the principles of DT-OCT, relating the detected optical signal from a minimum of six probe beams with the six unique diffusion tensor and three flow vector components. The optimal geometry of the probe beams is determined given a finite numerical aperture, and a high-speed hardware implementation is proposed. Finally, Monte Carlo simulations are employed to assess the ability of the proposed DT-OCT system to quantify anisotropic diffusion of nanoparticles in a collagen matrix, an extracellular constituent that is known to become highly aligned during tumor development.

  5. In utero diffusion tensor imaging of the fetal brain: A reproducibility study.

    Science.gov (United States)

    Jakab, András; Tuura, Ruth; Kellenberger, Christian; Scheer, Ianina

    2017-01-01

    Our purpose was to evaluate the within-subject reproducibility of in utero diffusion tensor imaging (DTI) metrics and the visibility of major white matter structures. Images for 30 fetuses (20-33. postmenstrual weeks, normal neurodevelopment: 6 cases, cerebral pathology: 24 cases) were acquired on 1.5 T or 3.0 T MRI. DTI with 15 diffusion-weighting directions was repeated three times for each case, TR/TE: 2200/63 ms, voxel size: 1 ∗ 1 mm, slice thickness: 3-5 mm, b-factor: 700 s/mm 2 . Reproducibility was evaluated from structure detectability, variability of DTI measures using the coefficient of variation (CV), image correlation and structural similarity across repeated scans for six selected structures. The effect of age, scanner type, presence of pathology was determined using Wilcoxon rank sum test. White matter structures were detectable in the following percentage of fetuses in at least two of the three repeated scans: corpus callosum genu 76%, splenium 64%, internal capsule, posterior limb 60%, brainstem fibers 40% and temporooccipital association pathways 60%. The mean CV of DTI metrics ranged between 3% and 14.6% and we measured higher reproducibility in fetuses with normal brain development. Head motion was negatively correlated with reproducibility, this effect was partially ameliorated by motion-correction algorithm using image registration. Structures on 3.0 T had higher variability both with- and without motion correction. Fetal DTI is reproducible for projection and commissural bundles during mid-gestation, however, in 16-30% of the cases, data were corrupted by artifacts, resulting in impaired detection of white matter structures. To achieve robust results for the quantitative analysis of diffusivity and anisotropy values, fetal-specific image processing is recommended and repeated DTI is needed to ensure the detectability of fiber pathways.

  6. Potential long-term effects of MDMA on the basal ganglia-thalamocortical circuit: a proton MR spectroscopy and diffusion-tensor imaging study.

    Science.gov (United States)

    Liu, Hua-Shan; Chou, Ming-Chung; Chung, Hsiao-Wen; Cho, Nai-Yu; Chiang, Shih-Wei; Wang, Chao-Ying; Kao, Hung-Wen; Huang, Guo-Shu; Chen, Cheng-Yu

    2011-08-01

    To investigate the effects of 3,4-methylenedioxymethamphetamine (MDMA, commonly known as "ecstasy") on the alterations of brain metabolites and anatomic tissue integrity related to the function of the basal ganglia-thalamocortical circuit by using proton magnetic resonance (MR) spectroscopy and diffusion-tensor MR imaging. This study was approved by a local institutional review board, and written informed consent was obtained from all subjects. Thirty-one long-term (>1 year) MDMA users and 33 healthy subjects were enrolled. Proton MR spectroscopy from the middle frontal cortex and bilateral basal ganglia and whole-brain diffusion-tensor MR imaging were performed with a 3.0-T system. Absolute concentrations of metabolites were computed, and diffusion-tensor data were registered to the International Consortium for Brain Mapping template to facilitate voxel-based group comparison. The mean myo-inositol level in the basal ganglia of MDMA users (left: 4.55 mmol/L ± 2.01 [standard deviation], right: 4.48 mmol/L ± 1.33) was significantly higher than that in control subjects (left: 3.25 mmol/L ± 1.30, right: 3.31 mmol/L ± 1.19) (P 50 voxels). Increased myo-inositol and Cho concentrations in the basal ganglia of MDMA users are suggestive of glial response to degenerating serotonergic functions. The abnormal metabolic changes in the basal ganglia may consequently affect the inhibitory effect of the basal ganglia to the thalamus, as suggested by the increased FA in the thalamus and abnormal changes in water diffusion in the corresponding basal ganglia-thalamocortical circuit. © RSNA, 2011.

  7. Chronic Effects of Boxing: Diffusion Tensor Imaging and Cognitive Findings.

    Science.gov (United States)

    Wilde, Elisabeth A; Hunter, Jill V; Li, Xiaoqi; Amador, Cristian; Hanten, Gerri; Newsome, Mary R; Wu, Trevor C; McCauley, Stephen R; Vogt, Gregory S; Chu, Zili David; Biekman, Brian; Levin, Harvey S

    2016-04-01

    We used magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) to evaluate the effects of boxing on brain structure and cognition in 10 boxers (8 retired, 2 active; mean age = 45.7 years; standard deviation [SD] = 9.71) and 9 participants (mean age = 43.44; SD = 9.11) in noncombative sports. Evans Index (maximum width of the anterior horns of the lateral ventricles/maximal width of the internal diameter of the skull) was significantly larger in the boxers (F = 4.52; p = 0.050; Cohen's f = 0.531). Word list recall was impaired in the boxers (F(1,14) = 10.70; p = 0.006; f = 0.84), whereas implicit memory measured by faster reaction time (RT) to a repeating sequence of numbers than to a random sequence was preserved (t = 2.52; p boxing had the most consistent, negative correlations with FA, ranging from -0.65 for the right ventral striatum to -0.92 for the right cerebral peduncle. Years of boxing was negatively related to the number of words consistently recalled over trials (r = -0.74; p = 0.02), delayed recall (r = -0.83; p = 0.003), and serial RT (r = 0.66; p = 0.05). We conclude that microstructural integrity of white matter tracts is related to declarative memory and response speed in boxers and to the extent of boxing exposure. Implications for chronic traumatic encephalopathy are discussed.

  8. TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow

    OpenAIRE

    Hafner, Danijar; Davidson, James; Vanhoucke, Vincent

    2017-01-01

    We introduce TensorFlow Agents, an efficient infrastructure paradigm for building parallel reinforcement learning algorithms in TensorFlow. We simulate multiple environments in parallel, and group them to perform the neural network computation on a batch rather than individual observations. This allows the TensorFlow execution engine to parallelize computation, without the need for manual synchronization. Environments are stepped in separate Python processes to progress them in parallel witho...

  9. A RENORMALIZATION PROCEDURE FOR TENSOR MODELS AND SCALAR-TENSOR THEORIES OF GRAVITY

    OpenAIRE

    SASAKURA, NAOKI

    2010-01-01

    Tensor models are more-index generalizations of the so-called matrix models, and provide models of quantum gravity with the idea that spaces and general relativity are emergent phenomena. In this paper, a renormalization procedure for the tensor models whose dynamical variable is a totally symmetric real three-tensor is discussed. It is proven that configurations with certain Gaussian forms are the attractors of the three-tensor under the renormalization procedure. Since these Gaussian config...

  10. Diffusion tensor smoothing through weighted Karcher means

    Science.gov (United States)

    Carmichael, Owen; Chen, Jun; Paul, Debashis; Peng, Jie

    2014-01-01

    Diffusion tensor magnetic resonance imaging (MRI) quantifies the spatial distribution of water Diffusion at each voxel on a regular grid of locations in a biological specimen by Diffusion tensors– 3 × 3 positive definite matrices. Removal of noise from DTI is an important problem due to the high scientific relevance of DTI and relatively low signal to noise ratio it provides. Leading approaches to this problem amount to estimation of weighted Karcher means of Diffusion tensors within spatial neighborhoods, under various metrics imposed on the space of tensors. However, it is unclear how the behavior of these estimators varies with the magnitude of DTI sensor noise (the noise resulting from the thermal e!ects of MRI scanning) as well as the geometric structure of the underlying Diffusion tensor neighborhoods. In this paper, we combine theoretical analysis, empirical analysis of simulated DTI data, and empirical analysis of real DTI scans to compare the noise removal performance of three kernel-based DTI smoothers that are based on Euclidean, log-Euclidean, and affine-invariant metrics. The results suggest, contrary to conventional wisdom, that imposing a simplistic Euclidean metric may in fact provide comparable or superior noise removal, especially in relatively unstructured regions and/or in the presence of moderate to high levels of sensor noise. On the contrary, log-Euclidean and affine-invariant metrics may lead to better noise removal in highly structured anatomical regions, especially when the sensor noise is of low magnitude. These findings emphasize the importance of considering the interplay of sensor noise magnitude and tensor field geometric structure when assessing Diffusion tensor smoothing options. They also point to the necessity for continued development of smoothing methods that perform well across a large range of scenarios. PMID:25419264

  11. Diffusion tensor magnetic resonance imaging of the pancreas.

    Directory of Open Access Journals (Sweden)

    Noam Nissan

    Full Text Available To develop a diffusion-tensor-imaging (DTI protocol that is sensitive to the complex diffusion and perfusion properties of the healthy and malignant pancreas tissues.Twenty-eight healthy volunteers and nine patients with pancreatic-ductal-adenocacinoma (PDAC, were scanned at 3T with T2-weighted and DTI sequences. Healthy volunteers were also scanned with multi-b diffusion-weighted-imaging (DWI, whereas a standard clinical protocol complemented the PDAC patients' scans. Image processing at pixel resolution yielded parametric maps of three directional diffusion coefficients λ1, λ2, λ3, apparent diffusion coefficient (ADC, and fractional anisotropy (FA, as well as a λ1-vector map, and a main diffusion-direction map.DTI measurements of healthy pancreatic tissue at b-values 0,500 s/mm² yielded: λ1 = (2.65±0.35×10⁻³, λ2 = (1.87±0.22×10⁻³, λ3 = (1.20±0.18×10⁻³, ADC = (1.91±0.22×10⁻³ (all in mm²/s units and FA = 0.38±0.06. Using b-values of 100,500 s/mm² led to a significant reduction in λ1, λ2, λ3 and ADC (p<.0001 and a significant increase (p<0.0001 in FA. The reduction in the diffusion coefficients suggested a contribution of a fast intra-voxel-incoherent-motion (IVIM component at b≤100 s/mm², which was confirmed by the multi-b DWI results. In PDACs, λ1, λ2, λ3 and ADC in both 0,500 s/mm² and 100,500 s/mm² b-values sets, as well as the reduction in these diffusion coefficients between the two sets, were significantly lower in comparison to the distal normal pancreatic tissue, suggesting higher cellularity and diminution of the fast-IVIM component in the cancer tissue.DTI using two reference b-values 0 and 100 s/mm² enabled characterization of the water diffusion and anisotropy of the healthy pancreas, taking into account a contribution of IVIM. The reduction in the diffusion coefficients of PDAC, as compared to normal pancreatic tissue, and the smaller change in these coefficients in PDAC

  12. Classification of materials for conducting spheroids based on the first order polarization tensor

    Science.gov (United States)

    Khairuddin, TK Ahmad; Mohamad Yunos, N.; Aziz, ZA; Ahmad, T.; Lionheart, WRB

    2017-09-01

    Polarization tensor is an old terminology in mathematics and physics with many recent industrial applications including medical imaging, nondestructive testing and metal detection. In these applications, it is theoretically formulated based on the mathematical modelling either in electrics, electromagnetics or both. Generally, polarization tensor represents the perturbation in the electric or electromagnetic fields due to the presence of conducting objects and hence, it also desribes the objects. Understanding the properties of the polarization tensor is necessary and important in order to apply it. Therefore, in this study, when the conducting object is a spheroid, we show that the polarization tensor is positive-definite if and only if the conductivity of the object is greater than one. In contrast, we also prove that the polarization tensor is negative-definite if and only if the conductivity of the object is between zero and one. These features categorize the conductivity of the spheroid based on in its polarization tensor and can then help to classify the material of the spheroid.

  13. Time integration of tensor trains

    OpenAIRE

    Lubich, Christian; Oseledets, Ivan; Vandereycken, Bart

    2014-01-01

    A robust and efficient time integrator for dynamical tensor approximation in the tensor train or matrix product state format is presented. The method is based on splitting the projector onto the tangent space of the tensor manifold. The algorithm can be used for updating time-dependent tensors in the given data-sparse tensor train / matrix product state format and for computing an approximate solution to high-dimensional tensor differential equations within this data-sparse format. The formul...

  14. Tensor spaces and exterior algebra

    CERN Document Server

    Yokonuma, Takeo

    1992-01-01

    This book explains, as clearly as possible, tensors and such related topics as tensor products of vector spaces, tensor algebras, and exterior algebras. You will appreciate Yokonuma's lucid and methodical treatment of the subject. This book is useful in undergraduate and graduate courses in multilinear algebra. Tensor Spaces and Exterior Algebra begins with basic notions associated with tensors. To facilitate understanding of the definitions, Yokonuma often presents two or more different ways of describing one object. Next, the properties and applications of tensors are developed, including the classical definition of tensors and the description of relative tensors. Also discussed are the algebraic foundations of tensor calculus and applications of exterior algebra to determinants and to geometry. This book closes with an examination of algebraic systems with bilinear multiplication. In particular, Yokonuma discusses the theory of replicas of Chevalley and several properties of Lie algebras deduced from them.

  15. MR neurography of ulnar nerve entrapment at the cubital tunnel: a diffusion tensor imaging study

    International Nuclear Information System (INIS)

    Breitenseher, Julia B.; Berzaczy, Dominik; Nemec, Stefan F.; Weber, Michael; Prayer, Daniela; Kasprian, Gregor; Kranz, Gottfried; Sycha, Thomas; Hold, Alina

    2015-01-01

    MR neurography, diffusion tensor imaging (DTI) and tractography at 3 Tesla were evaluated for the assessment of patients with ulnar neuropathy at the elbow (UNE). Axial T2-weighted and single-shot DTI sequences (16 gradient encoding directions) were acquired, covering the cubital tunnel of 46 patients with clinically and electrodiagnostically confirmed UNE and 20 healthy controls. Cross-sectional area (CSA) was measured at the retrocondylar sulcus and FA and ADC values on each section along the ulnar nerve. Three-dimensional nerve tractography and T2-weighted neurography results were independently assessed by two raters. Patients showed a significant reduction of ulnar nerve FA values at the retrocondylar sulcus (p = 0.002) and the deep flexor fascia (p = 0.005). At tractography, a complete or partial discontinuity of the ulnar nerve was found in 26/40 (65 %) of patients. Assessment of T2 neurography was most sensitive in detecting UNE (sensitivity, 91 %; specificity, 79 %), followed by tractography (88 %/69 %). CSA and FA measurements were less effective in detecting UNE. T2-weighted neurography remains the most sensitive MR technique in the imaging evaluation of clinically manifest UNE. DTI-based neurography at 3 Tesla supports the MR imaging assessment of UNE patients by adding quantitative and 3D imaging data. (orig.)

  16. MR neurography of ulnar nerve entrapment at the cubital tunnel: a diffusion tensor imaging study

    Energy Technology Data Exchange (ETDEWEB)

    Breitenseher, Julia B.; Berzaczy, Dominik; Nemec, Stefan F.; Weber, Michael; Prayer, Daniela; Kasprian, Gregor [Medical University of Vienna, Department of Biomedical Imaging and Image-guided Therapy, Vienna (Austria); Kranz, Gottfried; Sycha, Thomas [Medical University of Vienna, Department of Neurology, Vienna (Austria); Hold, Alina [Medical University of Vienna, Department of Plastic and Reconstructive Surgery, Vienna (Austria)

    2015-07-15

    MR neurography, diffusion tensor imaging (DTI) and tractography at 3 Tesla were evaluated for the assessment of patients with ulnar neuropathy at the elbow (UNE). Axial T2-weighted and single-shot DTI sequences (16 gradient encoding directions) were acquired, covering the cubital tunnel of 46 patients with clinically and electrodiagnostically confirmed UNE and 20 healthy controls. Cross-sectional area (CSA) was measured at the retrocondylar sulcus and FA and ADC values on each section along the ulnar nerve. Three-dimensional nerve tractography and T2-weighted neurography results were independently assessed by two raters. Patients showed a significant reduction of ulnar nerve FA values at the retrocondylar sulcus (p = 0.002) and the deep flexor fascia (p = 0.005). At tractography, a complete or partial discontinuity of the ulnar nerve was found in 26/40 (65 %) of patients. Assessment of T2 neurography was most sensitive in detecting UNE (sensitivity, 91 %; specificity, 79 %), followed by tractography (88 %/69 %). CSA and FA measurements were less effective in detecting UNE. T2-weighted neurography remains the most sensitive MR technique in the imaging evaluation of clinically manifest UNE. DTI-based neurography at 3 Tesla supports the MR imaging assessment of UNE patients by adding quantitative and 3D imaging data. (orig.)

  17. Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan; Spell, Gregory; Carin, Lawrence

    2017-04-20

    We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rank impacts both overcompleteness and sparsity.

  18. Low Multilinear Rank Approximation of Tensors and Application in Missing Traffic Data

    Directory of Open Access Journals (Sweden)

    Huachun Tan

    2014-02-01

    Full Text Available The problem of missing data in multiway arrays (i.e., tensors is common in many fields such as bibliographic data analysis, image processing, and computer vision. We consider the problems of approximating a tensor by another tensor with low multilinear rank in the presence of missing data and possibly reconstructing it (i.e., tensor completion. In this paper, we propose a weighted Tucker model which models only the known elements for capturing the latent structure of the data and reconstructing the missing elements. To treat the nonuniqueness of the proposed weighted Tucker model, a novel gradient descent algorithm based on a Grassmann manifold, which is termed Tucker weighted optimization (Tucker-Wopt, is proposed for guaranteeing the global convergence to a local minimum of the problem. Based on extensive experiments, Tucker-Wopt is shown to successfully reconstruct tensors with noise and up to 95% missing data. Furthermore, the experiments on traffic flow volume data demonstrate the usefulness of our algorithm on real-world application.

  19. Diffusion Tensor Imaging Tractography in Pure Neuritic Leprosy: First Experience Report and Review of the Literature

    Directory of Open Access Journals (Sweden)

    Michele R. Colonna

    2016-01-01

    Full Text Available Five years after both right ulnar and median nerve decompression for paraesthesias and palsy, a patient, coming from Nigeria but living in Italy, came to our unit claiming to have persistent pain and combined median and ulnar palsy. Under suspicion of leprosy, skin and left sural nerve biopsy were performed. Skin tests were negative, but Schwann cells resulted as positive for acid-fast bacilli (AFB, leading to the diagnosis of Pure Neuritic Leprosy (PNL. The patient was given PB multidrug therapy and recovered from pain in two months. After nine months both High Resolution Ultrasonography (HRUS and Magnetic Resonance Imaging (MRI were performed, revealing thickening of the nerves. Since demyelination is common in PNL, the Authors started to use Diffusion Tensor Imaging Tractography (DTIT to get better morphological and functional data about myelination than does the traditional imaging. DTIT proved successful in showing myelin discontinuity, reorganization, and myelination, and the Authors suggest that it can give more information about the evolution of the disease, as well as further indications for surgery (nerve decompression, nerve transfers, and babysitting for distal effector protection, and should be added to traditional imaging tools in leprosy.

  20. Correction for Eddy Current-Induced Echo-Shifting Effect in Partial-Fourier Diffusion Tensor Imaging.

    Science.gov (United States)

    Truong, Trong-Kha; Song, Allen W; Chen, Nan-Kuei

    2015-01-01

    In most diffusion tensor imaging (DTI) studies, images are acquired with either a partial-Fourier or a parallel partial-Fourier echo-planar imaging (EPI) sequence, in order to shorten the echo time and increase the signal-to-noise ratio (SNR). However, eddy currents induced by the diffusion-sensitizing gradients can often lead to a shift of the echo in k-space, resulting in three distinct types of artifacts in partial-Fourier DTI. Here, we present an improved DTI acquisition and reconstruction scheme, capable of generating high-quality and high-SNR DTI data without eddy current-induced artifacts. This new scheme consists of three components, respectively, addressing the three distinct types of artifacts. First, a k-space energy-anchored DTI sequence is designed to recover eddy current-induced signal loss (i.e., Type 1 artifact). Second, a multischeme partial-Fourier reconstruction is used to eliminate artificial signal elevation (i.e., Type 2 artifact) associated with the conventional partial-Fourier reconstruction. Third, a signal intensity correction is applied to remove artificial signal modulations due to eddy current-induced erroneous T2(∗) -weighting (i.e., Type 3 artifact). These systematic improvements will greatly increase the consistency and accuracy of DTI measurements, expanding the utility of DTI in translational applications where quantitative robustness is much needed.

  1. Long-Term Follow-up of a Patient with Traumatic Brain Injury Using Diffusion Tensor Imaging

    International Nuclear Information System (INIS)

    Skoglund, T.S.; Nilsson, D.; Ljungberg, M.; Joensson, L.; Rydenhag, B.

    2008-01-01

    This case report describes a patient who sustained severe head trauma with diffuse axonal injury (DAI). Examination with magnetic resonance diffusion tensor imaging (MR-DTI), 6 days post-injury, showed a severe reduction in fractional anisotropy (FA) in the rostral pons containing the corticospinal tract, which correlated to the patient's severe hemiparesis. By 18 months post-accident, the patient had recovered completely and conventional MRI showed no pathology. However, although her FA values in the rostral pons had increased, they were still not normalized. It seems that a complete normalization of the FA values is not required to achieve clinical recovery, and that MR-DTI seems to be more sensitive to DAI compared to conventional MRI

  2. Long-Term Follow-up of a Patient with Traumatic Brain Injury Using Diffusion Tensor Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Skoglund, T.S.; Nilsson, D.; Ljungberg, M.; Joensson, L.; Rydenhag, B. (Dept. of Neurosurgery, Dept. of Medical Physics and Biomedical Engineering, and Dept. of Radiology, Sahlgrenska Univ. Hospital, Goeteborg (Sweden))

    2008-02-15

    This case report describes a patient who sustained severe head trauma with diffuse axonal injury (DAI). Examination with magnetic resonance diffusion tensor imaging (MR-DTI), 6 days post-injury, showed a severe reduction in fractional anisotropy (FA) in the rostral pons containing the corticospinal tract, which correlated to the patient's severe hemiparesis. By 18 months post-accident, the patient had recovered completely and conventional MRI showed no pathology. However, although her FA values in the rostral pons had increased, they were still not normalized. It seems that a complete normalization of the FA values is not required to achieve clinical recovery, and that MR-DTI seems to be more sensitive to DAI compared to conventional MRI

  3. Gogny interactions with tensor terms

    Energy Technology Data Exchange (ETDEWEB)

    Anguiano, M.; Lallena, A.M.; Bernard, R.N. [Universidad de Granada, Departamento de Fisica Atomica, Molecular y Nuclear, Granada (Spain); Co' , G. [INFN, Lecce (Italy); De Donno, V. [Universita del Salento, Dipartimento di Matematica e Fisica ' ' E. De Giorgi' ' , Lecce (Italy); Grasso, M. [Universite Paris-Sud, Institut de Physique Nucleaire, IN2P3-CNRS, Orsay (France)

    2016-07-15

    We present a perturbative approach to include tensor terms in the Gogny interaction. We do not change the values of the usual parameterisations, with the only exception of the spin-orbit term, and we add tensor terms whose only free parameters are the strengths of the interactions. We identify observables sensitive to the presence of the tensor force in Hartree-Fock, Hartree-Fock-Bogoliubov and random phase approximation calculations. We show the need of including two tensor contributions, at least: a pure tensor term and a tensor-isospin term. We show results relevant for the inclusion of the tensor term for single-particle energies, charge-conserving magnetic excitations and Gamow-Teller excitations. (orig.)

  4. 3 T magnetic resonance diffusion tensor imaging and fibre tracking in cervical myelopathy

    International Nuclear Information System (INIS)

    Xiangshui, M.; Xiangjun, C.; Xiaoming, Z.; Qingshi, Z.; Yi, C.; Chuanqiang, Q.; Xiangxing, M.; Chuanfu, L.; Jinwen, H.

    2010-01-01

    Aim: To analyse the characterization of diffusion tensor imaging (DTI) with 3 T magnetic resonance imaging (MRI) in cervical myelopathy. Methods: A total of 21 healthy controls and 84 patients with cervical myelopathy underwent T2-weighted imaging and DTI. The patients were divided into four groups based on the degree of cord compression and MRI signal intensity of the compressed cord as seen on T2-weighted images. The values of apparent diffusion coefficient (ADC), fractional anisotropy (FA), and eigenvalues (λ i ) were analysed, and fibre tracking (FT) was performed. Results: For healthy controls, the mean values from the DTI of the cervical spinal cord were ADC = 0.784 ± 0.083 x 10 -3 mm 2 /s, FA = 0.721 ± 0.027, λ 1 , λ 2 , and λ 3 = 1.509 ± 0.145 x 10 -3 , 0.416 ± 0.094 x 10 -3 , and 0.411 ± 0.102 x 10 -3 mm 2 /s, respectively. Only values for λ 2 and λ 3 differed significantly between the control and A groups (p 2 and λ 3 of group A were 0.516 ± 0.105 x 10 -3 and 0.525 ± 0.129 x 10 -3 mm 2 /s, respectively. ADC, FA, λ 1 , λ 2 and λ 3 differed significantly between the control and B, C, D groups (p i obtained with DTI could assess subtle structural damage and changes of anisotropy in the cord of cervical myelopathy. Fibre tracking was useful in verifying changes in the compressed cord.

  5. Tensor structure for Nori motives

    OpenAIRE

    Barbieri-Viale, Luca; Huber, Annette; Prest, Mike

    2018-01-01

    We construct a tensor product on Freyd's universal abelian category attached to an additive tensor category or a tensor quiver and establish a universal property. This is used to give an alternative construction for the tensor product on Nori motives.

  6. Tensor SOM and tensor GTM: Nonlinear tensor analysis by topographic mappings.

    Science.gov (United States)

    Iwasaki, Tohru; Furukawa, Tetsuo

    2016-05-01

    In this paper, we propose nonlinear tensor analysis methods: the tensor self-organizing map (TSOM) and the tensor generative topographic mapping (TGTM). TSOM is a straightforward extension of the self-organizing map from high-dimensional data to tensorial data, and TGTM is an extension of the generative topographic map, which provides a theoretical background for TSOM using a probabilistic generative model. These methods are useful tools for analyzing and visualizing tensorial data, especially multimodal relational data. For given n-mode relational data, TSOM and TGTM can simultaneously organize a set of n-topographic maps. Furthermore, they can be used to explore the tensorial data space by interactively visualizing the relationships between modes. We present the TSOM algorithm and a theoretical description from the viewpoint of TGTM. Various TSOM variations and visualization techniques are also described, along with some applications to real relational datasets. Additionally, we attempt to build a comprehensive description of the TSOM family by adapting various data structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Prediction of motor outcomes and activities of daily living function using diffusion tensor tractography in acute hemiparetic stroke patients.

    Science.gov (United States)

    Imura, Takeshi; Nagasawa, Yuki; Inagawa, Tetsuji; Imada, Naoki; Izumi, Hiroaki; Emoto, Katsuya; Tani, Itaru; Yamasaki, Hiroyuki; Ota, Yuichiro; Oki, Shuichi; Maeda, Tadanori; Araki, Osamu

    2015-05-01

    [Purpose] The efficacy of diffusion tensor imaging in the prediction of motor outcomes and activities of daily living function remains unclear. We evaluated the most appropriate diffusion tensor parameters and methodology to determine whether the region of interest- or tractography-based method was more useful for predicting motor outcomes and activities of daily living function in stroke patients. [Subjects and Methods] Diffusion tensor imaging data within 10 days after stroke onset were collected and analyzed for 25 patients. The corticospinal tract was analyzed. Fractional anisotropy, number of fibers, and apparent diffusion coefficient were used as diffusion tensor parameters. Motor outcomes and activities of daily living function were evaluated on the same day as diffusion tensor imaging and at 1 month post-onset. [Results] The fractional anisotropy value of the affected corticospinal tract significantly correlated with the motor outcome and activities of daily living function within 10 days post-onset and at 1 month post-onset. Tthere were no significant correlations between other diffusion tensor parameters and motor outcomes or activities of daily living function. [Conclusion] The fractional anisotropy value of the affected corticospinal tract obtained using the tractography-based method was useful for predicting motor outcomes and activities of daily living function in stroke patients.

  8. MR-NTD: Manifold Regularization Nonnegative Tucker Decomposition for Tensor Data Dimension Reduction and Representation.

    Science.gov (United States)

    Li, Xutao; Ng, Michael K; Cong, Gao; Ye, Yunming; Wu, Qingyao

    2017-08-01

    With the advancement of data acquisition techniques, tensor (multidimensional data) objects are increasingly accumulated and generated, for example, multichannel electroencephalographies, multiview images, and videos. In these applications, the tensor objects are usually nonnegative, since the physical signals are recorded. As the dimensionality of tensor objects is often very high, a dimension reduction technique becomes an important research topic of tensor data. From the perspective of geometry, high-dimensional objects often reside in a low-dimensional submanifold of the ambient space. In this paper, we propose a new approach to perform the dimension reduction for nonnegative tensor objects. Our idea is to use nonnegative Tucker decomposition (NTD) to obtain a set of core tensors of smaller sizes by finding a common set of projection matrices for tensor objects. To preserve geometric information in tensor data, we employ a manifold regularization term for the core tensors constructed in the Tucker decomposition. An algorithm called manifold regularization NTD (MR-NTD) is developed to solve the common projection matrices and core tensors in an alternating least squares manner. The convergence of the proposed algorithm is shown, and the computational complexity of the proposed method scales linearly with respect to the number of tensor objects and the size of the tensor objects, respectively. These theoretical results show that the proposed algorithm can be efficient. Extensive experimental results have been provided to further demonstrate the effectiveness and efficiency of the proposed MR-NTD algorithm.

  9. Physical and Geometric Interpretations of the Riemann Tensor, Ricci Tensor, and Scalar Curvature

    OpenAIRE

    Loveridge, Lee C.

