Brain tumor segmentation with Deep Neural Networks.

Science.gov (United States)

Havaei, Mohammad; Davy, Axel; Warde-Farley, David; Biard, Antoine; Courville, Aaron; Bengio, Yoshua; Pal, Chris; Jodoin, Pierre-Marc; Larochelle, Hugo

2017-01-01

In this paper, we present a fully automatic brain tumor segmentation method based on Deep Neural Networks (DNNs). The proposed networks are tailored to glioblastomas (both low and high grade) pictured in MR images. By their very nature, these tumors can appear anywhere in the brain and have almost any kind of shape, size, and contrast. These reasons motivate our exploration of a machine learning solution that exploits a flexible, high capacity DNN while being extremely efficient. Here, we give a description of different model choices that we've found to be necessary for obtaining competitive performance. We explore in particular different architectures based on Convolutional Neural Networks (CNN), i.e. DNNs specifically adapted to image data. We present a novel CNN architecture which differs from those traditionally used in computer vision. Our CNN exploits both local features as well as more global contextual features simultaneously. Also, different from most traditional uses of CNNs, our networks use a final layer that is a convolutional implementation of a fully connected layer which allows a 40 fold speed up. We also describe a 2-phase training procedure that allows us to tackle difficulties related to the imbalance of tumor labels. Finally, we explore a cascade architecture in which the output of a basic CNN is treated as an additional source of information for a subsequent CNN. Results reported on the 2013 BRATS test data-set reveal that our architecture improves over the currently published state-of-the-art while being over 30 times faster. Copyright © 2016 Elsevier B.V. All rights reserved.

Segmentation of tumors in magnetic resonance brain images using an interactive multiscale watershed algorithm

DEFF Research Database (Denmark)

Letteboer, Marloes M J; Olsen, Ole F; Dam, Erik B

2004-01-01

RATIONALE AND OBJECTIVE: This article presents the evaluation of an interactive multiscale watershed segmentation algorithm for segmenting tumors in magnetic resonance brain images of patients scheduled for neuronavigational procedures. MATERIALS AND METHODS: The watershed method is compared...... delineation shows that the two methods are interchangeable according to the Bland and Altman criterion, and thus equally accurate. The repeatability of the watershed method and the manual method are compared by looking at the similarity of the segmented volumes. The similarity for intraobserver...

Method of image segmentation using a neural network. Application to MR imaging of brain tumors

International Nuclear Information System (INIS)

Engler, E.; Gautherie, M.

1992-01-01

An original method of numerical images segmentation has been developed. This method is based on pixel clustering using a formal neural network configurated by supervised learning of pre-classified examples. The method has been applied to series of MR images of brain tumors (gliomas) with a view to proceed with a 3D-extraction of the tumor volume. This study is part of a project on cancer thermotherapy including the development of a scan-focused ultrasound system of tumor heating and a 3D-numerical thermal model

Image Denoising And Segmentation Approchto Detect Tumor From BRAINMRI Images

Directory of Open Access Journals (Sweden)

Shanta Rangaswamy

2018-04-01

Full Text Available The detection of the Brain Tumor is a challenging problem, due to the structure of the Tumor cells in the brain. This project presents a systematic method that enhances the detection of brain tumor cells and to analyze functional structures by training and classification of the samples in SVM and tumor cell segmentation of the sample using DWT algorithm. From the input MRI Images collected, first noise is removed from MRI images by applying wiener filtering technique. In image enhancement phase, all the color components of MRI Images will be converted into gray scale image and make the edges clear in the image to get better identification and improvised quality of the image. In the segmentation phase, DWT on MRI Image to segment the grey-scale image is performed. During the post-processing, classification of tumor is performed by using SVM classifier. Wiener Filter, DWT, SVM Segmentation strategies were used to find and group the tumor position in the MRI filtered picture respectively. An essential perception in this work is that multi arrange approach utilizes various leveled classification strategy which supports execution altogether. This technique diminishes the computational complexity quality in time and memory. This classification strategy works accurately on all images and have achieved the accuracy of 93%.

Anisotropic Diffusion based Brain MRI Segmentation and 3D Reconstruction

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M. Arfan Jaffar

2012-06-01

Full Text Available In medical field visualization of the organs is very imperative for accurate diagnosis and treatment of any disease. Brain tumor diagnosis and surgery also required impressive 3D visualization of the brain to the radiologist. Detection and 3D reconstruction of brain tumors from MRI is a computationally time consuming and error-prone task. Proposed system detects and presents a 3D visualization model of the brain and tumor inside which greatly helps the radiologist to effectively diagnose and analyze the brain tumor. We proposed a multi-phase segmentation and visualization technique which overcomes the many problems of 3D volume segmentation methods like lake of fine details. In this system segmentation is done in three different phases which reduces the error chances. The system finds contours for skull, brain and tumor. These contours are stacked over and two novel methods are used to find the 3D visualization models. The results of these techniques, particularly of interpolation based, are impressive. Proposed system is tested against publically available data set [41] and MRI datasets available from MRI aamp; CT center Rawalpindi, Pakistan [42].

FLAIR lesion segmentation: Application in patients with brain tumors and acute ischemic stroke

International Nuclear Information System (INIS)

Artzi, Moran; Aizenstein, Orna; Jonas-Kimchi, Tali; Myers, Vicki; Hallevi, Hen; Ben Bashat, Dafna

2013-01-01

Background: Lesion size in fluid attenuation inversion recovery (FLAIR) images is an important clinical parameter for patient assessment and follow-up. Although manual delineation of lesion areas considered as ground truth, it is time-consuming, highly user-dependent and difficult to perform in areas of indistinct borders. In this study, an automatic methodology for FLAIR lesion segmentation is proposed, and its application in patients with brain tumors undergoing therapy; and in patients following stroke is demonstrated. Materials and methods: FLAIR lesion segmentation was performed in 57 magnetic resonance imaging (MRI) data sets obtained from 44 patients: 28 patients with primary brain tumors; 5 patients with recurrent-progressive glioblastoma (rGB) who were scanned longitudinally during anti-angiogenic therapy (18 MRI scans); and 11 patients following ischemic stroke. Results: FLAIR lesion segmentation was obtained in all patients. When compared to manual delineation, a high visual similarity was observed, with an absolute relative volume difference of 16.80% and 20.96% and a volumetric overlap error of 24.87% and 27.50% obtained for two raters: accepted values for automatic methods. Quantitative measurements of the segmented lesion volumes were in line with qualitative radiological assessment in four patients who received anti-anogiogenic drugs. In stroke patients the proposed methodology enabled identification of the ischemic lesion and differentiation from other FLAIR hyperintense areas, such as pre-existing disease. Conclusion: This study proposed a replicable methodology for FLAIR lesion detection and quantification and for discrimination between lesion of interest and pre-existing disease. Results from this study show the wide clinical applications of this methodology in research and clinical practice

FLAIR lesion segmentation: Application in patients with brain tumors and acute ischemic stroke

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Artzi, Moran, E-mail: artzimy@gmail.com [The Functional Brain Center, The Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel); Aizenstein, Orna, E-mail: ornaaize@gmail.com [The Functional Brain Center, The Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Jonas-Kimchi, Tali, E-mail: talijk@tlvmc.gov.il [Radiology Department, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Myers, Vicki, E-mail: vicki_myers@hotmail.com [The Functional Brain Center, The Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Hallevi, Hen, E-mail: hen.hallevi@gmail.com [Neurology Department, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Ben Bashat, Dafna, E-mail: dafnab@tlvmc.gov.il [The Functional Brain Center, The Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel Aviv (Israel); Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv (Israel)

2013-09-15

Background: Lesion size in fluid attenuation inversion recovery (FLAIR) images is an important clinical parameter for patient assessment and follow-up. Although manual delineation of lesion areas considered as ground truth, it is time-consuming, highly user-dependent and difficult to perform in areas of indistinct borders. In this study, an automatic methodology for FLAIR lesion segmentation is proposed, and its application in patients with brain tumors undergoing therapy; and in patients following stroke is demonstrated. Materials and methods: FLAIR lesion segmentation was performed in 57 magnetic resonance imaging (MRI) data sets obtained from 44 patients: 28 patients with primary brain tumors; 5 patients with recurrent-progressive glioblastoma (rGB) who were scanned longitudinally during anti-angiogenic therapy (18 MRI scans); and 11 patients following ischemic stroke. Results: FLAIR lesion segmentation was obtained in all patients. When compared to manual delineation, a high visual similarity was observed, with an absolute relative volume difference of 16.80% and 20.96% and a volumetric overlap error of 24.87% and 27.50% obtained for two raters: accepted values for automatic methods. Quantitative measurements of the segmented lesion volumes were in line with qualitative radiological assessment in four patients who received anti-anogiogenic drugs. In stroke patients the proposed methodology enabled identification of the ischemic lesion and differentiation from other FLAIR hyperintense areas, such as pre-existing disease. Conclusion: This study proposed a replicable methodology for FLAIR lesion detection and quantification and for discrimination between lesion of interest and pre-existing disease. Results from this study show the wide clinical applications of this methodology in research and clinical practice.

An Ensemble of 2D Convolutional Neural Networks for Tumor Segmentation

DEFF Research Database (Denmark)

Lyksborg, Mark; Puonti, Oula; Agn, Mikael

2015-01-01

Accurate tumor segmentation plays an important role in radiosurgery planning and the assessment of radiotherapy treatment efficacy. In this paper we propose a method combining an ensemble of 2D convolutional neural networks for doing a volumetric segmentation of magnetic resonance images....... The segmentation is done in three steps; first the full tumor region, is segmented from the background by a voxel-wise merging of the decisions of three networks learned from three orthogonal planes, next the segmentation is refined using a cellular automaton-based seed growing method known as growcut. Finally......, within-tumor sub-regions are segmented using an additional ensemble of networks trained for the task. We demonstrate the method on the MICCAI Brain Tumor Segmentation Challenge dataset of 2014, and show improved segmentation accuracy compared to an axially trained 2D network and an ensemble segmentation...

FCM Clustering Algorithms for Segmentation of Brain MR Images

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Yogita K. Dubey

2016-01-01

Full Text Available The study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main tissue types: Cerebrospinal Fluid (CSF, Gray Matter (GM, and White Matter (WM, has important role in computer aided neurosurgery and diagnosis. Brain images mostly contain noise, intensity inhomogeneity, and weak boundaries. Therefore, accurate segmentation of brain images is still a challenging area of research. This paper presents a review of fuzzy c-means (FCM clustering algorithms for the segmentation of brain MR images. The review covers the detailed analysis of FCM based algorithms with intensity inhomogeneity correction and noise robustness. Different methods for the modification of standard fuzzy objective function with updating of membership and cluster centroid are also discussed.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

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Cui, Shaoguo; Mao, Lei; Jiang, Jingfeng; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice.

Brain tumor locating in 3D MR volume using symmetry

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Dvorak, Pavel; Bartusek, Karel

2014-03-01

This work deals with the automatic determination of a brain tumor location in 3D magnetic resonance volumes. The aim of this work is not the precise segmentation of the tumor and its parts but only the detection of its location. This work is the first step in the tumor segmentation process, an important topic in neuro-image processing. The algorithm expects 3D magnetic resonance volumes of brain containing a tumor. The detection is based on locating the area that breaks the left-right symmetry of the brain. This is done by multi-resolution comparing of corresponding regions in left and right hemisphere. The output of the computation is the probabilistic map of the tumor location. The created algorithm was tested on 80 volumes from publicly available BRATS databases containing 3D brain volumes afflicted by a brain tumor. These pathological structures had various sizes and shapes and were located in various parts of the brain. The locating performance of the algorithm was 85% for T1-weighted volumes, 91% for T1-weighted contrast enhanced volumes, 96% for FLAIR and T2-wieghted volumes and 95% for their combinations.

Brain's tumor image processing using shearlet transform

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Cadena, Luis; Espinosa, Nikolai; Cadena, Franklin; Korneeva, Anna; Kruglyakov, Alexey; Legalov, Alexander; Romanenko, Alexey; Zotin, Alexander

2017-09-01

Brain tumor detection is well known research area for medical and computer scientists. In last decades there has been much research done on tumor detection, segmentation, and classification. Medical imaging plays a central role in the diagnosis of brain tumors and nowadays uses methods non-invasive, high-resolution techniques, especially magnetic resonance imaging and computed tomography scans. Edge detection is a fundamental tool in image processing, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image has discontinuities. Shearlets is the most successful frameworks for the efficient representation of multidimensional data, capturing edges and other anisotropic features which frequently dominate multidimensional phenomena. The paper proposes an improved brain tumor detection method by automatically detecting tumor location in MR images, its features are extracted by new shearlet transform.

A survey of MRI-based medical image analysis for brain tumor studies

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Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P.; Reyes, Mauricio

2013-07-01

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

A survey of MRI-based medical image analysis for brain tumor studies

International Nuclear Information System (INIS)

Bauer, Stefan; Nolte, Lutz-P; Reyes, Mauricio; Wiest, Roland

2013-01-01

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines. (topical review)

Brain Tumors

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A brain tumor is a growth of abnormal cells in the tissues of the brain. Brain tumors can be benign, with no cancer cells, ... cancer cells that grow quickly. Some are primary brain tumors, which start in the brain. Others are ...

Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

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Tushar H Jaware

2013-10-01

Full Text Available Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clusteringmethods is presented.

Brain tumor - children

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... children; Neuroglioma - children; Oligodendroglioma - children; Meningioma - children; Cancer - brain tumor (children) ... The cause of primary brain tumors is unknown. Primary brain tumors may ... (spread to nearby areas) Cancerous (malignant) Brain tumors ...

Understanding Brain Tumors

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... to Know About Brain Tumors . What is a Brain Tumor? A brain tumor is an abnormal growth
 ... Tumors” from Frankly Speaking Frankly Speaking About Cancer: Brain Tumors Download the full book Questions to ask ...

Delineation and segmentation of cerebral tumors by mapping blood-brain barrier disruption with dynamic contrast-enhanced CT and tracer kinetics modeling-a feasibility study

International Nuclear Information System (INIS)

Bisdas, S.; Vogl, T.J.; Yang, X.; Koh, T.S.; Lim, C.C.T.

2008-01-01

Dynamic contrast-enhanced (DCE) imaging is a promising approach for in vivo assessment of tissue microcirculation. Twenty patients with clinical and routine computed tomography (CT) evidence of intracerebral neoplasm were examined with DCE-CT imaging. Using a distributed-parameter model for tracer kinetics modeling of DCE-CT data, voxel-level maps of cerebral blood flow (F), intravascular blood volume (v i ) and intravascular mean transit time (t 1 ) were generated. Permeability-surface area product (PS), extravascular extracellular blood volume (v e ) and extraction ratio (E) maps were also calculated to reveal pathologic locations of tracer extravasation, which are indicative of disruptions in the blood-brain barrier (BBB). All maps were visually assessed for quality of tumor delineation and measurement of tumor extent by two radiologists. Kappa (κ) coefficients and their 95% confidence intervals (CI) were calculated to determine the interobserver agreement for each DCE-CT map. There was a substantial agreement for the tumor delineation quality in the F, v e and t 1 maps. The agreement for the quality of the tumor delineation was excellent for the v i , PS and E maps. Concerning the measurement of tumor extent, excellent and nearly excellent agreement was achieved only for E and PS maps, respectively. According to these results, we performed a segmentation of the cerebral tumors on the base of the E maps. The interobserver agreement for the tumor extent quantification based on manual segmentation of tumor in the E maps vs. the computer-assisted segmentation was excellent (κ = 0.96, CI: 0.93-0.99). The interobserver agreement for the tumor extent quantification based on computer segmentation in the mean images and the E maps was substantial (κ = 0.52, CI: 0.42-0.59). This study illustrates the diagnostic usefulness of parametric maps associated with BBB disruption on a physiology-based approach and highlights the feasibility for automatic segmentation of

PCA based clustering for brain tumor segmentation of T1w MRI images.

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Kaya, Irem Ersöz; Pehlivanlı, Ayça Çakmak; Sekizkardeş, Emine Gezmez; Ibrikci, Turgay

2017-03-01

Medical images are huge collections of information that are difficult to store and process consuming extensive computing time. Therefore, the reduction techniques are commonly used as a data pre-processing step to make the image data less complex so that a high-dimensional data can be identified by an appropriate low-dimensional representation. PCA is one of the most popular multivariate methods for data reduction. This paper is focused on T1-weighted MRI images clustering for brain tumor segmentation with dimension reduction by different common Principle Component Analysis (PCA) algorithms. Our primary aim is to present a comparison between different variations of PCA algorithms on MRIs for two cluster methods. Five most common PCA algorithms; namely the conventional PCA, Probabilistic Principal Component Analysis (PPCA), Expectation Maximization Based Principal Component Analysis (EM-PCA), Generalize Hebbian Algorithm (GHA), and Adaptive Principal Component Extraction (APEX) were applied to reduce dimensionality in advance of two clustering algorithms, K-Means and Fuzzy C-Means. In the study, the T1-weighted MRI images of the human brain with brain tumor were used for clustering. In addition to the original size of 512 lines and 512 pixels per line, three more different sizes, 256 × 256, 128 × 128 and 64 × 64, were included in the study to examine their effect on the methods. The obtained results were compared in terms of both the reconstruction errors and the Euclidean distance errors among the clustered images containing the same number of principle components. According to the findings, the PPCA obtained the best results among all others. Furthermore, the EM-PCA and the PPCA assisted K-Means algorithm to accomplish the best clustering performance in the majority as well as achieving significant results with both clustering algorithms for all size of T1w MRI images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Semiautomatic segmentation and follow-up of multicomponent low-grade tumors in longitudinal brain MRI studies

International Nuclear Information System (INIS)

Weizman, Lior; Sira, Liat Ben; Joskowicz, Leo; Rubin, Daniel L.; Yeom, Kristen W.; Constantini, Shlomi; Shofty, Ben; Bashat, Dafna Ben

2014-01-01

Purpose: Tracking the progression of low grade tumors (LGTs) is a challenging task, due to their slow growth rate and associated complex internal tumor components, such as heterogeneous enhancement, hemorrhage, and cysts. In this paper, the authors show a semiautomatic method to reliably track the volume of LGTs and the evolution of their internal components in longitudinal MRI scans. Methods: The authors' method utilizes a spatiotemporal evolution modeling of the tumor and its internal components. Tumor components gray level parameters are estimated from the follow-up scan itself, obviating temporal normalization of gray levels. The tumor delineation procedure effectively incorporates internal classification of the baseline scan in the time-series as prior data to segment and classify a series of follow-up scans. The authors applied their method to 40 MRI scans of ten patients, acquired at two different institutions. Two types of LGTs were included: Optic pathway gliomas and thalamic astrocytomas. For each scan, a “gold standard” was obtained manually by experienced radiologists. The method is evaluated versus the gold standard with three measures: gross total volume error, total surface distance, and reliability of tracking tumor components evolution. Results: Compared to the gold standard the authors' method exhibits a mean Dice similarity volumetric measure of 86.58% and a mean surface distance error of 0.25 mm. In terms of its reliability in tracking the evolution of the internal components, the method exhibits strong positive correlation with the gold standard. Conclusions: The authors' method provides accurate and repeatable delineation of the tumor and its internal components, which is essential for therapy assessment of LGTs. Reliable tracking of internal tumor components over time is novel and potentially will be useful to streamline and improve follow-up of brain tumors, with indolent growth and behavior

A new method for brain tumor detection using the Bhattacharyya similarity coefficient, color conversions and neural network

Directory of Open Access Journals (Sweden)

Bahman Mansori

2015-10-01

Full Text Available Background: Magnetic resonance imaging (MRI is widely applied for examination and diagnosis of brain tumors based on its advantages of high resolution in detecting the soft tissues and especially of its harmless radiation damages to human bodies. The goal of the processing of images is automatic segmentation of brain edema and tumors, in different dimensions of the magnetic resonance images. Methods: The proposed method is based on the unsupervised method which discovers the tumor region, if there is any, by analyzing the similarities between two hemispheres and computes the image size of the goal function based on Bhattacharyya coefficient which is used in the next stage to detect the tumor region or some part of it. In this stage, for reducing the color variation, the gray brain image is segmented, then it is turned to gray again. The self-organizing map (SOM neural network is used the segmented brain image is colored and finally the tumor is detected by matching the detected region and the colored image. This method is proposed to analyze MRI images for discovering brain tumors, and done in Bu Ali Sina University, Hamedan, Iran, in 2014. Results: The results for 30 randomly selected images from data bank of MRI center in Hamedan was compared with manually segmentation of experts. The results showed that, our proposed method had the accuracy of more than 94% at Jaccard similarity index (JSI, 97% at Dice similarity score (DSS, and 98% and 99% at two measures of specificity and sensitivity. Conclusion: The experimental results showed that it was satisfactory and can be used in automatic separation of tumor from normal brain tissues and therefore it can be used in practical applications. The results showed that the use of SOM neural network to classify useful magnetic resonance imaging of the brain and demonstrated a good performance.