    2004-01-01

    Various interpretations of the Riemann Curvature Tensor, Ricci Tensor, and Scalar Curvature are described. Also, the physical meanings of the Einstein Tensor and Einstein's Equations are discussed. Finally a derivation of Newtonian Gravity from Einstein's Equations is given.

  10. Development of the Tensoral Computer Language

    Science.gov (United States)

    Ferziger, Joel; Dresselhaus, Eliot

    1996-01-01

    The research scientist or engineer wishing to perform large scale simulations or to extract useful information from existing databases is required to have expertise in the details of the particular database, the numerical methods and the computer architecture to be used. This poses a significant practical barrier to the use of simulation data. The goal of this research was to develop a high-level computer language called Tensoral, designed to remove this barrier. The Tensoral language provides a framework in which efficient generic data manipulations can be easily coded and implemented. First of all, Tensoral is general. The fundamental objects in Tensoral represent tensor fields and the operators that act on them. The numerical implementation of these tensors and operators is completely and flexibly programmable. New mathematical constructs and operators can be easily added to the Tensoral system. Tensoral is compatible with existing languages. Tensoral tensor operations co-exist in a natural way with a host language, which may be any sufficiently powerful computer language such as Fortran, C, or Vectoral. Tensoral is very-high-level. Tensor operations in Tensoral typically act on entire databases (i.e., arrays) at one time and may, therefore, correspond to many lines of code in a conventional language. Tensoral is efficient. Tensoral is a compiled language. Database manipulations are simplified optimized and scheduled by the compiler eventually resulting in efficient machine code to implement them.

  11. Killing-Yano tensors and Nambu mechanics

    International Nuclear Information System (INIS)

    Baleanu, D.

    1998-01-01

    Killing-Yano tensors were introduced in 1952 by Kentaro-Yano from mathematical point of view. The physical interpretation of Killing-Yano tensors of rank higher than two was unclear. We found that all Killing-Yano tensors η i 1 i 2 . .. i n with covariant derivative zero are Nambu tensors. We found that in the case of flat space case all Killing-Yano tensors are Nambu tensors. In the case of Taub-NUT and Kerr-Newmann metric Killing-Yano tensors of order two generate Nambu tensors of rank 3

  12. Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer's disease cases.

    Science.gov (United States)

    Taoka, Toshiaki; Masutani, Yoshitaka; Kawai, Hisashi; Nakane, Toshiki; Matsuoka, Kiwamu; Yasuno, Fumihiko; Kishimoto, Toshifumi; Naganawa, Shinji

    2017-04-01

    The activity of the glymphatic system is impaired in animal models of Alzheimer's disease (AD). We evaluated the activity of the human glymphatic system in cases of AD with a diffusion-based technique called diffusion tensor image analysis along the perivascular space (DTI-ALPS). Diffusion tensor images were acquired to calculate diffusivities in the x, y, and z axes of the plane of the lateral ventricle body in 31 patients. We evaluated the diffusivity along the perivascular spaces as well as projection fibers and association fibers separately, to acquire an index for diffusivity along the perivascular space (ALPS-index) and correlated them with the mini mental state examinations (MMSE) score. We found a significant negative correlation between diffusivity along the projection fibers and association fibers. We also observed a significant positive correlation between diffusivity along perivascular spaces shown as ALPS-index and the MMSE score, indicating lower water diffusivity along the perivascular space in relation to AD severity. Activity of the glymphatic system may be evaluated with diffusion images. Lower diffusivity along the perivascular space on DTI-APLS seems to reflect impairment of the glymphatic system. This method may be useful for evaluating the activity of the glymphatic system.

  13. Microsurgical anatomy of the ventral callosal radiations: new destination, correlations with diffusion tensor imaging fiber-tracking, and clinical relevance.

    Science.gov (United States)

    Peltier, Johann; Verclytte, Sébastien; Delmaire, Christine; Deramond, Hervé; Pruvo, Jean-Pierre; Le Gars, Daniel; Godefroy, Olivier

    2010-03-01

    In the current literature, there is a lack of a detailed map of the origin, course, and connections of the ventral callosal radiations of the human brain. The authors used an older dissection technique based on a freezing process as well as diffusion tensor imaging to investigate this area of the human brain. The authors demonstrated interconnections between areas 11, 12, and 25 for the callosal radiations of the trunk and rostrum of the corpus callosum; between areas 9, 10, and 32 for the genu; and between areas 6, 8, and 9 for the ventral third of the body. The authors identified new ventral callosal connections crossing the rostrum between both temporal poles and coursing within the temporal stem, and they named these connections the "callosal radiations of Peltier." They found that the breadth of the callosal radiations slightly increases along their course from the rostrum to the first third of the body of the corpus callosum. The fiber dissection and diffusion tensor imaging techniques are complementary not only in their application to the study of the commissural system in the human brain, but also in their practical use for diagnosis and surgical planning. Further investigations, neurocognitive tests, and other contributions will permit elucidation of the functional relevance of the newly identified callosal radiations in patients with disease involving the ventral corpus callosum.

  14. Using tensor-based morphometry to detect structural brain abnormalities in rats with adolescent intermittent alcohol exposure

    Science.gov (United States)

    Paniagua, Beatriz; Ehlers, Cindy; Crews, Fulton; Budin, Francois; Larson, Garrett; Styner, Martin; Oguz, Ipek

    2011-03-01

    Understanding the effects of adolescent binge drinking that persist into adulthood is a crucial public health issue. Adolescent intermittent ethanol exposure (AIE) is an animal model that can be used to investigate these effects in rodents. In this work, we investigate the application of a particular image analysis technique, tensor-based morphometry, for detecting anatomical differences between AIE and control rats using Diffusion Tensor Imaging (DTI). Deformation field analysis is a popular method for detecting volumetric changes analyzing Jacobian determinants calculated on deformation fields. Recent studies showed that computing deformation field metrics on the full deformation tensor, often referred to as tensor-based morphometry (TBM), increases the sensitivity to anatomical differences. In this paper we conduct a comprehensive TBM study for precisely locating differences between control and AIE rats. Using a DTI RARE sequence designed for minimal geometric distortion, 12-directional images were acquired postmortem for control and AIE rats (n=9). After preprocessing, average images for the two groups were constructed using an unbiased atlas building approach. We non-rigidly register the two atlases using Large Deformation Diffeomorphic Metric Mapping, and analyze the resulting deformation field using TBM. In particular, we evaluate the tensor determinant, geodesic anisotropy, and deformation direction vector (DDV) on the deformation field to detect structural differences. This yields data on the local amount of growth, shrinkage and the directionality of deformation between the groups. We show that TBM can thus be used to measure group morphological differences between rat populations, demonstrating the potential of the proposed framework.

  15. Diffusion tensor imaging for nerve fiber bundles in the brain stem and spinocerebellar degeneration

    International Nuclear Information System (INIS)

    Honma, Tsuguo

    2009-01-01

    Diffusion tensor imaging (DTI) can create an image of the anisotropic nature of diffusion and express it quantitatively. Nerve fibers have a large anisotropic diffusion, and it is possible to obtain images of the nerve fiber bundle. The purpose of this study is to observe the nerve fiber bundles in the brain stem using DTI and study its potential for diagnosing the type of spinocerebellar degeneration (SCD). Fractional anisotropy (FA) maps and 3D-tractography images were obtained for 41 subjects with no brain stem abnormalities. We created an apparent diffusion coefficient (ADC) map and an FA map using DTI for 16 subjects in the disease group (11 with hereditary SCD and 5 with non-hereditary SCD) and 25 in the control group. The diffusion value of the pons and middle cerebellar peduncle was measured using ADC, and the degree of anisotropic diffusion was measured using FA. The pyramidal tract, superior cerebellar peduncle, and inferior cerebellar peduncle were clearly demonstrated for all cases. ADC for the middle cerebellar peduncle in spinocerebellar ataxin (SCA)1 was significantly higher, similar to that for the pons in dentatorubro-pallidoluysian atrophy (DRPLA). In MSA-C, ADC for both the pons and middle cerebellar peduncle was significantly elevated and FA was significantly decreased. There were no significant changes in SCA3. We could observe the nerve fiber bundles in the brain stem using DTI. FA and ADC measurements with DTI can aid in diagnosing the type of SCD. (author)

  16. Categorical Tensor Network States

    Directory of Open Access Journals (Sweden)

    Jacob D. Biamonte

    2011-12-01

    Full Text Available We examine the use of string diagrams and the mathematics of category theory in the description of quantum states by tensor networks. This approach lead to a unification of several ideas, as well as several results and methods that have not previously appeared in either side of the literature. Our approach enabled the development of a tensor network framework allowing a solution to the quantum decomposition problem which has several appealing features. Specifically, given an n-body quantum state |ψ〉, we present a new and general method to factor |ψ〉 into a tensor network of clearly defined building blocks. We use the solution to expose a previously unknown and large class of quantum states which we prove can be sampled efficiently and exactly. This general framework of categorical tensor network states, where a combination of generic and algebraically defined tensors appear, enhances the theory of tensor network states.

  17. Diffusion tensor imaging in patients with obstetric antiphospholipid syndrome without neuropsychiatric symptoms

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Fabricio R. [University Hospital Center of Nimes and Research Team EA 2415, Department of Radiology (France); Macri, Francesco; Beregi, Jean-Paul [University Hospital Center of Nimes and Research Team EA 2415, Department of Radiology (France); Montpellier University, Faculty of Medicine, Montpellier (France); Jackowski, Marcel P. [University of Sao Paulo, Department of Computer Science, Institute of Mathematics and Statistics, Sao Paulo (Brazil); Kostis, William J. [Harvard Medical School, Massachusetts General Hospital, Boston, MA (United States); Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA (United States); Gris, Jean-Christophe [Montpellier University, Faculty of Medicine, Montpellier (France); University Hospital Center of Nimes, Department and Laboratory of Hematology (France); Mekkaoui, Choukri [University Hospital Center of Nimes and Research Team EA 2415, Department of Radiology (France); Montpellier University, Faculty of Medicine, Montpellier (France); Harvard Medical School, Massachusetts General Hospital, Boston, MA (United States); Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA (United States)

    2016-04-15

    To evaluate white matter (WM) integrity in neurologically asymptomatic antiphospholipid syndrome (APS) using diffusion tensor imaging (DTI) in women with no thrombotic history but with pregnancy loss. Imaging was performed with a 3 T scanner using structural MRI (T1-weighted, fluid attenuation inversion recovery [FLAIR]) and DTI sequences in 66 women with APS and a control group of 17 women. Women with APS were further categorized as positive for lupus anticoagulant (LA) and/or aβ2GPI-G antibodies (LA/aβ2GPI-G-positive, N = 29) or negative (LA/aβ2GPI-G-negative, N = 37) for both. Tract-based spatial statistics of standard DTI-based indices were compared among groups. Women with APS had significantly lower fractional anisotropy (p < 0.05) associated with higher mean diffusivity and radial diffusivity compared to the control group. There was a stronger association of abnormal DTI features among women positive for LA and/or aβ2GPI-IgG antibodies than those who were negative. DTI appears sensitive to subtle WM changes in women with APS with no thrombotic history but with pregnancy loss, compatible with alterations in axonal structure and in the myelin sheath. The preferential association of abnormal DTI features with the two most pathogenic aPLAbs reinforces the pathophysiological relevance of our findings. (orig.)

  18. Diffusion tensor imaging in patients with obstetric antiphospholipid syndrome without neuropsychiatric symptoms

    International Nuclear Information System (INIS)

    Pereira, Fabricio R.; Macri, Francesco; Beregi, Jean-Paul; Jackowski, Marcel P.; Kostis, William J.; Gris, Jean-Christophe; Mekkaoui, Choukri

    2016-01-01

    To evaluate white matter (WM) integrity in neurologically asymptomatic antiphospholipid syndrome (APS) using diffusion tensor imaging (DTI) in women with no thrombotic history but with pregnancy loss. Imaging was performed with a 3 T scanner using structural MRI (T1-weighted, fluid attenuation inversion recovery [FLAIR]) and DTI sequences in 66 women with APS and a control group of 17 women. Women with APS were further categorized as positive for lupus anticoagulant (LA) and/or aβ2GPI-G antibodies (LA/aβ2GPI-G-positive, N = 29) or negative (LA/aβ2GPI-G-negative, N = 37) for both. Tract-based spatial statistics of standard DTI-based indices were compared among groups. Women with APS had significantly lower fractional anisotropy (p < 0.05) associated with higher mean diffusivity and radial diffusivity compared to the control group. There was a stronger association of abnormal DTI features among women positive for LA and/or aβ2GPI-IgG antibodies than those who were negative. DTI appears sensitive to subtle WM changes in women with APS with no thrombotic history but with pregnancy loss, compatible with alterations in axonal structure and in the myelin sheath. The preferential association of abnormal DTI features with the two most pathogenic aPLAbs reinforces the pathophysiological relevance of our findings. (orig.)

  19. Tensor Permutation Matrices in Finite Dimensions

    OpenAIRE

    Christian, Rakotonirina

    2005-01-01

    We have generalised the properties with the tensor product, of one 4x4 matrix which is a permutation matrix, and we call a tensor commutation matrix. Tensor commutation matrices can be constructed with or without calculus. A formula allows us to construct a tensor permutation matrix, which is a generalisation of tensor commutation matrix, has been established. The expression of an element of a tensor commutation matrix has been generalised in the case of any element of a tensor permutation ma...

  20. Identification of Stria Medullaris Fibers in the Massa Intermedia Using Diffusion Tensor Imaging.

    Science.gov (United States)

    Kochanski, Ryan B; Dawe, Robert; Kocak, Mehmet; Sani, Sepehr

    2018-04-01

    The massa intermedia (MI) or interthalamic adhesion is an inconsistent band spanning between bilateral medial thalami that is absent in up to 20%-30% of individuals. Little is known of its significance, especially in regard to functional pathways. Probabilistic diffusion tensor imaging (DTI) has recently been used to seed the lateral habenula and define its afferent white matter pathway, the stria medullaris thalami (SM). We sought to determine whether the MI serves as a conduit for crossing of limbic fibers such as the SM. Probabilistic DTI was performed on 10 subjects who had presence of a MI as visualized on magnetic resonance imaging. Tractography was also performed on 2 subjects without MI. Manual identification of the lateral habenula on axial T1-weighted magnetic resonance imaging was used for the initial seed region for tractography. In all subjects, the SM was reliably visualized. In 7 of the 10 subjects with MI, there was evidence of SM fibers that crossed to the ipsilateral hemisphere. Three subjects with small diameter MI did not have tractographic evidence of crossing SM fibers. Of the 7 subjects with crossing SM fibers within the MI, 5 showed predilection toward the right orbitofrontal cortex from both the left and right seed regions. Probabilistic DTI provides evidence of SM fibers within the MI. Given its anatomic location as a bridging pathway between thalami, further studies are necessary to assess its role within the limbic functional network. Copyright © 2018 Elsevier Inc. All rights reserved.

  1. The geomagnetic field gradient tensor

    DEFF Research Database (Denmark)

    Kotsiaros, Stavros; Olsen, Nils

    2012-01-01

    We develop the general mathematical basis for space magnetic gradiometry in spherical coordinates. The magnetic gradient tensor is a second rank tensor consisting of 3 × 3 = 9 spatial derivatives. Since the geomagnetic field vector B is always solenoidal (∇ · B = 0) there are only eight independent...... tensor elements. Furthermore, in current free regions the magnetic gradient tensor becomes symmetric, further reducing the number of independent elements to five. In that case B is a Laplacian potential field and the gradient tensor can be expressed in series of spherical harmonics. We present properties...... of the magnetic gradient tensor and provide explicit expressions of its elements in terms of spherical harmonics. Finally we discuss the benefit of using gradient measurements for exploring the Earth’s magnetic field from space, in particular the advantage of the various tensor elements for a better determination...

  2. Algebraic classification of the Weyl tensor in higher dimensions based on its 'superenergy' tensor

    International Nuclear Information System (INIS)

    Senovilla, Jose M M

    2010-01-01

    The algebraic classification of the Weyl tensor in the arbitrary dimension n is recovered by means of the principal directions of its 'superenergy' tensor. This point of view can be helpful in order to compute the Weyl aligned null directions explicitly, and permits one to obtain the algebraic type of the Weyl tensor by computing the principal eigenvalue of rank-2 symmetric future tensors. The algebraic types compatible with states of intrinsic gravitational radiation can then be explored. The underlying ideas are general, so that a classification of arbitrary tensors in the general dimension can be achieved. (fast track communication)

  3. Analysis of the human brain in primary progressive multiple sclerosis with mapping of the spatial distributions using H-1 MR spectroscopy and diffusion tensor imaging

    NARCIS (Netherlands)

    Sijens, PE; Irwan, R; Potze, JH; Mostert, JP; De Keyser, J; Oudkerk, M

    Primary progressive multiple sclerosis (ppMS; n=4) patients and controls (n=4) were examined by 1H magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) in order to map choline (Cho), creatine and N-acetylaspartate (NAA), the fractional anisotropy (FA) and the apparent diffusion

  4. Symmetric Tensor Decomposition

    DEFF Research Database (Denmark)

    Brachat, Jerome; Comon, Pierre; Mourrain, Bernard

    2010-01-01

    We present an algorithm for decomposing a symmetric tensor, of dimension n and order d, as a sum of rank-1 symmetric tensors, extending the algorithm of Sylvester devised in 1886 for binary forms. We recall the correspondence between the decomposition of a homogeneous polynomial in n variables...... of polynomial equations of small degree in non-generic cases. We propose a new algorithm for symmetric tensor decomposition, based on this characterization and on linear algebra computations with Hankel matrices. The impact of this contribution is two-fold. First it permits an efficient computation...... of the decomposition of any tensor of sub-generic rank, as opposed to widely used iterative algorithms with unproved global convergence (e.g. Alternate Least Squares or gradient descents). Second, it gives tools for understanding uniqueness conditions and for detecting the rank....

  5. Bound-Preserving Reconstruction of Tensor Quantities for Remap in ALE Fluid Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Klima, Matej [Czech Technical Univ. in Prague, Praha (Czech Republic); Kucharik, MIlan [Czech Technical Univ. in Prague, Praha (Czech Republic); Shashkov, Mikhail Jurievich [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Velechovsky, Jan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-01-06

    We analyze several new and existing approaches for limiting tensor quantities in the context of deviatoric stress remapping in an ALE numerical simulation of elastic flow. Remapping and limiting of the tensor component-by-component is shown to violate radial symmetry of derived variables such as elastic energy or force. Therefore, we have extended the symmetry-preserving Vector Image Polygon algorithm, originally designed for limiting vector variables. This limiter constrains the vector (in our case a vector of independent tensor components) within the convex hull formed by the vectors from surrounding cells – an equivalent of the discrete maximum principle in scalar variables. We compare this method with a limiter designed specifically for deviatoric stress limiting which aims to constrain the J2 invariant that is proportional to the specific elastic energy and scale the tensor accordingly. We also propose a method which involves remapping and limiting the J2 invariant independently using known scalar techniques. The deviatoric stress tensor is then scaled to match this remapped invariant, which guarantees conservation in terms of elastic energy.

  6. Diffusion tensor imaging and tractography for assessment of renal allograft dysfunction - initial results

    Energy Technology Data Exchange (ETDEWEB)

    Hueper, Katja; Gutberlet, M.; Rodt, T.; Wacker, F.; Galanski, M.; Hartung, D. [Institute for Diagnostic and Interventional Radiology, Hannover Medical School - Germany, Hannover (Germany); Gwinner, W. [Clinic for Nephrology, Hannover Medical School - Germany, Hannover (Germany); Lehner, F. [Clinic for General, Abdominal and Transplant Surgery, Hannover Medical School - Germany, Hannover (Germany)

    2011-11-15

    To evaluate MR diffusion tensor imaging (DTI) as non-invasive diagnostic tool for detection of acute and chronic allograft dysfunction and changes of organ microstructure. 15 kidney transplanted patients with allograft dysfunction and 14 healthy volunteers were examined using a fat-saturated echo-planar DTI-sequence at 1.5 T (6 diffusion directions, b = 0, 600 s/mm{sup 2}). Mean apparent diffusion coefficient (ADC) and mean fractional anisotropy (FA) were calculated separately for the cortex and for the medulla and compared between healthy and transplanted kidneys. Furthermore, the correlation between diffusion parameters and estimated GFR was determined. The ADC in the cortex and in the medulla were lower in transplanted than in healthy kidneys (p < 0.01). Differences were more distinct for FA, especially in the renal medulla, with a significant reduction in allografts (p < 0.001). Furthermore, in transplanted patients a correlation between mean FA in the medulla and estimated GFR was observed (r = 0.72, p < 0.01). Tractography visualized changes in renal microstructure in patients with impaired allograft function. Changes in allograft function and microstructure can be detected and quantified using DTI. However, to prove the value of DTI for standard clinical application especially correlation of imaging findings and biopsy results is necessary. (orig.)

  7. Stereoscopic Visualization of Diffusion Tensor Imaging Data: A Comparative Survey of Visualization Techniques

    International Nuclear Information System (INIS)

    Raslan, O.; Debnam, J.M.; Ketonen, L.; Kumar, A.J.; Schellingerhout, D.; Wang, J.

    2013-01-01

    Diffusion tensor imaging (DTI) data has traditionally been displayed as a gray scale functional anisotropy map (GSFM) or color coded orientation map (CCOM). These methods use black and white or color with intensity values to map the complex multidimensional DTI data to a two-dimensional image. Alternative visualization techniques, such as V m ax maps utilize enhanced graphical representation of the principal eigenvector by means of a headless arrow on regular non stereoscopic (VM) or stereoscopic display (VMS). A survey of clinical utility of patients with intracranial neoplasms was carried out by 8 neuro radiologists using traditional and nontraditional methods of DTI display. Pairwise comparison studies of 5 intracranial neoplasms were performed with a structured questionnaire comparing GSFM, CCOM, VM, and VMS. Six of 8 neuro radiologists favored V m ax maps over traditional methods of display (GSFM and CCOM). When comparing the stereoscopic (VMS) and the non-stereoscopic (VM) modes, 4 favored VMS, 2 favored VM, and 2 had no preference. In conclusion, processing and visualizing DTI data stereoscopically is technically feasible. An initial survey of users indicated that V m ax based display methodology with or without stereoscopic visualization seems to be preferred over traditional methods to display DTI data.

  8. Value of Diffusion Tensor Imaging of Prostate Cancer: Comparison with Systemic Prostate Biopsy

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Seong Kuk; Kim, Dong Won; Ha, Dong Ho; Kwon, Hee Jin; Kang, Myong Jin; Choi, Sun Seob; Nam, Kyung Jin; Kim, Jung Il [Dong-A University, Medical Center, Busan (Korea, Republic of)

    2011-02-15

    This study was performed to evaluate the usefulness of diffusion tensor imaging (DTI) and to correlate systemic twelve biopsy in prostate cancer. Thirty-one patients with suspected prostate cancer underwent MR imaging. DTI was performed prior to a prostate biopsy. We prospectively calculated the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) value in each corresponding biopsy site. Twenty-three of 31 patients had histopathologically proven adenocarcinoma. Among the 276 biopsy cores of 23 patients with prostate cancer, 109 cores showed positive results (39%). The ADC and FA value of positive cores were 1.31 {+-} 0.34x10-3 mm2/s and 0.68 {+-} 0.07, and those of the negative cores were 1.74 {+-} 0.45x10-3 mm2/s and 0.54 {+-} 0.09, respectively. Eight patients without carcinoma showed an ADC value of 1.83 {+-} 0.26x10-3 mm2/s and an FA value of 0.47 {+-} 0.07. The ADC and FA value of positive cores were significantly lower and higher than those of negative cores and cancer-free patients, respectively (p < 0.05). The ADC and FA values using DTI may provide useful diagnostic information in the differentiation of cancerous tissues, although there is overlap in some cases

  9. Evaluation of the female pelvic floor in pelvic organ prolapse using 3.0-Tesla diffusion tensor imaging and fibre tractography

    Energy Technology Data Exchange (ETDEWEB)

    Zijta, F.M. [University of Amsterdam, Department of Radiology, Academic Medical Centre, Amsterdam (Netherlands); Onze Lieve Vrouwe Gasthuis, Amsterdam and Department of Radiology, Amsterdam (Netherlands); Academic Medical Center, Department of Radiology, Amsterdam, AZ (Netherlands); Lakeman, M.M.E.; Roovers, J.P. [University of Amsterdam the Netherlands and Biomedical NMR, Amsterdam and Department of Gynaecology, Academic Medical Centre, Amsterdam (Netherlands); Froeling, M. [University of Amsterdam, Department of Radiology, Academic Medical Centre, Amsterdam (Netherlands); Eindhoven University of Technology, Department of Biomedical Engineering, Eindhoven (Netherlands); Paardt, M.P. van der; Borstlap, C.S.V.; Bipat, S.; Nederveen, A.J.; Stoker, J. [University of Amsterdam, Department of Radiology, Academic Medical Centre, Amsterdam (Netherlands); Montauban van Swijndregt, A.D. [Onze Lieve Vrouwe Gasthuis, Amsterdam and Department of Radiology, Amsterdam (Netherlands); Strijkers, G.J. [Eindhoven University of Technology, Department of Biomedical Engineering, Eindhoven (Netherlands)

    2012-12-15

    To prospectively explore the clinical application of diffusion tensor imaging (DTI) and fibre tractography in evaluating the pelvic floor. Ten patients with pelvic organ prolapse, ten with pelvic floor symptoms and ten asymptomatic women were included. A two-dimensional (2D) spin-echo (SE) echo-planar imaging (EPI) sequence of the pelvic floor was acquired. Offline fibre tractography and morphological analysis of pelvic magnetic resonance imaging (MRI) were performed. Inter-rater agreement for quality assessment of fibre tracking results was evaluated using weighted kappa ({kappa}). From agreed tracking results, eigen values ({lambda}1, {lambda}2, {lambda}3), mean diffusivity (MD) and fractional anisotropy (FA) were calculated. MD and FA values were compared using ANOVA. Inter-rater reliability of DTI parameters was interpreted using the intra-class correlation coefficient (ICC). Substantial inter-rater agreement was found ({kappa} = 0.71 [95% CI 0.63-0.78]). Four anatomical structures were reliably identified. Substantial inter-rater agreement was found for MD and FA (ICC 0.60-0.91). No significant differences between groups were observed for anal sphincter, perineal body and puboperineal muscle. A significant difference in FA was found for internal obturator muscle between the prolapse group and the asymptomatic group (0.27 {+-} 0.05 vs 0.22 {+-} 0.03; P = 0.015). DTI with fibre tractography permits identification of part of the clinically relevant pelvic structures. Overall, no significant differences in DTI parameters were found between groups. circle Diffusion tensor MRI offers new insights into female pelvic floor problems. (orig.)

  10. Optimal factors of diffusion tensor imaging predicting cortico spinal tract injury in patients with brain tumors

    Energy Technology Data Exchange (ETDEWEB)

    Min, Zhi Gang; Niu, Chen; Zhang, Qiu Li; Zhang, Ming [Dept. of Radiology, First Affiliated Hospital of Xi' an Jiaotong University, Xi' an (China); Qian, Yu Cheng [Dept. of Medical Imaging, School of Medicine, Jiangsu University, Zhenjiang (China)

    2017-09-15

    To identify the optimal factors in diffusion tensor imaging for predicting corticospinal tract (CST) injury caused by brain tumors. This prospective study included 33 patients with motor weakness and 64 patients with normal motor function. The movement of the CST, minimum distance between the CST and the tumor, and relative fractional anisotropy (rFA) of the CST on diffusion tensor imaging, were compared between patients with motor weakness and normal function. Logistic regression analysis was used to obtain the optimal factor predicting motor weakness. In patients with motor weakness, the displacement (8.44 ± 6.64 mm) of the CST (p = 0.009), minimum distance (3.98 ± 7.49 mm) between the CST and tumor (p < 0.001), and rFA (0.83 ± 0.11) of the CST (p < 0.001) were significantly different from those of the normal group (4.64 ± 6.65 mm, 14.87 ± 12.04 mm, and 0.98 ± 0.05, respectively) (p = 0.009, p < 0.001, and p < 0.001). The frequencies of patients with the CST passing through the tumor (6%, p = 0.002), CST close to the tumor (23%, p < 0.001), CST close to a malignant tumor (high grade glioma, metastasis, or lymphoma) (19%, p < 0.001), and CST passing through infiltrating edema (19%, p < 0.001) in the motor weakness group, were significantly different from those of the patients with normal motor function (0, 8, 1, and 10%, respectively). Logistic regression analysis showed that decreased rFA and CST close to a malignant tumor were effective variables related to motor weakness. Decreased fractional anisotropy, combined with closeness of a malignant tumor to the CST, is the optimal factor in predicting CST injury caused by a brain tumor.

  11. Limbic-Auditory Interactions of Tinnitus: An Evaluation Using Diffusion Tensor Imaging.

    Science.gov (United States)

    Gunbey, H P; Gunbey, E; Aslan, K; Bulut, T; Unal, A; Incesu, L

    2017-06-01

    Tinnitus is defined as an imaginary subjective perception in the absence of an external sound. Convergent evidence proposes that tinnitus perception includes auditory, attentional and emotional components. The aim of this study was to investigate the thalamic, auditory and limbic interactions associated with tinnitus-related distress by Diffusion Tensor Imaging (DTI). A total of 36 tinnitus patients, 20 healthy controls underwent an audiological examination, as well as a magnetic resonance imaging protocol including structural and DTI sequences. All participants completed the Tinnitus Handicap Inventory (THI) and Visual Analog Scales (VAS) related with tinnitus. The fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were obtained for the auditory cortex (AC), inferior colliculus (IC), lateral lemniscus (LL), medial geniculate body (MGB), thalamic reticular nucleus (TRN), amygdala (AMG), hippocampus (HIP), parahippocampus (PHIP) and prefrontal cortex (PFC). In tinnitus patients the FA values of IC, MGB, TRN, AMG, HIP decreased and the ADC values of IC, MGB, TRN, AMG, PHIP increased significantly. The contralateral IC-LL and bilateral MGB FA values correlated negatively with hearing loss. A negative relation was found between the AMG-HIP FA values and THI and VAS scores. Bilateral ADC values of PHIP and PFC significantly correlated with the attention deficiency-VAS scores. In conclusion, this is the first DTI study to investigate the grey matter structures related to tinnitus perception and the significant correlation of FA and ADC with clinical parameters suggests that DTI can provide helpful information for tinnitus. Magnifying the microstructures in DTI can help evaluate the three faces of tinnitus nature: hearing, emotion and attention.