Brain tumor - primary - adults

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... Vestibular schwannoma (acoustic neuroma) - adults; Meningioma - adults; Cancer - brain tumor (adults) ... Primary brain tumors include any tumor that starts in the brain. Primary brain tumors can start from brain cells, ...

Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN

Science.gov (United States)

Pradhan, Nandita; Sinha, A. K.

2008-03-01

This paper presents an efficient region based segmentation technique for detecting pathological tissues (Tumor & Edema) of brain using fluid attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. This work segments FLAIR brain images for normal and pathological tissues based on statistical features and wavelet transform coefficients using k-means algorithm. The image is divided into small blocks of 4×4 pixels. The k-means algorithm is used to cluster the image based on the feature vectors of blocks forming different classes representing different regions in the whole image. With the knowledge of the feature vectors of different segmented regions, supervised technique is used to train Artificial Neural Network using fuzzy back propagation algorithm (FBPA). Segmentation for detecting healthy tissues and tumors has been reported by several researchers by using conventional MRI sequences like T1, T2 and PD weighted sequences. This work successfully presents segmentation of healthy and pathological tissues (both Tumors and Edema) using FLAIR images. At the end pseudo coloring of segmented and classified regions are done for better human visualization.

Brain Tumors (For Parents)

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... Staying Safe Videos for Educators Search English Español Brain Tumors KidsHealth / For Parents / Brain Tumors What's in ... radiation therapy or chemotherapy, or both. Types of Brain Tumors There are many different types of brain ...

Childhood Brain Tumors

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Brain tumors are abnormal growths inside the skull. They are among the most common types of childhood ... still be serious. Malignant tumors are cancerous. Childhood brain and spinal cord tumors can cause headaches and ...

Lung tumor segmentation in PET images using graph cuts.

Science.gov (United States)

Ballangan, Cherry; Wang, Xiuying; Fulham, Michael; Eberl, Stefan; Feng, David Dagan

2013-03-01

The aim of segmentation of tumor regions in positron emission tomography (PET) is to provide more accurate measurements of tumor size and extension into adjacent structures, than is possible with visual assessment alone and hence improve patient management decisions. We propose a segmentation energy function for the graph cuts technique to improve lung tumor segmentation with PET. Our segmentation energy is based on an analysis of the tumor voxels in PET images combined with a standardized uptake value (SUV) cost function and a monotonic downhill SUV feature. The monotonic downhill feature avoids segmentation leakage into surrounding tissues with similar or higher PET tracer uptake than the tumor and the SUV cost function improves the boundary definition and also addresses situations where the lung tumor is heterogeneous. We evaluated the method in 42 clinical PET volumes from patients with non-small cell lung cancer (NSCLC). Our method improves segmentation and performs better than region growing approaches, the watershed technique, fuzzy-c-means, region-based active contour and tumor customized downhill. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Pediatric brain tumors

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Poussaint, Tina Y. [Department of Radiology, Boston, MA (United States); Panigrahy, Ashok [Children' s Hospital of Pittsburgh of University of Pittsburgh Medical Center, Department of Radiology, Pittsburgh, PA (United States); Huisman, Thierry A.G.M. [Charlotte R. Bloomberg Children' s Center, Johns Hopkins Hospital, Division of Pediatric Radiology and Pediatric Neuroradiology, Baltimore, MD (United States)

2015-09-15

Among all causes of death in children from solid tumors, pediatric brain tumors are the most common. This article includes an overview of a subset of infratentorial and supratentorial tumors with a focus on tumor imaging features and molecular advances and treatments of these tumors. Key to understanding the imaging features of brain tumors is a firm grasp of other disease processes that can mimic tumor on imaging. We also review imaging features of a common subset of tumor mimics. (orig.)

Pediatric Brain Tumor Foundation

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... navigate their brain tumor diagnosis. WATCH AND SHARE Brain tumors and their treatment can be deadly so ... Pediatric Central Nervous System Cancers Read more >> Pediatric Brain Tumor Foundation 302 Ridgefield Court, Asheville, NC 28806 ...

Epilepsy and Brain Tumors

Institute of Scientific and Technical Information of China (English)

Zhi-yi Sha

2009-01-01

@@ Epidemiology It is estimated 61,414 new cases of primary brain tumors are expected to be diagnosed in 2009 in the U.S. The incidence statistic of 61,414 persons diagnosed per year includes both malignant (22,738) and non-malignant (38,677) brain tumors. (Data from American Brain Tumor Association). During the years 2004-2005, approximately 359,000 people in the United States were living with the diagnosis of a primary brain or central nervous system tumor. Specifically, more than 81,000 persons were living with a malignant tumor, more than 267,000 persons with a benign tumor. For every 100,000 people in the United States, approximately 131 are living following the diagnosis of a brain tumor. This represents a prevalence rate of 130.8 per 100,000 person years[1].

Tumor segmentation of whole-body magnetic resonance imaging in neurofibromatosis type 1 patients: tumor burden correlates

Energy Technology Data Exchange (ETDEWEB)

Heffler, Michael A.; Xi, Yin; Chhabra, Avneesh [University of Texas Southwestern Medical Center, Department of Radiology, Dallas, TX (United States); Le, Lu Q. [University of Texas Southwestern Medical Center, Department of Dermatology, Dallas, TX (United States)

2017-01-15

Segmentation of whole-body MRI (WBMRI) to assess the feasibility, quantitate the total tumor volume (tumor burden) in patients with neurofibromatosis type 1 (NF1) and examine associations with demographic, disease-related and anthropomorphic features. A consecutive series of patients with NF1 underwent WBMRI and were reviewed for tumors. Tumors were segmented using a semiautomated software-based tool. Tumors were classified as superficial or deep and discrete or plexiform. Segmentation times were recorded. Segmentation yielded the quantity and tumor burden of superficial, internal and plexiform tumors. Correlations between segmentation data and demographic, disease-related and anthropomorphic features were examined. Fifteen patients were evaluated (42.3 ± 13.6 years, 10 female, 5 male). Segmentation times were a median of 30 min and yielded 2,328 tumors (1,582 superficial, 746 internal and 23 plexiform). One tumor was malignant. Tumor counts ranged from 14 to 397. Tumor burden ranged from 6.95 cm3 to 571 cm3. Individual tumor volume ranged from 0.0120 cm3 to 298 cm3. Significant correlation was found between the total volume of superficial tumors and height (ρ = 0.5966, p < 0.02). Male patients had higher overall tumor burdens (p < 0.05) and higher superficial tumor burden (p < 0.03). Patients with negative family history had more tumors (p < 0.05). Segmentation of WBMRI in patients with NF1 is feasible and elucidates meaningful relationships among disease phenotype, anthropomorphic and demographic features. (orig.)

Tumor segmentation of whole-body magnetic resonance imaging in neurofibromatosis type 1 patients: tumor burden correlates

International Nuclear Information System (INIS)

Heffler, Michael A.; Xi, Yin; Chhabra, Avneesh; Le, Lu Q.

2017-01-01

Segmentation of whole-body MRI (WBMRI) to assess the feasibility, quantitate the total tumor volume (tumor burden) in patients with neurofibromatosis type 1 (NF1) and examine associations with demographic, disease-related and anthropomorphic features. A consecutive series of patients with NF1 underwent WBMRI and were reviewed for tumors. Tumors were segmented using a semiautomated software-based tool. Tumors were classified as superficial or deep and discrete or plexiform. Segmentation times were recorded. Segmentation yielded the quantity and tumor burden of superficial, internal and plexiform tumors. Correlations between segmentation data and demographic, disease-related and anthropomorphic features were examined. Fifteen patients were evaluated (42.3 ± 13.6 years, 10 female, 5 male). Segmentation times were a median of 30 min and yielded 2,328 tumors (1,582 superficial, 746 internal and 23 plexiform). One tumor was malignant. Tumor counts ranged from 14 to 397. Tumor burden ranged from 6.95 cm3 to 571 cm3. Individual tumor volume ranged from 0.0120 cm3 to 298 cm3. Significant correlation was found between the total volume of superficial tumors and height (ρ = 0.5966, p < 0.02). Male patients had higher overall tumor burdens (p < 0.05) and higher superficial tumor burden (p < 0.03). Patients with negative family history had more tumors (p < 0.05). Segmentation of WBMRI in patients with NF1 is feasible and elucidates meaningful relationships among disease phenotype, anthropomorphic and demographic features. (orig.)

Epidemiological features of brain tumors

Directory of Open Access Journals (Sweden)

Živković Nenad

2013-01-01

Full Text Available Brain tumors account for 1.4% of all cancers and 2.4% of all cancer-related deaths. The incidence of brain tumors varies and it is higher in developed countries of Western Europe, North America, Australia and New Zealand. In Serbia, according to data from 2009, malignant brain tumors account for 2. 2 of all tumors, and from all cancer­related deaths, 3.2% is caused by malignant brain tumors. According to recent statistical reports, an overall incidence of brain tumors for benign and malignant tumors combined is 18.71 per 100,000 persons/year. The most common benign brain tumor in adults is meningioma, which is most present in women, and the most common malignant tumor is glioblastoma, which is most present in adult men. Due to high mortality, especially in patients diagnosed with glioblastoma and significant brain tumor morbidity, there is a constant interest in understanding its etiology in order to possibly prevent tumor occurrence in future and enable more efficient treatment strategies for this fatal brain disease. Despite the continuously growing number of epidemiological studies on possible factors of tumor incidence, the etiology remains unclear. The only established environmental risk factor of gliomas is ionizing radiation exposure. Exposure to radiofrequency electromagnetic fields via cell phone use has gained a lot of attention as a potential risk factor of brain tumor development. However, studies have been inconsistent and inconclusive, so more definite results are still expected.

Brain tumor-targeted drug delivery strategies

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Xiaoli Wei

2014-06-01

Full Text Available Despite the application of aggressive surgery, radiotherapy and chemotherapy in clinics, brain tumors are still a difficult health challenge due to their fast development and poor prognosis. Brain tumor-targeted drug delivery systems, which increase drug accumulation in the tumor region and reduce toxicity in normal brain and peripheral tissue, are a promising new approach to brain tumor treatments. Since brain tumors exhibit many distinctive characteristics relative to tumors growing in peripheral tissues, potential targets based on continuously changing vascular characteristics and the microenvironment can be utilized to facilitate effective brain tumor-targeted drug delivery. In this review, we briefly describe the physiological characteristics of brain tumors, including blood–brain/brain tumor barriers, the tumor microenvironment, and tumor stem cells. We also review targeted delivery strategies and introduce a systematic targeted drug delivery strategy to overcome the challenges.

Neural - levelset shape detection segmentation of brain tumors in dynamic susceptibility contrast enhanced and diffusion weighted magnetic resonance images

International Nuclear Information System (INIS)

Vijayakumar, C.; Bhargava, Sunil; Gharpure, Damayanti Chandrashekhar

2008-01-01

A novel Neuro - level set shape detection algorithm is proposed and evaluated for segmentation and grading of brain tumours. The algorithm evaluates vascular and cellular information provided by dynamic contrast susceptibility magnetic resonance images and apparent diffusion coefficient maps. The proposed neural shape detection algorithm is based on the levels at algorithm (shape detection algorithm) and utilizes a neural block to provide the speed image for the level set methods. In this study, two different architectures of level set method have been implemented and their results are compared. The results show that the proposed Neuro-shape detection performs better in differentiating the tumor, edema, necrosis in reconstructed images of perfusion and diffusion weighted magnetic resonance images. (author)

Preoperative coiling of coexisting intracranial aneurysm and subsequent brain tumor surgery

Energy Technology Data Exchange (ETDEWEB)

Park, Keun Young; Kim, Byung Moon; Kim, Dong Joon [Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of)

2016-11-15

Few studies have investigated treatment strategies for brain tumor with a coexisting unruptured intracranial aneurysm (cUIA). The purpose of this study was to evaluate the safety and efficacy of preoperative coiling for cUIA, and subsequent brain tumor surgery. A total of 19 patients (mean age, 55.2 years; M:F = 4:15) underwent preoperative coiling for 23 cUIAs and subsequent brain tumor surgery. Primary brain tumors were meningiomas (n = 7, 36.8%), pituitary adenomas (n = 7, 36.8%), gliomas (n = 3, 15.8%), vestibular schwannoma (n = 1, 5.3%), and Rathke's cleft cyst (n = 1, 5.3%). cUIAs were located at the distal internal carotid artery (n = 9, 39.1%), anterior cerebral artery (n = 8, 34.8%), middle cerebral artery (n = 4, 17.4%), basilar artery top (n = 1, 4.3%), and posterior cerebral artery, P1 segment (n = 1, 4.3%). The outcomes of preoperative coiling of cUIA and subsequent brain tumor surgery were retrospectively evaluated. Single-microcatheter technique was used in 13 cases (56.5%), balloon-assisted in 4 cases (17.4%), double-microcatheter in 4 cases (17.4%), and stent-assisted in 2 cases (8.7%). Complete cUIA occlusion was achieved in 18 cases (78.3%), while residual neck occurred in 5 cases (21.7%). The only coiling-related complication was 1 transient ischemic attack (5.3%). Neurological deterioration did not occur in any patient during the period between coiling and tumor surgery. At the latest clinical follow-up (mean, 29 months; range, 2-120 months), 15 patients (78.9%) had favorable outcomes (modified Rankin Scale, 0-2), while 4 patients (21.1%) had unfavorable outcomes due to consequences of brain tumor surgery. Preoperative coiling and subsequent tumor surgery was safe and effective, making it a reasonable treatment option for patients with brain tumor and cUIA.

Preoperative coiling of coexisting intracranial aneurysm and subsequent brain tumor surgery

International Nuclear Information System (INIS)

Park, Keun Young; Kim, Byung Moon; Kim, Dong Joon

2016-01-01

Few studies have investigated treatment strategies for brain tumor with a coexisting unruptured intracranial aneurysm (cUIA). The purpose of this study was to evaluate the safety and efficacy of preoperative coiling for cUIA, and subsequent brain tumor surgery. A total of 19 patients (mean age, 55.2 years; M:F = 4:15) underwent preoperative coiling for 23 cUIAs and subsequent brain tumor surgery. Primary brain tumors were meningiomas (n = 7, 36.8%), pituitary adenomas (n = 7, 36.8%), gliomas (n = 3, 15.8%), vestibular schwannoma (n = 1, 5.3%), and Rathke's cleft cyst (n = 1, 5.3%). cUIAs were located at the distal internal carotid artery (n = 9, 39.1%), anterior cerebral artery (n = 8, 34.8%), middle cerebral artery (n = 4, 17.4%), basilar artery top (n = 1, 4.3%), and posterior cerebral artery, P1 segment (n = 1, 4.3%). The outcomes of preoperative coiling of cUIA and subsequent brain tumor surgery were retrospectively evaluated. Single-microcatheter technique was used in 13 cases (56.5%), balloon-assisted in 4 cases (17.4%), double-microcatheter in 4 cases (17.4%), and stent-assisted in 2 cases (8.7%). Complete cUIA occlusion was achieved in 18 cases (78.3%), while residual neck occurred in 5 cases (21.7%). The only coiling-related complication was 1 transient ischemic attack (5.3%). Neurological deterioration did not occur in any patient during the period between coiling and tumor surgery. At the latest clinical follow-up (mean, 29 months; range, 2-120 months), 15 patients (78.9%) had favorable outcomes (modified Rankin Scale, 0-2), while 4 patients (21.1%) had unfavorable outcomes due to consequences of brain tumor surgery. Preoperative coiling and subsequent tumor surgery was safe and effective, making it a reasonable treatment option for patients with brain tumor and cUIA

Application of Image Processing Algorithms for Brain Tumor Analysis in 2D and 3D Leading to Tumor’s Positioning in Skull: Overview

Directory of Open Access Journals (Sweden)

AYESHA AMIR SIDDIQI

2017-01-01

Full Text Available Segmentation of brain tumors has been found challenging throughout in the field of image processing. Different algorithms have been applied to the segmentation of solid or cystic tumors individually but little work has been done for solid cum cystic tumor. The papers reviewed in this article only deal with the case study of patients suffering from solid cum cystic brain tumor as this type of tumor is rarely found for the purpose of research. The research work conducted so far on this topic has been reviewed. The study begins with 2D (Two Dimensional segmentation of tumor using MATLAB. It is then extended to study of slices of tumor and its volume calculation using open source software named 3D Slicer which represents the tumor in 3D. This software can intake the 2D slices and process them to give a combined 3D view. Various techniques are available in the software. According to the particular requirement an appropriate algorithm can be chosen. This paper gives a promising hierarchy for volume calculation of tumor and the three dimensional view. Further we can also find the position of tumor in the skull using the same software. This piece of work is a valuable guideline for the researchers interested in segmentation and three dimensional representations of different areas of human body. The models extracted out using the given algorithms can also be treated for matching and comparison of any future research. This will also aid surgeons and physicians in efficient analysis and reporting techniques.

Epidemiological features of brain tumors

OpenAIRE

Živković Nenad; Mihailović Goran; Marković Marko; Berisavac Iva; Spaić Milan

2013-01-01

Brain tumors account for 1.4% of all cancers and 2.4% of all cancer-related deaths. The incidence of brain tumors varies and it is higher in developed countries of Western Europe, North America, Australia and New Zealand. In Serbia, according to data from 2009, malignant brain tumors account for 2. 2 of all tumors, and from all cancer­related deaths, 3.2% is caused by malignant brain tumors. According to recent statistical reports, an overall incidence of b...

Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing

Directory of Open Access Journals (Sweden)

Liao Chun-Chih

2011-08-01

Full Text Available Abstract Background In recent years, magnetic resonance imaging (MRI has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images. This paper uses an algorithm integrating fuzzy-c-mean (FCM and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain. Methods The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT on a pixel level. Overall data were then evaluated using a quantified system. Results The quantified parameters, including the "percent match" (PM and "correlation ratio" (CR, suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain. Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related. Conclusions Results indicated

Mechanism of brain tumor headache.

Science.gov (United States)

Taylor, Lynne P

2014-04-01

Headaches occur commonly in all patients, including those who have brain tumors. Using the search terms "headache and brain tumors," "intracranial neoplasms and headache," "facial pain and brain tumors," "brain neoplasms/pathology," and "headache/etiology," we reviewed the literature from the past 78 years on the proposed mechanisms of brain tumor headache, beginning with the work of Penfield. Most of what we know about the mechanisms of brain tumor associated headache come from neurosurgical observations from intra-operative dural and blood vessel stimulation as well as intra-operative observations and anecdotal information about resolution of headache symptoms with various tumor-directed therapies. There is an increasing overlap between the primary and secondary headaches and they may actually share a similar biological mechanism. While there can be some criticism that the experimental work with dural and arterial stimulation produced head pain and not actual headache, when considered with the clinical observations about headache type, coupled with improvement after treatment of the primary tumor, we believe that traction on these structures, coupled with increased intracranial pressure, is clearly part of the genesis of brain tumor headache and may also involve peripheral sensitization with neurogenic inflammation as well as a component of central sensitization through trigeminovascular afferents on the meninges and cranial vessels. © 2014 American Headache Society.

Brain MR image segmentation using NAMS in pseudo-color.

Science.gov (United States)

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

Segmentation of liver tumors on CT images

International Nuclear Information System (INIS)

Pescia, D.

2011-01-01

This thesis is dedicated to 3D segmentation of liver tumors in CT images. This is a task of great clinical interest since it allows physicians benefiting from reproducible and reliable methods for segmenting such lesions. Accurate segmentation would indeed help them during the evaluation of the lesions, the choice of treatment and treatment planning. Such a complex segmentation task should cope with three main scientific challenges: (i) the highly variable shape of the structures being sought, (ii) their similarity of appearance compared with their surrounding medium and finally (iii) the low signal to noise ratio being observed in these images. This problem is addressed in a clinical context through a two step approach, consisting of the segmentation of the entire liver envelope, before segmenting the tumors which are present within the envelope. We begin by proposing an atlas-based approach for computing pathological liver envelopes. Initially images are pre-processed to compute the envelopes that wrap around binary masks in an attempt to obtain liver envelopes from estimated segmentation of healthy liver parenchyma. A new statistical atlas is then introduced and used to segmentation through its diffeomorphic registration to the new image. This segmentation is achieved through the combination of image matching costs as well as spatial and appearance prior using a multi-scale approach with MRF. The second step of our approach is dedicated to lesions segmentation contained within the envelopes using a combination of machine learning techniques and graph based methods. First, an appropriate feature space is considered that involves texture descriptors being determined through filtering using various scales and orientations. Then, state of the art machine learning techniques are used to determine the most relevant features, as well as the hyper plane that separates the feature space of tumoral voxels to the ones corresponding to healthy tissues. Segmentation is then

Children's Brain Tumor Foundation

Science.gov (United States)

... 2 Family Donate Volunteer Justin's Hope Fund Children’s Brain Tumor Foundation, A non-profit organization, was founded ... and the long term outlook for children with brain and spinal cord tumors through research, support, education, ...

Asymptomatic brain tumor detected at brain check-up

International Nuclear Information System (INIS)

Onizuka, Masanari; Suyama, Kazuhiko; Shibayama, Akira; Hiura, Tsuyoshi; Horie, Nobutaka; Miyazaki, Hisaya

2001-01-01

Brain check-up was performed in 4000 healthy subjects who underwent medical and radiological examinations for possible brain diseases in our hospital from April 1996 to March 2000. Magnetic resonance imaging revealed 11 brain tumors which consisted of six meningiomas, three pituitary adenomas, one astrocytoma, and one epidermoid cyst. The detection rate of incidental brain tumor in our hospital was 0.3%. Nine patients underwent surgery, with one case of morbidity due to postoperative transient oculomotor nerve paresis. The widespread use of brain check-up may increasingly detect asymptomatic brain tumors. Surgical indications for such lesions remain unclear, and the strategy for treatment should be determined with consideration of the patient's wishes. (author)

Negative brain scintigrams in brain tumors

International Nuclear Information System (INIS)

Dalke, K.G.

1978-01-01

With 53 histologically verified and 2 histologically not identified brain tumors, that showed a negative scintigram, it was tried to find reasons for the wrong and negative dropout of these scintigrams. The electroencephalograms and angiograms, that were made simultaneously were taken into consideration with respect to their propositional capability and were compared with the scintigram findings. For the formation of the negative brain scintigrams there could be found no unique cause or causal constellation. The scintigraphic tumor representation is likely based on a complex process. Therefore the reasons for the negativity of the brain scintigrams can be a manifold of causes. An important role plays the vascularisation of the tumor, but not in a sole way. As well the tumor localisation gains some importance; especially in the temporal lobe or in the deeper structures situated tumors can be negative in the scintigram. To hold down the rate of wrong-negative quote in the case of intracranial tumor search, one is advised to continue with an further exposure after 2 to 4 hours besides the usual exposures, unless a sequential scintigraphy was made from the beginning. (orig./MG) [de

Multimodal navigated skull base tumor resection using image-based vascular and cranial nerve segmentation: A prospective pilot study.

Science.gov (United States)

Dolati, Parviz; Gokoglu, Abdulkerim; Eichberg, Daniel; Zamani, Amir; Golby, Alexandra; Al-Mefty, Ossama

2015-01-01

Skull base tumors frequently encase or invade adjacent normal neurovascular structures. For this reason, optimal tumor resection with incomplete knowledge of patient anatomy remains a challenge. To determine the accuracy and utility of image-based preoperative segmentation in skull base tumor resections, we performed a prospective study. Ten patients with skull base tumors underwent preoperative 3T magnetic resonance imaging, which included thin section three-dimensional (3D) space T2, 3D time of flight, and magnetization-prepared rapid acquisition gradient echo sequences. Imaging sequences were loaded in the neuronavigation system for segmentation and preoperative planning. Five different neurovascular landmarks were identified in each case and measured for accuracy using the neuronavigation system. Each segmented neurovascular element was validated by manual placement of the navigation probe, and errors of localization were measured. Strong correspondence between image-based segmentation and microscopic view was found at the surface of the tumor and tumor-normal brain interfaces in all cases. The accuracy of the measurements was 0.45 ± 0.21 mm (mean ± standard deviation). This information reassured the surgeon and prevented vascular injury intraoperatively. Preoperative segmentation of the related cranial nerves was possible in 80% of cases and helped the surgeon localize involved cranial nerves in all cases. Image-based preoperative vascular and neural element segmentation with 3D reconstruction is highly informative preoperatively and could increase the vigilance of neurosurgeons for preventing neurovascular injury during skull base surgeries. Additionally, the accuracy found in this study is superior to previously reported measurements. This novel preliminary study is encouraging for future validation with larger numbers of patients.

Response of avian embryonic brain to spatially segmented x-ray microbeams.

Science.gov (United States)

Dilmanian, F A; Morris, G M; Le Duc, G; Huang, X; Ren, B; Bacarian, T; Allen, J C; Kalef-Ezra, J; Orion, I; Rosen, E M; Sandhu, T; Sathé, P; Wu, X Y; Zhong, Z; Shivaprasad, H L

2001-05-01

Duck embryo was studied as a model for assessing the effects of microbeam radiation therapy (MRT) on the human infant brain. Because of the high risk of radiation-induced disruption of the developmental process in the immature brain, conventional wide-beam radiotherapy of brain tumors is seldom carried out in infants under the age of three. Other types of treatment for pediatric brain tumors are frequently ineffective. Recent findings from studies in Grenoble on the brain of suckling rats indicate that MRT could be of benefit for the treatment of early childhood tumors. In our studies, duck embryos were irradiated at 3-4 days prior to hatching. Irradiation was carried out using a single exposure of synchrotron-generated X-rays, either in the form of parallel microplanar beams (microbeams), or as non-segmented broad beam. The individual microplanar beams had a width of 27 microm and height of 11 mm, and a center-to-center spacing of 100 microm. Doses to the exposed areas of embryo brain were 40, 80, 160 and 450 Gy (in-slice dose) for the microbeam, and 6, 12 and 18 Gy for the broad beam. The biological end point employed in the study was ataxia. This neurological symptom of radiation damage to the brain developed within 75 days of hatching. Histopathological analysis of brain tissue did not reveal any radiation induced lesions for microbeam doses of 40-160 Gy (in-slice), although some incidences of ataxia were observed in that dose group. However, severe brain lesions did occur in animals in the 450 Gy microbeam dose groups, and mild lesions in the 18 Gy broad beam dose group. These results indicate that embryonic duck brain has an appreciably higher tolerance to the microbeam modality, as compared to the broad beam modality. When the microbeam dose was normalized to the full volume of the irradiated tissue. i.e., the dose averaged over microbeams and the space between the microbeams, brain tolerance was estimated to be about three times higher to microbeam

Application of PET in brain tumor

International Nuclear Information System (INIS)

Chung, June Key

2002-01-01

The annual incidence of primary brain tumors is 7-19 cases per 100,000 people. The unique capacity of visualizing biochemical processes allows PET to determine functional metabolic activities of the brain tumors. Like other malignant tumors, F-18 FDG has been used commonly in the imaging of brain tumors. FDG PET is valuable in grading malignancy, predicting prognosis, monitoring treatment, differentiating tumor recurrence from radiation nucrosis, and detecting primary lesion in metastatric brain tumors. Among amino acids labeled with positron emitters, C-11 methionine is used clinically.Tumor delineation is much better with methionine PET than with FDG PET. Low grade gliomas, in particular, are better evaluated with methionine than with FDG. PET opens another dimension in brain tumor imaging. PET imaging has clearly entered the clinical area with a profound impact on patient care in many indications

Electroporation-based treatment planning for deep-seated tumors based on automatic liver segmentation of MRI images.

Science.gov (United States)

Pavliha, Denis; Mušič, Maja M; Serša, Gregor; Miklavčič, Damijan

2013-01-01

Electroporation is the phenomenon that occurs when a cell is exposed to a high electric field, which causes transient cell membrane permeabilization. A paramount electroporation-based application is electrochemotherapy, which is performed by delivering high-voltage electric pulses that enable the chemotherapeutic drug to more effectively destroy the tumor cells. Electrochemotherapy can be used for treating deep-seated metastases (e.g. in the liver, bone, brain, soft tissue) using variable-geometry long-needle electrodes. To treat deep-seated tumors, patient-specific treatment planning of the electroporation-based treatment is required. Treatment planning is based on generating a 3D model of the organ and target tissue subject to electroporation (i.e. tumor nodules). The generation of the 3D model is done by segmentation algorithms. We implemented and evaluated three automatic liver segmentation algorithms: region growing, adaptive threshold, and active contours (snakes). The algorithms were optimized using a seven-case dataset manually segmented by the radiologist as a training set, and finally validated using an additional four-case dataset that was previously not included in the optimization dataset. The presented results demonstrate that patient's medical images that were not included in the training set can be successfully segmented using our three algorithms. Besides electroporation-based treatments, these algorithms can be used in applications where automatic liver segmentation is required.

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

Science.gov (United States)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

[Isolation and identification of brain tumor stem cells from human brain neuroepithelial tumors].

Science.gov (United States)

Fang, Jia-sheng; Deng, Yong-wen; Li, Ming-chu; Chen, Feng-Hua; Wang, Yan-jin; Lu, Ming; Fang, Fang; Wu, Jun; Yang, Zhuan-yi; Zhou, Xang-yang; Wang, Fei; Chen, Cheng

2007-01-30

To establish a simplified culture system for the isolation of brain tumor stem cells (BTSCs) from the tumors of human neuroepithelial tissue, to observe the growth and differentiation pattern of BTSCs, and to investigate their expression of the specific markers. Twenty-six patients with brain neuroepithelial tumors underwent tumor resection. Two pieces of tumor tissues were taken from each tumor to be dissociated, triturated into single cells in sterile DMEM-F12 medium, and then filtered. The tumor cells were seeded at a concentration of 200,000 viable cells per mL into serum-free DMEM-F12 medium simply supplemented with B27, human basic fibroblast growth factor (20 microg/L), human epidermal growth factor (20 microg /L), insulin (4 U/L), L-glutamine, penicillin and streptomycin. After the primary brain tumor spheres (BTSs) were generated, they were triturated again and passed in fresh medium. Limiting dilution assay was performed to observe the monoclone formation. 5-bromodeoxyuridine (BrdU) incorporation test was performed to observe the proliferation of the BTS. The BTSCs were cultured in mitogen-free DMEM-F12 medium supplemented with 10% fetal bovine serum to observe their differentiation. Immunocytochemistry was used to examine the expression of CD133 and nestin, specific markers of BTSC, and the rate of CD133 positive cells. Only a minority of subsets of cells from the tumors of neuroepithelial tissue had the capacity to survive, proliferate, and generate free-floating neurosphere-like BTSs in the simplified serum-free medium. These cells attached to the poly-L-lysine coated coverslips in the serum-supplemented medium and differentiated. The BTSCs were CD133 and nestin positive. The rate of CD133 positive cells in the tumor specimens was (21 +/- 6.2)% - (38 +/- 7.0)%. A new simplified culture system for the isolation of BTSCs is established. The tumors of human neuroepithelial tissue contain CD133 and nestin positive tumor stem cells which can be isolated

Notch Signaling and Brain Tumors

DEFF Research Database (Denmark)

Stockhausen, Marie; Kristoffersen, Karina; Poulsen, Hans Skovgaard

2011-01-01

Human brain tumors are a heterogenous group of neoplasms occurring inside the cranium and the central spinal cord. In adults and children, astrocytic glioma and medulloblastoma are the most common subtypes of primary brain tumors. These tumor types are thought to arise from cells in which Notch...

Segmentation and Visualisation of Human Brain Structures

Energy Technology Data Exchange (ETDEWEB)

Hult, Roger

2003-10-01

In this thesis the focus is mainly on the development of segmentation techniques for human brain structures and of the visualisation of such structures. The images of the brain are both anatomical images (magnet resonance imaging (MRI) and autoradiography) and functional images that show blood flow (functional magnetic imaging (fMRI), positron emission tomography (PET), and single photon emission tomography (SPECT)). When working with anatomical images, the structures segmented are visible as different parts of the brain, e.g. the brain cortex, the hippocampus, or the amygdala. In functional images, the activity or the blood flow that be seen. Grey-level morphology methods are used in the segmentations to make tissue types in the images more homogenous and minimise difficulties with connections to outside tissue. A method for automatic histogram thresholding is also used. Furthermore, there are binary operations such as logic operation between masks and binary morphology operations. The visualisation of the segmented structures uses either surface rendering or volume rendering. For the visualisation of thin structures, surface rendering is the better choice since otherwise some voxels might be missed. It is possible to display activation from a functional image on the surface of a segmented cortex. A new method for autoradiographic images has been developed, which integrates registration, background compensation, and automatic thresholding to get faster and more reliable results than the standard techniques give.

Segmentation and Visualisation of Human Brain Structures

International Nuclear Information System (INIS)

Hult, Roger

2003-01-01

In this thesis the focus is mainly on the development of segmentation techniques for human brain structures and of the visualisation of such structures. The images of the brain are both anatomical images (magnet resonance imaging (MRI) and autoradiography) and functional images that show blood flow (functional magnetic imaging (fMRI), positron emission tomography (PET), and single photon emission tomography (SPECT)). When working with anatomical images, the structures segmented are visible as different parts of the brain, e.g. the brain cortex, the hippocampus, or the amygdala. In functional images, the activity or the blood flow that be seen. Grey-level morphology methods are used in the segmentations to make tissue types in the images more homogenous and minimise difficulties with connections to outside tissue. A method for automatic histogram thresholding is also used. Furthermore, there are binary operations such as logic operation between masks and binary morphology operations. The visualisation of the segmented structures uses either surface rendering or volume rendering. For the visualisation of thin structures, surface rendering is the better choice since otherwise some voxels might be missed. It is possible to display activation from a functional image on the surface of a segmented cortex. A new method for autoradiographic images has been developed, which integrates registration, background compensation, and automatic thresholding to get faster and more reliable results than the standard techniques give

Brain tumors and syndromes in children

NARCIS (Netherlands)

Bleeker, Fonnet E.; Hopman, Saskia M. J.; Merks, Johannes H. M.; Aalfs, Cora M.; Hennekam, Raoul C. M.

2014-01-01

(Brain) tumors are usually a disorder of aged individuals. If a brain tumor occurs in a child, there is a possible genetic susceptibility for this. Such genetic susceptibilities often show other signs and symptoms. Therefore, every child with a brain tumor should be carefully evaluated for the

State-of-the-Art Methods for Brain Tissue Segmentation: A Review.

Science.gov (United States)

Dora, Lingraj; Agrawal, Sanjay; Panda, Rutuparna; Abraham, Ajith

2017-01-01

Brain tissue segmentation is one of the most sought after research areas in medical image processing. It provides detailed quantitative brain analysis for accurate disease diagnosis, detection, and classification of abnormalities. It plays an essential role in discriminating healthy tissues from lesion tissues. Therefore, accurate disease diagnosis and treatment planning depend merely on the performance of the segmentation method used. In this review, we have studied the recent advances in brain tissue segmentation methods and their state-of-the-art in neuroscience research. The review also highlights the major challenges faced during tissue segmentation of the brain. An effective comparison is made among state-of-the-art brain tissue segmentation methods. Moreover, a study of some of the validation measures to evaluate different segmentation methods is also discussed. The brain tissue segmentation, content in terms of methodologies, and experiments presented in this review are encouraging enough to attract researchers working in this field.

Robust generative asymmetric GMM for brain MR image segmentation.

Science.gov (United States)

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM

Heuristically improved Bayesian segmentation of brain MR images ...

African Journals Online (AJOL)

Heuristically improved Bayesian segmentation of brain MR images. ... or even the most prevalent task in medical image processing is image segmentation. Among them, brain MR images suffer ... show that our algorithm performs well in comparison with the one implemented in SPM. It can be concluded that incorporating ...

Intracerebral hemorrhage in brain tumors

International Nuclear Information System (INIS)

Fujita, Katsuzo; Matsumoto, Satoshi

1980-01-01

A series of 16 cases of intracerebral hemorrhage associated with brain tumors are described. The literature is reviewed and the incidence of these cases is reported to be low, but we had clinically encountered these cases more commonly than reported, since CT was introduced to the neurosurgical field as a diagnostic aid. The presenting symptoms were those of spontaneous intracerebral hemorrhage or brain tumor. The intracerebral hemorrhage associated with brain tumor may mask the cause of bleeding and confuse the diagnosis. The majority of the tumor causing the intracerebral hemorrhage are highly malignant as glioblastoma or metastatic brain tumor, but there are some benign tumors such as pituitary adenoma, hemangioblastoma, benign astrocytoma and meningioma, which would have good survival rates if discovered early. The mechanisms of massive hemorrhage with brain tumor are not clear. From pathological findings of our cases and other reports, the mechanism seems to be due to the vascular endothelial proliferation with subsequent obliteration of the lumen of the vessel. Thin walled, poorly formed vessels in tumor may also become distorted with growth of the tumor and these may easily rupture and bleed. Necrosis with subsequent loss of vessel support may be a factor in production of hemorrhage. Radiation therapy may be a predisposing factor. Children are rarely involved in these cases. The prognosis in the majority of cases would seen to be poor, since the majority of the tumor are highly malignant and most such patients are seen by the neurosurgeon some time after the hemorrhage has accomplished its fatal mischief. (author)

Intracerebral hemorrhage in brain tumors

Energy Technology Data Exchange (ETDEWEB)

Fujita, K; Matsumoto, S [Kobe Univ. (Japan). School of Medicine

1980-10-01

A series of 16 cases of intracerebral hemorrhage associated with brain tumors are described. The literature is reviewed and the incidence of these cases is reported to be low, but we had clinically encountered these cases more commonly than reported, since CT was introduced to the neurosurgical field as a diagnostic aid. The presenting symptoms were those of spontaneous intracerebral hemorrhage or brain tumor. The intracerebral hemorrhage associated with brain tumor may mask the cause of bleeding and confuse the diagnosis. The majority of the tumor causing the intracerebral hemorrhage are highly malignant as glioblastoma or metastatic brain tumor, but there are some benign tumors such as pituitary adenoma, hemangioblastoma, benign astrocytoma and meningioma, which would have good survival rates if discovered early. The mechanisms of massive hemorrhage with brain tumor are not clear. From pathological findings of our cases and other reports, the mechanism seems to be due to the vascular endothelial proliferation with subsequent obliteration of the lumen of the vessel. Thin walled, poorly formed vessels in tumor may also become distorted with growth of the tumor and these may easily rupture and bleed. Necrosis with subsequent loss of vessel support may be a factor in production of hemorrhage. Radiation therapy may be a predisposing factor. Children are rarely involved in these cases. The prognosis in the majority of cases would seen to be poor, since the majority of the tumor are highly malignant and most such patients are seen by the neurosurgeon some time after the hemorrhage has accomplished its fatal mischief.