  12. Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography.

    Science.gov (United States)

    Pierce, Theodore T; Calabrese, Evan; White, Leonard E; Chen, Steven D; Platt, Simon R; Provenzale, James M

    2014-01-01

    We set out to determine functional white matter (WM) connections passing through the canine corpus callosum; these WM connections would be useful for subsequent studies of canine brains that serve as models for human WM pathway disease. Based on prior studies, we anticipated that the anterior corpus callosum would send projections to the anterior cerebral cortex whereas progressively posterior segments would send projections to more posterior cortex. A postmortem canine brain was imaged using a 7-T MRI system producing 100-μm-isotropic-resolution diffusion-tensor imaging analyzed by tractography. Using regions of interest (ROIs) within cortical locations, which were confirmed by a Nissl stain that identified distinct cortical architecture, we successfully identified six important WM pathways. We also compared fractional anisotropy (FA), apparent diffusion coefficient (ADC), radial diffusivity, and axial diffusivity in tracts passing through the genu and splenium. Callosal fibers were organized on the basis of cortical destination (e.g., fibers from the genu project to the frontal cortex). Histologic results identified the motor cortex on the basis of cytoarchitectonic criteria that allowed placement of ROIs to discriminate between frontal and parietal lobes. We also identified cytoarchitecture typical of the orbital frontal, anterior frontal, and occipital regions and placed ROIs accordingly. FA, ADC, radial diffusivity, and axial diffusivity values were all higher in posterior corpus callosum fiber tracts. Using six cortical ROIs, we identified six major WM tracts that reflect major functional divisions of the cerebral hemispheres, and we derived quantitative values that can be used for study of canine models of human WM pathologic states.

  13. Relationship between suicidality and impulsivity in bipolar I disorder: a diffusion tensor imaging study

    Science.gov (United States)

    Mahon, Katie; Burdick, Katherine E; Wu, Jinghui; Ardekani, Babak A; Szeszko, Philip R

    2012-01-01

    Background Impulsivity is characteristic of individuals with bipolar disorder and may be a contributing factor to the high rate of suicide in patients with this disorder. Although white matter abnormalities have been implicated in the pathophysiology of bipolar disorder, their relationship to impulsivity and suicidality in this disorder has not been well-investigated. Methods Diffusion tensor imaging scans were acquired in 14 bipolar disorder patients with a prior suicide attempt, 15 bipolar disorder patients with no prior suicide attempt, and 15 healthy volunteers. Bipolar disorder patients received clinical assessments including measures of impulsivity, depression, mania, and anxiety. Images were processed using the Tract-Based Spatial Statistics method in the FSL software package. Results Bipolar disorder patients with a prior suicide attempt had lower fractional anisotropy (FA) within the left orbital frontal white matter (p impulsivity compared to patients without a previous suicide attempt. Among patients with a prior suicide attempt, FA in the orbital frontal white matter region correlated inversely with motor impulsivity. Conclusions Abnormal orbital frontal white matter may play a role in impulsive and suicidal behavior among patients with bipolar disorder. PMID:22329475

  14. Diffusion tensor imaging of the anterior cruciate ligament graft.

    Science.gov (United States)

    Van Dyck, Pieter; Froeling, Martijn; De Smet, Eline; Pullens, Pim; Torfs, Michaël; Verdonk, Peter; Sijbers, Jan; Parizel, Paul M; Jeurissen, Ben

    2017-11-01

    A great need exists for objective biomarkers to assess graft healing following ACL reconstruction to guide the time of return to sports. The purpose of this study was to evaluate the feasibility and reliability of diffusion tensor imaging (DTI) to delineate the anterior cruciate ligament (ACL) graft and to investigate its diffusion properties using a clinical 3T scanner. DTI of the knee (b = 0, 400, and 800 s/mm 2 , 10 diffusion directions, repeated 16 times for a total of 336 diffusion-weighted volumes) was performed at 3T in 17 patients between 3 and 7 months (mean, 4 months) following ACL reconstruction. Tractography was performed by two independent observers to delineate the ACL graft. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated within the graft. Interrater reliability was assessed using the intraclass correlation coefficient (ICC) and the scan-rescan reproducibility was evaluated based on the percentage coefficient of variance (%CV) across 20 repetition bootknife samples. In all subjects, tractography of the ACL graft was feasible. Quantitative evaluation of the diffusion properties of the ACL graft yielded the following mean ± SD values: FA = 0.23 ± 0.04; MD = 1.30 ± 0.11 × 10 -3 mm 2 /s; AD = 1.61 ± 0.12 × 10 -3 mm 2 /s, and RD = 1.15 ± 0.11 × 10 -3 mm 2 /s. Interrater reliability for the DTI parameters was excellent (ICC = 0.91-0.98). Mean %CVs for FA, MD, AD, and RD were 4.6%, 3.5%, 3.7%, and 4.4%, respectively. We demonstrated the feasibility and reliability of DTI for the visualization and quantitative evaluation of the ACL graft at 3T. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1423-1432. © 2017 International Society for Magnetic Resonance in Medicine.

  15. Monograph On Tensor Notations

    Science.gov (United States)

    Sirlin, Samuel W.

    1993-01-01

    Eight-page report describes systems of notation used most commonly to represent tensors of various ranks, with emphasis on tensors in Cartesian coordinate systems. Serves as introductory or refresher text for scientists, engineers, and others familiar with basic concepts of coordinate systems, vectors, and partial derivatives. Indicial tensor, vector, dyadic, and matrix notations, and relationships among them described.

  16. Comments on "A closed-form solution to Tensor voting: theory and applications"

    OpenAIRE

    Maggiori, Emmanuel; Lotito, Pablo Andres; Manterola, Hugo Luis; del Fresno, Mariana

    2017-01-01

    We comment on a paper that describes a closed-form formulation to Tensor Voting, a technique to perceptually group clouds of points, usually applied to infer features in images. The authors proved an analytic solution to the technique, a highly relevant contribution considering that the original formulation required numerical integration, a time-consuming task. Their work constitutes the first closed-form expression for the Tensor Voting framework. In this work we first observe that the propo...

  17. Direct diffusion tensor estimation using a model-based method with spatial and parametric constraints.

    Science.gov (United States)

    Zhu, Yanjie; Peng, Xi; Wu, Yin; Wu, Ed X; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

    2017-02-01

    To develop a new model-based method with spatial and parametric constraints (MB-SPC) aimed at accelerating diffusion tensor imaging (DTI) by directly estimating the diffusion tensor from highly undersampled k-space data. The MB-SPC method effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images using an L1-L2 norm and the smoothness of the diffusion tensor using a total variation seminorm. The undersampled k-space datasets were obtained from fully sampled DTI datasets of a simulated phantom and an ex-vivo experimental rat heart with acceleration factors ranging from 2 to 4. The diffusion tensor was directly reconstructed by solving a minimization problem with a nonlinear conjugate gradient descent algorithm. The reconstruction performance was quantitatively assessed using the normalized root mean square error (nRMSE) of the DTI indices. The MB-SPC method achieves acceptable DTI measures at an acceleration factor up to 4. Experimental results demonstrate that the proposed method can estimate the diffusion tensor more accurately than most existing methods operating at higher net acceleration factors. The proposed method can significantly reduce artifact, particularly at higher acceleration factors or lower SNRs. This method can easily be adapted to MR relaxometry parameter mapping and is thus useful in the characterization of biological tissue such as nerves, muscle, and heart tissue. © 2016 American Association of Physicists in Medicine.

  18. White matter impairments in autism, evidence from voxel-based morphometry and diffusion tensor imaging.

    Science.gov (United States)

    Ke, Xiaoyan; Tang, Tianyu; Hong, Shanshan; Hang, Yueyue; Zou, Bing; Li, Huiguo; Zhou, Zhenyu; Ruan, Zongcai; Lu, Zuhong; Tao, Guotai; Liu, Yijun

    2009-04-10

    This study explored white matter abnormalities in a group of Chinese children with high functioning autism (HFA). Twelve male children with HFA and ten matched typically developing children underwent diffusion tensor imaging (DTI) as well three-dimensional T1-weighted MRI for voxel-based morphometry (VBM). We found a significant decrease of the white matter density in the right frontal lobe, left parietal lobe and right anterior cingulate and a significant increase in the right frontal lobe, left parietal lobe and left cingulate gyrus in the HFA group compared with the control group. The HFA group also had decreased FA in the frontal lobe and left temporal lobe. By combining DT-MRI FA and MRI volumetric analyses based on the VBM model, the results showed consistent white matter abnormalities in a group of Chinese children with HFA.

  19. Aging effects on cerebral asymmetry: a voxel-based morphometry and diffusion tensor imaging study.

    Science.gov (United States)

    Takao, Hidemasa; Abe, Osamu; Yamasue, Hidenori; Aoki, Shigeki; Kasai, Kiyoto; Sasaki, Hiroki; Ohtomo, Kuni

    2010-01-01

    The hemispheres of the human brain are functionally and structurally asymmetric. The purpose of this study was to evaluate the effects of aging on gray and white matter asymmetry. Two hundred twenty-six right-handed normal volunteers aged 21-71 years were included in this study. The effects of aging on gray matter volume asymmetry and white matter fractional anisotropy asymmetry were evaluated with use of voxel-based morphometry and voxel-based analysis of fractional anisotropy maps derived from diffusion tensor imaging (DTI), respectively. The voxel-based morphometry showed no significant correlation between age and gray matter volume asymmetry. The voxel-based analysis of DTI also showed no significant correlation between age and white matter fractional anisotropy asymmetry. Our results showed no significant effects of aging on either gray matter volume asymmetry or white matter fractional anisotropy asymmetry.

  20. Cartesian tensors an introduction

    CERN Document Server

    Temple, G

    2004-01-01

    This undergraduate text provides an introduction to the theory of Cartesian tensors, defining tensors as multilinear functions of direction, and simplifying many theorems in a manner that lends unity to the subject. The author notes the importance of the analysis of the structure of tensors in terms of spectral sets of projection operators as part of the very substance of quantum theory. He therefore provides an elementary discussion of the subject, in addition to a view of isotropic tensors and spinor analysis within the confines of Euclidean space. The text concludes with an examination of t

  1. Diffusion tensor imaging in polymicrogyria: a report of three cases

    International Nuclear Information System (INIS)

    Trivedi, R.; Gupta, R.K.; Prasad, K.N.; Hasan, K.M.; Hou, P.; Narayana, P.A.

    2006-01-01

    Polymicrogyria (PMG), a neuronal migration disorder, commonly manifests as a seizure disorder. The aim of this study was to look for the abnormalities in the underlying white matter using diffusion tensor imaging (DTI) that appeared normal on conventional magnetic resonance imaging (MRI) in patients with PMG. DTI was performed in three patients with PMG and eight age- and sex-matched healthy controls. Fractional anisotropy (FA) and mean diffusivity (MD) values were calculated for the cortex and adjoining subcortical white matter in both controls and patients. We observed a significantly decreased mean FA value with no significant change in the MD value in subcortical white matter underlying polymicrogyric cortex (FA=0.23±0.04, MD=1.0±0.05 x 10 -3 mm 2 /s) as compared to both contralateral (FA=0.32±0.04, MD=1.0±0.05 x 10 -3 mm 2 /s) and normal control (FA=0.32±0.04, MD=1.0±0.06 x 10 -3 mm 2 /s) white matter. Significantly increased MD and decreased FA values were also observed in the polymicrogyric cortex (FA=0.08±0.01, MD=1.2±0.10 x 10 -3 mm 2 /s) as compared to normal contralateral (FA=0.12±0.04, MD=1.1±0.09 x 10 -3 mm 2 /s) and normal control (FA=0.12±0.01, MD=1.1±0.09 x 10 -3 mm 2 /s) cortex. Significantly decreased FA values with no change in MD values in the subcortical white matter subjacent to polymicrogyric cortex reflect microstructural changes in the white matter probably due to the presence of ectopic neurons. (orig.)

  2. Diffusion Tensor Imaging as a Biomarker to Differentiate Acute Disseminated Encephalomyelitis From Multiple Sclerosis at First Demyelination.

    Science.gov (United States)

    Aung, Wint Yan; Massoumzadeh, Parinaz; Najmi, Safa; Salter, Amber; Heaps, Jodi; Benzinger, Tammie L S; Mar, Soe

    2018-01-01

    There are no clinical features or biomarkers that can reliably differentiate acute disseminated encephalomyelitis from multiple sclerosis at the first demyelination attack. Consequently, a final diagnosis is sometimes delayed by months and years of follow-up. Early treatment for multiple sclerosis is recommended to reduce long-term disability. Therefore, we intend to explore neuroimaging biomarkers that can reliably distinguish between the two diagnoses. We reviewed prospectively collected clinical, standard MRI and diffusion tensor imaging data from 12 pediatric patients who presented with acute demyelination with and without encephalopathy. Patients were followed for an average of 6.5 years to determine the accuracy of final diagnosis. Final diagnosis was determined using 2013 International Pediatric MS Study Group criteria. Control subjects consisted of four age-matched healthy individuals for each patient. The study population consisted of six patients with central nervous system demyelination with encephalopathy with a presumed diagnosis of acute disseminated encephalomyelitis and six without encephalopathy with a presumed diagnosis of multiple sclerosis or clinically isolated syndrome at high risk for multiple sclerosis. During follow-up, two patients with initial diagnosis of acute disseminated encephalomyelitis were later diagnosed with multiple sclerosis. Diffusion tensor imaging region of interest analysis of baseline scans showed differences between final diagnosis of multiple sclerosis and acute disseminated encephalomyelitis patients, whereby low fractional anisotropy and high radial diffusivity occurred in multiple sclerosis patients compared with acute disseminated encephalomyelitis patients and the age-matched controls. Fractional anisotropy and radial diffusivity measures may have the potential to serve as biomarkers for distinguishing acute disseminated encephalomyelitis from multiple sclerosis at the onset. Copyright © 2017 Elsevier Inc. All

  3. Diffusion tensor imaging of the brain. Effects of distortion correction with correspondence to numbers of encoding directions

    International Nuclear Information System (INIS)

    Yoshikawa, Takeharu; Aoki, Shigeki; Abe, Osamu; Hayashi, Naoto; Masutani, Yoshitaka; Masumoto, Tomohiko; Mori, Harushi; Satake, Yoshiroh; Ohtomo, Kuni

    2008-01-01

    The aim of the study was to estimate the effect of distortion correction with correspondence to numbers of encoding directions to acquire diffusion tensor imaging (DTI) of improved quality. Ten volunteers underwent DTI of the head using echo planar imaging with 6, 13, 27, and 55 encoding directions. Fractional anisotropy (FA) maps and apparent diffusion coefficient (ADC) maps were created before and after distortion correction. Regions of interest were placed in the corpus callosum on each map, and standard deviations of FA and ADC were calculated. FA maps were also evaluated visually by experienced neuroradiologists. Dispersion of standard deviations tended to be reduced after distortion correction, with significant differences found in FA maps with 6 encoding directions, ADC maps with 6 directions, and ADC maps with 13 directions (P<0.001, P<0.005, and P<0.05, respectively). Visual image quality was improved after distortion correction (P<0.01 for all of the visual comparisons). Distortion correction is effective in providing DTI of enhanced quality, notwithstanding the number of encoding directions. (author)

  4. Fiber crossing in human brain depicted with diffusion tensor MR imaging

    DEFF Research Database (Denmark)

    Wiegell, M.R.; Larsson, H.B.; Wedeen, V.J.

    2000-01-01

    Human white matter fiber crossings were investigated with use of the full eigenstructure of the magnetic resonance diffusion tensor. Intravoxel fiber dispersions were characterized by the plane spanned by the major and medium eigenvectors and depicted with three-dimensional graphics. This method...

  5. Fourth meeting entitled “Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data”

    CERN Document Server

    Vilanova, Anna; Burgeth, Bernhard; Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data

    2014-01-01

    Arising from the fourth Dagstuhl conference entitled Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data (2011), this book offers a broad and vivid view of current work in this emerging field. Topics covered range from applications of the analysis of tensor fields to research on their mathematical and analytical properties. Part I, Tensor Data Visualization, surveys techniques for visualization of tensors and tensor fields in engineering, discusses the current state of the art and challenges, and examines tensor invariants and glyph design, including an overview of common glyphs. The second Part, Representation and Processing of Higher-order Descriptors, describes a matrix representation of local phase, outlines mathematical morphological operations techniques, extended for use in vector images, and generalizes erosion to the space of diffusion weighted MRI. Part III, Higher Order Tensors and Riemannian-Finsler Geometry, offers powerful mathematical language to model and...

  6. 4D cone beam CT via spatiotemporal tensor framelet

    International Nuclear Information System (INIS)

    Gao, Hao; Li, Ruijiang; Xing, Lei; Lin, Yuting

    2012-01-01

    Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.

  7. 4D cone beam CT via spatiotemporal tensor framelet

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Hao, E-mail: hao.gao@emory.edu [Departments of Mathematics and Computer Science, and Radiology and Imaging Sciences, Emory University, Atlanta, Georgia 30322 (United States); Li, Ruijiang; Xing, Lei [Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Lin, Yuting [Department of Radiological Sciences, University of California, Irvine, California 92697 (United States)

    2012-11-15

    Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.

  8. MATLAB tensor classes for fast algorithm prototyping.

    Energy Technology Data Exchange (ETDEWEB)

    Bader, Brett William; Kolda, Tamara Gibson (Sandia National Laboratories, Livermore, CA)

    2004-10-01

    Tensors (also known as mutidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to psychometrics. We describe four MATLAB classes for tensor manipulations that can be used for fast algorithm prototyping. The tensor class extends the functionality of MATLAB's multidimensional arrays by supporting additional operations such as tensor multiplication. The tensor as matrix class supports the 'matricization' of a tensor, i.e., the conversion of a tensor to a matrix (and vice versa), a commonly used operation in many algorithms. Two additional classes represent tensors stored in decomposed formats: cp tensor and tucker tensor. We descibe all of these classes and then demonstrate their use by showing how to implement several tensor algorithms that have appeared in the literature.

  9. Assessment of axonal degeneration in Alzheimer's disease with diffusion tensor MRI

    International Nuclear Information System (INIS)

    Stahl, R.; Dietrich, O.; Reiser, M.F.; Schoenberg, S.O.; Teipel, S.; Hampel, H.

    2003-01-01

    Alzheimer disease (AD) causes cortical degeneration with subsequent degenerative changes of the white matter. The aim of this study was to investigate the extent of white matter tissue damage of patients with Alzheimer's disease in comparison with healthy subjects using diffusion tensor MRI (DTI). The value of integrated parallel imaging techniques (iPAT) for reduction of image distortion was assessed. We studied 9 patients with mild AD and 10 age and gender matched healthy controls. DTI brain scans were obtained on a 1.5 tesla system (Siemens Magnetom Sonata) using parallel imaging (iPAT) and an EPI diffusion sequence with TE/TR 71 ms/6000 ms. We used an 8-element head coil and a GRAPPA reconstruction algorithm with an acceleration factor of 2. From the tensor, the mean diffusivity (D), the fractional anisotropy (FA), and the relative anisotropy (RA) of several white matter regions were determined. FA was significantly lower (p [de

  10. Killing-Yano tensors, rank-2 Killing tensors, and conserved quantities in higher dimensions

    Energy Technology Data Exchange (ETDEWEB)

    Krtous, Pavel [Institute of Theoretical Physics, Charles University, V Holesovickach 2, Prague (Czech Republic); Kubiznak, David [Institute of Theoretical Physics, Charles University, V Holesovickach 2, Prague (Czech Republic); Page, Don N. [Theoretical Physics Institute, University of Alberta, Edmonton T6G 2G7, Alberta (Canada); Frolov, Valeri P. [Theoretical Physics Institute, University of Alberta, Edmonton T6G 2G7, Alberta (Canada)

    2007-02-15

    From the metric and one Killing-Yano tensor of rank D-2 in any D-dimensional spacetime with such a principal Killing-Yano tensor, we show how to generate k = [(D+1)/2] Killing-Yano tensors, of rank D-2j for all 0 {<=} j {<=} k-1, and k rank-2 Killing tensors, giving k constants of geodesic motion that are in involution. For the example of the Kerr-NUT-AdS spacetime (hep-th/0604125) with its principal Killing-Yano tensor (gr-qc/0610144), these constants and the constants from the k Killing vectors give D independent constants in involution, making the geodesic motion completely integrable (hep-th/0611083). The constants of motion are also related to the constants recently obtained in the separation of the Hamilton-Jacobi and Klein-Gordon equations (hep-th/0611245)

  11. Killing-Yano tensors, rank-2 Killing tensors, and conserved quantities in higher dimensions

    International Nuclear Information System (INIS)

    Krtous, Pavel; Kubiznak, David; Page, Don N.; Frolov, Valeri P.

    2007-01-01

    From the metric and one Killing-Yano tensor of rank D-2 in any D-dimensional spacetime with such a principal Killing-Yano tensor, we show how to generate k = [(D+1)/2] Killing-Yano tensors, of rank D-2j for all 0 ≤ j ≤ k-1, and k rank-2 Killing tensors, giving k constants of geodesic motion that are in involution. For the example of the Kerr-NUT-AdS spacetime (hep-th/0604125) with its principal Killing-Yano tensor (gr-qc/0610144), these constants and the constants from the k Killing vectors give D independent constants in involution, making the geodesic motion completely integrable (hep-th/0611083). The constants of motion are also related to the constants recently obtained in the separation of the Hamilton-Jacobi and Klein-Gordon equations (hep-th/0611245)

  12. A voxel-based diffusion tensor imaging study of white matter in bipolar disorder.

    Science.gov (United States)

    Mahon, Katie; Wu, Jinghui; Malhotra, Anil K; Burdick, Katherine E; DeRosse, Pamela; Ardekani, Babak A; Szeszko, Philip R

    2009-05-01

    There is evidence from post-mortem and magnetic resonance imaging studies that hyperintensities, oligodendroglial abnormalities, and gross white matter volumetric alterations are involved in the pathophysiology of bipolar disorder. There is also functional imaging evidence for a defect in frontal cortico-subcortical pathways in bipolar disorder, but the white matter comprising these pathways has not been well investigated. Few studies have investigated white matter integrity in patients with bipolar disorder compared to healthy volunteers and the majority of studies have used manual region-of-interest approaches. In this study, we compared fractional anisotropy (FA) values between 30 patients with bipolar disorder and 38 healthy volunteers in the brain white matter using a voxelwise analysis following intersubject registration to Talairach space. Compared to healthy volunteers, patients demonstrated significantly (p or =50) higher FA within the right and left frontal white matter and lower FA within the left cerebellar white matter. Examination of individual eigenvalues indicated that group differences in both axial diffusivity and radial diffusivity contributed to abnormal FA within these regions. Tractography was performed in template space on averaged diffusion tensor imaging data from all individuals. Extraction of bundles passing through the clusters that differed significantly between groups suggested that white matter abnormalities along the pontine crossing tract, corticospinal/corticopontine tracts, and thalamic radiation fibers may be involved in the pathogenesis of bipolar disorder. Our findings are consistent with models of bipolar disorder that implicate dysregulation of cortico-subcortical and cerebellar regions in the disorder and may have relevance for phenomenology.

  13. Comments on "A Closed-Form Solution to Tensor Voting: Theory and Applications".

    Science.gov (United States)

    Maggiori, Emmanuel; Lotito, Pablo; Manterola, Hugo Luis; del Fresno, Mariana

    2014-12-01

    We comment on a paper that describes a closed-form formulation to Tensor Voting, a technique to perceptually group clouds of points, usually applied to infer features in images. The authors proved an analytic solution to the technique, a highly relevant contribution considering that the original formulation required numerical integration, a time-consuming task. Their work constitutes the first closed-form expression for the Tensor Voting framework. In this work we first observe that the proposed formulation leads to unexpected results which do not satisfy the constraints for a Tensor Voting output, hence they cannot be interpreted. Given that the closed-form expression is said to be an analytic equivalent solution, unexpected outputs should not be encountered unless there are flaws in the proof. We analyzed the underlying math to find which were the causes of these unexpected results. In this commentary we show that their proposal does not in fact provide a proper analytic solution to Tensor Voting and we indicate the flaws in the proof.

  14. Diffusion weighted imaging and diffusion tensor imaging in the evaluation of transplanted kidneys

    International Nuclear Information System (INIS)

    Palmucci, Stefano; Cappello, Giuseppina; Attinà, Giancarlo; Foti, Pietro Valerio; Siverino, Rita Olivia Anna; Roccasalva, Federica; Piccoli, Marina; Sinagra, Nunziata; Milone, Pietro; Veroux, Massimiliano; Ettorre, Giovanni Carlo

    2015-01-01

    The aim of this study is to investigate the relation between renal indexes and functional MRI in a population of kidney transplant recipients who underwent MR with diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) of the transplanted graft. Study population included 40 patients with single kidney transplant. The patients were divided into 3 groups, on the basis of creatinine clearance (CrCl) values calculated using Cockcroft-Gault formula: group A, including patients with normal renal function (CrCl ≥ 60 mL/min); group B, which refers to patients with moderate renal impairment (CrCl > 30 but <60 mL/min); and, finally, group C, which means severe renal deterioration (CrCl ≤ 30 mL/min). All patients were investigated with a 1.5 Tesla MRI scanner, acquiring DWI and DTI sequences. A Mann–Whitney U test was adopted to compare apparent diffusion coefficients (ADCs) and fractional anisotropy (FA) measurements between groups. Receiver operating characteristic (ROC) curves were created for prediction of normal renal function (group A) and renal failure (group C). Pearson correlation was performed between renal clearance and functional imaging parameter (ADC and FA), obtained for cortical and medullar regions. Mann–Whitney U test revealed a highly significant difference (p < 0.01) between patients with low CrCl (group C) and normal CrCl (group A) considering both medullar ADC and FA and cortical ADC. Regarding contiguous groups, the difference between group B and C was highly significant (p < 0.01) for medullar ADC and significant (p < 0.05) for cortical ADC and medullar FA. No difference between these groups was found considering cortical FA. Analyzing groups A and B, we found a significant difference (p < 0.05) for medullar both ADC and FA, while no difference was found for cortical ADC and FA. Strongest Pearson correlation was found between CrCl and medullar ADC (r = 0.65). For predicting normal renal function or severe renal impairment, highest

  15. The evaluation of a population based diffusion tensor image atlas using a ground truth method

    Science.gov (United States)

    Van Hecke, Wim; Leemans, Alexander; D'Agostino, Emiliano; De Backer, Steve; Vandervliet, Evert; Parizel, Paul M.; Sijbers, Jan

    2008-03-01

    Purpose: Voxel based morphometry (VBM) is increasingly being used to detect diffusion tensor (DT) image abnormalities in patients for different pathologies. An important requisite for these VBM studies is the use of a high-dimensional, non-rigid coregistration technique, which is able to align both the spatial and the orientational information. Recent studies furthermore indicate that high-dimensional DT information should be included during coregistration for an optimal alignment. In this context, a population based DTI atlas is created that preserves the orientational DT information robustly and contains a minimal bias towards any specific individual data set. Methods: A ground truth evaluation method is developed using a single subject DT image that is deformed with 20 deformation fields. Thereafter, an atlas is constructed based on these 20 resulting images. Thereby, the non-rigid coregistration algorithm is based on a viscous fluid model and on mutual information. The fractional anisotropy (FA) maps as well as the DT elements are used as DT image information during the coregistration algorithm, in order to minimize the orientational alignment inaccuracies. Results: The population based DT atlas is compared with the ground truth image using accuracy and precision measures of spatial and orientational dependent metrics. Results indicate that the population based atlas preserves the orientational information in a robust way. Conclusion: A subject independent population based DT atlas is constructed and evaluated with a ground truth method. This atlas contains all available orientational information and can be used in future VBM studies as a reference system.

  16. Test-Retest Reliability of Diffusion Tensor Imaging in Huntington's Disease.

    Science.gov (United States)

    Cole, James H; Farmer, Ruth E; Rees, Elin M; Johnson, Hans J; Frost, Chris; Scahill, Rachael I; Hobbs, Nicola Z

    2014-03-21

    Diffusion tensor imaging (DTI) has shown microstructural abnormalities in patients with Huntington's Disease (HD) and work is underway to characterise how these abnormalities change with disease progression. Using methods that will be applied in longitudinal research, we sought to establish the reliability of DTI in early HD patients and controls. Test-retest reliability, quantified using the intraclass correlation coefficient (ICC), was assessed using region-of-interest (ROI)-based white matter atlas and voxelwise approaches on repeat scan data from 22 participants (10 early HD, 12 controls). T1 data was used to generate further ROIs for analysis in a reduced sample of 18 participants. The results suggest that fractional anisotropy (FA) and other diffusivity metrics are generally highly reliable, with ICCs indicating considerably lower within-subject compared to between-subject variability in both HD patients and controls. Where ICC was low, particularly for the diffusivity measures in the caudate and putamen, this was partly influenced by outliers. The analysis suggests that the specific DTI methods used here are appropriate for cross-sectional research in HD, and give confidence that they can also be applied longitudinally, although this requires further investigation. An important caveat for DTI studies is that test-retest reliability may not be evenly distributed throughout the brain whereby highly anisotropic white matter regions tended to show lower relative within-subject variability than other white or grey matter regions.

  17. Tensor-based spatiotemporal saliency detection

    Science.gov (United States)

    Dou, Hao; Li, Bin; Deng, Qianqian; Zhang, LiRui; Pan, Zhihong; Tian, Jinwen

    2018-03-01

    This paper proposes an effective tensor-based spatiotemporal saliency computation model for saliency detection in videos. First, we construct the tensor representation of video frames. Then, the spatiotemporal saliency can be directly computed by the tensor distance between different tensors, which can preserve the complete temporal and spatial structure information of object in the spatiotemporal domain. Experimental results demonstrate that our method can achieve encouraging performance in comparison with the state-of-the-art methods.

  18. Performances of diffusion kurtosis imaging and diffusion tensor imaging in detecting white matter abnormality in schizophrenia

    Directory of Open Access Journals (Sweden)

    Jiajia Zhu

    2015-01-01

    Full Text Available Diffusion kurtosis imaging (DKI is an extension of diffusion tensor imaging (DTI, exhibiting improved sensitivity and specificity in detecting developmental and pathological changes in neural tissues. However, little attention was paid to the performances of DKI and DTI in detecting white matter abnormality in schizophrenia. In this study, DKI and DTI were performed in 94 schizophrenia patients and 91 sex- and age-matched healthy controls. White matter integrity was assessed by fractional anisotropy (FA, mean diffusivity (MD, axial diffusivity (AD, radial diffusivity (RD, mean kurtosis (MK, axial kurtosis (AK and radial kurtosis (RK of DKI and FA, MD, AD and RD of DTI. Group differences in these parameters were compared using tract-based spatial statistics (TBSS (P  AK (20% > RK (3% and RD (37% > FA (24% > MD (21% for DKI, and RD (43% > FA (30% > MD (21% for DTI. DKI-derived diffusion parameters (RD, FA and MD were sensitive to detect abnormality in white matter regions (the corpus callosum and anterior limb of internal capsule with coherent fiber arrangement; however, the kurtosis parameters (MK and AK were sensitive to reveal abnormality in white matter regions (the juxtacortical white matter and corona radiata with complex fiber arrangement. In schizophrenia, the decreased AK suggests axonal damage; however, the increased RD indicates myelin impairment. These findings suggest that diffusion and kurtosis parameters could provide complementary information and they should be jointly used to reveal pathological changes in schizophrenia.

  19. Applying tensor-based morphometry to parametric surfaces can improve MRI-based disease diagnosis.

    Science.gov (United States)

    Wang, Yalin; Yuan, Lei; Shi, Jie; Greve, Alexander; Ye, Jieping; Toga, Arthur W; Reiss, Allan L; Thompson, Paul M

    2013-07-01

    Many methods have been proposed for computer-assisted diagnostic classification. Full tensor information and machine learning with 3D maps derived from brain images may help detect subtle differences or classify subjects into different groups. Here we develop a new approach to apply tensor-based morphometry to parametric surface models for diagnostic classification. We use this approach to identify cortical surface features for use in diagnostic classifiers. First, with holomorphic 1-forms, we compute an efficient and accurate conformal mapping from a multiply connected mesh to the so-called slit domain. Next, the surface parameterization approach provides a natural way to register anatomical surfaces across subjects using a constrained harmonic map. To analyze anatomical differences, we then analyze the full Riemannian surface metric tensors, which retain multivariate information on local surface geometry. As the number of voxels in a 3D image is large, sparse learning is a promising method to select a subset of imaging features and to improve classification accuracy. Focusing on vertices with greatest effect sizes, we train a diagnostic classifier using the surface features selected by an L1-norm based sparse learning method. Stability selection is applied to validate the selected feature sets. We tested the algorithm on MRI-derived cortical surfaces from 42 subjects with genetically confirmed Williams syndrome and 40 age-matched controls, multivariate statistics on the local tensors gave greater effect sizes for detecting group differences relative to other TBM-based statistics including analysis of the Jacobian determinant and the largest eigenvalue of the surface metric. Our method also gave reasonable classification results relative to the Jacobian determinant, the pair of eigenvalues of the Jacobian matrix and volume features. This analysis pipeline may boost the power of morphometry studies, and may assist with image-based classification. Copyright © 2013

  20. Effects of MR parameter changes on the quantification of diffusion anisotropy and apparent diffusion coefficient in diffusion tensor imaging: Evaluation using a diffusional anisotropic phantom

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sang Joon; Choi, Choong Gon; Kim, Jeong Kon [Dept. of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Yun, Sung Cheol [Dept. of Biostatistics, University of Ulsan College of Medicine, Seoul (Korea, Republic of); Jeong, Ha Kyu [Dept. of Radiology, East-West Neomedical Center, Kyung Hee University College of Medicine, Seoul (Korea, Republic of); Kim, Eun Ju [Clinical Scientist, MR, Philips Healthcare, Seoul (Korea, Republic of)

    2015-04-15

    To validate the usefulness of a diffusional anisotropic capillary array phantom and to investigate the effects of diffusion tensor imaging (DTI) parameter changes on diffusion fractional anisotropy (FA) and apparent diffusion coefficient (ADC) using the phantom. Diffusion tensor imaging of a capillary array phantom was performed with imaging parameter changes, including voxel size, number of sensitivity encoding (SENSE) factor, echo time (TE), number of signal acquisitions, b-value, and number of diffusion gradient directions (NDGD), one-at-a-time in a stepwise-incremental fashion. We repeated the entire series of DTI scans thrice. The coefficients of variation (CoV) were evaluated for FA and ADC, and the correlation between each MR imaging parameter and the corresponding FA and ADC was evaluated using Spearman's correlation analysis. The capillary array phantom CoVs of FA and ADC were 7.1% and 2.4%, respectively. There were significant correlations between FA and SENSE factor, TE, b-value, and NDGD, as well as significant correlations between ADC and SENSE factor, TE, and b-value. A capillary array phantom enables repeated measurements of FA and ADC. Both FA and ADC can vary when certain parameters are changed during diffusion experiments. We suggest that the capillary array phantom can be used for quality control in longitudinal or multicenter clinical studies.

  1. Magnetic resonance imaging of the tensor vastus intermedius: A topographic study based on anatomical dissections.

    Science.gov (United States)

    Grob, Karl; Manestar, Mirjana; Gascho, Dominic; Ackland, Timothy; Gilbey, Helen; Fretz, Christian; Kuster, Markus S

    2017-11-01

    The tensor of the vastus intermedius (TVI) is a newly described component of the extensor apparatus of the knee joint. The objective of this study was to evaluate the appearance of the TVI on magnetic resonance (MR) imaging and its association with the adjacent vastus lateralis (VL) and vastus intermedius (VI) muscles and to compare these findings with the corresponding anatomy. MR images were analyzed from a cadaveric thigh where the TVI, as part of the extensor apparatus of the knee joint, had been dissected. The course of the TVI in relation to the adjacent VL and VI was studied. The anatomic dissection and MR imaging revealed a multilayered organization of the lateral extensor apparatus of the knee joint. The TVI is an intervening muscle between the VL and VI that combined into a broad flat aponeurosis in the midthigh and merged into the quadriceps tendon. Dorsally, the muscle fibers of the TVI joined those of the VL and VI and blended into the attachment at the lateral lip of the linea aspera. In this area, distinguishing between these three muscles was not possible macroscopically or virtually by MR imaging. In the dorsal aspect, the onion-like muscle layers of the VL, TVI, and VI fuse to a hardly separable muscle mass indicating that these muscles work in conjunction to produce knee extension torque when knee joint action is performed. Clin. Anat. 30:1096-1102, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  2. Preoperative Visualization of Cranial Nerves in Skull Base Tumor Surgery Using Diffusion Tensor Imaging Technology.

    Science.gov (United States)

    Ma, Jun; Su, Shaobo; Yue, Shuyuan; Zhao, Yan; Li, Yonggang; Chen, Xiaochen; Ma, Hui

    2016-01-01

    To visualize cranial nerves (CNs) using diffusion tensor imaging (DTI) with special parameters. This study also involved the evaluation of preoperative estimates and intraoperative confirmation of the relationship between nerves and tumor by verifying the accuracy of visualization. 3T magnetic resonance imaging scans including 3D-FSPGR, FIESTA, and DTI were used to collect information from 18 patients with skull base tumor. DTI data were integrated into the 3D slicer for fiber tracking and overlapped anatomic images to determine course of nerves. 3D reconstruction of tumors was achieved to perform neighboring, encasing, and invading relationship between lesion and nerves. Optic pathway including the optic chiasm could be traced in cases of tuberculum sellae meningioma and hypophysoma (pituitary tumor). The oculomotor nerve, from the interpeduncular fossa out of the brain stem to supraorbital fissure, was clearly visible in parasellar meningioma cases. Meanwhile, cisternal parts of trigeminal nerve and abducens nerve, facial nerve were also imaged well in vestibular schwannomas and petroclival meningioma cases. The 3D-spatial relationship between CNs and skull base tumor estimated preoperatively by tumor modeling and tractography corresponded to the results determined during surgery. Supported by DTI and 3D slicer, preoperative 3D reconstruction of most CNs related to skull base tumor is feasible in pathological circumstances. We consider DTI Technology to be a useful tool for predicting the course and location of most CNs, and syntopy between them and skull base tumor.

  3. Generalized dielectric permittivity tensor

    International Nuclear Information System (INIS)

    Borzdov, G.N.; Barkovskii, L.M.; Fedorov, F.I.

    1986-01-01

    The authors deal with the question of what is to be done with the formalism of the electrodynamics of dispersive media based on the introduction of dielectric-permittivity tensors for purely harmonic fields when Voigt waves and waves of more general form exist. An attempt is made to broaden and generalize the formalism to take into account dispersion of waves of the given type. In dispersive media, the polarization, magnetization, and conduction current-density vectors of point and time are determined by the values of the electromagnetic field vectors in the vicinity of this point (spatial dispersion) in the preceding instants of time (time dispersion). The dielectric-permittivity tensor and other tensors of electrodynamic parameters of the medium are introduced in terms of a set of evolution operators and not the set of harmonic function. It is noted that a magnetic-permeability tensor and an elastic-modulus tensor may be introduced for an acoustic field in dispersive anisotropic media with coupling equations of general form

  4. Tensor analysis for physicists

    CERN Document Server

    Schouten, J A

    1989-01-01

    This brilliant study by a famed mathematical scholar and former professor of mathematics at the University of Amsterdam integrates a concise exposition of the mathematical basis of tensor analysis with admirably chosen physical examples of the theory. The first five chapters incisively set out the mathematical theory underlying the use of tensors. The tensor algebra in EN and RN is developed in Chapters I and II. Chapter II introduces a sub-group of the affine group, then deals with the identification of quantities in EN. The tensor analysis in XN is developed in Chapter IV. In chapters VI through IX, Professor Schouten presents applications of the theory that are both intrinsically interesting and good examples of the use and advantages of the calculus. Chapter VI, intimately connected with Chapter III, shows that the dimensions of physical quantities depend upon the choice of the underlying group, and that tensor calculus is the best instrument for dealing with the properties of anisotropic media. In Chapte...

  5. Reconstruction of the arcuate fasciculus for surgical planning in the setting of peritumoral edema using two-tensor unscented Kalman filter tractography.

    Science.gov (United States)

    Chen, Zhenrui; Tie, Yanmei; Olubiyi, Olutayo; Rigolo, Laura; Mehrtash, Alireza; Norton, Isaiah; Pasternak, Ofer; Rathi, Yogesh; Golby, Alexandra J; O'Donnell, Lauren J

    2015-01-01

    Diffusion imaging tractography is increasingly used to trace critical fiber tracts in brain tumor patients to reduce the risk of post-operative neurological deficit. However, the effects of peritumoral edema pose a challenge to conventional tractography using the standard diffusion tensor model. The aim of this study was to present a novel technique using a two-tensor unscented Kalman filter (UKF) algorithm to track the arcuate fasciculus (AF) in brain tumor patients with peritumoral edema. Ten right-handed patients with left-sided brain tumors in the vicinity of language-related cortex and evidence of significant peritumoral edema were retrospectively selected for the study. All patients underwent 3-Tesla magnetic resonance imaging (MRI) including a diffusion-weighted dataset with 31 directions. Fiber tractography was performed using both single-tensor streamline and two-tensor UKF tractography. A two-regions-of-interest approach was applied to perform the delineation of the AF. Results from the two different tractography algorithms were compared visually and quantitatively. Using single-tensor streamline tractography, the AF appeared disrupted in four patients and contained few fibers in the remaining six patients. Two-tensor UKF tractography delineated an AF that traversed edematous brain areas in all patients. The volume of the AF was significantly larger on two-tensor UKF than on single-tensor streamline tractography (p tensor UKF tractography provides the ability to trace a larger volume AF than single-tensor streamline tractography in the setting of peritumoral edema in brain tumor patients.

  6. TensorPack: a Maple-based software package for the manipulation of algebraic expressions of tensors in general relativity

    International Nuclear Information System (INIS)

    Huf, P A; Carminati, J

    2015-01-01

    In this paper we: (1) introduce TensorPack, a software package for the algebraic manipulation of tensors in covariant index format in Maple; (2) briefly demonstrate the use of the package with an orthonormal tensor proof of the shearfree conjecture for dust. TensorPack is based on the Riemann and Canon tensor software packages and uses their functions to express tensors in an indexed covariant format. TensorPack uses a string representation as input and provides functions for output in index form. It extends the functionality to basic algebra of tensors, substitution, covariant differentiation, contraction, raising/lowering indices, symmetry functions and other accessory functions. The output can be merged with text in the Maple environment to create a full working document with embedded dynamic functionality. The package offers potential for manipulation of indexed algebraic tensor expressions in a flexible software environment. (paper)

  7. Brain microstructural abnormalities revealed by diffusion tensor images in patients with treatment-resistant depression compared with major depressive disorder before treatment

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Yan, E-mail: clare1475@hotmail.com [Department of Radiology, Ren-Ji Hospital, Jiao Tong University Medical School, Shanghai 200127 (China); Qin Lingdi, E-mail: flyfool318@hotmail.com [Department of Radiology, Ren-Ji Hospital, Jiao Tong University Medical School, Shanghai 200127 (China); Chen Jun, E-mail: doctor_cj@msn.com [Shanghai Mental Health Center, Jiao Tong University Medical School, Shanghai, 200030 (China); Qian Lijun, E-mail: dearqlj@hotmail.com [Department of Radiology, Ren-Ji Hospital, Jiao Tong University Medical School, Shanghai 200127 (China); Tao Jing, E-mail: jing318@hotmail.com [Department of Radiology, Ren-Ji Hospital, Jiao Tong University Medical School, Shanghai 200127 (China); Fang Yiru, E-mail: fangyr@sina.com [Shanghai Mental Health Center, Jiao Tong University Medical School, Shanghai, 200030 (China); Xu Jianrong, E-mail: xujianr@hotmail.com [Department of Radiology, Ren-Ji Hospital, Jiao Tong University Medical School, Shanghai 200127 (China)

    2011-11-15

    Treatment-resistant depression (TRD) is a therapeutic challenge for clinicians. Despite a growing interest in this area, an understanding of the pathophysiology of depression, particularly TRD, remains lacking. This study aims to detect the white matter abnormalities of whole brain fractional anisotropy (FA) in patients with TRD compared with major depressive disorder (MDD) before treatment by voxel-based analysis using diffusion tensor imaging. A total of 100 patients first diagnosed with untreated MDD underwent diffusion tensor imaging scans. 8 weeks after the first treatment, 54 patients showed response to the medication, whereas 46 did not. Finally, 20 patients were diagnosed with TRD after undergoing another treatment. A total of 20 patients with TRD and another 20 with MDD before treatment matched in gender, age, and education was enrolled in the research. For every subject, an FA map was generated and analyzed using SPM5. Subsequently, t-test was conducted to compare the FA values voxel to voxel between the two groups (p < 0.001 [FDR corrected], t > 7.57, voxel size > 30). Voxel-based morphometric (VBM) analysis was performed using T1W images. Significant reductions in FA were found in the white matter located in the bilateral of the hippocampus (left hippocampus: t = 7.63, voxel size = 50; right hippocampus: t = 7.82, voxel size = 48). VBM analysis revealed no morphological abnormalities between the two groups. Investigation of brain anisotropy revealed significantly decreased FA in both sides of the hippocampus. Although preliminary, our findings suggest that microstructural abnormalities in the hippocampus indicate vulnerability to treatment resistance.

  8. Brain microstructural abnormalities revealed by diffusion tensor images in patients with treatment-resistant depression compared with major depressive disorder before treatment

    International Nuclear Information System (INIS)

    Zhou Yan; Qin Lingdi; Chen Jun; Qian Lijun; Tao Jing; Fang Yiru; Xu Jianrong

    2011-01-01

    Treatment-resistant depression (TRD) is a therapeutic challenge for clinicians. Despite a growing interest in this area, an understanding of the pathophysiology of depression, particularly TRD, remains lacking. This study aims to detect the white matter abnormalities of whole brain fractional anisotropy (FA) in patients with TRD compared with major depressive disorder (MDD) before treatment by voxel-based analysis using diffusion tensor imaging. A total of 100 patients first diagnosed with untreated MDD underwent diffusion tensor imaging scans. 8 weeks after the first treatment, 54 patients showed response to the medication, whereas 46 did not. Finally, 20 patients were diagnosed with TRD after undergoing another treatment. A total of 20 patients with TRD and another 20 with MDD before treatment matched in gender, age, and education was enrolled in the research. For every subject, an FA map was generated and analyzed using SPM5. Subsequently, t-test was conducted to compare the FA values voxel to voxel between the two groups (p 7.57, voxel size > 30). Voxel-based morphometric (VBM) analysis was performed using T1W images. Significant reductions in FA were found in the white matter located in the bilateral of the hippocampus (left hippocampus: t = 7.63, voxel size = 50; right hippocampus: t = 7.82, voxel size = 48). VBM analysis revealed no morphological abnormalities between the two groups. Investigation of brain anisotropy revealed significantly decreased FA in both sides of the hippocampus. Although preliminary, our findings suggest that microstructural abnormalities in the hippocampus indicate vulnerability to treatment resistance.

  9. Diffusion tensor imaging in children with unilateral hearing loss: a pilot study

    Directory of Open Access Journals (Sweden)

    Tara eRachakonda

    2014-05-01

    Full Text Available Objective: Language acquisition was assumed to proceed normally in children with unilateral hearing loss (UHL since they have one functioning ear. However, children with UHL score poorly on speech-language tests and have higher rates of educational problems compared to normal hearing (NH peers. Diffusion tensor imaging (DTI is an imaging modality used to measure microstructural integrity of brain white matter. The purpose of this pilot study was to investigate differences in fractional anisotropy (FA and mean diffusivity (MD in hearing- and non-hearing-related structures in the brain between children with UHL and their NH siblings. Study Design: Prospective observational cohortSetting: Academic medical center.Subjects and Methods: 61 children were recruited, tested and imaged. 29 children with severe-to-profound UHL were compared to 20 siblings with NH using IQ and oral language testing, and MRI with DTI. 12 children had inadequate MRI data. Parents provided demographic data and indicated whether children had a need for an individualized educational program (IEP or speech therapy (ST. DTI parameters were measured in auditory and non-auditory regions of interest (ROIs. Between-group comparisons were evaluated with non-parametric tests. Results: Lower FA of left lateral lemniscus was observed for children with UHL compared to their NH siblings, as well as trends towards differences in other auditory and nonauditory regions. Correlation analyses showed associations between several DTI parameters and outcomes in children with UHL. Regression analyses revealed relationships between educational outcome variables and several DTI parameters, which may provide clinically useful information for guidance of speech therapy. Discussion/Conclusion: White matter microstructural patterns in several brain regions are preserved despite unilateral rather than bilateral auditory input which contrasts with findings in patients with bilateral hearing loss.

  10. Unique characterization of the Bel-Robinson tensor

    International Nuclear Information System (INIS)

    Bergqvist, G; Lankinen, P

    2004-01-01

    We prove that a completely symmetric and trace-free rank-4 tensor is, up to sign, a Bel-Robinson-type tensor, i.e., the superenergy tensor of a tensor with the same algebraic symmetries as the Weyl tensor, if and only if it satisfies a certain quadratic identity. This may be seen as the first Rainich theory result for rank-4 tensors

  11. Tensor Product of Polygonal Cell Complexes

    OpenAIRE

    Chien, Yu-Yen

    2017-01-01

    We introduce the tensor product of polygonal cell complexes, which interacts nicely with the tensor product of link graphs of complexes. We also develop the unique factorization property of polygonal cell complexes with respect to the tensor product, and study the symmetries of tensor products of polygonal cell complexes.

  12. Diffusion tensor imaging for long-term follow-up of corticospinal tract degeneration in amyotrophic lateral sclerosis

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, S.; Ehrenreich, H. [Max-Planck-Institute for Experimental Medicine, Georg-August-University, Hermann-Rein-Strasse 3, 37075, Goettingen (Germany); Departments of Neurology and Psychiatry, Georg-August-University, Goettingen (Germany); Finsterbusch, J.; Frahm, J. [Biomedizinische NMR Forschungs GmbH, Max-Planck-Institute for Biophysical Chemistry, Georg-August-University, Goettingen (Germany); Weishaupt, J.H. [Departments of Neurology and Psychiatry, Georg-August-University, Goettingen (Germany); Khorram-Sefat, D. [Department of Neuroradiology, Georg-August-University, Goettingen (Germany)

    2003-09-01

    Amyotrophic lateral sclerosis (ALS) is a predominantly clinical and electromyographic diagnosis. Conventional MRI reveals atrophy of the motor system, particularly the pyramidal tract, in the advanced stages but does not provide a sensitive measure of disease progression. Three patients with different principal symptoms of ALS, i.e., with predominant involvement of the upper (UMN) or lower (UMN) motor neurons, or bulbar disease, respectively, underwent serial clinical examination including lung function tests, conventional MRI, and diffusion tensor imaging (DTI). MRI demonstrated changes in of the pyramidal tract without measurable variation on follow-up. The patient with UMN involvement showed remarkable progressive loss of diffusion anisotropy in the pyramidal tract. DTI might be useful, together with clinical follow-up, as an objective morphological marker in therapeutic trials. (orig.)

  13. Lagrangian analysis of vector and tensor fields: Algorithmic foundations and applications in medical imaging and computational fluid dynamics

    OpenAIRE

    Ding, Zi'ang

    2016-01-01

    Both vector and tensor fields are important mathematical tools used to describe the physics of many phenomena in science and engineering. Effective vector and tensor field visualization techniques are therefore needed to interpret and analyze the corresponding data and achieve new insight into the considered problem. This dissertation is concerned with the extraction of important structural properties from vector and tensor datasets. Specifically, we present a unified approach for the charact...

  14. Notes on super Killing tensors

    Energy Technology Data Exchange (ETDEWEB)

    Howe, P.S. [Department of Mathematics, King’s College London,The Strand, London WC2R 2LS (United Kingdom); Lindström, University [Department of Physics and Astronomy, Theoretical Physics, Uppsala University,SE-751 20 Uppsala (Sweden); Theoretical Physics, Imperial College London,Prince Consort Road, London SW7 2AZ (United Kingdom)

    2016-03-14

    The notion of a Killing tensor is generalised to a superspace setting. Conserved quantities associated with these are defined for superparticles and Poisson brackets are used to define a supersymmetric version of the even Schouten-Nijenhuis bracket. Superconformal Killing tensors in flat superspaces are studied for spacetime dimensions 3,4,5,6 and 10. These tensors are also presented in analytic superspaces and super-twistor spaces for 3,4 and 6 dimensions. Algebraic structures associated with superconformal Killing tensors are also briefly discussed.

  15. Histogram Analysis of Diffusion Tensor Imaging Parameters in Pediatric Cerebellar Tumors.

    Science.gov (United States)

    Wagner, Matthias W; Narayan, Anand K; Bosemani, Thangamadhan; Huisman, Thierry A G M; Poretti, Andrea

    2016-05-01

    Apparent diffusion coefficient (ADC) values have been shown to assist in differentiating cerebellar pilocytic astrocytomas and medulloblastomas. Previous studies have applied only ADC measurements and calculated the mean/median values. Here we investigated the value of diffusion tensor imaging (DTI) histogram characteristics of the entire tumor for differentiation of cerebellar pilocytic astrocytomas and medulloblastomas. Presurgical DTI data were analyzed with a region of interest (ROI) approach to include the entire tumor. For each tumor, histogram-derived metrics including the 25th percentile, 75th percentile, and skewness were calculated for fractional anisotropy (FA) and mean (MD), axial (AD), and radial (RD) diffusivity. The histogram metrics were used as primary predictors of interest in a logistic regression model. Statistical significance levels were set at p histogram skewness showed statistically significant differences for MD between low- and high-grade tumors (P = .008). The 25th percentile for MD yields the best results for the presurgical differentiation between pediatric cerebellar pilocytic astrocytomas and medulloblastomas. The analysis of other DTI metrics does not provide additional diagnostic value. Our study confirms the diagnostic value of the quantitative histogram analysis of DTI data in pediatric neuro-oncology. Copyright © 2015 by the American Society of Neuroimaging.

  16. Utility of diffusion tensor imaging tractography in decision making for extratemporal resective epilepsy surgery.

    Science.gov (United States)

    Radhakrishnan, Ashalatha; James, Jija S; Kesavadas, Chandrasekharan; Thomas, Bejoy; Bahuleyan, Biji; Abraham, Mathew; Radhakrishnan, Kurupath

    2011-11-01

    To assess the utility of diffusion tensor imaging tractography (DTIT) in decision making in patients considered for extratemporal resective epilepsy surgery. We subjected 49 patients with drug-resistant focal seizures due to lesions located in frontal, parietal and occipital lobes to DTIT to map the white matter fiber anatomy in relation to the planned resection zone, in addition to routine presurgical evaluation. We stratified our patients preoperatively into different grades of risk for anticipated neurological deficits as judged by the distance of the white matter tracts from the resection zones and functional cortical areas. Thirty-seven patients underwent surgery; surgery was abandoned in 12 (24.5%) patients because of the high risk of postoperative neurological deficit. DTIT helped us to modify the surgical procedures in one-fourth of occipital, one-third of frontal, and two-thirds of parietal and multilobar resections. Overall, DTIT assisted us in surgical decision making in two-thirds of our patients. DTIT is a noninvasive imaging strategy that can be used effectively in planning resection of epileptogenic lesions at or close to eloquent cortical areas. DTIT helps in predicting postoperative neurological outcome and thereby assists in surgical decision making and in preoperative counseling of patients with extratemporal focal epilepsies. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. Tensor Train Neighborhood Preserving Embedding

    Science.gov (United States)

    Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin

    2018-05-01

    In this paper, we propose a Tensor Train Neighborhood Preserving Embedding (TTNPE) to embed multi-dimensional tensor data into low dimensional tensor subspace. Novel approaches to solve the optimization problem in TTNPE are proposed. For this embedding, we evaluate novel trade-off gain among classification, computation, and dimensionality reduction (storage) for supervised learning. It is shown that compared to the state-of-the-arts tensor embedding methods, TTNPE achieves superior trade-off in classification, computation, and dimensionality reduction in MNIST handwritten digits and Weizmann face datasets.

  18. Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling.

    Science.gov (United States)

    Ertas, Gokhan

    2018-07-01

    To assess the value of joint evaluation of diffusion tensor imaging (DTI) measures by using logistic regression modelling to detect high GS risk group prostate tumors. Fifty tumors imaged using DTI on a 3 T MRI device were analyzed. Regions of interests focusing on the center of tumor foci and noncancerous tissue on the maps of mean diffusivity (MD) and fractional anisotropy (FA) were used to extract the minimum, the maximum and the mean measures. Measure ratio was computed by dividing tumor measure by noncancerous tissue measure. Logistic regression models were fitted for all possible pair combinations of the measures using 5-fold cross validation. Systematic differences are present for all MD measures and also for all FA measures in distinguishing the high risk tumors [GS ≥ 7(4 + 3)] from the low risk tumors [GS ≤ 7(3 + 4)] (P Logistic regression modelling provides a favorable solution for the joint evaluations easily adoptable in clinical practice. Copyright © 2018 Elsevier Inc. All rights reserved.

  19. The Topology of Symmetric Tensor Fields

    Science.gov (United States)

    Levin, Yingmei; Batra, Rajesh; Hesselink, Lambertus; Levy, Yuval

    1997-01-01

    Combinatorial topology, also known as "rubber sheet geometry", has extensive applications in geometry and analysis, many of which result from connections with the theory of differential equations. A link between topology and differential equations is vector fields. Recent developments in scientific visualization have shown that vector fields also play an important role in the analysis of second-order tensor fields. A second-order tensor field can be transformed into its eigensystem, namely, eigenvalues and their associated eigenvectors without loss of information content. Eigenvectors behave in a similar fashion to ordinary vectors with even simpler topological structures due to their sign indeterminacy. Incorporating information about eigenvectors and eigenvalues in a display technique known as hyperstreamlines reveals the structure of a tensor field. The simplify and often complex tensor field and to capture its important features, the tensor is decomposed into an isotopic tensor and a deviator. A tensor field and its deviator share the same set of eigenvectors, and therefore they have a similar topological structure. A a deviator determines the properties of a tensor field, while the isotopic part provides a uniform bias. Degenerate points are basic constituents of tensor fields. In 2-D tensor fields, there are only two types of degenerate points; while in 3-D, the degenerate points can be characterized in a Q'-R' plane. Compressible and incompressible flows share similar topological feature due to the similarity of their deviators. In the case of the deformation tensor, the singularities of its deviator represent the area of vortex core in the field. In turbulent flows, the similarities and differences of the topology of the deformation and the Reynolds stress tensors reveal that the basic addie-viscosity assuptions have their validity in turbulence modeling under certain conditions.