Epilepsy and brain tumors

Science.gov (United States)

ENGLOT, DARIO J.; CHANG, EDWARD F.; VECHT, CHARLES J.

2016-01-01

Seizures are common in patients with brain tumors, and epilepsy can significantly impact patient quality of life. Therefore, a thorough understanding of rates and predictors of seizures, and the likelihood of seizure freedom after resection, is critical in the treatment of brain tumors. Among all tumor types, seizures are most common with glioneuronal tumors (70–80%), particularly in patients with frontotemporal or insular lesions. Seizures are also common in individuals with glioma, with the highest rates of epilepsy (60–75%) observed in patients with low-grade gliomas located in superficial cortical or insular regions. Approximately 20–50% of patients with meningioma and 20–35% of those with brain metastases also suffer from seizures. After tumor resection, approximately 60–90% are rendered seizure-free, with most favorable seizure outcomes seen in individuals with glioneuronal tumors. Gross total resection, earlier surgical therapy, and a lack of generalized seizures are common predictors of a favorable seizure outcome. With regard to anticonvulsant medication selection, evidence-based guidelines for the treatment of focal epilepsy should be followed, and individual patient factors should also be considered, including patient age, sex, organ dysfunction, comorbidity, or cotherapy. As concomitant chemotherapy commonly forms an essential part of glioma treatment, enzyme-inducing anticonvulsants should be avoided when possible. Seizure freedom is the ultimate goal in the treatment of brain tumor patients with epilepsy, given the adverse effects of seizures on quality of life. PMID:26948360

Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.

Science.gov (United States)

Dolz, Jose; Laprie, Anne; Ken, Soléakhéna; Leroy, Henri-Arthur; Reyns, Nicolas; Massoptier, Laurent; Vermandel, Maximilien

2016-01-01

To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk is required. This task is still manually performed, which is time-consuming and prone to observer variability. To address these issues, and as alternative to atlas-based segmentation methods, machine learning techniques, such as support vector machines (SVM), have been recently presented to segment subcortical structures on magnetic resonance images (MRI). SVM is proposed to segment the brainstem on MRI in multicenter brain cancer context. A dataset composed by 14 adult brain MRI scans is used to evaluate its performance. In addition to spatial and probabilistic information, five different image intensity values (IIVs) configurations are evaluated as features to train the SVM classifier. Segmentation accuracy is evaluated by computing the Dice similarity coefficient (DSC), absolute volumes difference (AVD) and percentage volume difference between automatic and manual contours. Mean DSC for all proposed IIVs configurations ranged from 0.89 to 0.90. Mean AVD values were below 1.5 cm(3), where the value for best performing IIVs configuration was 0.85 cm(3), representing an absolute mean difference of 3.99% with respect to the manual segmented volumes. Results suggest consistent volume estimation and high spatial similarity with respect to expert delineations. The proposed approach outperformed presented methods to segment the brainstem, not only in volume similarity metrics, but also in segmentation time. Preliminary results showed that the approach might be promising for adoption in clinical use.

Radiation therapy of brain tumor

International Nuclear Information System (INIS)

Sung, K. J.; Lee, D. H.; Park, C. Y.

1980-01-01

One hundred and six cases of brain tumors were treated at the Yonsei Cancer Center from January 1972 to August 1978 by Co-60 teletherapy unit. We analyses their clinical findings, histopathological findings, treatment and results. In those cases which computerized tomography had been used before and after radiation therapy, changes in tumor size and the presence of edema or necrosis following treatment was evaluated. 1. Among 106 cases, 90 cases were primary brain tumors and 16 cases were metastatic brain tumors. Pituitary tumors (38), glioma (34) and pinealoma (10) composed of most of primary brain tumors. 2. Post treatment follow-up was possible in 38 cases more than 1 years. Four among 11 cases of giloma expired and survivors had considerable neurological symptoms except 2 cases. Sixty five percent (12/20) of pituitary tumors showed improvement of visual symptoms and all cases (7) of pinealoma which post treatment follow-up was possible, showed remarkable good response. 3. Findings of CT scan after radiation treatment were compatible with results of clinical findings and post treatment follow-up. It showed complete regression of tumor mass in one case of pinealoma and medulloblastoma. One case of pituitary tumor showed almost complete regression of tumor mass. It also showed large residual lesion in cases of glioblastoma multiforme and cystic astrocytoma.

Mandatory chromosomal segment balance in aneuploid tumor cells

International Nuclear Information System (INIS)

Kost-Alimova, Maria; Stanbridge, Eric; Klein, George; Imreh, Stefan; Darai-Ramqvist, Eva; Yau, Wing Lung; Sandlund, Agneta; Fedorova, Ludmila; Yang, Ying; Kholodnyuk, Irina; Cheng, Yue; Li Lung, Maria

2007-01-01

Euploid chromosome balance is vitally important for normal development, but is profoundly changed in many tumors. Is each tumor dependent on its own structurally and numerically changed chromosome complement that has evolved during its development and progression? We have previously shown that normal chromosome 3 transfer into the KH39 renal cell carcinoma line and into the Hone1 nasopharyngeal carcinoma line inhibited their tumorigenicity. The aim of the present study was to distinguish between a qualitative and a quantitative model of this suppression. According to the former, a damaged or deleted tumor suppressor gene would be restored by the transfer of a normal chromosome. If so, suppression would be released only when the corresponding sequences of the exogenous normal chromosome are lost or inactivated. According to the alternative quantitative model, the tumor cell would not tolerate an increased dosage of the relevant gene or segment. If so, either a normal cell derived, or, a tumor derived endogenous segment could be lost. Fluorescence in Situ Hybridization based methods, as well as analysis of polymorphic microsatellite markers were used to follow chromosome 3 constitution changes in monochromosomal hybrids. In both tumor lines with introduced supernumerary chromosomes 3, the copy number of 3p21 or the entire 3p tended to fall back to the original level during both in vitro and in vivo growth. An exogenous, normal cell derived, or an endogenous, tumor derived, chromosome segment was lost with similar probability. Identification of the lost versus retained segments showed that the intolerance for increased copy number was particularly strong for 3p14-p21, and weaker for other 3p regions. Gains in copy number were, on the other hand, well tolerated in the long arm and particularly the 3q26-q27 region. The inability of the cell to tolerate an experimentally imposed gain in 3p14-p21 in contrast to the well tolerated gain in 3q26-q27 is consistent with the

Tumor sterilization dose and radiation induced change of the brain tissue in radiotherapy of brain tumors

International Nuclear Information System (INIS)

Yoshii, Yoshihiko; Maki, Yutaka; Takano, Shingo

1987-01-01

Ninety-seven patients with brain tumors (38 gliomas, 26 brain metastases, 18 sellar tumors, 15 others) were treated by cobalt gamma ray or proton radiotherapy. In this study, normal brain injury due to radiation was analysed in terms of time-dose-fractionation (TDF), nominal standard dose (NSD) by the Ellis formula and NeuNSD by a modification in which the N exponent was -0.44 and the T exponent was -0.06. Their calculated doses were analysed in relationship to the normal brain radiation induced change (RIC) and the tumor sterilization dose. All brain tumors with an exception of many patients with brain metastases were received a surgical extirpation subtotally or partially prior to radiotherapy. And all patients with glioma and brain metastasis received also immuno-chemotherapy in the usual manner during radiotherapy. The calculated dose expressed by NeuNSD and TDF showed a significant relationship between a therapeutic dose and a postradiation time in terms of the appearance of RIC. It was suggested that RIC was caused by a dose over 800 in NeuNSD and a dose over 70 in TDF. Furthermore, it was suggested that an aged patient and a patient who had the vulnerable brain tissue to radiation exposure in the irradiated field had the high risk of RIC. On the other hand, our results suggested that the tumor sterilization dose should be over 1,536 NeuNSD and the irradiated method should be further considered in addition to the radiobiological concepts for various brain tumors. (author)

Brain Tumor Epidemiology Consortium (BTEC)

Science.gov (United States)

The Brain Tumor Epidemiology Consortium is an open scientific forum organized to foster the development of multi-center, international and inter-disciplinary collaborations that will lead to a better understanding of the etiology, outcomes, and prevention of brain tumors.

Biomarkers of Pediatric Brain Tumors

Directory of Open Access Journals (Sweden)

Mark D Russell

2013-03-01

Full Text Available Background and Need for Novel Biomarkers: Brain tumors are the leading cause of death by solid tumors in children. Although improvements have been made in their radiological detection and treatment, our capacity to promptly diagnose pediatric brain tumors in their early stages remains limited. This contrasts several other cancers where serum biomarkers such as CA 19-9 and CA 125 facilitate early diagnosis and treatment. Aim: The aim of this article is to review the latest literature and highlight biomarkers which may be of clinical use in the common types of primary pediatric brain tumor. Methods: A PubMed search was performed to identify studies reporting biomarkers in the bodily fluids of pediatric patients with brain tumors. Details regarding the sample type (serum, cerebrospinal fluid or urine, biomarkers analyzed, methodology, tumor type and statistical significance were recorded. Results: A total of 12 manuscripts reporting 19 biomarkers in 367 patients vs. 397 controls were identified in the literature. Of the 19 biomarkers identified, 12 were isolated from cerebrospinal fluid, 2 from serum, 3 from urine, and 2 from multiple bodily fluids. All but one study reported statistically significant differences in biomarker expression between patient and control groups.Conclusions: This review identifies a panel of novel biomarkers for pediatric brain tumors. It provides a platform for the further studies necessary to validate these biomarkers and, in addition, highlights several techniques through which new biomarkers can be discovered.

Endothelial cell marker PAL-E reactivity in brain tumor, developing brain, and brain disease

NARCIS (Netherlands)

Leenstra, S.; Troost, D.; Das, P. K.; Claessen, N.; Becker, A. E.; Bosch, D. A.

1993-01-01

The endothelial cell marker PAL-E is not reactive to vessels in the normal brain. The present study concerns the PAL-E reactivity in brain tumors in contrast to normal brain and nonneoplastic brain disease. A total of 122 specimens were examined: brain tumors (n = 94), nonneoplastic brain disease (n

Multifunctional Nanoparticles for Brain Tumor Diagnosis and Therapy

Science.gov (United States)

Cheng, Yu; Morshed, Ramin; Auffinger, Brenda; Tobias, Alex L.; Lesniak, Maciej S.

2013-01-01

Brain tumors are a diverse group of neoplasms that often carry a poor prognosis for patients. Despite tremendous efforts to develop diagnostic tools and therapeutic avenues, the treatment of brain tumors remains a formidable challenge in the field of neuro-oncology. Physiological barriers including the blood-brain barrier result in insufficient accumulation of therapeutic agents at the site of a tumor, preventing adequate destruction of malignant cells. Furthermore, there is a need for improvements in brain tumor imaging to allow for better characterization and delineation of tumors, visualization of malignant tissue during surgery, and tracking of response to chemotherapy and radiotherapy. Multifunctional nanoparticles offer the potential to improve upon many of these issues and may lead to breakthroughs in brain tumor management. In this review, we discuss the diagnostic and therapeutic applications of nanoparticles for brain tumors with an emphasis on innovative approaches in tumor targeting, tumor imaging, and therapeutic agent delivery. Clinically feasible nanoparticle administration strategies for brain tumor patients are also examined. Furthermore, we address the barriers towards clinical implementation of multifunctional nanoparticles in the context of brain tumor management. PMID:24060923

Remodeling the blood–brain barrier microenvironment by natural products for brain tumor therapy

Institute of Scientific and Technical Information of China (English)

Xiao Zhao; Rujing Chen; Mei Liu; Jianfang Feng; Jun Chen; Kaili Hu

2017-01-01

Brain tumor incidence shows an upward trend in recent years; brain tumors account for 5% of adult tumors, while in children, this figure has increased to 70%. Moreover, 20%–30% of malignant tumors will eventually metastasize into the brain. Both benign and malignant tumors can cause an increase in intracranial pressure and brain tissue compression, leading to central nervous system(CNS) damage which endangers the patients’ lives. Despite the many approaches to treating brain tumors and the progress that has been made, only modest gains in survival time of brain tumor patients have been achieved. At present, chemotherapy is the treatment of choice for many cancers, but the special structure of the blood–brain barrier(BBB) limits most chemotherapeutic agents from passing through the BBB and penetrating into tumors in the brain. The BBB microenvironment contains numerous cell types, including endothelial cells, astrocytes, peripheral cells and microglia, and extracellular matrix(ECM). Many chemical components of natural products are reported to regulate the BBB microenvironment near brain tumors and assist in their treatment. This review focuses on the composition and function of the BBB microenvironment under both physiological and pathological conditions, and the current research progress in regulating the BBB microenvironment by natural products to promote the treatment of brain tumors.

Non-FDG PET imaging of brain tumors

Institute of Scientific and Technical Information of China (English)

HUANG Zemin; GUAN Yihui; ZUO Chuantao; ZHANG Zhengwei; XUE Fangping; LIN Xiangtong

2007-01-01

Due to relatively high uptake of glucose in the brain cortex, the use of FDG PET imaging is greatly limited in brain tumor imaging, especially for low-grade gliomas and some metastatic tumours. More and more tracers with higher specificity were developed lately for brain tumor imaging. There are 3 main types of non-FDG PET tracers:amino acid tracers, choline tracers and nucleic acid tracers. These tracers are now widely applied in many aspects of brain tumor imaging. This article summarized the general use of non-FDG PET in different aspects of brain tumor imaging.

Multidimensional Brain MRI segmentation using graph cuts

International Nuclear Information System (INIS)

Lecoeur, Jeremy

2010-01-01

This thesis deals with the segmentation of multimodal brain MRIs by graph cuts method. First, we propose a method that utilizes three MRI modalities by merging them. The border information given by the spectral gradient is then challenged by a region information, given by the seeds selected by the user, using a graph cut algorithm. Then, we propose three enhancements of this method. The first consists in finding an optimal spectral space because the spectral gradient is based on natural images and then inadequate for multimodal medical images. This results in a learning based segmentation method. We then explore the automation of the graph cut method. Here, the various pieces of information usually given by the user are inferred from a robust expectation-maximization algorithm. We show the performance of these two enhanced versions on multiple sclerosis lesions. Finally, we integrate atlases for the automatic segmentation of deep brain structures. These three new techniques show the adaptability of our method to various problems. Our different segmentation methods are better than most of nowadays techniques, speaking of computation time or segmentation accuracy. (authors)

Detection of tumor recurrence using technetium99m-tetrofosmin brain SPECT in patients with previously irradiated brain tumors

International Nuclear Information System (INIS)

Llamas A; Reyes A; Uribe, L F; Martinez T

2004-01-01

Objective: to assess the clinical utility of brain SPECT with Tc-99m Tetrofosmin to differentiate between tumor recurrence and radionecrosis in patients with primary brain tumors previously treated with external beam radiotherapy. Materials and methods: thirteen patients with clinical or radiological suspicion of tumor recurrence were studied with brain SPECT using 20-mCi of Tc-99m Tetrofosmin. Obtained images were interpreted by consensus between two experienced observers and subsequently classified as positive or negative for tumor viability. Results were compared to those of conventional diagnostic imaging techniques. Diagnostic test values and 95% confidence intervals were quantified. Results: SPECT results included 7 true-positives, 5 true-negatives and 1 false negative result. Conclusions: Tc-99m Tetrofosmin brain SPECT night be a useful alternative to diagnose recurrent brain tumors, especially with non-conclusive clinical and radiological findings

Associations Between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results

Directory of Open Access Journals (Sweden)

Hannah Lyden

2016-09-01

Full Text Available Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant. The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations between early family aggression exposure and brain volume depending on the segmentation method used.

Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results.

Science.gov (United States)

Lyden, Hannah; Gimbel, Sarah I; Del Piero, Larissa; Tsai, A Bryna; Sachs, Matthew E; Kaplan, Jonas T; Margolin, Gayla; Saxbe, Darby

2016-01-01

Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant). The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations were found between early family aggression exposure and brain volume depending on the segmentation method used.

Brain tumors in patients primarly treated psychiatrically

Directory of Open Access Journals (Sweden)

Ignjatović-Ristić Dragana

2011-01-01

Full Text Available Introduction. Psychiatric symptoms are not rare manifestations of brain tumors. Brain tumors presented by symptoms of raised intracranial pressure, focal neurological signs, or convulsions are usually first seen by the neurologist or less frequently by the neurosurgeon in routine diagnostic procedures. On the other hand, when psychiatric symptoms are the first manifestation in “neurologically silent” brain tumors, the patients are sent to the psychiatrist for the treatment of psychiatric symptoms and brain tumors are left misdiagnosed for a long period of time. Case Report. We presented three patients with the diagnosed brain tumor where psychiatrist had been the first specialist to be consulted. In all three cases neurological examination was generally unremarkable with no focal signs or features of raised intracranial pressure. CT scan demonstrated right insular tumor in a female patient with obsessive-compulsive disorder (OCD; right parietal temporal tumor in a patient with delusions and depression and left frontal tumor in a patient with history of alcohol dependency. Conclusion. Psychiatric symptoms/disorders in patients with brain tumors are not specific enough and can have the same clinical presentation as the genuine psychiatric disorder. Therefore, we emphasize the consideration of neuroimaging in patients with abrupt beginning of psychiatric symptoms, in those with a change in mental status, or when headaches suddenly appear or in cases of treatment resistant psychiatric disorders regardless the lack of neurological symptoms.

Pediatric brain tumors; Kindliche Hirntumoren

Energy Technology Data Exchange (ETDEWEB)

Reith, W.; Bodea, S. [Universitaetsklinikum des Saarlandes, Klinik fuer Diagnostische und Interventionelle Neuroradiologie, Homburg/Saar (Germany); Muehl-Benninghaus, R.

2017-09-15

Brain tumors differ between children and adults both in histology and localization. Malignant gliomas and meningiomas predominate in adults while medulloblastomas and low-grade astrocytomas are the most frequent brain tumors in children. More than one half (50-70%) of pediatric brain tumors have an infratentorial location but only approximately 30% in adults. Brain tumors can be recognized in sonography, cranial computed tomography (CCT) and magnetic resonance imaging (MRI) by their space-consuming character and by their divergent density and intensity in comparison to normal brain parenchyma. They can grow extrusively, even infiltrate the parenchyma or originate from it. Besides clinical symptoms and diagnostics this article describes the most common pediatric brain tumors, i.e. astrocytoma, medulloblastoma, brainstem glioma, craniopharyngioma, neurofibromatosis and ganglioglioma. The most important imaging criteria are outlined. (orig.) [German] Sowohl Histologie als auch Lokalisation von Hirntumoren unterscheiden sich bei Kindern und Erwachsenen. Waehrend maligne Gliome und Meningeome bei Erwachsenen vorherrschen, kommen bei Kindern ueberwiegend Medulloblastome und niedriggradige Astrozytome vor. Mehr als die Haelfte (50-70 %) aller kindlichen Hirntumoren sind infratentoriell lokalisiert, dagegen sind es bei Erwachsenen nur etwa 30 %. Im Ultraschall, in der kranialen CT (CCT) oder MRT koennen Hirntumoren durch ihren raumfordernden Charakter und ihrer zum normalen Parenchym abweichenden Dichte oder Signalintensitaet erkannt werden. Sie koennen verdraengend wachsen, z. T. auch das Parenchym infiltrieren oder von diesem ausgehen. Neben der klinischen Symptomatik und Diagnostik werden im vorliegenden Artikel die haeufigsten kindlichen Hirntumoren, das Astrozytom, Medulloblastom, Hirnstammgliom, Kraniopharyngeom, die Neurofibromatose und das Gangliogliom beschrieben. Die wichtigsten bildgebende Kriterien werden dargestellt. (orig.)

Three-Dimensional Segmentation of the Tumor in Computed Tomographic Images of Neuroblastoma

OpenAIRE

Deglint, Hanford J.; Rangayyan, Rangaraj M.; Ayres, Fábio J.; Boag, Graham S.; Zuffo, Marcelo K.

2006-01-01

Segmentation of the tumor in neuroblastoma is complicated by the fact that the mass is almost always heterogeneous in nature; furthermore, viable tumor, necrosis, and normal tissue are often intermixed. Tumor definition and diagnosis require the analysis of the spatial distribution and Hounsfield unit (HU) values of voxels in computed tomography (CT) images, coupled with a knowledge of normal anatomy. Segmentation and analysis of the tissue composition of the tumor can assist in quantitative ...

Preliminary study of MR elastography in brain tumors

International Nuclear Information System (INIS)

Xu Lei; Gao Peiyi; Lin Yan; Han Jiancheng; Xi Zhinong; Shen Hao

2008-01-01

Objective: To investigate the potential values of magnetic resonance elastography (MRE) for evaluating the brain tumor consistency in vivo. Methods: Fourteen patients with known solid brain tumor (5 male, 9 female; age range: 16-63 years) underwent brain MRE studies. Informed consent was obtained from all patients. A dedicated external force actuator for brain MRE study was developed. The actuator was fixed to the head coil. During scan, one side of the actuator was attached to the patients' head. Low frequency oscillation was produced by the actuator and caused shear waves propagating into brain tissue. The pulse sequence used in the study was phase-contrast gradient-echo sequence. Phase images of the brain were obtained and the shear waves within the brain were directly imaged. Phase images were processed with local frequency estimation (LFE) technique to obtain the elasticity image. Consistency of brain tumors was evaluated at surgery and was classified as soft, intermediate, or hard with comparison to the white matter of the brain. Correspondence of MRE evaluation with operative results was studied. Results: The elastic modulus of the tumor was lower than that of white matter in 1 patient, higher in 11 patients, and similar in 2 patients. At surgery, the tumor manifested a soft consistency in 1 patient, hard consistency in 11 patients, intermediate consistency in 2 patients. The elasticity of tumors in 14 patients evaluated by MRE was correlated with the tumor consistency on the operation. Conclusion: MRE can noninvasively display the elasticity of brain tumors in vivo, and evaluate the brain tumor consistency before operation. (authors)

Fetal brain volumetry through MRI volumetric reconstruction and segmentation

Science.gov (United States)

Estroff, Judy A.; Barnewolt, Carol E.; Connolly, Susan A.; Warfield, Simon K.

2013-01-01

Purpose Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested. Materials and methods The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation. Results Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses. Conclusion The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation. PMID:20625848

Brain tumor and CT, 1

International Nuclear Information System (INIS)

Suzuki, Nobuyuki; Katada, Kazuhiro; Shinomiya, Youichi; Sano, Hirotoshi; Kanno, Tetsuo

1981-01-01

It is very important for a neurosurgeon to know the consistency of a brain tumor preoperatively, since the information which is of much use in indicating the likely difficulty of the operation, which operative tools should be selected, the amount of bleeding to be expected from the tumor, and so on. The authors, therefore, tried to evaluate the consistency of brain tumors preoperatively 27 cases in which the margin of the tumor was made clear with a homogeneous stain were studied concerning the relationship between the tumor consistency and the CT findings. The results are as follows: 1) A higher CT number on a plain CT indicated a harder consistency of the tumor. 2) A lesser contrast index (CT number on enhancement CT/CT number on plain CT) showed a harder consistency of the tumor. (author)

Tumor Types: Understanding Brain Tumors

Science.gov (United States)

... May cause excessive secretion of hormones Common among men and women in their 50s-80s Accounts for about 13 percent of all brain tumors Symptoms Headache Depression Vision loss Nausea or vomiting Behavioral and cognitive ...

Unusual radiological characteristics of teratoid/rhabdoid brain tumor ...

African Journals Online (AJOL)

We report a case of atypical teratoid rhabdoid brain tumor for 4 months old male child, who presented with unusual radiological findings, that can be confused with other brain tumors ,so we high light these unusual imaging features to aid in making correct diagnosis. Keywords: atypical teratoid–rhabdoid tumor, brain tumor, ...

Local recurrence of metastatic brain tumor after surgery

International Nuclear Information System (INIS)

Shinoura, Nobusada; Yamada, Ryoji; Okamoto, Koichiro; Nakamura, Osamu; Shitara, Nobuyuki; Karasawa, Katsuyuki

2006-01-01

We analyzed factors associated with the local recurrence of brain metastases after surgery. Forty-seven patients with 67 metastatic brain tumors underwent surgery between 1994 and 2001. The survival time in the ''no recurrence'' group (34.7 months) was significantly longer than that in the recurrence group (21.9 months) (p=0.0008; log rank test). The factors affecting the local recurrence of brain metastases after surgery were as follows: cyst (p=0.0156), dural invasion (p=0.0029) of tumors, failure to totally remove tumors (p=0.0040), and lack of post-surgical irradiation (p<0.0001). Sex, age, tumor histology, tumor size, pre-surgical radiation, dose (≥45 vs <45, ≥50 vs <50 Gy) and the method (local vs whole brain) of post-surgical radiation did not affect the local recurrence rate of brain metastases after surgery. To avoid early recurrences of metastatic brain tumors, the factors associated with local recurrence should be considered in providing optimal treatment of tumors by surgery. (author)

Intensity-Modulated Radiation Therapy for Primary Brain Tumors

Institute of Scientific and Technical Information of China (English)

Zhong-min Wang

2004-01-01

Radiation therapy has been used to treat primary brain tumors as standard primary and/or adjunctive therapies for decades. It is difficult for conventional radiotherapy to deliver a lethal dose of radiation to the tumors while sparing surrounding normal brain due to complicated structures and multifunction in human brain. With the understanding of radiation physics and computer technology, a number of novel and more precise radiotherapies have been developed in recent years. Intensity modulated radiotherapy (IMRT) is one of these strategies. The use of IMRT in the treatment of primary brain tumors is being increasing nowadays. It shows great promise for some of primary brain tumors and also presents some problems, This review highlights current IMRT in the treatment of mainly primary brain tumors.

Reconstruction of segmental bone defect of long bones after tumor resection by devitalized tumor-bearing bone.

Science.gov (United States)

Qu, Huayi; Guo, Wei; Yang, Rongli; Li, Dasen; Tang, Shun; Yang, Yi; Dong, Sen; Zang, Jie

2015-09-24

The reconstruction of an intercalary bone defect after a tumor resection of a long bone remains a challenge to orthopedic surgeons. Though several methods have been adopted to enhance the union of long segmental allografts or retrieved segmental autografts to the host bones, still more progresses are required to achieve a better union rate. Several methods have been adopted to devitalize tumor bone for recycling usage, and the results varied. We describe our experiences of using devitalized tumor-bearing bones for the repairing of segmental defects after tumor resection. Twenty-seven eligible patients treated from February 2004 to May 2012 were included. The segmental tumor bone (mean length, 14 cm) was resected, and then devitalized in 20% sterile saline at 65 °C for 30 min after the tumor tissue was removed. The devitalized bone was implanted back into the defect by using nails or plates. Complete healing of 50 osteotomy ends was achieved at a median time of 11 months (interquartile range (IQR) 9-13 months). Major complications included bone nonunion in four bone junctions (7.4%), devitalized bone fracture in one patient (3.7%), deep infection in three patients (11.1%), and fixation failure in two patients (7.4%). The bone union rates at 1 and 2 years were 74.1 and 92.6%, respectively. The average functional score according to the Musculoskeletal Tumor Society (MSTS) 93 scoring system was 93 % (IQR 80-96.7%). Incubation in 20% sterile saline at 65 °C for 30 min is an effective method of devitalization of tumor-bearing bone. The retrieved bone graft may provide as a less expensive alternative for limb salvage. The structural bone and the preserved osteoinductivity of protein may improve bone union.

Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results

OpenAIRE

Lyden, Hannah; Gimbel, Sarah I.; Del Piero, Larissa; Tsai, A. Bryna; Sachs, Matthew E.; Kaplan, Jonas T.; Margolin, Gayla; Saxbe, Darby

2016-01-01

Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation appr...

Magnetic resonance imaging in brain-stem tumors

International Nuclear Information System (INIS)

Nomura, Mikio; Saito, Hisazumi; Akino, Minoru; Abe, Hiroshi.

1988-01-01

Four patients with brain-stem tumors underwent magnetic resonance imaging (MRI) before and after radiotherapy. The brain-stem tumors were seen as a low signal intensity on T1-weighted images and as a high signal intensity on T2-weighted images. A tumor and its anatomic involvement were more clearly visualized on MRI than on cuncurrently performed CT. Changes in tumor before and after radiotherapy could be determined by measuring the diameter of tumor on sagittal and coronal images. This allowed quantitative evaluation of the reduction of tumor in association with improvement of symptoms. The mean T1 value in the central part of tumors was shortened in all patients after radiotherapy. The results indicate that MRI may assist in determining the effect of radiotherapy for brain-stem tumors. (Namekawa, K)

SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

International Nuclear Information System (INIS)

Chen, L; Zhou, Z; Wang, J

2016-01-01

Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.

SU-C-207B-03: A Geometrical Constrained Chan-Vese Based Tumor Segmentation Scheme for PET

Energy Technology Data Exchange (ETDEWEB)

Chen, L; Zhou, Z; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan-Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices. Methods: The proposed scheme performs segmentation in a slice-by-slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering-based segmentation method under user’s guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan-Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan-Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme. Results: Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively. Conclusion: We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.

Increased expression of aquaporin-4 in human traumatic brain injury and brain tumors

Institute of Scientific and Technical Information of China (English)

HU Hua; YAO Hong-tian; ZHANG Wei-ping; ZHANG LEI; DING Wei; ZHANG Shi-hong; CHEN Zhong; WEI Er-qing

2005-01-01

Objective: To characterize the expression of aquaporin-4 (AQP4), one of the aquaporins (AQPs), in human brain specimens from patients with traumatic brain injury or brain tumors. Methods: Nineteen human brain specimens were obtained from the patients with traumatic brain injury, brain tumors, benign meningioma or early stage hemorrhagic stroke. MRI or CT imaging was used to assess brain edema. Hematoxylin and eosin staining were used to evaluate cell damage. Immunohistochemistry was used to detect the AQP4 expression. Results: AQP4 expression was increased from 15h to at least 8 d after injury. AQP4immunoreactivity was strong around astrocytomas, ganglioglioma and metastatic adenocarcinoma. However, AQP4 immunoreactivity was only found in the centers of astrocytomas and ganglioglioma, but not in metastatic adenocarcinoma derived from lung.Conclusion: AQP4 expression increases in human brains after traumatic brain injury, within brain-derived tumors, and around brain tumors.

Fuzzy object models for newborn brain MR image segmentation

Science.gov (United States)

Kobashi, Syoji; Udupa, Jayaram K.

2013-03-01

Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

A Hybrid DE-RGSO-ELM for Brain Tumor Tissue Categorization in 3D Magnetic Resonance Images

Directory of Open Access Journals (Sweden)

K. Kothavari

2014-01-01

Full Text Available Medical diagnostics, a technique used for visualizing the internal structures and functions of human body, serves as a scientific tool to assist physicians and involves direct use of digital imaging system analysis. In this scenario, identification of brain tumors is complex in the diagnostic process. Magnetic resonance imaging (MRI technique is noted to best assist tissue contrast for anatomical details and also carries out mechanisms for investigating the brain by functional imaging in tumor predictions. Considering 3D MRI model, analyzing the anatomy features and tissue characteristics of brain tumor is complex in nature. Henceforth, in this work, feature extraction is carried out by computing 3D gray-level cooccurence matrix (3D GLCM and run-length matrix (RLM and feature subselection for dimensionality reduction is performed with basic differential evolution (DE algorithm. Classification is performed using proposed extreme learning machine (ELM, with refined group search optimizer (RGSO technique, to select the best parameters for better simplification and training of the classifier for brain tissue and tumor characterization as white matter (WM, gray matter (GM, cerebrospinal fluid (CSF, and tumor. Extreme learning machine outperforms the standard binary linear SVM and BPN for medical image classifier and proves better in classifying healthy and tumor tissues. The comparison between the algorithms proves that the mean and standard deviation produced by volumetric feature extraction analysis are higher than the other approaches. The proposed work is designed for pathological brain tumor classification and for 3D MRI tumor image segmentation. The proposed approaches are applied for real time datasets and benchmark datasets taken from dataset repositories.

Examination of Blood-Brain Barrier (BBB) Integrity In A Mouse Brain Tumor Model

Science.gov (United States)

On, Ngoc; Mitchell, Ryan; Savant, Sanjot D.; Bachmeier, Corbin. J.; Hatch, Grant M.; Miller, Donald W.

2013-01-01

The present study evaluates, both functionally and biochemically, brain tumor-induced alterations in brain capillary endothelial cells. Brain tumors were induced in Balb/c mice via intracranial injection of Lewis Lung carcinoma (3LL) cells into the right hemisphere of the mouse brain using stereotaxic apparatus. Blood-brain barrier (BBB) permeability was assessed at various stages of tumor development, using both radiolabeled tracer permeability and magnetic resonance imaging (MRI) with gadolinium diethylene-triamine-pentaacetate contrast enhancement (Gad-DTPA). The expression of the drug efflux transporter, P-glycoprotein (P-gp), in the BBB at various stages of tumor development was also evaluated by Western blot and immunohistochemistry. Median mouse survival following tumor cell injection was 17 days. The permeability of the BBB to 3H-mannitol was similar in both brain hemispheres at 7 and 10 days post-injection. By day 15, there was a 2-fold increase in 3H-mannitol permeability in the tumor bearing hemispheres compared to the non-tumor hemispheres. Examination of BBB permeability with Gad-DTPA contrast enhanced MRI indicated cerebral vascular permeability changes were confined to the tumor area. The permeability increase observed at the later stages of tumor development correlated with an increase in cerebral vascular volume suggesting angiogenesis within the tumor bearing hemisphere. Furthermore, the Gad-DPTA enhancement observed within the tumor area was significantly less than Gad-DPTA enhancement within the circumventricular organs not protected by the BBB. Expression of P-gp in both the tumor bearing and non-tumor bearing portions of the brain appeared similar at all time points examined. These studies suggest that although BBB integrity is altered within the tumor site at later stages of development, the BBB is still functional and limiting in terms of solute and drug permeability in and around the tumor. PMID:23184143

Expression of iron-related genes in human brain and brain tumors

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Britton Robert S

2009-04-01

Full Text Available Abstract Background Defective iron homeostasis may be involved in the development of some diseases within the central nervous system. Although the expression of genes involved in normal iron balance has been intensively studied in other tissues, little is known about their expression in the brain. We investigated the mRNA levels of hepcidin (HAMP, HFE, neogenin (NEO1, transferrin receptor 1 (TFRC, transferrin receptor 2 (TFR2, and hemojuvelin (HFE2 in normal human brain, brain tumors, and astrocytoma cell lines. The specimens included 5 normal brain tissue samples, 4 meningiomas, one medulloblastoma, 3 oligodendrocytic gliomas, 2 oligoastrocytic gliomas, 8 astrocytic gliomas, and 3 astrocytoma cell lines. Results Except for hemojuvelin, all genes studied had detectable levels of mRNA. In most tumor types, the pattern of gene expression was diverse. Notable findings include high expression of transferrin receptor 1 in the hippocampus and medulla oblongata compared to other brain regions, low expression of HFE in normal brain with elevated HFE expression in meningiomas, and absence of hepcidin mRNA in astrocytoma cell lines despite expression in normal brain and tumor specimens. Conclusion These results indicate that several iron-related genes are expressed in normal brain, and that their expression may be dysregulated in brain tumors.

3D segmentation of kidney tumors from freehand 2D ultrasound

Science.gov (United States)

Ahmad, Anis; Cool, Derek; Chew, Ben H.; Pautler, Stephen E.; Peters, Terry M.

2006-03-01

To completely remove a tumor from a diseased kidney, while minimizing the resection of healthy tissue, the surgeon must be able to accurately determine its location, size and shape. Currently, the surgeon mentally estimates these parameters by examining pre-operative Computed Tomography (CT) images of the patient's anatomy. However, these images do not reflect the state of the abdomen or organ during surgery. Furthermore, these images can be difficult to place in proper clinical context. We propose using Ultrasound (US) to acquire images of the tumor and the surrounding tissues in real-time, then segmenting these US images to present the tumor as a three dimensional (3D) surface. Given the common use of laparoscopic procedures that inhibit the range of motion of the operator, we propose segmenting arbitrarily placed and oriented US slices individually using a tracked US probe. Given the known location and orientation of the US probe, we can assign 3D coordinates to the segmented slices and use them as input to a 3D surface reconstruction algorithm. We have implemented two approaches for 3D segmentation from freehand 2D ultrasound. Each approach was evaluated on a tissue-mimicking phantom of a kidney tumor. The performance of our approach was determined by measuring RMS surface error between the segmentation and the known gold standard and was found to be below 0.8 mm.

Blood Brain Barrier: A Challenge for Effectual Therapy of Brain Tumors

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Arijit Bhowmik

2015-01-01

Full Text Available Brain tumors are one of the most formidable diseases of mankind. They have only a fair to poor prognosis and high relapse rate. One of the major causes of extreme difficulty in brain tumor treatment is the presence of blood brain barrier (BBB. BBB comprises different molecular components and transport systems, which in turn create efflux machinery or hindrance for the entry of several drugs in brain. Thus, along with the conventional techniques, successful modification of drug delivery and novel therapeutic strategies are needed to overcome this obstacle for treatment of brain tumors. In this review, we have elucidated some critical insights into the composition and function of BBB and along with it we have discussed the effective methods for delivery of drugs to the brain and therapeutic strategies overcoming the barrier.

Anisotropic Diffusion based Brain MRI Segmentation and 3D Reconstruction

OpenAIRE

M. Arfan Jaffar; Sultan Zia; Ghaznafar Latif; AnwarM. Mirza; Irfan Mehmood; Naveed Ejaz; Sung Wook Baik

2012-01-01

In medical field visualization of the organs is very imperative for accurate diagnosis and treatment of any disease. Brain tumor diagnosis and surgery also required impressive 3D visualization of the brain to the radiologist. Detection and 3D reconstruction of brain tumors from MRI is a computationally time consuming and error-prone task. Proposed system detects and presents a 3D visualization model of the brain and tumor inside which greatly helps the radiologist to effectively diagnose and ...

Reconstruction of segmental bone defect of long bones after tumor resection by devitalized tumor-bearing bone

OpenAIRE

Qu, Huayi; Guo, Wei; Yang, Rongli; Li, Dasen; Tang, Shun; Yang, Yi; Dong, Sen; Zang, Jie

2015-01-01

Background The reconstruction of an intercalary bone defect after a tumor resection of a long bone remains a challenge to orthopedic surgeons. Though several methods have been adopted to enhance the union of long segmental allografts or retrieved segmental autografts to the host bones, still more progresses are required to achieve a better union rate. Several methods have been adopted to devitalize tumor bone for recycling usage, and the results varied. We describe our experiences of using de...