  20. Radiation-Induced Changes in Normal-Appearing White Matter in Patients With Cerebral Tumors: A Diffusion Tensor Imaging Study

    International Nuclear Information System (INIS)

    Nagesh, Vijaya; Tsien, Christina I.; Chenevert, Thomas L.; Ross, Brian D.; Lawrence, Theodore S.; Junick, Larry; Cao Yue

    2008-01-01

    Purpose: To quantify the radiation-induced changes in normal-appearing white matter before, during, and after radiotherapy (RT) in cerebral tumor patients. Methods and Materials: Twenty-five patients with low-grade glioma, high-grade glioma, or benign tumor treated with RT were studied using diffusion tensor magnetic resonance imaging. The biologically corrected doses ranged from 50 to 81 Gy. The temporal changes were assessed before, during, and to 45 weeks after the start of RT. The mean diffusivity of water ( ), fractional anisotropy of diffusion, diffusivity perpendicular (λ perpendicular ) and parallel (λ parallel ) to white matter fibers were calculated in normal-appearing genu and splenium of the corpus callosum. Results: In the genu and splenium, fractional anisotropy decreased and , λ parallel , λ -perpendicular increased linearly and significantly with time (p -perpendicular had increased ∼30% in the genu and splenium, and λ parallel had increased 5% in the genu and 9% in the splenium, suggesting that demyelination is predominant. The increases in λ perpendicular and λ parallel were dose dependent, starting at 3 weeks and continuing to 32 weeks from the start of RT. The dose-dependent increase in λ perpendicular and λ parallel was not sustained after 32 weeks, indicating the transition from focal to diffuse effects. Conclusion: The acute and subacute changes in normal-appearing white matter fibers indicate radiation-induced demyelination and mild structural degradation of axonal fibers. The structural changes after RT are progressive, with early dose-dependent demyelination and subsequent diffuse dose-independent demyelination and mild axonal degradation. Diffusion tensor magnetic resonance imaging is potentially a biomarker for the assessment of radiation-induced white matter injury

  1. Diffusion tensor imaging of the spinal cord at 1.5 and 3.0 Tesla

    Energy Technology Data Exchange (ETDEWEB)

    Rossi, C. [Radiologische Universitaetsklinik, Tuebingen (Germany). Sektion fuer Experimentelle Radiologie; CNR-INFM CRS-Soft, La Sapienza-Univ. Roma (Italy); Enrico Fern Center, Roma (Italy); Boss, A.; Martirosian, P.; Steidle, G.; Schick, F. [Radiologische Universitaetsklinik, Tuebingen (Germany). Sektion fuer Experimentelle Radiologie; Lindig, T.M. [Enrico Fern Center, Roma (Italy); Radiologische Universitaetsklinik, Tuebingen (Germany). Sektion fuer Experimentelle Kernspinresonanz des ZNS; Universitaetsklinikum Tuebingen (Germany). Zentrum fuer Neurologie und Hertie-Inst. fuer klinische Hirnforschung; Maetzler, W. [Universitaetsklinikum Tuebingen (Germany). Zentrum fuer Neurologie und Hertie-Inst. fuer klinische Hirnforschung; Claussen, C.D. [Radiologische Universitaetsklinik, Tuebingen (Germany). Abt. fuer Radiologische Diagnostik; Klose, U. [Radiologische Universitaetsklinik, Tuebingen (Germany). Sektion fuer Experimentelle Kernspinresonanz des ZNS

    2007-03-15

    Purpose: The feasibility of highly resolved diffusion tensor imaging (DTI) of the human cervical spinal cord was tested on a clinical MR unit operating at 3.0 Tesla. DTI parametrical maps and signal-to-noise ratios (SNRs) were compared to results recorded at 1.5 Tesla. Materials and Methods: Eight healthy volunteers and one patient participated in the study. A transverse oriented single-shot ECG-triggered echo-planar imaging (EPI) sequence with double spin-echo diffusion preparation was applied for highly resolved DTI of the spinal cord. The signal yield, fractional anisotropy (FA), and mean diffusivity (MD) were compared for both field strengths. The clinical applicability of the protocol was also tested in one patient with amyotrophic lateral sclerosis (ALS) at 3.0 T. Results: A mean increase in SNR of 95.7 {+-} 4.6% was found at 3.0 Tesla compared to 1.5 Tesla. Improved quality of the DTI parametrical maps was observed at higher field strength (p < 0.02). Comparable FA and MD (reported in units of 10 - 3 mm2/s) values were computed in the dorsal white matter at both field strengths (1.5 T: FA = 0.75 {+-} 0.08, MD = 0.84 {+-} 0.12, 3.0 T: FA = 0.74 {+-} 0.04, MD = 0.93 {+-} 0.14). The DTI images exhibited diagnostic image quality in the patient. At the site of the diseased corticospinal tract, a decrease of 46.0 {+-} 3.8% in FA (0.40 {+-} 0.03) and an increase of 50.3 {+-} 5.6% in MD (1.40 {+-} 0.05) were found in the ALS patient. (orig.)

  2. Diffusion tensor imaging of the spinal cord at 1.5 and 3.0 Tesla

    International Nuclear Information System (INIS)

    Rossi, C.; Boss, A.; Martirosian, P.; Steidle, G.; Schick, F.; Lindig, T.M.; Radiologische Universitaetsklinik, Tuebingen; Universitaetsklinikum Tuebingen; Maetzler, W.; Claussen, C.D.; Klose, U.

    2007-01-01

    Purpose: The feasibility of highly resolved diffusion tensor imaging (DTI) of the human cervical spinal cord was tested on a clinical MR unit operating at 3.0 Tesla. DTI parametrical maps and signal-to-noise ratios (SNRs) were compared to results recorded at 1.5 Tesla. Materials and Methods: Eight healthy volunteers and one patient participated in the study. A transverse oriented single-shot ECG-triggered echo-planar imaging (EPI) sequence with double spin-echo diffusion preparation was applied for highly resolved DTI of the spinal cord. The signal yield, fractional anisotropy (FA), and mean diffusivity (MD) were compared for both field strengths. The clinical applicability of the protocol was also tested in one patient with amyotrophic lateral sclerosis (ALS) at 3.0 T. Results: A mean increase in SNR of 95.7 ± 4.6% was found at 3.0 Tesla compared to 1.5 Tesla. Improved quality of the DTI parametrical maps was observed at higher field strength (p < 0.02). Comparable FA and MD (reported in units of 10 - 3 mm2/s) values were computed in the dorsal white matter at both field strengths (1.5 T: FA = 0.75 ± 0.08, MD = 0.84 ± 0.12, 3.0 T: FA 0.74 ± 0.04, MD = 0.93 ± 0.14). The DTI images exhibited diagnostic image quality in the patient. At the site of the diseased corticospinal tract, a decrease of 46.0 ± 3.8% in FA (0.40 ± 0.03) and an increase of 50.3 ± 5.6% in MD (1.40 ± 0.05) were found in the ALS patient. (orig.)

  3. Tunable Tensor Voting Improves Grouping of Membrane-Bound Macromolecules

    Energy Technology Data Exchange (ETDEWEB)

    Loss, Leandro A.; Bebis, George; Parvin, Bahram

    2009-04-15

    Membrane-bound macromolecules are responsible for structural support and mediation of cell-cell adhesion in tissues. Quantitative analysis of these macromolecules provides morphological indices for damage or loss of tissue, for example as a result of exogenous stimuli. From an optical point of view, a membrane signal may have nonuniform intensity around the cell boundary, be punctate or diffused, and may even be perceptual at certain locations along the boundary. In this paper, a method for the detection and grouping of punctate, diffuse curvilinear signals is proposed. Our work builds upon the tensor voting and the iterative voting frameworks to propose an efficient method to detect and refine perceptually interesting curvilinear structures in images. The novelty of our method lies on the idea of iteratively tuning the tensor voting fields, which allows the concentration of the votes only over areas of interest. We validate the utility of our system with synthetic and annotated real data. The effectiveness of the tunable tensor voting is demonstrated on complex phenotypic signals that are representative of membrane-bound macromolecular structures.

  4. In vivo 3D neuroanatomical evaluation of periprostatic nerve plexus with 3T-MR Diffusion Tensor Imaging

    International Nuclear Information System (INIS)

    Panebianco, Valeria; Barchetti, Flavio; Sciarra, Alessandro; Marcantonio, Andrea; Zini, Chiara; Salciccia, Stefano; Collettini, Federico; Gentile, Vincenzo; Hamm, Bernard; Catalano, Carlo

    2013-01-01

    Objectives: To evaluate if Diffusion Tensor Imaging technique (DTI) can improve the visualization of periprostatic nerve fibers describing the location and distribution of entire neurovascular plexus around the prostate in patients who are candidates for prostatectomy. Materials and methods: Magnetic Resonance Imaging (MRI), including a 2D T2-weighted FSE sequence in 3 planes, 3D T2-weighted and DTI using 16 gradient directions and b = 0 and 1000, was performed on 36 patients. Three out of 36 patients were excluded from the analysis due to poor image quality (blurring N = 2, artifact N = 1). The study was approved by local ethics committee and all patients gave an informed consent. Images were evaluated by two radiologists with different experience in MRI. DTI images were analyzed qualitatively using dedicated software. Also 2D and 3D T2 images were independently considered. Results: 3D-DTI allowed description of the entire plexus of the periprostatic nerve fibers in all directions, while 2D and 3D T2 morphological sequences depicted part of the fibers, in a plane by plane analysis of fiber courses. DTI demonstrated in all patients the dispersion of nerve fibers around the prostate on both sides including the significant percentage present in the anterior and anterolateral sectors. Conclusions: DTI offers optimal representation of the widely distributed periprostatic plexus. If validated, it may help guide nerve-sparing radical prostatectomy

  5. Random SU(2) invariant tensors

    Science.gov (United States)

    Li, Youning; Han, Muxin; Ruan, Dong; Zeng, Bei

    2018-04-01

    SU(2) invariant tensors are states in the (local) SU(2) tensor product representation but invariant under the global group action. They are of importance in the study of loop quantum gravity. A random tensor is an ensemble of tensor states. An average over the ensemble is carried out when computing any physical quantities. The random tensor exhibits a phenomenon known as ‘concentration of measure’, which states that for any bipartition the average value of entanglement entropy of its reduced density matrix is asymptotically the maximal possible as the local dimensions go to infinity. We show that this phenomenon is also true when the average is over the SU(2) invariant subspace instead of the entire space for rank-n tensors in general. It is shown in our earlier work Li et al (2017 New J. Phys. 19 063029) that the subleading correction of the entanglement entropy has a mild logarithmic divergence when n  =  4. In this paper, we show that for n  >  4 the subleading correction is not divergent but a finite number. In some special situation, the number could be even smaller than 1/2, which is the subleading correction of random state over the entire Hilbert space of tensors.

  6. White matter microstructure in transsexuals and controls investigated by diffusion tensor imaging.

    Science.gov (United States)

    Kranz, Georg S; Hahn, Andreas; Kaufmann, Ulrike; Küblböck, Martin; Hummer, Allan; Ganger, Sebastian; Seiger, Rene; Winkler, Dietmar; Swaab, Dick F; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

    2014-11-12

    Biological causes underpinning the well known gender dimorphisms in human behavior, cognition, and emotion have received increased attention in recent years. The advent of diffusion-weighted magnetic resonance imaging has permitted the investigation of the white matter microstructure in unprecedented detail. Here, we aimed to study the potential influences of biological sex, gender identity, sex hormones, and sexual orientation on white matter microstructure by investigating transsexuals and healthy controls using diffusion tensor imaging (DTI). Twenty-three female-to-male (FtM) and 21 male-to-female (MtF) transsexuals, as well as 23 female (FC) and 22 male (MC) controls underwent DTI at 3 tesla. Fractional anisotropy, axial, radial, and mean diffusivity were calculated using tract-based spatial statistics (TBSS) and fiber tractography. Results showed widespread significant differences in mean diffusivity between groups in almost all white matter tracts. FCs had highest mean diffusivities, followed by FtM transsexuals with lower values, MtF transsexuals with further reduced values, and MCs with lowest values. Investigating axial and radial diffusivities showed that a transition in axial diffusivity accounted for mean diffusivity results. No significant differences in fractional anisotropy maps were found between groups. Plasma testosterone levels were strongly correlated with mean, axial, and radial diffusivities. However, controlling for individual estradiol, testosterone, or progesterone plasma levels or for subjects' sexual orientation did not change group differences. Our data harmonize with the hypothesis that fiber tract development is influenced by the hormonal environment during late prenatal and early postnatal brain development. Copyright © 2014 the authors 0270-6474/14/3415466-10$15.00/0.

  7. White Matter Microstructure in Transsexuals and Controls Investigated by Diffusion Tensor Imaging

    Science.gov (United States)

    Kranz, Georg S.; Hahn, Andreas; Kaufmann, Ulrike; Küblböck, Martin; Hummer, Allan; Ganger, Sebastian; Seiger, Rene; Winkler, Dietmar; Swaab, Dick F.; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

    2015-01-01

    Biological causes underpinning the well known gender dimorphisms in human behavior, cognition, and emotion have received increased attention in recent years. The advent of diffusion-weighted magnetic resonance imaging has permitted the investigation of the white matter microstructure in unprecedented detail. Here, we aimed to study the potential influences of biological sex, gender identity, sex hormones, and sexual orientation on white matter microstructure by investigating transsexuals and healthy controls using diffusion tensor imaging (DTI). Twenty-three female-to-male (FtM) and 21 male-to-female (MtF) transsexuals, as well as 23 female (FC) and 22 male (MC) controls underwent DTI at 3 tesla. Fractional anisotropy, axial, radial, and mean diffusivity were calculated using tract-based spatial statistics (TBSS) and fiber tractography. Results showed widespread significant differences in mean diffusivity between groups in almost all white matter tracts. FCs had highest mean diffusivities, followed by FtM transsexuals with lower values, MtF transsexuals with further reduced values, and MCs with lowest values. Investigating axial and radial diffusivities showed that a transition in axial diffusivity accounted for mean diffusivity results. No significant differences in fractional anisotropy maps were found between groups. Plasma testosterone levels were strongly correlated with mean, axial, and radial diffusivities. However, controlling for individual estradiol, testosterone, or progesterone plasma levels or for subjects’ sexual orientation did not change group differences. Our data harmonize with the hypothesis that fiber tract development is influenced by the hormonal environment during late prenatal and early postnatal brain development. PMID:25392513

  8. Diffusion tensor imaging and fiber tractography in cervical compressive myelopathy: preliminary results

    International Nuclear Information System (INIS)

    Lee, Joon Woo; Kim, Jae Hyoung; Park, Jong Bin; Lee, Guen Young; Kang, Heung Sik; Park, Kun Woo; Yeom, Jin S.

    2011-01-01

    To assess diffusion tensor imaging (DTI) parameters in cervical compressive myelopathy (CCM) patients compared to normal volunteers, to relate them with myelopathy severity, and to relate tractography patterns with postoperative neurologic improvement. Twenty patients suffering from CCM were prospectively enrolled (M:F = 13:7, mean age, 49.6 years; range 22-67 years) from September 2009 to March 2010. Sensitivity encoding (SENSE) single-shot echo-planar imaging (EPI) was used for the sagittal DTI. Twenty sex- and age-matched normal volunteers underwent the same scanning procedure. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values in the spinal cord were compared between the patients and normal volunteers and were related to myelopathy severity based on Japanese Orthopedic Association (JOA) scores. Tractography patterns were related to myelopathy severity and postoperative improvement. There were significant differences between patients and normal volunteers in terms of FA (0.498 ± 0.114 vs. 0.604 ± 0.057; p = 0.001) and ADC (1.442 ± 0.389 vs. 1.169 ± 0.098; p = 0.001). DTI parameters and tractography patterns were not related to myelopathy severity. In ten patients in the neurologically worse group, postoperative neurologic improvement was seen in four of five patients with intact fiber tracts, but only one of five patients with interrupted fiber tracts exhibited neurologic improvement. DTI parameters in CCM patients were significantly different from those in normal volunteers but were not significantly related to myelopathy severity. The patterns of tractography appear to correlate with postoperative neurologic improvement. (orig.)

  9. Improved tensor multiplets

    International Nuclear Information System (INIS)

    Wit, B. de; Rocek, M.

    1982-01-01

    We construct a conformally invariant theory of the N = 1 supersymmetric tensor gauge multiplet and discuss the situation in N = 2. We show that our results give rise to the recently proposed variant of Poincare supergravity, and provide the complete tensor calculus for the theory. Finally, we argue that this theory cannot be quantized sensibly. (orig.)

  10. MR diffusion tensor analysis of schizophrenic brain using statistical parametric mapping

    International Nuclear Information System (INIS)

    Yamada, Haruyasu; Abe, Osamu; Kasai, Kiyoto

    2005-01-01

    The purpose of this study is to investigate diffusion anisotropy in the schizophrenic brain by voxel-based analysis of diffusion tensor imaging (DTI), using statistical parametric mapping (SPM). We studied 33 patients with schizophrenia diagnosed by diagnostic and statistical manual of mental disorders (DSM)-IV criteria and 42 matched controls. The data was obtained with a 1.5 T MRI system. We used single-shot spin-echo planar sequences (repetition time/echo time (TR/TE)=5000/102 ms, 5 mm slice thickness and 1.5 mm gap, field of view (FOV)=21 x 21 cm 2 , number of excitation (NEX)=4, 128 x 128 pixel matrix) for diffusion tensor acquisition. Diffusion gradients (b-value of 500 or 1000 s/mm 2 ) were applied on two axes simultaneously. Diffusion properties were measured along 6 non-linear directions. The structural distortion induced by the large diffusion gradients was corrected, based on each T 2 -weighted echo-planar image (b=0 s/mm 2 ). The fractional anisotropy (FA) maps were generated on a voxel-by-voxel basis. T 2 -weighted echo-planar images were then segmented into gray matter, white matter, and cerebrospinal fluid, using SPM (Wellcome Department of Imaging, University College London, UK). All apparent diffusion coefficient (ADC) and FA maps in native space were transformed to the stereotactic space by registering each of the images to the same template image. The normalized data was smoothed and analyzed using SPM. The significant FA decrease in the patient group was found in the uncinate fasciculus, parahippocampal white matter, anterior cingulum and other areas (corrected p<0.05). No significant increased region was noted. Our results may reflect reduced diffusion anisotropy of the white matter pathway of the limbic system as shown by the decreased FA. Manual region-of-interest analysis is usually more sensitive than voxel-based analysis, but it is subjective and difficult to set with anatomical reproducibility. Voxel-based analysis of the diffusion tensor

  11. The evolution of tensor polarization

    International Nuclear Information System (INIS)

    Huang, H.; Lee, S.Y.; Ratner, L.

    1993-01-01

    By using the equation of motion for the vector polarization, the spin transfer matrix for spin tensor polarization, the spin transfer matrix for spin tensor polarization is derived. The evolution equation for the tensor polarization is studied in the presence of an isolate spin resonance and in the presence of a spin rotor, or snake

  12. Tensor-based morphometry of fibrous structures with application to human brain white matter.

    Science.gov (United States)

    Zhang, Hui; Yushkevich, Paul A; Rueckert, Daniel; Gee, James C

    2009-01-01

    Tensor-based morphometry (TBM) is a powerful approach for examining shape changes in anatomy both across populations and in time. Our work extends the standard TBM for quantifying local volumetric changes to establish both rich and intuitive descriptors of shape changes in fibrous structures. It leverages the data from diffusion tensor imaging to determine local spatial configuration of fibrous structures and combines this information with spatial transformations derived from image registration to quantify fibrous structure-specific changes, such as local changes in fiber length and in thickness of fiber bundles. In this paper, we describe the theoretical framework of our approach in detail and illustrate its application to study brain white matter. Our results show that additional insights can be gained with the proposed analysis.

  13. Tensor algebra and tensor analysis for engineers with applications to continuum mechanics

    CERN Document Server

    Itskov, Mikhail

    2015-01-01

    This is the fourth and revised edition of a well-received book that aims at bridging the gap between the engineering course of tensor algebra on the one side and the mathematical course of classical linear algebra on the other side. In accordance with the contemporary way of scientific publications, a modern absolute tensor notation is preferred throughout. The book provides a comprehensible exposition of the fundamental mathematical concepts of tensor calculus and enriches the presented material with many illustrative examples. In addition, the book also includes advanced chapters dealing with recent developments in the theory of isotropic and anisotropic tensor functions and their applications to continuum mechanics. Hence, this monograph addresses graduate students as well as scientists working in this field. In each chapter numerous exercises are included, allowing for self-study and intense practice. Solutions to the exercises are also provided.

  14. Diffusion tensor imaging and neuromodulation: DTI as key technology for deep brain stimulation.

    Science.gov (United States)

    Coenen, Volker Arnd; Schlaepfer, Thomas E; Allert, Niels; Mädler, Burkhard

    2012-01-01

    Diffusion tensor imaging (DTI) is more than just a useful adjunct to invasive techniques like optogenetics which recently have tremendously influenced our understanding of the mechanisms of deep brain stimulation (DBS). In combination with other technologies, DTI helps us to understand which parts of the brain tissue are connected to others and which ones are truly influenced with neuromodulation. The complex interaction of DBS with the surrounding tissues-scrutinized with DTI-allows to create testable hypotheses that can explain network interactions. Those interactions are vital for our understanding of the net effects of neuromodulation. This work naturally was first done in the field of movement disorder surgery, where a lot of experience regarding therapeutic effects and only a short latency between initiation of neuromodulation and alleviation of symptoms exist. This chapter shows the journey over the past 10 years with first applications in DBS toward current research in affect regulating network balances and their therapeutic alterations with the neuromodulation technology. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Tensor Calculus: Unlearning Vector Calculus

    Science.gov (United States)

    Lee, Wha-Suck; Engelbrecht, Johann; Moller, Rita

    2018-01-01

    Tensor calculus is critical in the study of the vector calculus of the surface of a body. Indeed, tensor calculus is a natural step-up for vector calculus. This paper presents some pitfalls of a traditional course in vector calculus in transitioning to tensor calculus. We show how a deeper emphasis on traditional topics such as the Jacobian can…

  16. Link prediction via generalized coupled tensor factorisation

    DEFF Research Database (Denmark)

    Ermiş, Beyza; Evrim, Acar Ataman; Taylan Cemgil, A.

    2012-01-01

    and higher-order tensors. We propose to use an approach based on probabilistic interpretation of tensor factorisation models, i.e., Generalised Coupled Tensor Factorisation, which can simultaneously fit a large class of tensor models to higher-order tensors/matrices with com- mon latent factors using...... different loss functions. Numerical experiments demonstrate that joint analysis of data from multiple sources via coupled factorisation improves the link prediction performance and the selection of right loss function and tensor model is crucial for accurately predicting missing links....

  17. Sonographic and MRI appearance of tensor fasciae suralis muscle, an uncommon cause of popliteal swelling

    International Nuclear Information System (INIS)

    Montet, Xavier; Mauget, Denis; Sandoz, Alain; Martinoli, Carlo; Bianchi, Stefano

    2002-01-01

    A 20-year-old white man presented with a localized unilateral swelling in the popliteal fossa. Ultrasound (US) showed the presence of an accessory muscle, the tensor fasciae suralis. The muscle was located in the proximal portion of the popliteal fossa, superficial to the medial head of the gastrocnemius. Its long tendon extended inferiorly to join the Achilles tendon. Magnetic resonance images correlated well with the US findings, confirming the diagnosis. Tensor fasciae suralis muscle is a rare cause of popliteal swelling and must be differentiated from other masses. Both US and magnetic resonance imaging can diagnose it but we suggest US as the first-line technique in its evaluation. (orig.)

  18. Combined brain voxel-based morphometry and diffusion tensor imaging study in idiopathic restless legs syndrome patients.

    Science.gov (United States)

    Rizzo, G; Manners, D; Vetrugno, R; Tonon, C; Malucelli, E; Plazzi, G; Marconi, S; Pizza, F; Testa, C; Provini, F; Montagna, P; Lodi, R

    2012-07-01

      The aim of this study was to evaluate the presence of abnormalities in the brain of patients with restless legs syndrome (RLS) using voxel-based morphometry and diffusion tensor imaging (DTI).   Twenty patients and twenty controls were studied. Voxel-based morphometry analysis was performed using statistical parametric mapping (SPM8) and FSL-VBM software tools. For voxel-wise analysis of DTI, tract-based spatial statistics (TBSS) and SPM8 were used.   Applying an appropriate threshold of probability, no significant results were found either in comparison or in correlation analyses.   Our data argue against clear structural or microstructural abnormalities in the brain of patients with idiopathic RLS, suggesting a prevalent role of functional or metabolic impairment. © 2011 The Author(s) European Journal of Neurology © 2011 EFNS.

  19. Bilateral Tensor Fasciae Suralis Muscles in a Cadaver with Unilateral Accessory Flexor Digitorum Longus Muscle

    Directory of Open Access Journals (Sweden)

    Logan S. W. Bale

    2017-01-01

    Full Text Available Muscle variants are routinely encountered in the dissection laboratory and in clinical practice and therefore anatomists and clinicians need to be aware of their existence. Here we describe two different accessory muscles identified while performing educational dissection of a 51-year-old male cadaver. Tensor fasciae suralis, a rare muscle variant, was identified bilaterally and accessory flexor digitorum longus, a more common muscle variant, was present unilaterally. Tensor fasciae suralis and accessory flexor digitorum longus are clinically relevant muscle variants. To our knowledge, the coexistence of tensor fasciae suralis and accessory flexor digitorum longus in the same individual has not been reported in either cadaveric or imaging studies.

  20. Energy-momentum tensor of the electromagnetic field

    International Nuclear Information System (INIS)

    Horndeski, G.W.; Wainwright, J.

    1977-01-01

    In this paper we investigate the energy-momentum tensor of the most general second-order vector-tensor theory of gravitation and electromagnetism which has field equations which are (i) derivable from a variational principle, (ii) consistent with the notion of conservation of charge, and (iii) compatible with Maxwell's equations in a flat space. This energy-momentum tensor turns out to be quadratic in the first partial derivatives of the electromagnetic field tensor and depends upon the curvature tensor. The asymptotic behavior of this energy-momentum tensor is examined for solutions to Maxwell's equations in Minkowski space, and it is demonstrated that this energy-momentum tensor predicts regions of negative energy density in the vicinity of point sources

  1. Comparing a diffusion tensor and non-tensor approach to white matter fiber tractography in chronic stroke.

    Science.gov (United States)

    Auriat, A M; Borich, M R; Snow, N J; Wadden, K P; Boyd, L A

    2015-01-01

    Diffusion tensor imaging (DTI)-based tractography has been used to demonstrate functionally relevant differences in white matter pathway status after stroke. However, it is now known that the tensor model is insensitive to the complex fiber architectures found in the vast majority of voxels in the human brain. The inability to resolve intra-voxel fiber orientations may have important implications for the utility of standard DTI-based tract reconstruction methods. Intra-voxel fiber orientations can now be identified using novel, tensor-free approaches. Constrained spherical deconvolution (CSD) is one approach to characterize intra-voxel diffusion behavior. In the current study, we performed DTI- and CSD-based tract reconstruction of the corticospinal tract (CST) and corpus callosum (CC) to test the hypothesis that characterization of complex fiber orientations may improve the robustness of fiber tract reconstruction and increase the sensitivity to identify functionally relevant white matter abnormalities in individuals with chronic stroke. Diffusion weighted magnetic resonance imaging was performed in 27 chronic post-stroke participants and 12 healthy controls. Transcallosal pathways and the CST bilaterally were reconstructed using DTI- and CSD-based tractography. Mean fractional anisotropy (FA), apparent diffusion coefficient (ADC), axial diffusivity (AD), and radial diffusivity (RD) were calculated across the tracts of interest. The total number and volume of reconstructed tracts was also determined. Diffusion measures were compared between groups (Stroke, Control) and methods (CSD, DTI). The relationship between post-stroke motor behavior and diffusion measures was evaluated. Overall, CSD methods identified more tracts than the DTI-based approach for both CC and CST pathways. Mean FA, ADC, and RD differed between DTI and CSD for CC-mediated tracts. In these tracts, we discovered a difference in FA for the CC between stroke and healthy control groups using CSD but

  2. Comparing a diffusion tensor and non-tensor approach to white matter fiber tractography in chronic stroke

    Directory of Open Access Journals (Sweden)

    A.M. Auriat

    2015-01-01

    Full Text Available Diffusion tensor imaging (DTI-based tractography has been used to demonstrate functionally relevant differences in white matter pathway status after stroke. However, it is now known that the tensor model is insensitive to the complex fiber architectures found in the vast majority of voxels in the human brain. The inability to resolve intra-voxel fiber orientations may have important implications for the utility of standard DTI-based tract reconstruction methods. Intra-voxel fiber orientations can now be identified using novel, tensor-free approaches. Constrained spherical deconvolution (CSD is one approach to characterize intra-voxel diffusion behavior. In the current study, we performed DTI- and CSD-based tract reconstruction of the corticospinal tract (CST and corpus callosum (CC to test the hypothesis that characterization of complex fiber orientations may improve the robustness of fiber tract reconstruction and increase the sensitivity to identify functionally relevant white matter abnormalities in individuals with chronic stroke. Diffusion weighted magnetic resonance imaging was performed in 27 chronic post-stroke participants and 12 healthy controls. Transcallosal pathways and the CST bilaterally were reconstructed using DTI- and CSD-based tractography. Mean fractional anisotropy (FA, apparent diffusion coefficient (ADC, axial diffusivity (AD, and radial diffusivity (RD were calculated across the tracts of interest. The total number and volume of reconstructed tracts was also determined. Diffusion measures were compared between groups (Stroke, Control and methods (CSD, DTI. The relationship between post-stroke motor behavior and diffusion measures was evaluated. Overall, CSD methods identified more tracts than the DTI-based approach for both CC and CST pathways. Mean FA, ADC, and RD differed between DTI and CSD for CC-mediated tracts. In these tracts, we discovered a difference in FA for the CC between stroke and healthy control groups

  3. Active brain changes after initiating fingolimod therapy in multiple sclerosis patients using individual voxel-based analyses for diffusion tensor imaging.

    Science.gov (United States)

    Senda, Joe; Watanabe, Hirohisa; Endo, Kuniyuki; Yasui, Keizo; Hawsegawa, Yasuhiro; Yoneyama, Noritaka; Tsuboi, Takashi; Hara, Kazuhiro; Ito, Mizuki; Atsuta, Naoki; Epifanio, Bagarinao; Katsuno, Masahisa; Naganawa, Shinji; Sobue, Gen

    2016-12-01

    Voxel-based analysis (VBA) of diffusion tensor images (DTI) and voxel-based morphometry (VBM) in patients with multiple sclerosis (MS) can sensitively detect occult tissue damage that underlies pathological changes in the brain. In the present study, both at the start of fingolimod and post-four months clinical remission, we assessed four patients with MS who were evaluated with VBA of DTI, VBM, and fluid-attenuated inversion recovery (FLAIR). DTI images for all four patients showed widespread areas of increased mean diffusivity (MD) and decreased fractional anisotropy (FA) that were beyond the high-intensity signal areas across images. After four months of continuous fingolimod therapy, DTI abnormalities progressed; in particular, MD was significantly increased, while brain volume and high-intensity signals were unchanged. These findings suggest that VBA of DTI (e.g., MD) may help assess MS demyelination as neuroinflammatory conditions, even though clinical manifestations of MS appear to be in complete remission during fingolimod.

  4. A new Weyl-like tensor of geometric origin

    Science.gov (United States)

    Vishwakarma, Ram Gopal

    2018-04-01

    A set of new tensors of purely geometric origin have been investigated, which form a hierarchy. A tensor of a lower rank plays the role of the potential for the tensor of one rank higher. The tensors have interesting mathematical and physical properties. The highest rank tensor of the hierarchy possesses all the geometrical properties of the Weyl tensor.

  5. Tensor calculus for physics a concise guide

    CERN Document Server

    Neuenschwander, Dwight E

    2015-01-01

    Understanding tensors is essential for any physics student dealing with phenomena where causes and effects have different directions. A horizontal electric field producing vertical polarization in dielectrics; an unbalanced car wheel wobbling in the vertical plane while spinning about a horizontal axis; an electrostatic field on Earth observed to be a magnetic field by orbiting astronauts—these are some situations where physicists employ tensors. But the true beauty of tensors lies in this fact: When coordinates are transformed from one system to another, tensors change according to the same rules as the coordinates. Tensors, therefore, allow for the convenience of coordinates while also transcending them. This makes tensors the gold standard for expressing physical relationships in physics and geometry. Undergraduate physics majors are typically introduced to tensors in special-case applications. For example, in a classical mechanics course, they meet the "inertia tensor," and in electricity and magnetism...

  6. Tensor norms and operator ideals

    CERN Document Server

    Defant, A; Floret, K

    1992-01-01

    The three chapters of this book are entitled Basic Concepts, Tensor Norms, and Special Topics. The first may serve as part of an introductory course in Functional Analysis since it shows the powerful use of the projective and injective tensor norms, as well as the basics of the theory of operator ideals. The second chapter is the main part of the book: it presents the theory of tensor norms as designed by Grothendieck in the Resumé and deals with the relation between tensor norms and operator ideals. The last chapter deals with special questions. Each section is accompanied by a series of exer

  7. Machine Learning Interface for Medical Image Analysis.

    Science.gov (United States)

    Zhang, Yi C; Kagen, Alexander C

    2017-10-01

    TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

  8. Post-mortem cardiac diffusion tensor imaging: detection of myocardial infarction and remodeling of myofiber architecture

    International Nuclear Information System (INIS)

    Winklhofer, Sebastian; Berger, Nicole; Stolzmann, Paul; Stoeck, Christian T.; Kozerke, Sebastian; Thali, Michael; Manka, Robert; Alkadhi, Hatem

    2014-01-01

    To investigate the accuracy of post-mortem diffusion tensor imaging (DTI) for the detection of myocardial infarction (MI) and to demonstrate the feasibility of helix angle (HA) calculation to study remodelling of myofibre architecture. Cardiac DTI was performed in 26 deceased subjects prior to autopsy for medicolegal reasons. Fractional anisotropy (FA) and mean diffusivity (MD) were determined. Accuracy was calculated on per-segment (AHA classification), per-territory, and per-patient basis, with pathology as reference standard. HAs were calculated and compared between healthy segments and those with MI. Autopsy demonstrated MI in 61/440 segments (13.9 %) in 12/26 deceased subjects. Healthy myocardial segments had significantly higher FA (p 0.05). Post-mortem cardiac DTI enablesdifferentiation between healthy and infarcted myocardial segments by means of FA and MD. HA assessment allows for the demonstration of remodelling of myofibre architecture following chronic MI. (orig.)

  9. Primary progressive aphasia patients evaluated using diffusion tensor imaging and voxel based volumetry-preliminary results

    Directory of Open Access Journals (Sweden)

    Fábio Pascotto de Oliveira

    2011-06-01

    Full Text Available There are individuals who have a progressive language deficit without presenting cognitive deficits in other areas. One of the diseases related to this presentation is primary progressive aphasia (PPA. OBJECTIVE: Identify by means of diffusion tensor imaging (DTI and measurements of cortical volume, brain areas that lead to dysphasia when presenting signs of impaired connectivity or reduced volume. METHOD: Four patients with PPA were evaluated using DTI, and measurements of cortical volumes in temporal areas. These patients were compared with two normal volunteers. RESULTS: There is a trend to a difference in the number and volume of related fibers between control group and patients with PPA. Comparing cortical volumes in temporal areas between groups yielded a trend to a smaller volume in PPA patients. CONCLUSION: Patients with PPA have a trend to impairment in cortical and subcortical levels regarding relevant areas.

  10. Evaluation of diffusion-tensor imaging-based global search and tractography for tumor surgery close to the language system.

    Directory of Open Access Journals (Sweden)

    Mirco Richter

    Full Text Available Pre-operative planning and intra-operative guidance in neurosurgery require detailed information about the location of functional areas and their anatomo-functional connectivity. In particular, regarding the language system, post-operative deficits such as aphasia can be avoided. By combining functional magnetic resonance imaging and diffusion tensor imaging, the connectivity between functional areas can be reconstructed by tractography techniques that need to cope with limitations such as limited resolution and low anisotropic diffusion close to functional areas. Tumors pose particular challenges because of edema, displacement effects on brain tissue and infiltration of white matter. Under these conditions, standard fiber tracking methods reconstruct pathways of insufficient quality. Therefore, robust global or probabilistic approaches are required. In this study, two commonly used standard fiber tracking algorithms, streamline propagation and tensor deflection, were compared with a previously published global search, Gibbs tracking and a connection-oriented probabilistic tractography approach. All methods were applied to reconstruct neuronal pathways of the language system of patients undergoing brain tumor surgery, and control subjects. Connections between Broca and Wernicke areas via the arcuate fasciculus (AF and the inferior fronto-occipital fasciculus (IFOF were validated by a clinical expert to ensure anatomical feasibility, and compared using distance- and diffusion-based similarity metrics to evaluate their agreement on pathway locations. For both patients and controls, a strong agreement between all methods was observed regarding the location of the AF. In case of the IFOF however, standard fiber tracking and Gibbs tracking predominantly identified the inferior longitudinal fasciculus that plays a secondary role in semantic language processing. In contrast, global search resolved connections in almost every case via the IFOF which

  11. Quantification of diffusion tensor imaging in normal white matter maturation of early childhood using an automated processing pipeline

    International Nuclear Information System (INIS)

    Loh, K.B.; Ramli, N.; Tan, L.K.; Roziah, M.; Rahmat, K.; Ariffin, H.

    2012-01-01

    The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas. Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction. DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued. DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data. (orig.)

  12. Quantification of diffusion tensor imaging in normal white matter maturation of early childhood using an automated processing pipeline

    Energy Technology Data Exchange (ETDEWEB)

    Loh, K.B.; Ramli, N.; Tan, L.K.; Roziah, M. [University of Malaya, Department of Biomedical Imaging, University Malaya Research Imaging Centre (UMRIC), Faculty of Medicine, Kuala Lumpur (Malaysia); Rahmat, K. [University of Malaya, Department of Biomedical Imaging, University Malaya Research Imaging Centre (UMRIC), Faculty of Medicine, Kuala Lumpur (Malaysia); University Malaya, Biomedical Imaging Department, Kuala Lumpur (Malaysia); Ariffin, H. [University of Malaya, Department of Paediatrics, Faculty of Medicine, Kuala Lumpur (Malaysia)

    2012-07-15

    The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas. Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction. DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued. DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data. (orig.)

  13. Tensors and their applications

    CERN Document Server

    Islam, Nazrul

    2006-01-01

    About the Book: The book is written is in easy-to-read style with corresponding examples. The main aim of this book is to precisely explain the fundamentals of Tensors and their applications to Mechanics, Elasticity, Theory of Relativity, Electromagnetic, Riemannian Geometry and many other disciplines of science and engineering, in a lucid manner. The text has been explained section wise, every concept has been narrated in the form of definition, examples and questions related to the concept taught. The overall package of the book is highly useful and interesting for the people associated with the field. Contents: Preliminaries Tensor Algebra Metric Tensor and Riemannian Metric Christoffel`s Symbols and Covariant Differentiation Riemann-Christoffel Tensor The e-Systems and the Generalized Krönecker Deltas Geometry Analytical Mechanics Curvature of a Curve, Geodesic Parallelism of Vectors Ricci`s Coefficients of Rotation and Congruence Hyper Surfaces

  14. Tensor Completion Algorithms in Big Data Analytics

    OpenAIRE

    Song, Qingquan; Ge, Hancheng; Caverlee, James; Hu, Xia

    2017-01-01

    Tensor completion is a problem of filling the missing or unobserved entries of partially observed tensors. Due to the multidimensional character of tensors in describing complex datasets, tensor completion algorithms and their applications have received wide attention and achievement in areas like data mining, computer vision, signal processing, and neuroscience. In this survey, we provide a modern overview of recent advances in tensor completion algorithms from the perspective of big data an...

  15. Efficient MATLAB computations with sparse and factored tensors.

    Energy Technology Data Exchange (ETDEWEB)

    Bader, Brett William; Kolda, Tamara Gibson (Sandia National Lab, Livermore, CA)

    2006-12-01

    In this paper, the term tensor refers simply to a multidimensional or N-way array, and we consider how specially structured tensors allow for efficient storage and computation. First, we study sparse tensors, which have the property that the vast majority of the elements are zero. We propose storing sparse tensors using coordinate format and describe the computational efficiency of this scheme for various mathematical operations, including those typical to tensor decomposition algorithms. Second, we study factored tensors, which have the property that they can be assembled from more basic components. We consider two specific types: a Tucker tensor can be expressed as the product of a core tensor (which itself may be dense, sparse, or factored) and a matrix along each mode, and a Kruskal tensor can be expressed as the sum of rank-1 tensors. We are interested in the case where the storage of the components is less than the storage of the full tensor, and we demonstrate that many elementary operations can be computed using only the components. All of the efficiencies described in this paper are implemented in the Tensor Toolbox for MATLAB.

  16. Reciprocal mass tensor : a general form

    International Nuclear Information System (INIS)

    Roy, C.L.

    1978-01-01

    Using the results of earlier treatment of wave packets, a general form of reciprocal mass tensor has been obtained. The elements of this tensor are seen to be dependent on momentum as well as space coordinates of the particle under consideration. The conditions under which the tensor would reduce to the usual space-independent form, are discussed and the impact of the space-dependence of this tensor on the motion of Bloch electrons, is examined. (author)

  17. A new deteriorated energy-momentum tensor

    International Nuclear Information System (INIS)

    Duff, M.J.

    1982-01-01

    The stress-tensor of a scalar field theory is not unique because of the possibility of adding an 'improvement term'. In supersymmetric field theories the stress-tensor will appear in a super-current multiplet along with the sypersymmetry current. The general question of the supercurrent multiplet for arbitrary deteriorated stress tensors and their relationship to supercurrent multiplets for models with gauge antisymmetric tensors is answered for various models of N = 1, 2 and 4 supersymmetry. (U.K.)

  18. Antisymmetric tensor generalizations of affine vector fields.

    Science.gov (United States)

    Houri, Tsuyoshi; Morisawa, Yoshiyuki; Tomoda, Kentaro

    2016-02-01

    Tensor generalizations of affine vector fields called symmetric and antisymmetric affine tensor fields are discussed as symmetry of spacetimes. We review the properties of the symmetric ones, which have been studied in earlier works, and investigate the properties of the antisymmetric ones, which are the main theme in this paper. It is shown that antisymmetric affine tensor fields are closely related to one-lower-rank antisymmetric tensor fields which are parallelly transported along geodesics. It is also shown that the number of linear independent rank- p antisymmetric affine tensor fields in n -dimensions is bounded by ( n + 1)!/ p !( n - p )!. We also derive the integrability conditions for antisymmetric affine tensor fields. Using the integrability conditions, we discuss the existence of antisymmetric affine tensor fields on various spacetimes.

  19. (Ln-bar, g)-spaces. Special tensor fields

    International Nuclear Information System (INIS)

    Manoff, S.; Dimitrov, B.

    1998-01-01

    The Kronecker tensor field, the contraction tensor field, as well as the multi-Kronecker and multi-contraction tensor fields are determined and the action of the covariant differential operator, the Lie differential operator, the curvature operator, and the deviation operator on these tensor fields is established. The commutation relations between the operators Sym and Asym and the covariant and Lie differential operators are considered acting on symmetric and antisymmetric tensor fields over (L n bar, g)-spaces

  20. The Riemann-Lovelock Curvature Tensor

    OpenAIRE

    Kastor, David

    2012-01-01

    In order to study the properties of Lovelock gravity theories in low dimensions, we define the kth-order Riemann-Lovelock tensor as a certain quantity having a total 4k-indices, which is kth-order in the Riemann curvature tensor and shares its basic algebraic and differential properties. We show that the kth-order Riemann-Lovelock tensor is determined by its traces in dimensions 2k \\le D

  1. Tractography of the brainstem in major depressive disorder using diffusion tensor imaging.

    Directory of Open Access Journals (Sweden)

    Yun Ju C Song

    Full Text Available BACKGROUND: The brainstem is the main region that innervates neurotransmitter release to the Hypothalamic-Pituitary Adrenal (HPA axis and fronto-limbic circuits, two key brain circuits found to be dysfunctional in Major Depressive Disorder (MDD. However, the brainstem's role in MDD has only been evaluated in limited reports. Using Diffusion Tensor Imaging (DTI, we investigated whether major brainstem white matter tracts that relate to these two circuits differ in MDD patients compared to healthy controls. METHODS: MDD patients (n = 95 and age- and gender-matched controls (n = 34 were assessed using probabilistic tractography of DTI to delineate three distinct brainstem tracts: the nigrostriatal tract (connecting brainstem to striatum, solitary tract (connecting brainstem to amygdala and corticospinal tract (connecting brainstem to precentral cortex. Fractional anisotropy (FA was used to measure the white matter integrity of these tracts, and measures were compared between MDD and control participants. RESULTS: MDD participants were characterized by a significant and specific decrease in white matter integrity of the right solitary tract (p<0.009 using independent t-test, which is a "bottom up" afferent pathway that connects the brainstem to the amygdala. This decrease was not related to symptom severity. CONCLUSIONS: The results provide new evidence to suggest that structural connectivity between the brainstem and the amygdala is altered in MDD. These results are interesting in light of predominant theories regarding amygdala-mediated emotional reactivity observed in functional imaging studies of MDD. The characterization of altered white matter integrity in the solitary tract in MDD supports the possibility of dysfunctional brainstem-amygdala connectivity impacting vulnerable circuits in MDD.

  2. Subcortical White Matter Changes with Normal Aging Detected by Multi-Shot High Resolution Diffusion Tensor Imaging.

    Directory of Open Access Journals (Sweden)

    Sheng Xie

    Full Text Available Subcortical white matter builds neural connections between cortical and subcortical regions and constitutes the basis of neural networks. It plays a very important role in normal brain function. Various studies have shown that white matter deteriorates with aging. However, due to the limited spatial resolution provided by traditional diffusion imaging techniques, microstructural information from subcortical white matter with normal aging has not been comprehensively assessed. This study aims to investigate the deterioration effect with aging in the subcortical white matter and provide a baseline standard for pathological disorder diagnosis. We apply our newly developed multi-shot high resolution diffusion tensor imaging, using self-feeding multiplexed sensitivity-encoding, to measure subcortical white matter changes in regions of interest of healthy persons with a wide age range. Results show significant fractional anisotropy decline and radial diffusivity increasing with age, especially in the anterior part of the brain. We also find that subcortical white matter has more prominent changes than white matter close to the central brain. The observed changes in the subcortical white matter may be indicative of a mild demyelination and a loss of myelinated axons, which may contribute to normal age-related functional decline.

  3. Diffusion tensor imaging applications in multiple sclerosis patients using 3T magnetic resonance: a preliminary study

    Energy Technology Data Exchange (ETDEWEB)

    Testaverde, Lorenzo; Caporali, Laura [University ' ' Sapienza' ' of Rome, Department of Radiological Sciences, Rome (Italy); Venditti, Eugenio; Grillea, Giovanni [U.O.C. Neuroradiologia, I.R.C.C.S. ' ' Neuromed' ' , Pozzilli (Italy); Colonnese, Claudio [University ' ' Sapienza' ' of Rome, Department of Radiological Sciences, Rome (Italy); U.O.C. Neuroradiologia, I.R.C.C.S. ' ' Neuromed' ' , Pozzilli (Italy)

    2012-05-15

    This study evaluated patients with multiple sclerosis using diffusion tensor imaging (DTI) to obtain fractional anisotropy (FA) and mean diffusivity (MD) values. We investigated the possible statistically significant variation of MD and FA in different MS patients, compared simultaneously, putting in comparison their normal appearing white matter (NAWM) and white matter affected by disease (plaques), both during activity and in remission, with normal white matter (NWM) of control subjects. Statistical analysis using Levene's test for comparison of variances revealed significant (P < 0.05) differences between FA values of the NWM of the controls and those of NAWM and active or inactive lesions, of the patients in the study. However, the differences between MD values of the NWM of the controls and those of NAWM and active or inactive lesions of the patients in the study were judged not significant (P > 0.05). Imaging of MS using MRI techniques is constantly searching for reproducible quantitative parameter. This study shows how these parameters can be identified in the MD and FA values, and thus suggests the implementation of MRI routine protocols for diagnosing MS with the DTI analysis, since it can provide valuable information otherwise unobtainable. (orig.)

  4. Accelerated magnetic resonance diffusion tensor imaging of the median nerve using simultaneous multi-slice echo planar imaging with blipped CAIPIRINHA

    Energy Technology Data Exchange (ETDEWEB)

    Filli, Lukas; Kenkel, David; Boss, Andreas; Manoliu, Andrei; Andreisek, Gustav; Runge, Val M.; Guggenberger, Roman [University Hospital of Zurich, University of Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland); Piccirelli, Marco [University Hospital of Zurich, Department of Neuroradiology, Zurich (Switzerland); Bhat, Himanshu [Siemens Medical Solutions USA Inc, Charlestown, MA (United States)

    2016-06-15

    To investigate the feasibility of MR diffusion tensor imaging (DTI) of the median nerve using simultaneous multi-slice echo planar imaging (EPI) with blipped CAIPIRINHA. After federal ethics board approval, MR imaging of the median nerves of eight healthy volunteers (mean age, 29.4 years; range, 25-32) was performed at 3 T using a 16-channel hand/wrist coil. An EPI sequence (b-value, 1,000 s/mm{sup 2}; 20 gradient directions) was acquired without acceleration as well as with twofold and threefold slice acceleration. Fractional anisotropy (FA), mean diffusivity (MD) and quality of nerve tractography (number of tracks, average track length, track homogeneity, anatomical accuracy) were compared between the acquisitions using multivariate ANOVA and the Kruskal-Wallis test. Acquisition time was 6:08 min for standard DTI, 3:38 min for twofold and 2:31 min for threefold acceleration. No differences were found regarding FA (standard DTI: 0.620 ± 0.058; twofold acceleration: 0.642 ± 0.058; threefold acceleration: 0.644 ± 0.061; p ≥ 0.217) and MD (standard DTI: 1.076 ± 0.080 mm{sup 2}/s; twofold acceleration: 1.016 ± 0.123 mm{sup 2}/s; threefold acceleration: 0.979 ± 0.153 mm{sup 2}/s; p ≥ 0.074). Twofold acceleration yielded similar tractography quality compared to standard DTI (p > 0.05). With threefold acceleration, however, average track length and track homogeneity decreased (p = 0.004-0.021). Accelerated DTI of the median nerve is feasible. Twofold acceleration yields similar results to standard DTI. (orig.)

  5. Magnetic resonance imaging and tensor-based morphometry in the MPTP non-human primate model of Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Michel Modo

    Full Text Available Parkinson's disease (PD is the second most common neurodegenerative disorder producing a variety of motor and cognitive deficits with the causes remaining largely unknown. The gradual loss of the nigrostriatal pathway is currently considered the pivotal pathological event. To better understand the progression of PD and improve treatment management, defining the disease on a structural basis and expanding brain analysis to extra-nigral structures is indispensable. The anatomical complexity and the presence of neuromelanin, make the use of non-human primates an essential element in developing putative imaging biomarkers of PD. To this end, ex vivo T2-weighted magnetic resonance images were acquired from control and 1-methyl-4 phenyl-1,2,3,6-tetrahydropyridine (MPTP-treated marmosets. Volume measurements of the caudate, putamen, and substantia nigra indicated significant atrophy and cortical thinning. Tensor-based morphometry provided a more extensive and hypothesis free assessment of widespread changes caused by the toxin insult to the brain, especially highlighting regional cortical atrophy. The results highlight the importance of developing imaging biomarkers of PD in non-human primate models considering their distinct neuroanatomy. It is essential to further develop these biomarkers in vivo to provide non-invasive tools to detect pre-symptomatic PD and to monitor potential disease altering therapeutics.

  6. Magnetic resonance imaging and tensor-based morphometry in the MPTP non-human primate model of Parkinson's disease.

    Science.gov (United States)

    Modo, Michel; Crum, William R; Gerwig, Madeline; Vernon, Anthony C; Patel, Priya; Jackson, Michael J; Rose, Sarah; Jenner, Peter; Iravani, Mahmoud M

    2017-01-01

    Parkinson's disease (PD) is the second most common neurodegenerative disorder producing a variety of motor and cognitive deficits with the causes remaining largely unknown. The gradual loss of the nigrostriatal pathway is currently considered the pivotal pathological event. To better understand the progression of PD and improve treatment management, defining the disease on a structural basis and expanding brain analysis to extra-nigral structures is indispensable. The anatomical complexity and the presence of neuromelanin, make the use of non-human primates an essential element in developing putative imaging biomarkers of PD. To this end, ex vivo T2-weighted magnetic resonance images were acquired from control and 1-methyl-4 phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated marmosets. Volume measurements of the caudate, putamen, and substantia nigra indicated significant atrophy and cortical thinning. Tensor-based morphometry provided a more extensive and hypothesis free assessment of widespread changes caused by the toxin insult to the brain, especially highlighting regional cortical atrophy. The results highlight the importance of developing imaging biomarkers of PD in non-human primate models considering their distinct neuroanatomy. It is essential to further develop these biomarkers in vivo to provide non-invasive tools to detect pre-symptomatic PD and to monitor potential disease altering therapeutics.

  7. The Physical Interpretation of the Lanczos Tensor

    OpenAIRE

    Roberts, Mark D.

    1999-01-01

    The field equations of general relativity can be written as first order differential equations in the Weyl tensor, the Weyl tensor in turn can be written as a first order differential equation in a three index tensor called the Lanczos tensor. The Lanczos tensor plays a similar role in general relativity to that of the vector potential in electro-magnetic theory. The Aharonov-Bohm effect shows that when quantum mechanics is applied to electro-magnetic theory the vector potential is dynamicall...

  8. High Order Tensor Formulation for Convolutional Sparse Coding

    KAUST Repository

    Bibi, Adel Aamer

    2017-12-25

    Convolutional sparse coding (CSC) has gained attention for its successful role as a reconstruction and a classification tool in the computer vision and machine learning community. Current CSC methods can only reconstruct singlefeature 2D images independently. However, learning multidimensional dictionaries and sparse codes for the reconstruction of multi-dimensional data is very important, as it examines correlations among all the data jointly. This provides more capacity for the learned dictionaries to better reconstruct data. In this paper, we propose a generic and novel formulation for the CSC problem that can handle an arbitrary order tensor of data. Backed with experimental results, our proposed formulation can not only tackle applications that are not possible with standard CSC solvers, including colored video reconstruction (5D- tensors), but it also performs favorably in reconstruction with much fewer parameters as compared to naive extensions of standard CSC to multiple features/channels.

  9. Non-Newtonian stress tensor and thermal conductivity tensor in granular plane shear flow

    Science.gov (United States)

    Alam, Meheboob; Saha, Saikat

    2014-11-01

    The non-Newtonian stress tensor and the heat flux in the plane shear flow of smooth inelastic disks are analysed from the Grad-level moment equations using the anisotropic Gaussian as a reference. Closed-form expressions for shear viscosity, pressure, first normal stress difference (N1) and the dissipation rate are given as functions of (i) the density or the area fraction (ν), (ii) the restitution coefficient (e), (iii) the dimensionless shear rate (R), (iv) the temperature anisotropy [ η, the difference between the principal eigenvalues of the second moment tensor] and (v) the angle (ϕ) between the principal directions of the shear tensor and the second moment tensor. Particle simulation data for a sheared hard-disk system is compared with theoretical results, with good agreement for p, μ and N1 over a large range of density. In contrast, the predictions from a Navier-Stokes order constitutive model are found to deviate significantly from both the simulation and the moment theory even at moderate values of e. We show that the gradient of the deviatoric part of the kinetic stress drives a heat current and the thermal conductivity is characterized by an anisotropic 2nd rank tensor for which explicit expressions are derived.

  10. An adaptive tensor voting algorithm combined with texture spectrum

    Science.gov (United States)

    Wang, Gang; Su, Qing-tang; Lü, Gao-huan; Zhang, Xiao-feng; Liu, Yu-huan; He, An-zhi

    2015-01-01

    An adaptive tensor voting algorithm combined with texture spectrum is proposed. The image texture spectrum is used to get the adaptive scale parameter of voting field. Then the texture information modifies both the attenuation coefficient and the attenuation field so that we can use this algorithm to create more significant and correct structures in the original image according to the human visual perception. At the same time, the proposed method can improve the edge extraction quality, which includes decreasing the flocculent region efficiently and making image clear. In the experiment for extracting pavement cracks, the original pavement image is processed by the proposed method which is combined with the significant curve feature threshold procedure, and the resulted image displays the faint crack signals submerged in the complicated background efficiently and clearly.

  11. The role of diffusion tensor imaging and fractional anisotropy in the evaluation of patients with idiopathic normal pressure hydrocephalus: a literature review.

    Science.gov (United States)

    Siasios, Ioannis; Kapsalaki, Eftychia Z; Fountas, Kostas N; Fotiadou, Aggeliki; Dorsch, Alexander; Vakharia, Kunal; Pollina, John; Dimopoulos, Vassilios

    2016-09-01

    OBJECTIVE Diffusion tensor imaging (DTI) for the assessment of fractional anisotropy (FA) and involving measurements of mean diffusivity (MD) and apparent diffusion coefficient (ADC) represents a novel, MRI-based, noninvasive technique that may delineate microstructural changes in cerebral white matter (WM). For example, DTI may be used for the diagnosis and differentiation of idiopathic normal pressure hydrocephalus (iNPH) from other neurodegenerative diseases with similar imaging findings and clinical symptoms and signs. The goal of the current study was to identify and analyze recently published series on the use of DTI as a diagnostic tool. Moreover, the authors also explored the utility of DTI in identifying patients with iNPH who could be managed by surgical intervention. METHODS The authors performed a literature search of the PubMed database by using any possible combinations of the following terms: "Alzheimer's disease," "brain," "cerebrospinal fluid," "CSF," "diffusion tensor imaging," "DTI," "hydrocephalus," "idiopathic," "magnetic resonance imaging," "normal pressure," "Parkinson's disease," and "shunting." Moreover, all reference lists from the retrieved articles were reviewed to identify any additional pertinent articles. RESULTS The literature search retrieved 19 studies in which DTI was used for the identification and differentiation of iNPH from other neurodegenerative diseases. The DTI protocols involved different approaches, such as region of interest (ROI) methods, tract-based spatial statistics, voxel-based analysis, and delta-ADC analysis. The most studied anatomical regions were the periventricular WM areas, such as the internal capsule (IC), the corticospinal tract (CST), and the corpus callosum (CC). Patients with iNPH had significantly higher MD in the periventricular WM areas of the CST and the CC than had healthy controls. In addition, FA and ADCs were significantly higher in the CST of iNPH patients than in any other patients with other

  12. Weyl tensors for asymmetric complex curvatures

    International Nuclear Information System (INIS)

    Oliveira, C.G.