SU-E-J-224: Multimodality Segmentation of Head and Neck Tumors

International Nuclear Information System (INIS)

Aristophanous, M; Yang, J; Beadle, B

2014-01-01

Purpose: Develop an algorithm that is able to automatically segment tumor volume in Head and Neck cancer by integrating information from CT, PET and MR imaging simultaneously. Methods: Twenty three patients that were recruited under an adaptive radiotherapy protocol had MR, CT and PET/CT scans within 2 months prior to start of radiotherapy. The patients had unresectable disease and were treated either with chemoradiotherapy or radiation therapy alone. Using the Velocity software, the PET/CT and MR (T1 weighted+contrast) scans were registered to the planning CT using deformable and rigid registration respectively. The PET and MR images were then resampled according to the registration to match the planning CT. The resampled images, together with the planning CT, were fed into a multi-channel segmentation algorithm, which is based on Gaussian mixture models and solved with the expectation-maximization algorithm and Markov random fields. A rectangular region of interest (ROI) was manually placed to identify the tumor area and facilitate the segmentation process. The auto-segmented tumor contours were compared with the gross tumor volume (GTV) manually defined by the physician. The volume difference and Dice similarity coefficient (DSC) between the manual and autosegmented GTV contours were calculated as the quantitative evaluation metrics. Results: The multimodality segmentation algorithm was applied to all 23 patients. The volumes of the auto-segmented GTV ranged from 18.4cc to 32.8cc. The average (range) volume difference between the manual and auto-segmented GTV was −42% (−32.8%–63.8%). The average DSC value was 0.62, ranging from 0.39 to 0.78. Conclusion: An algorithm for the automated definition of tumor volume using multiple imaging modalities simultaneously was successfully developed and implemented for Head and Neck cancer. This development along with more accurate registration algorithms can aid physicians in the efforts to interpret the multitude of

SU-E-J-224: Multimodality Segmentation of Head and Neck Tumors

Energy Technology Data Exchange (ETDEWEB)

Aristophanous, M; Yang, J; Beadle, B [UT MD Anderson Cancer Center, Houston, TX (United States)

2014-06-01

Purpose: Develop an algorithm that is able to automatically segment tumor volume in Head and Neck cancer by integrating information from CT, PET and MR imaging simultaneously. Methods: Twenty three patients that were recruited under an adaptive radiotherapy protocol had MR, CT and PET/CT scans within 2 months prior to start of radiotherapy. The patients had unresectable disease and were treated either with chemoradiotherapy or radiation therapy alone. Using the Velocity software, the PET/CT and MR (T1 weighted+contrast) scans were registered to the planning CT using deformable and rigid registration respectively. The PET and MR images were then resampled according to the registration to match the planning CT. The resampled images, together with the planning CT, were fed into a multi-channel segmentation algorithm, which is based on Gaussian mixture models and solved with the expectation-maximization algorithm and Markov random fields. A rectangular region of interest (ROI) was manually placed to identify the tumor area and facilitate the segmentation process. The auto-segmented tumor contours were compared with the gross tumor volume (GTV) manually defined by the physician. The volume difference and Dice similarity coefficient (DSC) between the manual and autosegmented GTV contours were calculated as the quantitative evaluation metrics. Results: The multimodality segmentation algorithm was applied to all 23 patients. The volumes of the auto-segmented GTV ranged from 18.4cc to 32.8cc. The average (range) volume difference between the manual and auto-segmented GTV was −42% (−32.8%–63.8%). The average DSC value was 0.62, ranging from 0.39 to 0.78. Conclusion: An algorithm for the automated definition of tumor volume using multiple imaging modalities simultaneously was successfully developed and implemented for Head and Neck cancer. This development along with more accurate registration algorithms can aid physicians in the efforts to interpret the multitude of

Regional cerebral blood flow measurement in brain tumors

International Nuclear Information System (INIS)

Izunaga, Hiroshi; Hirota, Yoshihisa; Takahashi, Mutsumasa; Fuwa, Isao; Kodama, Takafumi; Matsukado, Yasuhiko

1986-01-01

The regional cerebral blood flow (CBF) was determined on seventeen patients with brain tumors. Ring type single photon emission CT (SPECT) was used following intravenous injection of 133 Xe. Case materials included eleven meningiomas and six malignant gliomas. Evaluation was performed with emphasis on the following points; 1. Correlation of the flow data within tumors to the angiographic tumor stains, 2. Influence of tumors on the cerebral blood flow of the normal brain tissue, 3. Correlation between degree of peripheral edema and the flow data of the affected hemispheres. There was significant correlation between flow data within tumors and angiographic tumor stains in meningiomas. Influence of tumors on cerebral blood flow of the normal tissue was greater in meningiomas than in gliomas. There was negative correlation between the degree of peripheral edema and the flow data of the affected hemisphere. It has been concluded that the measurement of CBF in brain tumors is a valuable method in evaluation of brain tumors. (author)

Regional cerebral blood flow measurement in brain tumors

Energy Technology Data Exchange (ETDEWEB)

Izunaga, Hiroshi; Hirota, Yoshihisa; Takahashi, Mutsumasa; Fuwa, Isao; Kodama, Takafumi; Matsukado, Yasuhiko

1986-10-01

The regional cerebral blood flow (CBF) was determined on seventeen patients with brain tumors. Ring type single photon emission CT (SPECT) was used following intravenous injection of /sup 133/Xe. Case materials included eleven meningiomas and six malignant gliomas. Evaluation was performed with emphasis on the following points; 1. Correlation of the flow data within tumors to the angiographic tumor stains, 2. Influence of tumors on the cerebral blood flow of the normal brain tissue, 3. Correlation between degree of peripheral edema and the flow data of the affected hemispheres. There was significant correlation between flow data within tumors and angiographic tumor stains in meningiomas. Influence of tumors on cerebral blood flow of the normal tissue was greater in meningiomas than in gliomas. There was negative correlation between the degree of peripheral edema and the flow data of the affected hemisphere. It has been concluded that the measurement of CBF in brain tumors is a valuable method in evaluation of brain tumors.

Automated segmentation of ventricles from serial brain MRI for the quantification of volumetric changes associated with communicating hydrocephalus in patients with brain tumor

Science.gov (United States)

Pura, John A.; Hamilton, Allison M.; Vargish, Geoffrey A.; Butman, John A.; Linguraru, Marius George

2011-03-01

Accurate ventricle volume estimates could improve the understanding and diagnosis of postoperative communicating hydrocephalus. For this category of patients, associated changes in ventricle volume can be difficult to identify, particularly over short time intervals. We present an automated segmentation algorithm that evaluates ventricle size from serial brain MRI examination. The technique combines serial T1- weighted images to increase SNR and segments the means image to generate a ventricle template. After pre-processing, the segmentation is initiated by a fuzzy c-means clustering algorithm to find the seeds used in a combination of fast marching methods and geodesic active contours. Finally, the ventricle template is propagated onto the serial data via non-linear registration. Serial volume estimates were obtained in an automated robust and accurate manner from difficult data.

A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

Science.gov (United States)

Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

2013-01-01

In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

BNCT for malignant brain tumors in children

International Nuclear Information System (INIS)

Kageji, T.; Mizobuchi, Y.; Nagahiro, S.; Nakagawa, Y.; Kumada, Hiroaki

2006-01-01

BSH-based intra-operative BNCT as an initial treatment underwent in 4 children with malignant brain tumors since 1998. There were 2 glioblastomas, one primitive neuroectodermal tumor (PNET) and one anaplastic ependymoma patient. They included two children under 3-year-old. All GBM patients were died of CSF dissemination without tumor regrowth in the primary site. Another PNET and anaplastic ependymoma patients are still alive without tumor recurrence. We can consider BNCT is optimal treatment modality for malignant brain tumor in children. (author)

Obstacles to Brain Tumor Therapy: Key ABC Transporters

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Juwina Wijaya

2017-11-01

Full Text Available The delivery of cancer chemotherapy to treat brain tumors remains a challenge, in part, because of the inherent biological barrier, the blood–brain barrier. While its presence and role as a protector of the normal brain parenchyma has been acknowledged for decades, it is only recently that the important transporter components, expressed in the tightly knit capillary endothelial cells, have been deciphered. These transporters are ATP-binding cassette (ABC transporters and, so far, the major clinically important ones that functionally contribute to the blood–brain barrier are ABCG2 and ABCB1. A further limitation to cancer therapy of brain tumors or brain metastases is the blood–tumor barrier, where tumors erect a barrier of transporters that further impede drug entry. The expression and regulation of these two transporters at these barriers, as well as tumor derived alteration in expression and/or mutation, are likely obstacles to effective therapy.

Neonatal Brain Tissue Classification with Morphological Adaptation and Unified Segmentation

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Richard eBeare

2016-03-01

Full Text Available Measuring the distribution of brain tissue types (tissue classification in neonates is necessary for studying typical and atypical brain development, such as that associated with preterm birth, and may provide biomarkers for neurodevelopmental outcomes. Compared with magnetic resonance images of adults, neonatal images present specific challenges that require the development of specialized, population-specific methods. This paper introduces MANTiS (Morphologically Adaptive Neonatal Tissue Segmentation, which extends the unified segmentation approach to tissue classification implemented in Statistical Parametric Mapping (SPM software to neonates. MANTiS utilizes a combination of unified segmentation, template adaptation via morphological segmentation tools and topological filtering, to segment the neonatal brain into eight tissue classes: cortical gray matter, white matter, deep nuclear gray matter, cerebellum, brainstem, cerebrospinal fluid (CSF, hippocampus and amygdala. We evaluated the performance of MANTiS using two independent datasets. The first dataset, provided by the NeoBrainS12 challenge, consisted of coronal T2-weighted images of preterm infants (born ≤30 weeks’ gestation acquired at 30 weeks’ corrected gestational age (n= 5, coronal T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5 and axial T2-weighted images of preterm infants acquired at 40 weeks’ corrected gestational age (n= 5. The second dataset, provided by the Washington University NeuroDevelopmental Research (WUNDeR group, consisted of T2-weighted images of preterm infants (born <30 weeks’ gestation acquired shortly after birth (n= 12, preterm infants acquired at term-equivalent age (n= 12, and healthy term-born infants (born ≥38 weeks’ gestation acquired within the first nine days of life (n= 12. For the NeoBrainS12 dataset, mean Dice scores comparing MANTiS with manual segmentations were all above 0.7, except for

Automated brain structure segmentation based on atlas registration and appearance models

DEFF Research Database (Denmark)

van der Lijn, Fedde; de Bruijne, Marleen; Klein, Stefan

2012-01-01

Accurate automated brain structure segmentation methods facilitate the analysis of large-scale neuroimaging studies. This work describes a novel method for brain structure segmentation in magnetic resonance images that combines information about a structure’s location and appearance. The spatial...... with different magnetic resonance sequences, in which the hippocampus and cerebellum were segmented by an expert. Furthermore, the method is compared to two other segmentation techniques that were applied to the same data. Results show that the atlas- and appearance-based method produces accurate results...

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

DEFF Research Database (Denmark)

Menze, Bjoern H.; Jakab, Andras; Bauer, Stefan

2015-01-01

a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing...

Brain tumor and CT, 1. Relationship between the consistency of a brain tumor and the CT findings

Energy Technology Data Exchange (ETDEWEB)

Suzuki, N.; Katada, K.; Shinomiya, Y.; Sano, H.; Kanno, T. (Fujita Gakuen Univ., School of Medicine, Toyoake, Aichi (Japan))

1981-08-01

It is very important for a neurosurgeon to know the consistency of a brain tumor preoperatively, since the information is of much use in indicating the likely difficulty of the operation, which operative tools should be selected, the amount of bleeding to be expected from the tumor, and so on. The authors, therefore, tried to evaluate the consistency of brain tumors preoperatively. Twenty-seven cases in which the margin of the tumor was made clear with a homogeneous stain were studied concerning the relationship between the tumor consistency and the CT findings. The results are as follows: 1) A higher CT number on a plain CT indicated a harder consistency of the tumor. 2) A lesser contrast index (CT number on enhancement CT/CT number on plain CT) showed a harder consistency of the tumor.

Targeting Nanomedicine to Brain Tumors: Latest Progress and Achievements.

Science.gov (United States)

Van't Root, Moniek; Lowik, Clemens; Mezzanotte, Laura

2017-01-01

Targeting nanomedicine to brain tumors is hampered by the heterogeneity of brain tumors and the blood brain barrier. These represent the main reasons of unsuccessful treatments. Nanomedicine based approaches hold promise for improved brain tissue distribution of drugs and delivery of combination therapies. In this review, we describe the recent advancements and latest achievements in the use of nanocarriers, virus and cell-derived nanoparticles for targeted therapy of brain tumors. We provide successful examples of nanomedicine based approaches for direct targeting of receptors expressed in brain tumor cells or modulation of pathways involved in cell survival as well as approaches for indirect targeting of cells in the tumor stroma and immunotherapies. Although the field is at its infancy, clinical trials involving nanomedicine based approaches for brain tumors are ongoing and many others will start in the near future. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Blood Brain Barrier: A Challenge for Effectual Therapy of Brain Tumors

OpenAIRE

Bhowmik, Arijit; Khan, Rajni; Ghosh, Mrinal Kanti

2015-01-01

Brain tumors are one of the most formidable diseases of mankind. They have only a fair to poor prognosis and high relapse rate. One of the major causes of extreme difficulty in brain tumor treatment is the presence of blood brain barrier (BBB). BBB comprises different molecular components and transport systems, which in turn create efflux machinery or hindrance for the entry of several drugs in brain. Thus, along with the conventional techniques, successful modification of drug delivery and n...

Breast tumor segmentation in high resolution x-ray phase contrast analyzer based computed tomography.

Science.gov (United States)

Brun, E; Grandl, S; Sztrókay-Gaul, A; Barbone, G; Mittone, A; Gasilov, S; Bravin, A; Coan, P

2014-11-01

Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer based phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedure's possible applications. A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.

Treatment of malignant brain tumor. Today and tomorrow. Image-guided neurosurgery for brain tumor. A current perspective

International Nuclear Information System (INIS)

Kajita, Yasukazu; Fujii, Masazumi; Yoshida, Jun; Maesawa, Satoshi

2008-01-01

Although usefulness of the image-guided neurosurgery is well documented, there are scarce facilities having the actually operating system in Japan. Since 2006, authors' Nagoya University Hospital has had an operating room named ''Brain THEATER'', where an open MRI system APERTO (Hitachi-Medical Co.) and a navigation system Vector Vision (BrainLAB) are connected to conduct the complete image-guided neurosurgery for brain tumor by using the intraoperative MRI for continuously updating the residual tumor tissue to be dissected out. The room is pre- and intra-operatively supported by Departments of image analysis and of radiation technology in the University, and as well, is connected by net-working with another image-guided surgical room ''Brain Suite'' (Siemens 1.5 T MRI system: BrainLAB) in the neighboring facility, Nagoya Central Hospital. This paper describes the circumstances of the introduction of these systems in the Hospital, details of the image-guided surgery in the operation rooms with illustration of actual photos of the rooms and of pre-, intra- and post-operative images, outcomes of image-guided neurosurgery for brain tumor reported hitherto, image-guided neurosurgery for brain tumor's future perspectives involving robotic surgery and operation on the virtual 3D image including the net-worked one. Efforts should be made to further spread the system for performing the more non-invasive and precise surgery, and for conducting the diagnosis united with treatment. (R.T.)

Automatic segmentation of MR brain images with a convolutional neural network

NARCIS (Netherlands)

Moeskops, P.; Viergever, M.A.; Mendrik, A.M.; de Vries, L.S.; Benders, M.J.N.L.; Išgum, I.

2016-01-01

Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages. This paper presents a method for the automatic segmentation of MR brain images into a number of tissue classes using a convolutional neural network. To ensure

Brain tumors in children; Hirntumoren beim Kind

Energy Technology Data Exchange (ETDEWEB)

Harting, I.; Seitz, A. [Universitaetsklinikum Heidelberg (Germany). Abt. Neuroradiologie

2009-06-15

Brain tumors are common in children; in Germany approximately 400 children are diagnosed every year. In the posterior fossa, cerebellar neoplasms outnumber brainstem gliomas. In contrast to their rarity in adults, brainstem gliomas are not uncommon in children. Supratentorial tumors can be subdivided by location into neoplasms of the cerebral hemispheres, suprasellar and pineal tumors. Astrocytoma is the most common pediatric brain tumor followed by medulloblastoma, ependymoma and craniopharyngeoma. The combination of imaging morphology, tumor localisation and patient age at manifestation form the basis of the neuroradiological differential diagnosis. (orig.)

Anticonvulsant therapy in brain-tumor related epilepsy

Directory of Open Access Journals (Sweden)

Fröscher Walter

2016-06-01

Full Text Available Background. The lifetime risk of patients with brain tumors to have focal epileptic seizures is 10-100%; the risk depends on different histology. Specific guidelines for drug treatment of brain tumor-related seizures have not yet been established.

Hypofractionation Regimens for Stereotactic Radiotherapy for Large Brain Tumors

International Nuclear Information System (INIS)

Yuan Jiankui; Wang, Jian Z.; Lo, Simon; Grecula, John C.; Ammirati, Mario; Montebello, Joseph F.; Zhang Hualin; Gupta, Nilendu; Yuh, William T.C.; Mayr, Nina A.

2008-01-01

Purpose: To investigate equivalent regimens for hypofractionated stereotactic radiotherapy (HSRT) for brain tumor treatment and to provide dose-escalation guidance to maximize the tumor control within the normal brain tolerance. Methods and Materials: The linear-quadratic model, including the effect of nonuniform dose distributions, was used to evaluate the HSRT regimens. The α/β ratio was estimated using the Gammaknife stereotactic radiosurgery (GKSRS) and whole-brain radiotherapy experience for large brain tumors. The HSRT regimens were derived using two methods: (1) an equivalent tumor control approach, which matches the whole-brain radiotherapy experience for many fractions and merges it with the GKSRS data for few fractions; and (2) a normal-tissue tolerance approach, which takes advantages of the dose conformity and fractionation of HSRT to approach the maximal dose tolerance of the normal brain. Results: A plausible α/β ratio of 12 Gy for brain tumor and a volume parameter n of 0.23 for normal brain were derived from the GKSRS and whole-brain radiotherapy data. The HSRT prescription regimens for the isoeffect of tumor irradiation were calculated. The normal-brain equivalent uniform dose decreased as the number of fractions increased, because of the advantage of fractionation. The regimens for potential dose escalation of HSRT within the limits of normal-brain tolerance were derived. Conclusions: The designed hypofractionated regimens could be used as a preliminary guide for HSRT dose prescription for large brain tumors to mimic the GKSRS experience and for dose escalation trials. Clinical studies are necessary to further tune the model parameters and validate these regimens

Adversarial training and dilated convolutions for brain MRI segmentation

NARCIS (Netherlands)

Moeskops, P.; Veta, M.; Lafarge, M.W.; Eppenhof, K.A.J.; Pluim, J.P.W.

2017-01-01

Convolutional neural networks (CNNs) have been applied to various automatic image segmentation tasks in medical image analysis, including brain MRI segmentation. Generative adversarial networks have recently gained popularity because of their power in generating images that are difficult to

Advance MRI for pediatric brain tumors with emphasis on clinical benefits

Energy Technology Data Exchange (ETDEWEB)

Goo, Hyun Woo; Ra, Young Shin [Asan Medical Center, University of Ulsan College of Medicine, Seoul(Korea, Republic of)

2017-01-15

Conventional anatomic brain MRI is often limited in evaluating pediatric brain tumors, the most common solid tumors and a leading cause of death in children. Advanced brain MRI techniques have great potential to improve diagnostic performance in children with brain tumors and overcome diagnostic pitfalls resulting from diverse tumor pathologies as well as nonspecific or overlapped imaging findings. Advanced MRI techniques used for evaluating pediatric brain tumors include diffusion-weighted imaging, diffusion tensor imaging, functional MRI, perfusion imaging, spectroscopy, susceptibility-weighted imaging, and chemical exchange saturation transfer imaging. Because pediatric brain tumors differ from adult counterparts in various aspects, MRI protocols should be designed to achieve maximal clinical benefits in pediatric brain tumors. In this study, we review advanced MRI techniques and interpretation algorithms for pediatric brain tumors.