    Considering a second rank Hermitian field tensor and a general Hermitian connection the associated complex curvature tensor is constructed. The Weyl tensor that corresponds to this complex curvature is determined. The formalism is applied to the Weyl unitary field theory and to the Moffat gravitational theory. (Author) [pt

  13. Diagnostic performance of conventional diffusion weighted imaging and diffusion tensor imaging for the liver fibrosis and inflammation

    International Nuclear Information System (INIS)

    Tosun, Mesude; Inan, Nagihan; Sarisoy, Hasan Tahsin; Akansel, Gur; Gumustas, Sevtap; Gürbüz, Yeşim; Demirci, Ali

    2013-01-01

    Objective: To evaluate the diagnostic accuracy of liver apparent diffusion coefficient (ADC) measured with conventional diffusion-weighted imaging (CDI) and diffusion tensor imaging (DTI) for the diagnosis of liver fibrosis and inflammation. Materials and methods: Thirty-seven patients with histologic diagnosis of chronic viral hepatitis and 34 healthy volunteers were included in this prospective study. All patients and healthy volunteers were examined by 3 T MRI. CDI and DTI were performed using a breath-hold single-shot echo-planar spin echo sequence with b factors of 0 and 1000 s/mm 2 . ADCs were obtained with CDI and DTI. Histopathologically, fibrosis of the liver parenchyma was classified with the use of a 5-point scale (0–4) and inflammation was classified with use of a 4-point scale (0–3) in accordance with the METAVIR score. Quantitatively, signal intensity and the ADCs of the liver parenchyma were compared between patients stratified by fibrosis stage and inflammation grade. Results: With a b factor of 1000 s/mm 2 , the signal intensity of the cirrhotic livers was significantly higher than those of the normal volunteers. In addition, ADCs reconstructed from CDI and DTI of the patients were significantly lower than those of the normal volunteers. Liver ADC values inversely correlated with fibrosis and inflammation but there was only statistically significant for inflammatory grading. CDI performed better than DTI for the diagnosis of fibrosis and inflammation. Conclusion: ADC values measured with CDI and DTI may help in the detection of liver fibrosis. They may also give contributory to the inflammatory grading, particularly in distinguishing high from low grade

  14. Diagnostic performance of conventional diffusion weighted imaging and diffusion tensor imaging for the liver fibrosis and inflammation

    Energy Technology Data Exchange (ETDEWEB)

    Tosun, Mesude, E-mail: mesude.tosun@kocaeli.edu.tr [Department of Radiology, School of Medicine, University of Kocaeli (Turkey); Inan, Nagihan, E-mail: inannagihan@ekolay.net [Department of Radiology, School of Medicine, University of Kocaeli (Turkey); Sarisoy, Hasan Tahsin, E-mail: htssarisoy@yahoo.com [Department of Radiology, School of Medicine, University of Kocaeli (Turkey); Akansel, Gur, E-mail: gakansel@gmail.com [Department of Radiology, School of Medicine, University of Kocaeli (Turkey); Gumustas, Sevtap, E-mail: svtgumustas@hotmail.com [Department of Radiology, School of Medicine, University of Kocaeli (Turkey); Gürbüz, Yeşim, E-mail: yesimgurbuz2002@yahoo.com [Department of Pathology, School of Medicine, University of Kocaeli (Turkey); Demirci, Ali, E-mail: alidemirci@kocaeli.edu.tr [Department of Radiology, School of Medicine, University of Kocaeli (Turkey)

    2013-02-15

    Objective: To evaluate the diagnostic accuracy of liver apparent diffusion coefficient (ADC) measured with conventional diffusion-weighted imaging (CDI) and diffusion tensor imaging (DTI) for the diagnosis of liver fibrosis and inflammation. Materials and methods: Thirty-seven patients with histologic diagnosis of chronic viral hepatitis and 34 healthy volunteers were included in this prospective study. All patients and healthy volunteers were examined by 3 T MRI. CDI and DTI were performed using a breath-hold single-shot echo-planar spin echo sequence with b factors of 0 and 1000 s/mm{sup 2}. ADCs were obtained with CDI and DTI. Histopathologically, fibrosis of the liver parenchyma was classified with the use of a 5-point scale (0–4) and inflammation was classified with use of a 4-point scale (0–3) in accordance with the METAVIR score. Quantitatively, signal intensity and the ADCs of the liver parenchyma were compared between patients stratified by fibrosis stage and inflammation grade. Results: With a b factor of 1000 s/mm{sup 2}, the signal intensity of the cirrhotic livers was significantly higher than those of the normal volunteers. In addition, ADCs reconstructed from CDI and DTI of the patients were significantly lower than those of the normal volunteers. Liver ADC values inversely correlated with fibrosis and inflammation but there was only statistically significant for inflammatory grading. CDI performed better than DTI for the diagnosis of fibrosis and inflammation. Conclusion: ADC values measured with CDI and DTI may help in the detection of liver fibrosis. They may also give contributory to the inflammatory grading, particularly in distinguishing high from low grade.

  15. Evaluation of left-right asymmetry of pyramidal tracts in preterm neonates by diffusion tensor imaging and tractography

    International Nuclear Information System (INIS)

    Ogita, Kaori

    2010-01-01

    Diffusion Tensor Tractography (DTT) is a new noninvasive brain imaging technique to detect the neural tract and is expected to be instrumental in diagnosing diseases with white matter involvement. Assessing the pyramidal tract with DTT will be useful in diagnosing motor dysfunction. However, the pyramidal tract (PT) has not been fully investigated with this technique especially in neonates. The aim of this study is to clarify the normal characteristics, especially the latevility, of the PT in healthy neonates. Fourteen preterm neonates were examined with DTT before being discharged from the neonatal intensive care unit (NICU). Free software dTV and Volume-One were used to depict the PT and analyze the fractional anisotrophy (FA) value, a parameter used in Diffusion Tensor Imaging (DTI). In the beginning, the FA at the medulla oblongata as the initial region of interest was determined to be 0.18 or more to depict the PT by DTT. The FA values at the level of the posterior limb of the Internal Capsule (IC), the Corona Radiate (CR), and the Centrum Semiovale (CS) of the depicted PT were measured and compared with the contralateral. The upper limit of the level of the FA at the medulla oblongata value capable of depicting the PT was measured and compared with the contralateral. All data was analyzed using the Mann-Whitney test. A p-value of less than 0.05 was considered to indicate significant difference. The FA value of the left CS was higher than that of the right in all 14 cases, and the FA value of the left CA was higher than that of the right in 13 cases. The upper limit of the FA value of the medulla oblongata as the initial region of interest to depict the left side of the PT was higher than for the right side of the PT in all 14 cases. We clarified the laterality of the PT in healthy neonates using DTT. This laterality must be taken into consideration when involvement of the PT is diagnosed using this technique. (author)

  16. Diffusion tensor imaging and T2 mapping in early denervated skeletal muscle in rats.

    Science.gov (United States)

    Ha, Dong-Ho; Choi, Sunseob; Kang, Eun-Ju; Park, Hwan Tae

    2015-09-01

    To evaluate the temporal changes of diffusion tensor imaging (DTI) indices, T2 values, and visual signal intensity on various fat suppression techniques in the early state of denervated skeletal muscle in a rat model. Institutional Animal Care and Use Committee approval was obtained. Sciatic nerves of eight rats were transected for irreversible neurotmesis model. We examined normal lower leg and denervated muscles at 3 days, 1 week, and 2 weeks on a 3 Tesla MR. fractional anisotropy (FA), mean apparent diffusion coefficient (mADC), and T2 values were measured by using DTI and T2 mapping scan. We subjectively classified the signal intensity change on various fat suppression images into the following three grades: negative, suspicious, and definite change. Wilcoxon-sign rank test and Kruskal-Wallis test were used for the comparison of FA, mADC, T2 values. McNemar's test was used for comparing signal intensity change among fat suppression techniques. FA values of denervated muscles at 3 days (0.35 ± 0.06), 1 week (0.29 ± 0.04), and 2 weeks (0.34 ± 0.05) were significantly (P  0.05) change. T2 values were significantly increased at 1 week (38.11 ± 6.42 ms, P = 0.017) and markedly increased at 2 weeks (46.53 ± 5.17 ms, P = 0.012). The grade of visual signal intensity change on chemical shift selective fat saturation, STIR and IDEAL images were identical in all cases (P = 1.000). FA and T2 values can demonstrate the early temporal changes in denervated rat skeletal muscle. © 2014 Wiley Periodicals, Inc.

  17. Should I use TensorFlow

    OpenAIRE

    Schrimpf, Martin

    2016-01-01

    Google's Machine Learning framework TensorFlow was open-sourced in November 2015 [1] and has since built a growing community around it. TensorFlow is supposed to be flexible for research purposes while also allowing its models to be deployed productively. This work is aimed towards people with experience in Machine Learning considering whether they should use TensorFlow in their environment. Several aspects of the framework important for such a decision are examined, such as the heterogenity,...

  18. Diffusion tensor analysis with nuclear magnetic resonance in human central nervous system

    International Nuclear Information System (INIS)

    Nakayama, Naoki

    1998-01-01

    Nuclear magnetic resonance has been used to measure the diffusivity of water molecules. In central nervous system, anisotropic diffusion, which is characterized by apparent diffusion tensor D app ξ , is thought to be related to neuronal fiber tract orientation. For precise observation of anisotropic diffusion, it is needed to determine the diagonal and off-diagonal elements of D app ξ . Once D app ξ is estimated from a series of diffusion weighted images, a tissue's orthotropic principal axes and diffusivity of each direction are determined from eigenvalues and eigenvectors of D app ξ . There are several methods to represent anisotropic diffusion with D app ξ . Examples are diffusion ellipsoids constructed in each voxel depicting both these principal axes and the mean diffusion length in these directions, trace invariant values and its mapping image, largest eigenvalue, and ratio of largest eigenvalue to the other eigenvalue. In this study, the author investigated practical procedure to analyze diffusion tensor D app ξ using both of spin-echo end echo-planer diffusion weighted imagings with 3-tesla magnetic resonance machine in human brain. The ellipsoid representation provided particularly useful information about microanatomy including neuronal fiber tract orientation and molecular mobility reflective of microstructure. Furthermore, in the lesion of Wallerian degeneration, the loss of anisotropy of local apparent diffusion was observed. It is suggested that the function of axons can be observed via degree of anisotropy of apparent diffusion. Consequently, diffusion tensor analysis is expected to be a powerful, noninvasive method capable of quantitative and functional evaluation of the central nervous system. (author)

  19. Energy-momentum tensor in the fermion-pairing model

    International Nuclear Information System (INIS)

    Kawati, S.; Miyata, H.

    1980-01-01

    The symmetric energy-momentum tensor for the self-interacting fermion theory (psi-barpsi) 2 is expressed in terms of the collective mode within the Hartree approximation. The divergent part of the energy-momentum tensor for the fermion theory induces an effective energy-momentum tensor for the collective mode, and this effective energy-momentum tensor automatically has the Callan-Coleman-Jackiw improved form. The renormalized energy-momentum tensor is structurally equivalent to the Callan-Coleman-Jackiw improved tensor for the Yukawa theory

  20. Automated multiscale morphometry of muscle disease from second harmonic generation microscopy using tensor-based image processing.

    Science.gov (United States)

    Garbe, Christoph S; Buttgereit, Andreas; Schürmann, Sebastian; Friedrich, Oliver

    2012-01-01

    Practically, all chronic diseases are characterized by tissue remodeling that alters organ and cellular function through changes to normal organ architecture. Some morphometric alterations become irreversible and account for disease progression even on cellular levels. Early diagnostics to categorize tissue alterations, as well as monitoring progression or remission of disturbed cytoarchitecture upon treatment in the same individual, are a new emerging field. They strongly challenge spatial resolution and require advanced imaging techniques and strategies for detecting morphological changes. We use a combined second harmonic generation (SHG) microscopy and automated image processing approach to quantify morphology in an animal model of inherited Duchenne muscular dystrophy (mdx mouse) with age. Multiphoton XYZ image stacks from tissue slices reveal vast morphological deviation in muscles from old mdx mice at different scales of cytoskeleton architecture: cell calibers are irregular, myofibrils within cells are twisted, and sarcomere lattice disruptions (detected as "verniers") are larger in number compared to samples from healthy mice. In young mdx mice, such alterations are only minor. The boundary-tensor approach, adapted and optimized for SHG data, is a suitable approach to allow quick quantitative morphometry in whole tissue slices. The overall detection performance of the automated algorithm compares very well with manual "by eye" detection, the latter being time consuming and prone to subjective errors. Our algorithm outperfoms manual detection by time with similar reliability. This approach will be an important prerequisite for the implementation of a clinical image databases to diagnose and monitor specific morphological alterations in chronic (muscle) diseases. © 2011 IEEE

  1. White matter microstructure and cognitive decline in metabolic syndrome: a review of diffusion tensor imaging.

    Science.gov (United States)

    Alfaro, Freddy J; Gavrieli, Anna; Saade-Lemus, Patricia; Lioutas, Vasileios-Arsenios; Upadhyay, Jagriti; Novak, Vera

    2018-01-01

    Metabolic syndrome is a cluster of cardiovascular risk factors defined by the presence of abdominal obesity, glucose intolerance, hypertension and/or dyslipidemia. It is a major public health epidemic worldwide, and a known risk factor for the development of cognitive dysfunction and dementia. Several studies have demonstrated a positive association between the presence of metabolic syndrome and worse cognitive outcomes, however, evidence of brain structure pathology is limited. Diffusion tensor imaging has offered new opportunities to detect microstructural white matter changes in metabolic syndrome, and a possibility to detect associations between functional and structural abnormalities. This review analyzes the impact of metabolic syndrome on white matter microstructural integrity, brain structure abnormalities and their relationship to cognitive function. Each of the metabolic syndrome components exerts a specific signature of white matter microstructural abnormalities. Metabolic syndrome and its components exert both additive/synergistic, as well as, independent effects on brain microstructure thus accelerating brain aging and cognitive decline. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Characterizing Intraorbital Optic Nerve Changes on Diffusion Tensor Imaging in Thyroid Eye Disease Before Dysthyroid Optic Neuropathy.

    Science.gov (United States)

    Lee, Hwa; Lee, Young Hen; Suh, Sang-Il; Jeong, Eun-Kee; Baek, Sehyun; Seo, Hyung Suk

    The aim of this study was to determine whether the optic nerve is affected by thyroid eye disease (TED) before the development of dysthyroid optic neuropathy with diffusion-tensor imaging (DTI). Twenty TED patients and 20 controls were included. The mean, axial, and radial diffusivities and fractional anisotropy (FA) value were measured at the optic nerves in DTI. Extraocular muscle diameters were measured on computed tomography. The diffusivities and FA of the optic nerves were compared between TED and controls and between active and inactive stages of TED. The correlations between these DTI parameters and the clinical features were determined. The mean, axial, and radial diffusivities were lower in TED compared with the controls (P optic nerve before dysthyroid optic neuropathy in TED. The FA, in particular, reflected TED activity and severity.

  3. Diffusion Tensor Imaging of Incentive Effects in Prospective Memory after Pediatric Traumatic Brain Injury

    Science.gov (United States)

    Wilde, Elisabeth A.; Bigler, Erin D.; Chu, Zili; Yallampalli, Ragini; Oni, Margaret B.; Wu, Trevor C.; Ramos, Marco A.; Pedroza, Claudia; Vásquez, Ana C.; Hunter, Jill V.; Levin, Harvey S.

    2011-01-01

    Abstract Few studies exist investigating the brain-behavior relations of event-based prospective memory (EB-PM) impairments following traumatic brain injury (TBI). To address this, children with moderate-to-severe TBI performed an EB-PM test with two motivational enhancement conditions and underwent concurrent diffusion tensor imaging (DTI) at 3 months post-injury. Children with orthopedic injuries (OI; n = 37) or moderate-to-severe TBI (n = 40) were contrasted. Significant group differences were found for fractional anisotropy (FA) and apparent diffusion coefficient for orbitofrontal white matter (WM), cingulum bundles, and uncinate fasciculi. The FA of these WM structures in children with TBI significantly correlated with EB-PM performance in the high, but not the low motivation condition. Regression analyses within the TBI group indicated that the FA of the left cingulum bundle (p = 0.003), left orbitofrontal WM (p motivation condition. We infer that the cingulum bundles, orbitofrontal WM, and uncinate fasciculi are important WM structures mediating motivation-based EB-PM responses following moderate-to-severe TBI in children. PMID:21250917

  4. In vivo reconstruction of lumbar erector spinae architecture using diffusion tensor MRI

    NARCIS (Netherlands)

    Sieben, Judith M.; Van Otten, Ilse; Lataster, Arno; Froeling, Martijn; Nederveen, Aart J.; Strijkers, Gustav J.; Drost, Maarten R.

    2016-01-01

    Study Design: Diffusion tensor magnetic resonance imaging (DTMRI) reconstruction of lumbar erector spinae (ES) compared with cadaver dissection. Objective: The aim of this study was to reconstruct the human lumbar ES from in vivo DT-MRI measurements and to compare the results with literature and

  5. The Einstein tensor characterizing some Riemann spaces

    International Nuclear Information System (INIS)

    Rahman, M.S.

    1993-07-01

    A formal definition of the Einstein tensor is given. Mention is made of how this tensor plays a role of expressing certain conditions in a precise form. The cases of reducing the Einstein tensor to a zero tensor are studied on its merit. A lucid account of results, formulated as theorems, on Einstein symmetric and Einstein recurrent spaces is then presented. (author). 5 refs

  6. Radiative corrections in a vector-tensor model

    International Nuclear Information System (INIS)

    Chishtie, F.; Gagne-Portelance, M.; Hanif, T.; Homayouni, S.; McKeon, D.G.C.

    2006-01-01

    In a recently proposed model in which a vector non-Abelian gauge field interacts with an antisymmetric tensor field, it has been shown that the tensor field possesses no physical degrees of freedom. This formal demonstration is tested by computing the one-loop contributions of the tensor field to the self-energy of the vector field. It is shown that despite the large number of Feynman diagrams in which the tensor field contributes, the sum of these diagrams vanishes, confirming that it is not physical. Furthermore, if the tensor field were to couple with a spinor field, it is shown at one-loop order that the spinor self-energy is not renormalizable, and hence this coupling must be excluded. In principle though, this tensor field does couple to the gravitational field

  7. Automated segmentation of white matter fiber bundles using diffusion tensor imaging data and a new density based clustering algorithm.

    Science.gov (United States)

    Kamali, Tahereh; Stashuk, Daniel

    2016-10-01

    Robust and accurate segmentation of brain white matter (WM) fiber bundles assists in diagnosing and assessing progression or remission of neuropsychiatric diseases such as schizophrenia, autism and depression. Supervised segmentation methods are infeasible in most applications since generating gold standards is too costly. Hence, there is a growing interest in designing unsupervised methods. However, most conventional unsupervised methods require the number of clusters be known in advance which is not possible in most applications. The purpose of this study is to design an unsupervised segmentation algorithm for brain white matter fiber bundles which can automatically segment fiber bundles using intrinsic diffusion tensor imaging data information without considering any prior information or assumption about data distributions. Here, a new density based clustering algorithm called neighborhood distance entropy consistency (NDEC), is proposed which discovers natural clusters within data by simultaneously utilizing both local and global density information. The performance of NDEC is compared with other state of the art clustering algorithms including chameleon, spectral clustering, DBSCAN and k-means using Johns Hopkins University publicly available diffusion tensor imaging data. The performance of NDEC and other employed clustering algorithms were evaluated using dice ratio as an external evaluation criteria and density based clustering validation (DBCV) index as an internal evaluation metric. Across all employed clustering algorithms, NDEC obtained the highest average dice ratio (0.94) and DBCV value (0.71). NDEC can find clusters with arbitrary shapes and densities and consequently can be used for WM fiber bundle segmentation where there is no distinct boundary between various bundles. NDEC may also be used as an effective tool in other pattern recognition and medical diagnostic systems in which discovering natural clusters within data is a necessity. Copyright

  8. Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

    Directory of Open Access Journals (Sweden)

    Fernández-Espejo Davinia

    2010-09-01

    Full Text Available Abstract Background The rate of recovery from the vegetative state (VS is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI and diffusion tensor imaging (DTI to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

  9. Voxel-based morphometry and diffusion-tensor MR imaging of the brain in long-term survivors of childhood leukemia.

    Science.gov (United States)

    Porto, L; Preibisch, C; Hattingen, E; Bartels, M; Lehrnbecher, T; Dewitz, R; Zanella, F; Good, C; Lanfermann, H; DuMesnil, R; Kieslich, M

    2008-11-01

    The aims of this study were to detect morphological changes in neuroanatomical components in adult survivors of acute lymphoblastic leukemia (ALL). Voxel-based morphometry (VBM) can be used to detect subtle structural changes in brain morphology and via analysis of fractional anisotropy (FA), diffusion-tensor imaging (DTI) can non-invasively probe white matter (WM) integrity. We used VBM and DTI to examine 20 long-term survivors of ALL and 21 healthy matched controls. Ten ALL survivors received chemotherapy and irradiation; ten survivors received chemotherapy alone during childhood. Imaging was performed on a 3.0-T MRI. For VBM, group comparisons of segmented T1-weighted grey matter (GM) and WM images from controls and ALL survivors were performed separately for patients who received chemotherapy alone and who received chemotherapy and irradiation. For DTI, FA in WM was compared for the same groups. Survivors of childhood ALL who underwent cranial irradiation during childhood had smaller WM volumes and reduced GM concentration within the caudate nucleus and thalamus. The FA in WM was reduced in adult survivors of ALL but the effect was more severe after combined treatment with irradiation and chemotherapy. Our results indicate that DTI and VBM can reveal persistent long-term WM and caudate changes in children after ALL treatment, even without T2 changes in conventional imaging.

  10. Transposes, L-Eigenvalues and Invariants of Third Order Tensors

    OpenAIRE

    Qi, Liqun

    2017-01-01

    Third order tensors have wide applications in mechanics, physics and engineering. The most famous and useful third order tensor is the piezoelectric tensor, which plays a key role in the piezoelectric effect, first discovered by Curie brothers. On the other hand, the Levi-Civita tensor is famous in tensor calculus. In this paper, we study third order tensors and (third order) hypermatrices systematically, by regarding a third order tensor as a linear operator which transforms a second order t...

  11. Diffusion tensor tractography of the mammillothalamic tract in the human brain using a high spatial resolution DTI technique.

    Science.gov (United States)

    Kamali, Arash; Zhang, Caroline C; Riascos, Roy F; Tandon, Nitin; Bonafante-Mejia, Eliana E; Patel, Rajan; Lincoln, John A; Rabiei, Pejman; Ocasio, Laura; Younes, Kyan; Hasan, Khader M

    2018-03-27

    The mammillary bodies as part of the hypothalamic nuclei are in the central limbic circuitry of the human brain. The mammillary bodies are shown to be directly or indirectly connected to the amygdala, hippocampus, and thalami as the major gray matter structures of the human limbic system. Although it is not primarily considered as part of the human limbic system, the thalamus is shown to be involved in many limbic functions of the human brain. The major direct connection of the thalami with the hypothalamic nuclei is known to be through the mammillothalamic tract. Given the crucial role of the mammillothalamic tracts in memory functions, diffusion tensor imaging may be helpful in better visualizing the surgical anatomy of this pathway noninvasively. This study aimed to investigate the utility of high spatial resolution diffusion tensor tractography for mapping the trajectory of the mammillothalamic tract in the human brain. Fifteen healthy adults were studied after obtaining written informed consent. We used high spatial resolution diffusion tensor imaging data at 3.0 T. We delineated, for the first time, the detailed trajectory of the mammillothalamic tract of the human brain using deterministic diffusion tensor tractography.

  12. Joint Tensor Feature Analysis For Visual Object Recognition.

    Science.gov (United States)

    Wong, Wai Keung; Lai, Zhihui; Xu, Yong; Wen, Jiajun; Ho, Chu Po

    2015-11-01

    Tensor-based object recognition has been widely studied in the past several years. This paper focuses on the issue of joint feature selection from the tensor data and proposes a novel method called joint tensor feature analysis (JTFA) for tensor feature extraction and recognition. In order to obtain a set of jointly sparse projections for tensor feature extraction, we define the modified within-class tensor scatter value and the modified between-class tensor scatter value for regression. The k-mode optimization technique and the L(2,1)-norm jointly sparse regression are combined together to compute the optimal solutions. The convergent analysis, computational complexity analysis and the essence of the proposed method/model are also presented. It is interesting to show that the proposed method is very similar to singular value decomposition on the scatter matrix but with sparsity constraint on the right singular value matrix or eigen-decomposition on the scatter matrix with sparse manner. Experimental results on some tensor datasets indicate that JTFA outperforms some well-known tensor feature extraction and selection algorithms.

  13. Graded tensor calculus

    International Nuclear Information System (INIS)

    Scheunert, M.

    1982-10-01

    We develop a graded tensor calculus corresponding to arbitrary Abelian groups of degrees and arbitrary commutation factors. The standard basic constructions and definitions like tensor products, spaces of multilinear mappings, contractions, symmetrization, symmetric algebra, as well as the transpose, adjoint, and trace of a linear mapping, are generalized to the graded case and a multitude of canonical isomorphisms is presented. Moreover, the graded versions of the classical Lie algebras are introduced and some of their basic properties are described. (orig.)

  14. Early microstructural white matter changes in patients with HIV: A diffusion tensor imaging study

    Directory of Open Access Journals (Sweden)

    Stubbe-Drger Bianca

    2012-05-01

    Full Text Available Abstract Background Previous studies have reported white matter (WM brain alterations in asymptomatic patients with human immunodeficiency virus (HIV. Methods We compared diffusion tensor imaging (DTI derived WM fractional anisotropy (FA between HIV-patients with and without mild macroscopic brain lesions determined using standard magnetic resonance imaging (MRI. We furthermore investigated whether WM alterations co-occurred with neurocognitive deficits and depression. We performed structural MRI and DTI for 19 patients and 19 age-matched healthy controls. Regionally-specific WM integrity was investigated using voxel-based statistics of whole-brain FA maps and region-of-interest analysis. Each patient underwent laboratory and neuropsychological tests. Results Structural MRI revealed no lesions in twelve (HIV-MRN and unspecific mild macrostructural lesions in seven patients (HIV-MRL. Both analyses revealed widespread FA-alterations in all patients. Patients with HIV-MRL had FA-alterations primarily adjacent to the observed lesions and, whilst reduced in extent, patients with HIV-MRN also exhibited FA-alterations in similar regions. Patients with evidence of depression showed FA-increase in the ventral tegmental area, pallidum and nucleus accumbens in both hemispheres, and patients with evidence of HIV-associated neurocognitive disorder showed widespread FA-reduction. Conclusion These results show that patients with HIV-MRN have evidence of FA-alterations in similar regions that are lesioned in HIV-MRL patients, suggesting common neuropathological processes. Furthermore, they suggest a biological rather than a reactive origin of depression in HIV-patients.

  15. Diffusion tensor magnetic resonance imaging driven growth modeling for radiotherapy target definition in glioblastoma.

    Science.gov (United States)

    Jensen, Morten B; Guldberg, Trine L; Harbøll, Anja; Lukacova, Slávka; Kallehauge, Jesper F

    2017-11-01

    The clinical target volume (CTV) in radiotherapy is routinely based on gadolinium contrast enhanced T1 weighted (T1w + Gd) and T2 weighted fluid attenuated inversion recovery (T2w FLAIR) magnetic resonance imaging (MRI) sequences which have been shown to over- or underestimate the microscopic tumor cell spread. Gliomas favor spread along the white matter fiber tracts. Tumor growth models incorporating the MRI diffusion tensors (DTI) allow to account more consistently for the glioma growth. The aim of the study was to investigate the potential of a DTI driven growth model to improve target definition in glioblastoma (GBM). Eleven GBM patients were scanned using T1w, T2w FLAIR, T1w + Gd and DTI. The brain was segmented into white matter, gray matter and cerebrospinal fluid. The Fisher-Kolmogorov growth model was used assuming uniform proliferation and a difference in white and gray matter diffusion of a ratio of 10. The tensor directionality was tested using an anisotropy weighting parameter set to zero (γ0) and twenty (γ20). The volumetric comparison was performed using Hausdorff distance, Dice similarity coefficient (DSC) and surface area. The median of the standard CTV (CTVstandard) was 180 cm 3 . The median surface area of CTVstandard was 211 cm 2 . The median surface area of respective CTV γ0 and CTV γ20 significantly increased to 338 and 376 cm 2 , respectively. The Hausdorff distance was greater than zero and significantly increased for both CTV γ0 and CTV γ20 with respective median of 18.7 and 25.2 mm. The DSC for both CTV γ0 and CTV γ20 were significantly below one with respective median of 0.74 and 0.72, which means that 74 and 72% of CTVstandard were included in CTV γ0 and CTV γ20, respectively. DTI driven growth models result in CTVs with a significantly increased surface area, a significantly increased Hausdorff distance and decreased overlap between the standard and model derived volume.

  16. LOW AND MEAN RADIATION DOSES IMPACT ON THE CEREBRAL TRACTS STRUCTURE OF THE CHERNOBYL ACCIDENT LIQUIDATORS IN THE REMOTE PERIOD (BASED ON ROUTINE AND DIFFUSION-TENSOR MAGNETIC RESONANCE IMAGING DATA)

    OpenAIRE

    I. M. Levashkina; S. S. Aleksanin; S. V. Serebryakova; T. G. Gribanova

    2017-01-01

    To evaluate correlation between brain structural damages and radiation exposure level for the Chernobyl nuclear power plant accident liquidators, routine and diffusion tensor magnetic resonance imaging methods are efficient to visualize and evaluate those damages; it is also important to compare magnetic resonance imaging data of liquidators with results, received for people of the same age and the same stage of cerebral vascular disease (the discirculatory encephalopathy of I and II stage), ...

  17. Diffusion tensor imaging of the human calf: Variation of inter- and intramuscle-specific diffusion parameters.

    Science.gov (United States)

    Schlaffke, Lara; Rehmann, Robert; Froeling, Martijn; Kley, Rudolf; Tegenthoff, Martin; Vorgerd, Matthias; Schmidt-Wilcke, Tobias

    2017-10-01

    To investigate to what extent inter- and intramuscular variations of diffusion parameters of human calf muscles can be explained by age, gender, muscle location, and body mass index (BMI) in a specific age group (20-35 years). Whole calf muscles of 18 healthy volunteers were evaluated. Magnetic resonance imaging (MRI) was performed using a 3T scanner and a 16-channel Torso XL coil. Diffusion-weighted images were acquired to perform fiber tractography and diffusion tensor imaging (DTI) analysis for each muscle of both legs. Fiber tractography was used to separate seven lower leg muscles. Associations between DTI parameters and confounds were evaluated. All muscles were additionally separated in seven identical segments along the z-axis to evaluate intramuscular differences in diffusion parameters. Fractional anisotropy (FA) and mean diffusivity (MD) were obtained for each muscle with low standard deviations (SDs) (SD FA : 0.01-0.02; SD MD : 0.07-0.14(10 -3 )). We found significant differences in FA values of the tibialis anterior muscle (AT) and extensor digitorum longus (EDL) muscles between men and women for whole muscle FA (two-sample t-tests; AT: P = 0.0014; EDL: P = 0.0004). We showed significant intramuscular differences in diffusion parameters between adjacent segments in most calf muscles (P < 0.001). Whereas muscle insertions showed higher (SD 0.03-0.06) than muscle bellies (SD 0.01-0.03), no relationships between FA or MD with age or BMI were found. Inter- and intramuscular variations in diffusion parameters of the calf were shown, which are not related to age or BMI in this age group. Differences between muscle belly and insertion should be considered when interpreting datasets not including whole muscles. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1137-1148. © 2017 International Society for Magnetic Resonance in Medicine.