Intrapontine malignant nerve sheath tumor

DEFF Research Database (Denmark)

Kozić, Dusko; Nagulić, Mirjana; Samardzić, Miroslav

2008-01-01

. On pathological examination, the neoplasm appeared to be an intrapontine nerve sheath tumor originating most likely from the intrapontine segment of one of the cranial nerve fibres. The tumor showed exophytic growth, with consequent spread to adjacent subaracnoid space. MR spectroscopy revealed the presence......The primary source of malignant intracerebral nerve sheath tumors is still unclear We report the imaging and MR spectroscopic findings in a 39-year-old man with a very rare brain stem tumor MR examination revealed the presence of intraaxial brain stem tumor with a partial exophytic growth...

Childhood brain tumors: epidemiology, current management and future directions.

Science.gov (United States)

Pollack, Ian F; Jakacki, Regina I

2011-07-26

Brain tumors are the most common solid tumors in children. With the increasingly widespread availability of MRI, the incidence of childhood brain tumors seemed to rise in the 1980s, but has subsequently remained relatively stable. However, management of brain tumors in children has evolved substantially during this time, reflecting refinements in classification of tumors, delineation of risk groups within histological subsets of tumors, and incorporation of molecular techniques to further define tumor subgroups. Although considerable progress has been made in the outcomes of certain tumors, prognosis in other childhood brain tumor types is poor. Among the tumor groups with more-favorable outcomes, attention has been focused on reducing long-term morbidity without sacrificing survival rates. Studies for high-risk groups have examined the use of intensive therapy or novel, molecularly targeted approaches to improve disease control rates. In addition to reviewing the literature and providing an overview of the complexities in diagnosing childhood brain tumors, we will discuss advances in the treatment and categorization of several tumor types in which progress has been most apparent, as well as those in which improvements have been lacking. The latest insights from molecular correlative studies that hold potential for future refinements in therapy will also be discussed.

Semi-automated segmentation of a glioblastoma multiforme on brain MR images for radiotherapy planning.

Science.gov (United States)

Hori, Daisuke; Katsuragawa, Shigehiko; Murakami, Ryuuji; Hirai, Toshinori

2010-04-20

We propose a computerized method for semi-automated segmentation of the gross tumor volume (GTV) of a glioblastoma multiforme (GBM) on brain MR images for radiotherapy planning (RTP). Three-dimensional (3D) MR images of 28 cases with a GBM were used in this study. First, a sphere volume of interest (VOI) including the GBM was selected by clicking a part of the GBM region in the 3D image. Then, the sphere VOI was transformed to a two-dimensional (2D) image by use of a spiral-scanning technique. We employed active contour models (ACM) to delineate an optimal outline of the GBM in the transformed 2D image. After inverse transform of the optimal outline to the 3D space, a morphological filter was applied to smooth the shape of the 3D segmented region. For evaluation of our computerized method, we compared the computer output with manually segmented regions, which were obtained by a therapeutic radiologist using a manual tracking method. In evaluating our segmentation method, we employed the Jaccard similarity coefficient (JSC) and the true segmentation coefficient (TSC) in volumes between the computer output and the manually segmented region. The mean and standard deviation of JSC and TSC were 74.2+/-9.8% and 84.1+/-7.1%, respectively. Our segmentation method provided a relatively accurate outline for GBM and would be useful for radiotherapy planning.

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

Science.gov (United States)

Akkus, Zeynettin; Galimzianova, Alfiia; Hoogi, Assaf; Rubin, Daniel L; Erickson, Bradley J

2017-08-01

Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest. Deep learning-based segmentation approaches for brain MRI are gaining interest due to their self-learning and generalization ability over large amounts of data. As the deep learning architectures are becoming more mature, they gradually outperform previous state-of-the-art classical machine learning algorithms. This review aims to provide an overview of current deep learning-based segmentation approaches for quantitative brain MRI. First we review the current deep learning architectures used for segmentation of anatomical brain structures and brain lesions. Next, the performance, speed, and properties of deep learning approaches are summarized and discussed. Finally, we provide a critical assessment of the current state and identify likely future developments and trends.

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

Science.gov (United States)

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching

Directory of Open Access Journals (Sweden)

Ward Kevin R

2009-11-01

Full Text Available Abstract Background Accurate analysis of CT brain scans is vital for diagnosis and treatment of Traumatic Brain Injuries (TBI. Automatic processing of these CT brain scans could speed up the decision making process, lower the cost of healthcare, and reduce the chance of human error. In this paper, we focus on automatic processing of CT brain images to segment and identify the ventricular systems. The segmentation of ventricles provides quantitative measures on the changes of ventricles in the brain that form vital diagnosis information. Methods First all CT slices are aligned by detecting the ideal midlines in all images. The initial estimation of the ideal midline of the brain is found based on skull symmetry and then the initial estimate is further refined using detected anatomical features. Then a two-step method is used for ventricle segmentation. First a low-level segmentation on each pixel is applied on the CT images. For this step, both Iterated Conditional Mode (ICM and Maximum A Posteriori Spatial Probability (MASP are evaluated and compared. The second step applies template matching algorithm to identify objects in the initial low-level segmentation as ventricles. Experiments for ventricle segmentation are conducted using a relatively large CT dataset containing mild and severe TBI cases. Results Experiments show that the acceptable rate of the ideal midline detection is over 95%. Two measurements are defined to evaluate ventricle recognition results. The first measure is a sensitivity-like measure and the second is a false positive-like measure. For the first measurement, the rate is 100% indicating that all ventricles are identified in all slices. The false positives-like measurement is 8.59%. We also point out the similarities and differences between ICM and MASP algorithms through both mathematically relationships and segmentation results on CT images. Conclusion The experiments show the reliability of the proposed algorithms. The

Novel strategies of Raman imaging for brain tumor research.

Science.gov (United States)

Anna, Imiela; Bartosz, Polis; Lech, Polis; Halina, Abramczyk

2017-10-17

Raman diagnostics and imaging have been shown to be an effective tool for the analysis and discrimination of human brain tumors from normal structures. Raman spectroscopic methods have potential to be applied in clinical practice as they allow for identification of tumor margins during surgery. In this study, we investigate medulloblastoma (grade IV WHO) (n= 5), low-grade astrocytoma (grades I-II WHO) (n =4), ependymoma (n=3) and metastatic brain tumors (n= 1) and the tissue from the negative margins used as normal controls. We compare a high grade medulloblastoma, low grade astrocytoma and non-tumor samples from human central nervous system (CNS) tissue. Based on the properties of the Raman vibrational features and Raman images we provide a real-time feedback method that is label-free to monitor tumor metabolism that reveals reprogramming of biosynthesis of lipids, proteins, DNA and RNA. Our results indicate marked metabolic differences between low and high grade brain tumors. We discuss molecular mechanisms causing these metabolic changes, particularly lipid alterations in malignant medulloblastoma and low grade gliomas that may shed light on the mechanisms driving tumor recurrence thereby revealing new approaches for the treatment of malignant glioma. We have found that the high-grade tumors of central nervous system (medulloblastoma) exhibit enhanced level of β-sheet conformation and down-regulated level of α-helix conformation when comparing against normal tissue. We have found that almost all tumors studied in the paper have increased Raman signals of nucleic acids. This increase can be interpreted as increased DNA/RNA turnover in brain tumors. We have shown that the ratio of Raman intensities I 2930 /I 2845 at 2930 and 2845 cm -1 is a good source of information on the ratio of lipid and protein contents. We have found that the ratio reflects the different lipid and protein contents of cancerous brain tissue compared to the non-tumor tissue. We found that

Breast tumor segmentation in high resolution x-ray phase contrast analyzer based computed tomography

Energy Technology Data Exchange (ETDEWEB)

Brun, E., E-mail: emmanuel.brun@esrf.fr [European Synchrotron Radiation Facility (ESRF), Grenoble 380000, France and Department of Physics, Ludwig-Maximilians University, Garching 85748 (Germany); Grandl, S.; Sztrókay-Gaul, A.; Gasilov, S. [Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital Munich, 81377 Munich (Germany); Barbone, G. [Department of Physics, Harvard University, Cambridge, Massachusetts 02138 (United States); Mittone, A.; Coan, P. [Department of Physics, Ludwig-Maximilians University, Garching 85748, Germany and Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital Munich, 81377 Munich (Germany); Bravin, A. [European Synchrotron Radiation Facility (ESRF), Grenoble 380000 (France)

2014-11-01

Purpose: Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. Methods: The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer based phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedure’s possible applications. Results: A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. Conclusions: The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.

Multiparametric MR assessment of pediatric brain tumors

International Nuclear Information System (INIS)

Tzika, A.A.; Astrakas, L.G.; Zarifi, M.K.; Petridou, N.; Young-Poussaint, T.; Goumnerova, L.; Black, P.McL.; Zurakowski, D.; Anthony, D.C.

2003-01-01

MR assessment of pediatric brain tumors has expanded to include physiologic information related to cellular metabolites, hemodynamic and diffusion parameters. The purpose of this study was to investigate the relationship between MR and proton MR spectroscopic imaging in children with primary brain tumors. Twenty-one patients (mean age 9 years) with histologically verified brain tumors underwent conventional MR imaging, hemodynamic MR imaging (HMRI) and proton MR spectroscopic imaging (MRSI). Fourteen patients also had diffusion-weighted MR imaging (DWMRI). Metabolic indices including choline-containing compounds (Cho), total creatine (tCr) and lipids/lactate (L) were derived by proton MRSI, relative cerebral blood volume (rCBV) by HMRI, and apparent tissue water diffusion coefficients (ADC) by DWMRI. Variables were examined by linear regression and correlation as well as by ANOVA. Cho (suggestive of tumor cellularity and proliferative activity) correlated positively with rCBV, while the relationship between Cho and ADC (suggestive of cellular density) was inverse (P<0.001). The relationship between rCBV and ADC was also inverse (P=0.004). Cho and lipids (suggestive of necrosis and/or apoptosis) were not significantly correlated (P=0.51). A positive relationship was found between lipids and ADC (P=0.002). The relationships between Cho, rCBV, ADC and lipids signify that tumor physiology is influenced by the tumor's physical and chemical environment. Normalized Cho and lipids distinguished high-grade from low-grade tumors (P<0.05). Multiparametric MR imaging using MRSI, HMRI and DWMRI enhances assessment of brain tumors in children and improves our understanding of tumor physiology while promising to distinguish higher- from lower-malignancy tumors, a distinction that is particularly clinically important among inoperable tumors. (orig.)

Isointense infant brain MRI segmentation with a dilated convolutional neural network

OpenAIRE

Moeskops, Pim; Pluim, Josien P. W.

2017-01-01

Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D convolutional neural network for the segmentation of white matter, gray matter and cerebrospinal fluid in infant brain MR images, as provided by the MICCAI grand challenge on 6-month infant brain MRI segmentation.

MR imaging of the brain: tumors

International Nuclear Information System (INIS)

Sartor, K.

1999-01-01

The radiologic modality that most likely provides the imaging information needed in a patient suspected of having a brain tumor is MR imaging. A brain tumor can be reliably ruled out if the MR examination is performed properly and experts interpret the results as negative. If there is a tumor, however, its exact location and topography must be determined. Important for therapy and prognosis are also tumor properties such as histologic type and grade, as well as effects on adjacent brain structures. Although potentially a noninvasive method of in vivo neuropathology, MR is still far from being sufficiently specific, as dissimilar lesions may look the same despite the use of refined imaging protocols. The evolution of MR imaging continues, however, making further methodologic improvement likely. Presently, advanced methods, such as diffusion- and perfusion-weighted MR imaging, functional MR imaging, neuronavigation based on MR imaging data, and the use of MR imaging during surgery (intraoperative MR imaging), influence the way patients are treated. Likewise, follow-up imaging (monitoring) of tumor patients by MR has become more effective, and experience has shown how to distinguish reactive changes from recurrent tumor. In the future, MR imaging may gain importance in the development of novel therapeutic concepts. (orig.)

Diagnosis and prognosis of brain tumors in clinical trials

OpenAIRE

Gorlia, Thierry

2013-01-01

textabstractAccording to the Central Brain Registry Of The United States (CBTRUS) statistical report (February 2012) the incidence rate of all primary non malignant and malignant brain and central nervous system tumors is 19.89 cases per 100.000 (11.58 for non-malignant tumors and 7.31 for malignant tumors). Malignant brain tumors account for only 1% to 2% of all adult cancers. As a comparison, in 2012, the incidence of women breast cancer was 121.2 (per 100.000). Tumors of neuroepithelial ti...

Subacute brain atrophy induced by radiation therapy to the malignant brain tumors

International Nuclear Information System (INIS)

Asai, Akio; Matsutani, Masao; Takakura, Kintomo.

1987-01-01

In order to analyze brain atrophy after radiation therapy to the brain tumors, we calculated a CSF-cranial volume ratio on CT scan as an index of brain atrophy, and estimated dementia-score by Hasegawa's method in 91 post-irradiated patients with malignant brain tumors. Radiation-induced brain atrophy was observed in 51 out of 91 patients (56 %) and dementia in 23 out of 47 patients (49 %). These two conditions were closely related, and observed significantly more often in aged and whole-brain-irradiated patients. As radiation-induced brain atrophy accompanied by dementia appeared 2 - 3 months after the completion of radiation therapy, it should be regarded as a subacute brain injury caused by radiation therapy. (author)

Fully convolutional networks (FCNs)-based segmentation method for colorectal tumors on T2-weighted magnetic resonance images.

Science.gov (United States)

Jian, Junming; Xiong, Fei; Xia, Wei; Zhang, Rui; Gu, Jinhui; Wu, Xiaodong; Meng, Xiaochun; Gao, Xin

2018-06-01

Segmentation of colorectal tumors is the basis of preoperative prediction, staging, and therapeutic response evaluation. Due to the blurred boundary between lesions and normal colorectal tissue, it is hard to realize accurate segmentation. Routinely manual or semi-manual segmentation methods are extremely tedious, time-consuming, and highly operator-dependent. In the framework of FCNs, a segmentation method for colorectal tumor was presented. Normalization was applied to reduce the differences among images. Borrowing from transfer learning, VGG-16 was employed to extract features from normalized images. We conducted five side-output blocks from the last convolutional layer of each block of VGG-16 along the network, these side-output blocks can deep dive multiscale features, and produced corresponding predictions. Finally, all of the predictions from side-output blocks were fused to determine the final boundaries of the tumors. A quantitative comparison of 2772 colorectal tumor manual segmentation results from T2-weighted magnetic resonance images shows that the average Dice similarity coefficient, positive predictive value, specificity, sensitivity, Hammoude distance, and Hausdorff distance were 83.56, 82.67, 96.75, 87.85%, 0.2694, and 8.20, respectively. The proposed method is superior to U-net in colorectal tumor segmentation (P colorectal tumor segmentation (P > 0.05). The results indicate that the introduction of FCNs contributed to accurate segmentation of colorectal tumors. This method has the potential to replace the present time-consuming and nonreproducible manual segmentation method.

Quantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation

Directory of Open Access Journals (Sweden)

Kazemi K

2014-03-01

Full Text Available Background: Accurate brain tissue segmentation from magnetic resonance (MR images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM, white matter (WM and cerebrospinal fluid (CSF is needed for the neuroimaging applications. Methods: In this paper, performance evaluation of three widely used brain segmentation software packages SPM8, FSL and Brainsuite is presented. Segmentation with SPM8 has been performed in three frameworks: i default segmentation, ii SPM8 New-segmentation and iii modified version using hidden Markov random field as implemented in SPM8-VBM toolbox. Results: The accuracy of the segmented GM, WM and CSF and the robustness of the tools against changes of image quality has been assessed using Brainweb simulated MR images and IBSR real MR images. The calculated similarity between the segmented tissues using different tools and corresponding ground truth shows variations in segmentation results. Conclusion: A few studies has investigated GM, WM and CSF segmentation. In these studies, the skull stripping and bias correction are performed separately and they just evaluated the segmentation. Thus, in this study, assessment of complete segmentation framework consisting of pre-processing and segmentation of these packages is performed. The obtained results can assist the users in choosing an appropriate segmentation software package for the neuroimaging application of interest.

Research on segmentation based on multi-atlas in brain MR image

Science.gov (United States)

Qian, Yuejing

2018-03-01

Accurate segmentation of specific tissues in brain MR image can be effectively achieved with the multi-atlas-based segmentation method, and the accuracy mainly depends on the image registration accuracy and fusion scheme. This paper proposes an automatic segmentation method based on the multi-atlas for brain MR image. Firstly, to improve the registration accuracy in the area to be segmented, we employ a target-oriented image registration method for the refinement. Then In the label fusion, we proposed a new algorithm to detect the abnormal sparse patch and simultaneously abandon the corresponding abnormal sparse coefficients, this method is made based on the remaining sparse coefficients combined with the multipoint label estimator strategy. The performance of the proposed method was compared with those of the nonlocal patch-based label fusion method (Nonlocal-PBM), the sparse patch-based label fusion method (Sparse-PBM) and majority voting method (MV). Based on our experimental results, the proposed method is efficient in the brain MR images segmentation compared with MV, Nonlocal-PBM, and Sparse-PBM methods.

Assessing the scale of tumor heterogeneity by complete hierarchical segmentation of MRI.

Science.gov (United States)

Gensheimer, Michael F; Hawkins, Douglas S; Ermoian, Ralph P; Trister, Andrew D

2015-02-07

In many cancers, intratumoral heterogeneity has been found in histology, genetic variation and vascular structure. We developed an algorithm to interrogate different scales of heterogeneity using clinical imaging. We hypothesize that heterogeneity of perfusion at coarse scale may correlate with treatment resistance and propensity for disease recurrence. The algorithm recursively segments the tumor image into increasingly smaller regions. Each dividing line is chosen so as to maximize signal intensity difference between the two regions. This process continues until the tumor has been divided into single voxels, resulting in segments at multiple scales. For each scale, heterogeneity is measured by comparing each segmented region to the adjacent region and calculating the difference in signal intensity histograms. Using digital phantom images, we showed that the algorithm is robust to image artifacts and various tumor shapes. We then measured the primary tumor scales of contrast enhancement heterogeneity in MRI of 18 rhabdomyosarcoma patients. Using Cox proportional hazards regression, we explored the influence of heterogeneity parameters on relapse-free survival. Coarser scale of maximum signal intensity heterogeneity was prognostic of shorter survival (p = 0.05). By contrast, two fractal parameters and three Haralick texture features were not prognostic. In summary, our algorithm produces a biologically motivated segmentation of tumor regions and reports the amount of heterogeneity at various distance scales. If validated on a larger dataset, this prognostic imaging biomarker could be useful to identify patients at higher risk for recurrence and candidates for alternative treatment.

Comparison of two brain tumor-localizing MRI agent. GD-BOPTA and GD-DTPA. MRI and ICP study of rat brain tumor model

International Nuclear Information System (INIS)

Zhang, T.; Matsumura, A.; Yamamoto, T.; Yoshida, F.; Nose, T.