  18. Test-retest reliability of diffusion tensor imaging of the liver at 3.0 T.

    Science.gov (United States)

    Girometti, Rossano; Maieron, Marta; Lissandrello, Giovanni; Bazzocchi, Massimo; Zuiani, Chiara

    2015-06-01

    This study was done to evaluate test-retest reliability of liver diffusion tensor imaging (LDTI). Ten healthy volunteers (median age 23 years) underwent two LDTI scans on a 3.0 T magnet during two imaging sessions separated by 2 weeks (session-1/-2, respectively). Fifteen gradient directions and b values of 0-1,000 s/mm(2) were used. Two radiologists in consensus assessed liver apparent diffusion coefficient (ADC) and fraction of anisotropy (FA) values on ADC and FA maps at four reference levels, namely: right upper level (RUL), right lower level (RLL), left upper level (LUL) and left lower level (LLL). We then assessed (a) whether ADC and FA values overlapped when measured on different levels within the same imaging session or between different imaging sessions; (b) the degree of variability on an intra-session and inter-session basis, respectively, using the coefficient of variation (CV). In sessions 1 and 2, the ADC/FA values were significantly larger in the left liver lobe (LUL/LLL) compared to right liver lobe (RUL/RLL) (p < 0.05/6). Intra-session CVs were 9.51 % (session 1) and 9.73 % (session 2) for ADC, and 12.93 % (session 1) and 11.82 % (session 2) for FA, respectively. When comparing RUL, RLL, LUL and LLL on an inter-session basis, CVs were 6.52, 8.20, 6.52 and 11.06 % for ADC, and 15.42, 15.80, 15.42 and 6.80 % for FA, respectively. LDTI provides consistent and repeatable measurements. However, since larger left lobe ADC/FA values can be attributed to artefacts, right lobe values should be considered the most reliable measurements of water diffusivity within the liver.

  19. Total magnitude of diffusion tensor imaging as an effective tool for the differentiation of glioma

    Energy Technology Data Exchange (ETDEWEB)

    Smitha, Karavallil A., E-mail: mithamahesh@gmail.com [Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram (India); Gupta, Arun kumar, E-mail: gupta209@gmail.com [Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neuro Sciences, Bangalore (India); Jayasree, Ramapurath S., E-mail: jayashreemenon@gmail.com [Biophotonics and Imaging Laboratory, Biomedical Technology Wing, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram (India)

    2013-05-15

    Objectives: The study aims to evaluate the difference in diffusion properties between high grade glioma and low grade glioma by measuring the total magnitude of diffusion tensor (L), and its isotropic (p) and anisotropic (q) components. Methods: The diffusion tensor parameters p, q, L and FA from the tumor area, adjacent area to the tumor and corresponding contra lateral normal area of 30 high grade glioma and 49 low grade glioma were calculated. Chi square analysis was done to find the changes in age and sex. One Way ANOVA was performed to compare the mean and ROC curve analysis to confirm the discriminative sensitivity. Results: Major variation in the mean values of p, L and FA was observed in different brain areas considered. Variation in the p and L values between low grade and high grade glioma were statistically significant (p < 0.001) and their ROC curve analysis yielded 93.9% and 91.8% sensitivity and 53.3% specificity respectively. Conclusion: Measurement of the isotropic component p and the total value of diffusion tensor L can be effectively correlated with different grades of glioma and can be used to study the diffusion properties of tumor affected brain.

  20. (Ln-bar, g)-spaces. Ordinary and tensor differentials

    International Nuclear Information System (INIS)

    Manoff, S.; Dimitrov, B.

    1998-01-01

    Different types of differentials as special cases of differential operators acting on tensor fields over (L n bar, g)-spaces are considered. The ordinary differential, the covariant differential as a special case of the covariant differential operator, and the Lie differential as a special case of the Lie differential operator are investigated. The tensor differential and its special types (Covariant tensor differential, and Lie tensor differential) are determined and their properties are discussed. Covariant symmetric and antisymmetric (external) tensor differentials, Lie symmetric, and Lie antisymmetric (external) tensor differentials are determined and considered over (L n bar, g)-spaces

  1. Tensor network method for reversible classical computation

    Science.gov (United States)

    Yang, Zhi-Cheng; Kourtis, Stefanos; Chamon, Claudio; Mucciolo, Eduardo R.; Ruckenstein, Andrei E.

    2018-03-01

    We develop a tensor network technique that can solve universal reversible classical computational problems, formulated as vertex models on a square lattice [Nat. Commun. 8, 15303 (2017), 10.1038/ncomms15303]. By encoding the truth table of each vertex constraint in a tensor, the total number of solutions compatible with partial inputs and outputs at the boundary can be represented as the full contraction of a tensor network. We introduce an iterative compression-decimation (ICD) scheme that performs this contraction efficiently. The ICD algorithm first propagates local constraints to longer ranges via repeated contraction-decomposition sweeps over all lattice bonds, thus achieving compression on a given length scale. It then decimates the lattice via coarse-graining tensor contractions. Repeated iterations of these two steps gradually collapse the tensor network and ultimately yield the exact tensor trace for large systems, without the need for manual control of tensor dimensions. Our protocol allows us to obtain the exact number of solutions for computations where a naive enumeration would take astronomically long times.

  2. Robust estimation of adaptive tensors of curvature by tensor voting.

    Science.gov (United States)

    Tong, Wai-Shun; Tang, Chi-Keung

    2005-03-01

    Although curvature estimation from a given mesh or regularly sampled point set is a well-studied problem, it is still challenging when the input consists of a cloud of unstructured points corrupted by misalignment error and outlier noise. Such input is ubiquitous in computer vision. In this paper, we propose a three-pass tensor voting algorithm to robustly estimate curvature tensors, from which accurate principal curvatures and directions can be calculated. Our quantitative estimation is an improvement over the previous two-pass algorithm, where only qualitative curvature estimation (sign of Gaussian curvature) is performed. To overcome misalignment errors, our improved method automatically corrects input point locations at subvoxel precision, which also rejects outliers that are uncorrectable. To adapt to different scales locally, we define the RadiusHit of a curvature tensor to quantify estimation accuracy and applicability. Our curvature estimation algorithm has been proven with detailed quantitative experiments, performing better in a variety of standard error metrics (percentage error in curvature magnitudes, absolute angle difference in curvature direction) in the presence of a large amount of misalignment noise.

  3. On the concircular curvature tensor of Riemannian manifolds

    International Nuclear Information System (INIS)

    Rahman, M.S.; Lal, S.

    1990-06-01

    Definition of the concircular curvature tensor, Z hijk , along with Z-tensor, Z ij , is given and some properties of Z hijk are described. Tensors identical with Z hijk are shown. A necessary and sufficient condition that a Riemannian V n has zero Z-tensor is found. A number of theorems on concircular symmetric space, concircular recurrent space (Z n -space) and Z n -space with zero Z-tensor are deduced. (author). 6 refs

  4. Tensoral for post-processing users and simulation authors

    Science.gov (United States)

    Dresselhaus, Eliot

    1993-01-01

    The CTR post-processing effort aims to make turbulence simulations and data more readily and usefully available to the research and industrial communities. The Tensoral language, which provides the foundation for this effort, is introduced here in the form of a user's guide. The Tensoral user's guide is presented in two main sections. Section one acts as a general introduction and guides database users who wish to post-process simulation databases. Section two gives a brief description of how database authors and other advanced users can make simulation codes and/or the databases they generate available to the user community via Tensoral database back ends. The two-part structure of this document conforms to the two-level design structure of the Tensoral language. Tensoral has been designed to be a general computer language for performing tensor calculus and statistics on numerical data. Tensoral's generality allows it to be used for stand-alone native coding of high-level post-processing tasks (as described in section one of this guide). At the same time, Tensoral's specialization to a minute task (namely, to numerical tensor calculus and statistics) allows it to be easily embedded into applications written partly in Tensoral and partly in other computer languages (here, C and Vectoral). Embedded Tensoral, aimed at advanced users for more general coding (e.g. of efficient simulations, for interfacing with pre-existing software, for visualization, etc.), is described in section two of this guide.

  5. Renal water molecular diffusion characteristics in healthy native kidneys: assessment with diffusion tensor MR imaging.

    Directory of Open Access Journals (Sweden)

    Zhenfeng Zheng

    Full Text Available BACKGROUND: To explore the characteristics of diffusion tensor imaging (DTI and magnetic resonance (MR imaging in healthy native kidneys. METHODS: Seventy-three patients without chronic kidney disease underwent DTI-MRI with spin echo-echo planar (SE-EPI sequences accompanied by an array spatial sensitivity encoding technique (ASSET. Cortical and medullary mean, axial and radial diffusivity (MD, AD and RD, fractional anisotropy (FA and primary, secondary and tertiary eigenvalues (λ1, λ2, λ3 were analysed in both kidneys and in different genders. RESULTS: Cortical MD, λ2, λ3, and RD values were higher than corresponding medullary values. The cortical FA value was lower than the medullary FA value. Medullary λ1 and RD values in the left kidney were lower than in the right kidney. Medullary λ2, and λ3 values in women were higher than those in men. Medullary FA values in women were lower than those in men. Medullary FA (r = 0.351, P = 0.002 and λ1 (r = 0.277, P = 0.018 positively correlated with eGFR. Medullary FA (r = -0.25, P = 0.033 negatively correlated with age. CONCLUSIONS: Renal water molecular diffusion differences exist in human kidneys and genders. Age and eGFR correlate with medullary FA and primary eigenvalue.

  6. Quantitative analysis of diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) for brain disorders

    Science.gov (United States)

    Lee, Jae-Seung; Im, In-Chul; Kang, Su-Man; Goo, Eun-Hoe; Kwak, Byung-Joon

    2013-07-01

    This study aimed to quantitatively analyze data from diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) in patients with brain disorders and to assess its potential utility for analyzing brain function. DTI was obtained by performing 3.0-T magnetic resonance imaging for patients with Alzheimer's disease (AD) and vascular dementia (VD), and the data were analyzed using Matlab-based SPM software. The two-sample t-test was used for error analysis of the location of the activated pixels. We compared regions of white matter where the fractional anisotropy (FA) values were low and the apparent diffusion coefficients (ADCs) were increased. In the AD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right sub-lobar insula, and right occipital lingual gyrus whereas the ADCs were significantly increased in the right inferior frontal gyrus and right middle frontal gyrus. In the VD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right limbic cingulate gyrus, and right sub-lobar caudate tail whereas the ADCs were significantly increased in the left lateral globus pallidus and left medial globus pallidus. In conclusion by using DTI and SPM analysis, we were able to not only determine the structural state of the regions affected by brain disorders but also quantitatively analyze and assess brain function.

  7. Magnetic resonance imaging and tensor-based morphometry in the MPTP non-human primate model of Parkinson’s disease

    Science.gov (United States)

    Crum, William R.; Gerwig, Madeline; Vernon, Anthony C.; Patel, Priya; Jackson, Michael J.; Rose, Sarah; Jenner, Peter; Iravani, Mahmoud M.

    2017-01-01

    Parkinson’s disease (PD) is the second most common neurodegenerative disorder producing a variety of motor and cognitive deficits with the causes remaining largely unknown. The gradual loss of the nigrostriatal pathway is currently considered the pivotal pathological event. To better understand the progression of PD and improve treatment management, defining the disease on a structural basis and expanding brain analysis to extra-nigral structures is indispensable. The anatomical complexity and the presence of neuromelanin, make the use of non-human primates an essential element in developing putative imaging biomarkers of PD. To this end, ex vivo T2-weighted magnetic resonance images were acquired from control and 1-methyl-4 phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated marmosets. Volume measurements of the caudate, putamen, and substantia nigra indicated significant atrophy and cortical thinning. Tensor-based morphometry provided a more extensive and hypothesis free assessment of widespread changes caused by the toxin insult to the brain, especially highlighting regional cortical atrophy. The results highlight the importance of developing imaging biomarkers of PD in non-human primate models considering their distinct neuroanatomy. It is essential to further develop these biomarkers in vivo to provide non-invasive tools to detect pre-symptomatic PD and to monitor potential disease altering therapeutics. PMID:28738061

  8. Geometric decomposition of the conformation tensor in viscoelastic turbulence

    Science.gov (United States)

    Hameduddin, Ismail; Meneveau, Charles; Zaki, Tamer A.; Gayme, Dennice F.

    2018-05-01

    This work introduces a mathematical approach to analysing the polymer dynamics in turbulent viscoelastic flows that uses a new geometric decomposition of the conformation tensor, along with associated scalar measures of the polymer fluctuations. The approach circumvents an inherent difficulty in traditional Reynolds decompositions of the conformation tensor: the fluctuating tensor fields are not positive-definite and so do not retain the physical meaning of the tensor. The geometric decomposition of the conformation tensor yields both mean and fluctuating tensor fields that are positive-definite. The fluctuating tensor in the present decomposition has a clear physical interpretation as a polymer deformation relative to the mean configuration. Scalar measures of this fluctuating conformation tensor are developed based on the non-Euclidean geometry of the set of positive-definite tensors. Drag-reduced viscoelastic turbulent channel flow is then used an example case study. The conformation tensor field, obtained using direct numerical simulations, is analysed using the proposed framework.

  9. Diagnostic utility of novel MRI-based biomarkers for Alzheimer's disease: diffusion tensor imaging and deformation-based morphometry.

    Science.gov (United States)

    Friese, Uwe; Meindl, Thomas; Herpertz, Sabine C; Reiser, Maximilian F; Hampel, Harald; Teipel, Stefan J

    2010-01-01

    We report evidence that multivariate analyses of deformation-based morphometry and diffusion tensor imaging (DTI) data can be used to discriminate between healthy participants and patients with Alzheimer's disease (AD) with comparable diagnostic accuracy. In contrast to other studies on MRI-based biomarkers which usually only focus on a single modality, we derived deformation maps from high-dimensional normalization of T1-weighted images, as well as mean diffusivity maps and fractional anisotropy maps from DTI of the same group of 21 patients with AD and 20 healthy controls. Using an automated multivariate analysis of the entire brain volume, widespread decreased white matter integrity and atrophy effects were found in cortical and subcortical regions of AD patients. Mean diffusivity maps and deformation maps were equally effective in discriminating between AD patients and controls (AUC =0.88 vs. AUC=0.85) while fractional anisotropy maps performed slightly inferior. Combining the maps from different modalities in a logistic regression model resulted in a classification accuracy of AUC=0.86 after leave-one-out cross-validation. It remains to be shown if this automated multivariate analysis of DTI-measures can improve early diagnosis of AD in predementia stages.

  10. Diffusion tensor imaging in evaluation of posterior fossa tumors in children on a 3T MRI scanner

    International Nuclear Information System (INIS)

    Assis, Zarina Abdul; Saini, Jitender; Ranjan, Manish; Gupta, Arun Kumar; Sabharwal, Paramveer; Naidu, Purushotham R

    2015-01-01

    Primary intracranial tumors in children are commonly located in the posterior fossa. Conventional MRI offers limited information regarding the histopathological type of tumor which is essential for better patient management. The purpose of the study was to evaluate the usefulness of advanced MR imaging techniques like diffusion tensor imaging (DTI) in distinguishing the various histopathological types of posterior fossa tumors in children. DTI was performed on a 3T MRI scanner in 34 untreated children found to have posterior fossa lesions. Using third party software, various DTI parameters [apparent diffusion coefficient (ADC), fractional anisotropy (FA), radial diffusivity, planar index, spherical index, and linear index] were calculated for the lesion. Data were subjected to statistical analysis [analysis of variance (ANOVA)] using SPSS 15.0 software. We observed significant correlation (P < 0.01) between ADC mean and maximum, followed by radial diffusivity (RD) with the histopathological types of the lesions. Rest of the DTI parameters did not show any significant correlation in our study. The results of our study support the hypothesis that most cellular tumors and those with greater nuclear area like medulloblastoma would have the lowest ADC values, as compared to less cellular tumors like pilocytic astrocytoma

  11. Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson's correlation.

    Science.gov (United States)

    Graña, M; Termenon, M; Savio, A; Gonzalez-Pinto, A; Echeveste, J; Pérez, J M; Besga, A

    2011-09-20

    The aim of this paper is to obtain discriminant features from two scalar measures of Diffusion Tensor Imaging (DTI) data, Fractional Anisotropy (FA) and Mean Diffusivity (MD), and to train and test classifiers able to discriminate Alzheimer's Disease (AD) patients from controls on the basis of features extracted from the FA or MD volumes. In this study, support vector machine (SVM) classifier was trained and tested on FA and MD data. Feature selection is done computing the Pearson's correlation between FA or MD values at voxel site across subjects and the indicative variable specifying the subject class. Voxel sites with high absolute correlation are selected for feature extraction. Results are obtained over an on-going study in Hospital de Santiago Apostol collecting anatomical T1-weighted MRI volumes and DTI data from healthy control subjects and AD patients. FA features and a linear SVM classifier achieve perfect accuracy, sensitivity and specificity in several cross-validation studies, supporting the usefulness of DTI-derived features as an image-marker for AD and to the feasibility of building Computer Aided Diagnosis systems for AD based on them. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  12. Assessment of tissue heterogeneity using diffusion tensor and diffusion kurtosis imaging for grading gliomas

    Energy Technology Data Exchange (ETDEWEB)

    Raja, Rajikha; Sinha, Neelam [International Institute of Information Technology-Bangalore, Bangalore (India); Saini, Jitender; Mahadevan, Anita; Rao, K.V.L. Narasinga; Swaminathan, Aarthi [National Institute of Mental Health and Neurosciences, Bangalore (India)

    2016-12-15

    In this work, we aim to assess the significance of diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) parameters in grading gliomas. Retrospective studies were performed on 53 subjects with gliomas belonging to WHO grade II (n = 19), grade III (n = 20) and grade IV (n = 14). Expert marked regions of interest (ROIs) covering the tumour on T2-weighted images. Statistical texture measures such as entropy and busyness calculated over ROIs on diffusion parametric maps were used to assess the tumour heterogeneity. Additionally, we propose a volume heterogeneity index derived from cross correlation (CC) analysis as a tool for grading gliomas. The texture measures were compared between grades by performing the Mann-Whitney test followed by receiver operating characteristic (ROC) analysis for evaluating diagnostic accuracy. Entropy, busyness and volume heterogeneity index for all diffusion parameters except fractional anisotropy and anisotropy of kurtosis showed significant differences between grades. The Mann-Whitney test on mean diffusivity (MD), among DTI parameters, resulted in the highest discriminability with values of P = 0.029 (0.0421) for grade II vs. III and P = 0.0312 (0.0415) for III vs. IV for entropy (busyness). In DKI, mean kurtosis (MK) showed the highest discriminability, P = 0.018 (0.038) for grade II vs. III and P = 0.022 (0.04) for III vs. IV for entropy (busyness). Results of CC analysis illustrate the existence of homogeneity in volume (uniformity across slices) for lower grades, as compared to higher grades. Hypothesis testing performed on volume heterogeneity index showed P values of 0.0002 (0.0001) and 0.0003 (0.0003) between grades II vs. III and III vs. IV, respectively, for MD (MK). In summary, the studies demonstrated great potential towards automating grading gliomas by employing tumour heterogeneity measures on DTI and DKI parameters. (orig.)

  13. Assessment of tissue heterogeneity using diffusion tensor and diffusion kurtosis imaging for grading gliomas

    International Nuclear Information System (INIS)

    Raja, Rajikha; Sinha, Neelam; Saini, Jitender; Mahadevan, Anita; Rao, K.V.L. Narasinga; Swaminathan, Aarthi

    2016-01-01

    In this work, we aim to assess the significance of diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) parameters in grading gliomas. Retrospective studies were performed on 53 subjects with gliomas belonging to WHO grade II (n = 19), grade III (n = 20) and grade IV (n = 14). Expert marked regions of interest (ROIs) covering the tumour on T2-weighted images. Statistical texture measures such as entropy and busyness calculated over ROIs on diffusion parametric maps were used to assess the tumour heterogeneity. Additionally, we propose a volume heterogeneity index derived from cross correlation (CC) analysis as a tool for grading gliomas. The texture measures were compared between grades by performing the Mann-Whitney test followed by receiver operating characteristic (ROC) analysis for evaluating diagnostic accuracy. Entropy, busyness and volume heterogeneity index for all diffusion parameters except fractional anisotropy and anisotropy of kurtosis showed significant differences between grades. The Mann-Whitney test on mean diffusivity (MD), among DTI parameters, resulted in the highest discriminability with values of P = 0.029 (0.0421) for grade II vs. III and P = 0.0312 (0.0415) for III vs. IV for entropy (busyness). In DKI, mean kurtosis (MK) showed the highest discriminability, P = 0.018 (0.038) for grade II vs. III and P = 0.022 (0.04) for III vs. IV for entropy (busyness). Results of CC analysis illustrate the existence of homogeneity in volume (uniformity across slices) for lower grades, as compared to higher grades. Hypothesis testing performed on volume heterogeneity index showed P values of 0.0002 (0.0001) and 0.0003 (0.0003) between grades II vs. III and III vs. IV, respectively, for MD (MK). In summary, the studies demonstrated great potential towards automating grading gliomas by employing tumour heterogeneity measures on DTI and DKI parameters. (orig.)

  14. Diffusion tensor MR imaging (DTI) metrics in the cervical spinal cord in asymptomatic HIV-positive patients

    Energy Technology Data Exchange (ETDEWEB)

    Mueller-Mang, Christina; Mang, Thomas; Fruehwald-Pallamar, Julia; Weber, Michael; Thurnher, Majda M. [Medical University of Vienna, Department of Radiology, Vienna (Austria); Law, Meng [University of Southern California, Los Angeles County Hospital and USC Medical Center, Department of Radiology, Keck School of Medicine, Los Angeles, CA (United States)

    2011-08-15

    This study was conducted to compare diffusion tensor MR imaging (DTI) metrics of the cervical spinal cord in asymptomatic human immunodeficiency virus (HIV)-positive patients with those measured in healthy volunteers, and to assess whether DTI is a valuable diagnostic tool in the early detection of HIV-associated myelopathy (HIVM). MR imaging of the cervical spinal cord was performed in 20 asymptomatic HIV-positive patients and in 20 healthy volunteers on a 3-T MR scanner. Average fractional anisotropy (FA), mean diffusivity (MD), and major (E1) and minor (E2, E3) eigenvalues were calculated within regions of interest (ROIs) at the C2/3 level (central and bilateral anterior, lateral and posterior white matter). Statistical analysis showed significant differences with regard to mean E3 values between patients and controls (p = 0.045; mixed-model analysis of variance (ANOVA) test). Mean FA was lower, and mean MD, mean E1, and mean E2 were higher in each measured ROI in patients compared to controls, but these differences were not statistically significant. Asymptomatic HIV-positive patients demonstrate only subtle changes in DTI metrics measured in the cervical spinal cord compared to healthy volunteers that currently do not support using DTI as a diagnostic tool for the early detection of HIVM. (orig.)

  15. Detecting brain growth patterns in normal children using tensor-based morphometry.

    Science.gov (United States)

    Hua, Xue; Leow, Alex D; Levitt, Jennifer G; Caplan, Rochelle; Thompson, Paul M; Toga, Arthur W

    2009-01-01

    Previous magnetic resonance imaging (MRI)-based volumetric studies have shown age-related increases in the volume of total white matter and decreases in the volume of total gray matter of normal children. Recent adaptations of image analysis strategies enable the detection of human brain growth with improved spatial resolution. In this article, we further explore the spatio-temporal complexity of adolescent brain maturation with tensor-based morphometry. By utilizing a novel non-linear elastic intensity-based registration algorithm on the serial structural MRI scans of 13 healthy children, individual Jacobian growth maps are generated and then registered to a common anatomical space. Statistical analyses reveal significant tissue growth in cerebral white matter, contrasted with gray matter loss in parietal, temporal, and occipital lobe. In addition, a linear regression with age and gender suggests a slowing down of the growth rate in regions with the greatest white matter growth. We demonstrate that a tensor-based Jacobian map is a sensitive and reliable method to detect regional tissue changes during development. (c) 2007 Wiley-Liss, Inc.

  16. Applications of tensor functions in creep mechanics

    International Nuclear Information System (INIS)

    Betten, J.

    1991-01-01

    Within this contribution a short survey is given of some recent advances in the mathematical modelling of materials behaviour under creep conditions. The mechanical behaviour of anisotropic solids requires a suitable mathematical modelling. The properties of tensor functions with several argument tensors constitute a rational basis for a consistent mathematical modelling of complex material behaviour. This paper presents certain principles, methods, and recent successfull applications of tensor functions in solid mechanics. The rules for specifying irreducible sets of tensor invariants and tensor generators for material tensors of rank two and four are also discussed. Furthermore, it is very important that the scalar coefficients in constitutive and evolutional equations are determined as functions of the integrity basis and experimental data. It is explained in detail that these coefficients can be determined by using tensorial interpolation methods. Some examples for practical use are discussed. (orig./RHM)

  17. Gap filling of 3-D microvascular networks by tensor voting.

    Science.gov (United States)

    Risser, L; Plouraboue, F; Descombes, X

    2008-05-01

    We present a new algorithm which merges discontinuities in 3-D images of tubular structures presenting undesirable gaps. The application of the proposed method is mainly associated to large 3-D images of microvascular networks. In order to recover the real network topology, we need to fill the gaps between the closest discontinuous vessels. The algorithm presented in this paper aims at achieving this goal. This algorithm is based on the skeletonization of the segmented network followed by a tensor voting method. It permits to merge the most common kinds of discontinuities found in microvascular networks. It is robust, easy to use, and relatively fast. The microvascular network images were obtained using synchrotron tomography imaging at the European Synchrotron Radiation Facility. These images exhibit samples of intracortical networks. Representative results are illustrated.

  18. ZOOM or Non-ZOOM? Assessing Spinal Cord Diffusion Tensor Imaging Protocols for Multi-Centre Studies.

    Directory of Open Access Journals (Sweden)

    Rebecca S Samson

    Full Text Available The purpose of this study was to develop and evaluate two spinal cord (SC diffusion tensor imaging (DTI protocols, implemented at multiple sites (using scanners from two different manufacturers, one available on any clinical scanner, and one using more advanced options currently available in the research setting, and to use an automated processing method for unbiased quantification. DTI parameters are sensitive to changes in the diseased SC. However, imaging the cord can be technically challenging due to various factors including its small size, patient-related and physiological motion, and field inhomogeneities. Rapid acquisition sequences such as Echo Planar Imaging (EPI are desirable but may suffer from image distortions. We present a multi-centre comparison of two acquisition protocols implemented on scanners from two different vendors (Siemens and Philips, one using a reduced field-of-view (rFOV EPI sequence, and one only using options available on standard clinical scanners such as outer volume suppression (OVS. Automatic analysis was performed with the Spinal Cord Toolbox for unbiased and reproducible quantification of DTI metrics in the white matter. Images acquired using the rFOV sequence appear less distorted than those acquired using OVS alone. SC DTI parameter values obtained using both sequences at all sites were consistent with previous measurements made at 3T. For the same scanner manufacturer, DTI parameter inter-site SDs were smaller for the rFOV sequence compared to the OVS sequence. The higher inter-site reproducibility (for the same manufacturer and acquisition details, i.e. ZOOM data acquired at the two Philips sites of rFOV compared to the OVS sequence supports the idea that making research options such as rFOV more widely available would improve accuracy of measurements obtained in multi-centre clinical trials. Future multi-centre studies should also aim to match the rFOV technique and signal-to-noise ratios in all

  19. Tensor interaction in heavy-ion scattering. Pt. 1

    International Nuclear Information System (INIS)

    Nishioka, H.; Johnson, R.C.

    1985-01-01

    The Heidelberg shape-effect model for heavy-ion tensor interactions is reformulated and generalized using the Hooton-Johnson formulation. The generalized semiclassical model (the turning-point model) predicts that the components of the tensor analysing power anti Tsub(2q) have certain relations with each other for each type of tensor interaction (Tsub(R), Tsub(P) and Tsub(L) types). The predicted relations between the anti Tsub(2q) are very simple and have a direct connection with the properties of the tensor interaction at the turning point. The model predictions are satisfied in quantum-mechanical calculations for 7 Li and 23 Na elastic scattering from 58 Ni in the Fresnel-diffraction energy region. As a consequence of this model, it becomes possible to single out effects from a Tsub(P)- or Tsub(L)-type tensor interaction in polarized heavy-ion scattering. The presence of a Tsub(P)-type tensor interaction is suggested by measured anti T 20 /anti T 22 ratios for 7 Li + 58 Ni scattering. In the turning-point model the three types of tensor operator are not independent, and this is found to be true also in a quantum-mechanical calculation. The model also predicts relations between the components of higher-rank tensor analysing power in the presence of a higher-rank tensor interaction. The rank-3 tensor case is discussed in detail. (orig.)

  20. Serial Diffusion Tensor Imaging of the Optic Radiations after Acute Optic Neuritis

    Directory of Open Access Journals (Sweden)

    Scott C. Kolbe

    2016-01-01

    Full Text Available Previous studies have reported diffusion tensor imaging (DTI changes within the optic radiations of patients after optic neuritis (ON. We aimed to study optic radiation DTI changes over 12 months following acute ON and to study correlations between DTI parameters and damage to the optic nerve and primary visual cortex (V1. We measured DTI parameters [fractional anisotropy (FA, axial diffusivity (AD, radial diffusivity (RD, and mean diffusivity (MD] from the optic radiations of 38 acute ON patients at presentation and 6 and 12 months after acute ON. In addition, we measured retinal nerve fibre layer thickness, visual evoked potential amplitude, optic radiation lesion load, and V1 thickness. At baseline, FA was reduced and RD and MD were increased compared to control. Over 12 months, FA reduced in patients at an average rate of −2.6% per annum (control = −0.51%; p=0.006. Change in FA, RD, and MD correlated with V1 thinning over 12 months (FA: R=0.450, p=0.006; RD: R=-0.428, p=0.009; MD: R=-0.365, p=0.029. In patients with no optic radiation lesions, AD significantly correlated with RNFL thinning at 12 months (R=0.489, p=0.039. In conclusion, DTI can detect optic radiation changes over 12 months following acute ON that correlate with optic nerve and V1 damage.