2000-01-01

In this study, we compared the behavior of Gd-BOPTA as a brain tumor selective contrast agent with Gd-DTPA in a common dose of 0.1 mmol/kg. We performed a MRI study using those two agent as contrast material, and we measured tissue Gd-concentrations by ICP-AES. As a result, Gd-BOPTA showed a better MRI enhancement in brain tumor. ICP showed significantly greater uptake of Gd-BOPTA in tumor samples, at all time course peaked at 5 minutes after administration, Gd being retained for a longer time in brain tumor till 2 hours, without rapid elimination as Gd-DTPA. We conclude that Gd-BOPTA is a new useful contrast material for MR imaging in brain tumor and an effective absorption agent for neutron capture therapy for further research. (author)

US-Cut: interactive algorithm for rapid detection and segmentation of liver tumors in ultrasound acquisitions

Science.gov (United States)

Egger, Jan; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Chen, Xiaojun; Zoller, Wolfram G.; Schmalstieg, Dieter; Hann, Alexander

2016-04-01

Ultrasound (US) is the most commonly used liver imaging modality worldwide. It plays an important role in follow-up of cancer patients with liver metastases. We present an interactive segmentation approach for liver tumors in US acquisitions. Due to the low image quality and the low contrast between the tumors and the surrounding tissue in US images, the segmentation is very challenging. Thus, the clinical practice still relies on manual measurement and outlining of the tumors in the US images. We target this problem by applying an interactive segmentation algorithm to the US data, allowing the user to get real-time feedback of the segmentation results. The algorithm has been developed and tested hand-in-hand by physicians and computer scientists to make sure a future practical usage in a clinical setting is feasible. To cover typical acquisitions from the clinical routine, the approach has been evaluated with dozens of datasets where the tumors are hyperechoic (brighter), hypoechoic (darker) or isoechoic (similar) in comparison to the surrounding liver tissue. Due to the interactive real-time behavior of the approach, it was possible even in difficult cases to find satisfying segmentations of the tumors within seconds and without parameter settings, and the average tumor deviation was only 1.4mm compared with manual measurements. However, the long term goal is to ease the volumetric acquisition of liver tumors in order to evaluate for treatment response. Additional aim is the registration of intraoperative US images via the interactive segmentations to the patient's pre-interventional CT acquisitions.

Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software.

Science.gov (United States)

Lee, Myungeun; Woo, Boyeong; Kuo, Michael D; Jamshidi, Neema; Kim, Jong Hyo

2017-01-01

The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC NDR ≥1), while above 35% of the texture features showed poor NDR (software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics.

Radionecrosis after radiotherapy for brain tumor

International Nuclear Information System (INIS)

Yoshii, Yoshihiko; Maki, Yutaka; Tosa, Junichi; Tsuboi, Koji; Matsumura, Akira

1984-01-01

The neurological deterioration after radiotherapy of brain tumor may depend on radionecrosis or regrowth of the tumor. In the present study, five patients with brain tumor were irradiated with doses of 3,900 to 6,800 rads. The neurological deterioration appeared 3.5 to 46 months after radiotherapy in three patients, who received 5,000 to 5,680 rads, immediately after radiotherapy in one patient, who received 6,800 rads, and during radiotherapy in one patient, who received 3,900 rads. Ring enhancement was observed on sequential CT scans. This enhanced area was surgically removed and the correlation between histology and CT scans and superimposed dose distributions was studied in order to differentiate radionecrosis from regrowth of tumor. The radionecrosis was confirmed at the second operation in five patients, but regrowth of the tumor was also observed in the brain adjacent to radionecrosis in three out of five patients. Coagulation necrosis and fibrinoid necrosis were observed microscopically at the rim of the ring enhancement and necrotic and hyalinized debri were observed in the central low density area of the ring enhancement. Viable tumor cells were noted in the enhanced area adjacent to the ring enhancement on CT scans. Both radionecrosis and regrowth of tumor were observed in the dose distribution area of 3,500 to 6,120 rads on CT scans. This suggested that the superimposed dose distributions could not differentiate radionecrosis from tumor regrowth. Forty-eight cases of cerebral radionecrosis gathered from the literature were reviewed. (J.P.N.)

Three-dimensional segmentation of the tumor mass in computed tomographic images of neuroblastoma

Science.gov (United States)

Deglint, Hanford J.; Rangayyan, Rangaraj M.; Boag, Graham S.

2004-05-01

Tumor definition and diagnosis require the analysis of the spatial distribution and Hounsfield unit (HU) values of voxels in computed tomography (CT) images, coupled with a knowledge of normal anatomy. Segmentation of the tumor in neuroblastoma is complicated by the fact that the mass is almost always heterogeneous in nature; furthermore, viable tumor, necrosis, fibrosis, and normal tissue are often intermixed. Rather than attempt to separate these tissue types into distinct regions, we propose to explore methods to delineate the normal structures expected in abdominal CT images, remove them from further consideration, and examine the remaining parts of the images for the tumor mass. We explore the use of fuzzy connectivity for this purpose. Expert knowledge provided by the radiologist in the form of the expected structures and their shapes, HU values, and radiological characteristics are also incorporated in the segmentation algorithm. Segmentation and analysis of the tissue composition of the tumor can assist in quantitative assessment of the response to chemotherapy and in the planning of delayed surgery for resection of the tumor. The performance of the algorithm is evaluated using cases acquired from the Alberta Children's Hospital.

Brain Tumor Database, a free relational database for collection and analysis of brain tumor patient information.

Science.gov (United States)

Bergamino, Maurizio; Hamilton, David J; Castelletti, Lara; Barletta, Laura; Castellan, Lucio

2015-03-01

In this study, we describe the development and utilization of a relational database designed to manage the clinical and radiological data of patients with brain tumors. The Brain Tumor Database was implemented using MySQL v.5.0, while the graphical user interface was created using PHP and HTML, thus making it easily accessible through a web browser. This web-based approach allows for multiple institutions to potentially access the database. The BT Database can record brain tumor patient information (e.g. clinical features, anatomical attributes, and radiological characteristics) and be used for clinical and research purposes. Analytic tools to automatically generate statistics and different plots are provided. The BT Database is a free and powerful user-friendly tool with a wide range of possible clinical and research applications in neurology and neurosurgery. The BT Database graphical user interface source code and manual are freely available at http://tumorsdatabase.altervista.org. © The Author(s) 2013.

Fast and robust multi-atlas segmentation of brain magnetic resonance images

DEFF Research Database (Denmark)

Lötjönen, Jyrki Mp; Wolz, Robin; Koikkalainen, Juha R

2010-01-01

We introduce an optimised pipeline for multi-atlas brain MRI segmentation. Both accuracy and speed of segmentation are considered. We study different similarity measures used in non-rigid registration. We show that intensity differences for intensity normalised images can be used instead of stand......We introduce an optimised pipeline for multi-atlas brain MRI segmentation. Both accuracy and speed of segmentation are considered. We study different similarity measures used in non-rigid registration. We show that intensity differences for intensity normalised images can be used instead...... of standard normalised mutual information in registration without compromising the accuracy but leading to threefold decrease in the computation time. We study and validate also different methods for atlas selection. Finally, we propose two new approaches for combining multi-atlas segmentation and intensity...

Clinical impact of anatomo-functional evaluation of brain function during brain tumor surgery

International Nuclear Information System (INIS)

Mikuni, Nobuhiro; Kikuchi, Takayuki; Matsumoto, Atsushi; Yokoyama, Yohei; Takahashi, Jun; Hashimoto, Nobuo

2009-01-01

To attempt to improve surgical outcome of brain surgery, clinical significance of anatomo-functional evaluation of brain function during resection of brain tumors was assessed. Seventy four patients with glioma located near eloquent areas underwent surgery while awake. Intraoperative tractography-integrated functional neuronavigation and cortical/subcortical electrical stimulation were correlated with clinical symptoms during and after resection of tumors. Cortical functional areas were safely removed with negative electric stimulation and eloquent cortices could be removed in some circumstances. Subcortical functional mapping was difficult except for motor function. Studying cortical functional compensation allows more extensive removal of brain tumors located in the eloquent areas. (author)

An Efficient Implementation of Deep Convolutional Neural Networks for MRI Segmentation.

Science.gov (United States)

Hoseini, Farnaz; Shahbahrami, Asadollah; Bayat, Peyman

2018-02-27

Image segmentation is one of the most common steps in digital image processing, classifying a digital image into different segments. The main goal of this paper is to segment brain tumors in magnetic resonance images (MRI) using deep learning. Tumors having different shapes, sizes, brightness and textures can appear anywhere in the brain. These complexities are the reasons to choose a high-capacity Deep Convolutional Neural Network (DCNN) containing more than one layer. The proposed DCNN contains two parts: architecture and learning algorithms. The architecture and the learning algorithms are used to design a network model and to optimize parameters for the network training phase, respectively. The architecture contains five convolutional layers, all using 3 × 3 kernels, and one fully connected layer. Due to the advantage of using small kernels with fold, it allows making the effect of larger kernels with smaller number of parameters and fewer computations. Using the Dice Similarity Coefficient metric, we report accuracy results on the BRATS 2016, brain tumor segmentation challenge dataset, for the complete, core, and enhancing regions as 0.90, 0.85, and 0.84 respectively. The learning algorithm includes the task-level parallelism. All the pixels of an MR image are classified using a patch-based approach for segmentation. We attain a good performance and the experimental results show that the proposed DCNN increases the segmentation accuracy compared to previous techniques.

Growth of Malignant Non-CNS Tumors Alters Brain Metabolome

Science.gov (United States)

Kovalchuk, Anna; Nersisyan, Lilit; Mandal, Rupasri; Wishart, David; Mancini, Maria; Sidransky, David; Kolb, Bryan; Kovalchuk, Olga

2018-01-01

Cancer survivors experience numerous treatment side effects that negatively affect their quality of life. Cognitive side effects are especially insidious, as they affect memory, cognition, and learning. Neurocognitive deficits occur prior to cancer treatment, arising even before cancer diagnosis, and we refer to them as “tumor brain.” Metabolomics is a new area of research that focuses on metabolome profiles and provides important mechanistic insights into various human diseases, including cancer, neurodegenerative diseases, and aging. Many neurological diseases and conditions affect metabolic processes in the brain. However, the tumor brain metabolome has never been analyzed. In our study we used direct flow injection/mass spectrometry (DI-MS) analysis to establish the effects of the growth of lung cancer, pancreatic cancer, and sarcoma on the brain metabolome of TumorGraft™ mice. We found that the growth of malignant non-CNS tumors impacted metabolic processes in the brain, affecting protein biosynthesis, and amino acid and sphingolipid metabolism. The observed metabolic changes were similar to those reported for neurodegenerative diseases and brain aging, and may have potential mechanistic value for future analysis of the tumor brain phenomenon. PMID:29515623

Selective targeting of brain tumors with gold nanoparticle-induced radiosensitization.

Directory of Open Access Journals (Sweden)

Daniel Y Joh

Full Text Available Successful treatment of brain tumors such as glioblastoma multiforme (GBM is limited in large part by the cumulative dose of Radiation Therapy (RT that can be safely given and the blood-brain barrier (BBB, which limits the delivery of systemic anticancer agents into tumor tissue. Consequently, the overall prognosis remains grim. Herein, we report our pilot studies in cell culture experiments and in an animal model of GBM in which RT is complemented by PEGylated-gold nanoparticles (GNPs. GNPs significantly increased cellular DNA damage inflicted by ionizing radiation in human GBM-derived cell lines and resulted in reduced clonogenic survival (with dose-enhancement ratio of ~1.3. Intriguingly, combined GNP and RT also resulted in markedly increased DNA damage to brain blood vessels. Follow-up in vitro experiments confirmed that the combination of GNP and RT resulted in considerably increased DNA damage in brain-derived endothelial cells. Finally, the combination of GNP and RT increased survival of mice with orthotopic GBM tumors. Prior treatment of mice with brain tumors resulted in increased extravasation and in-tumor deposition of GNP, suggesting that RT-induced BBB disruption can be leveraged to improve the tumor-tissue targeting of GNP and thus further optimize the radiosensitization of brain tumors by GNP. These exciting results together suggest that GNP may be usefully integrated into the RT treatment of brain tumors, with potential benefits resulting from increased tumor cell radiosensitization to preferential targeting of tumor-associated vasculature.

Fiber tracking for brain tumor

International Nuclear Information System (INIS)

Yamada, Kei; Nakamura, Hisao; Ito, Hirotoshi; Tanaka, Osamu; Kubota, Takao; Yuen, Sachiko; Kizu, Osamu; Nishimura, Tsunehiko

2003-01-01

The purpose of this study was to validate an innovative scanning method for patients diagnosed with brain tumors. Using a 1.5 Tesla whole body magnetic resonance (MR) imager, 23 patients with brain tumors were scanned. The recorded data points of the diffusion-tensor imaging (DTI) sequences were 128 x 37 with the parallel imaging technique. The parallel imaging technique was equivalent to a true resolution of 128 x 74. The scan parameters were repetition time (TR)=6000, echo time (TE)=88, 6 averaging with a b-value of 800 s/mm 2 . The total scan time for DTI was 4 minutes and 24 seconds. DTI scans and subsequent fiber tracking were successfully applied in all cases. All fiber tracts on the contralesional side were visualized in the expected locations. Fiber tracts on the lesional side had varying degrees of displacement, disruption, or a combination of displacement and disruption due to the tumor. Tract disruption resulted from direct tumor involvement, compression upon the tract, and vasogenic edema surrounding the tumor. This DTI method using a parallel imaging technique allows for clinically feasible fiber tracking that can be incorporated into a routine MR examination. (author)

Computerized tomographic evaluation of primary brain tumors

Energy Technology Data Exchange (ETDEWEB)

Choi, Jin Ok; Lee, Jong Soon; Jeon, Doo Sung; Kim, Hong Soo; Rhee, Hak Song [Presbyterian Mediacal center, Cheonju (Korea, Republic of); Kim, Jong Deok [Inje Medical College, Paik Hospital, Pusan (Korea, Republic of)

1985-10-15

In a study of primary brain tumors 104 cases having satisfactory clinical, operative and histological proofs were analyzed by computerized tomography at Presbyterian Medical Center from May, 1982 to April 1985. The results were as follows: 1. The male to female ratio of primary brain tumor was 54 : 46. 2. The 2nd decade group (26%) was the most prevalent age group, followed by the 5th decade (16.3%), 1st decade (14.4%) , 3rd decade (12.5%), 4th decade (11.5%), 6th decade (10.6%), 7th decade (8.7%) in that order. 3. The incidence of primary brain tumors was found to be: glioma 64 cases (61.6%) among the GM, the most frequent 17 cases (16.3%), followed by meningioma 12 cases (11.5%), pituitary adenoma 10 cases (9.6%), craniopharyngioma 6 cases (5.8%), pinealoma and germinoma 3 cases (2.9%) respectively, and dermoid cyst 2 cases (1.9%) in that order. 4. The location of the primary brain tumors were as follows: cb. hemisphere (49%) of these 24.5% in parietal region, 11.9% in temporal region, 9.7% in frontal region, 3.0% in occipital region: juxtasella area (16.3%), cerebellar hemisphere (8.7%), parapineal and intraventricle (7.7%) respectively, cerebello-pontine angle area (5.8%), vermis and 4th ventricular region (4.8%). 5. There were no remarkable differences in the findings of pre- and post-contrast CT scanning of primary brain tumors computed with others.

Usefulness of dynamic magnetic resonance imaging in brain tumors

International Nuclear Information System (INIS)

Joo, Yang Gu; Suh, Soo Jhi; Zeon, Seok Kil; Woo, Sung Ku; Kim, Hong; Kim, Jung Sik; Lee, Sung Moon; Lee, Hee Jung; Takahashi, Mutsumasa

1994-01-01

To investigate the usefulness of dynamic MR imaging in the differential diagnosis of brain tumors. Dynamic MR imaging was performed in 43 patients with histopathologically proved brain tumors. Serial images were sequentially obtained every 30 seconds for 3-5 minutes with use of spin-echo technique(TR 200msec/TE 15msec) after rapid injection of Gd-DTPA in a dose of 0.1mmol/kg body weight. Dynamics of contrast enhancement of the brain tumors were analyzed visually and by the sequential contrast enhancement ratio(CER). On the dynamic MR imaging, contrast enhancement pattern of the gliomas showed gradual increase in signal intensity(SI) till 180 seconds and usually had a longer time to peak of the CER. The SI of metastatic brain tumors increased steeply till 30 seconds and then rapidly or gradually decreased and the tumors had a shorter time to peak of the CER. Meningiomas showed a rapid ascent in SI till 30 to 60 seconds and then made a plateau or slight descent of the CER. Lymphomas and germinomas showed relatively rapid increase of SI till 30 seconds and usually had a longer time peak of the CER. Dynamic MR imaging with Gd-DTPA may lead to further information about the brain tumors as the sequential contrast enhancement pattern and CER parameters seem to be helpful in discriminating among the brain tumors

The fibrinolytic system facilitates tumor cell migration across the blood-brain barrier in experimental melanoma brain metastasis

International Nuclear Information System (INIS)

Perides, George; Zhuge, Yuzheng; Lin, Tina; Stins, Monique F; Bronson, Roderick T; Wu, Julian K

2006-01-01

Patients with metastatic tumors to the brain have a very poor prognosis. Increased metastatic potential has been associated with the fibrinolytic system. We investigated the role of the fibrinolytic enzyme plasmin in tumor cell migration across brain endothelial cells and growth of brain metastases in an experimental metastatic melanoma model. Metastatic tumors to the brain were established by direct injection into the striatum or by intracarotid injection of B16F10 mouse melanoma cells in C57Bl mice. The role of plasminogen in the ability of human melanoma cells to cross a human blood-brain barrier model was studied on a transwell system. Wild type mice treated with the plasmin inhibitor epsilon-aminocaproic acid (EACA) and plg -/- mice developed smaller tumors and survived longer than untreated wild type mice. Tumors metastasized to the brain of wild type mice treated with EACA and plg -/- less efficiently than in untreated wild type mice. No difference was observed in the tumor growth in any of the three groups of mice. Human melanoma cells were able to cross the human blood-brain barrier model in a plasmin dependent manner. Plasmin facilitates the development of tumor metastasis to the brain. Inhibition of the fibrinolytic system could be considered as means to prevent tumor metastasis to the brain

Differential diagnostic value of diffusion weighted imaging on brain abscess and necrotic or cystic brain tumors

International Nuclear Information System (INIS)

Zhang Xiaoya; Yin Jie; Wang Kunpeng; Zhang Jiandang; Liang Biling

2009-01-01

Objective: To investigate the value of diffusion weighted imaging (DWI)on brain abscess and necrotic or cystic brain tumors. Methods: 27 cases with brain abscesses and 33 cases with necrotic or cystic brain tumors (gliomas or metastases) were performed conventional MRI and DWI. Apparent diffusion coefficient (ADC) of region of interest (ROI) was measured and statistically tested. Sensitivity and specificity were calculated and compared with conventional MR and DWI. Results: Hyperintensity signal was seen on most brain abscesses. All necrotic or cystic brain tumors showed hypointensity signal on DWI. There was statistical significance on ADC of them. The sensitivity and specificity of conventional MRI was lower than that of DWI. Conclusion: DWI and ADC were useful in distinguishing brain abscessed from necrotic or cystic brain tumors, which was important in addition to conventional MRI. (authors)

Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

DEFF Research Database (Denmark)

Puonti, Oula; Van Leemput, Koen

2016-01-01

In this paper we propose a new generative model for simultaneous brain parcellation and white matter lesion segmentation from multi-contrast magnetic resonance images. The method combines an existing whole-brain segmentation technique with a novel spatial lesion model based on a convolutional...... restricted Boltzmann machine. Unlike current state-of-the-art lesion detection techniques based on discriminative modeling, the proposed method is not tuned to one specific scanner or imaging protocol, and simultaneously segments dozens of neuroanatomical structures. Experiments on a public benchmark dataset...... in multiple sclerosis indicate that the method’s lesion segmentation accuracy compares well to that of the current state-of-the-art in the field, while additionally providing robust whole-brain segmentations....

Irradiation effects on the tumor and adjacent tissues of brain tumor-bearing mice

International Nuclear Information System (INIS)

Yoshii, Yoshihiko; Maki, Yutaka; Tsunemoto, Hiroshi; Koike, Sachiko; Furukawa, Shigeo.

1979-01-01

C 3 H mice aged 56 - 70 days, weighing 27 - 37 g were used throughout this experiment. A transplantable fibrosarcoma arising spontaneously from C 3 H mice was used. For experiment, 10 4 tumor cells suspended in 0.025 ml of saline solution were injected into the cerebral hemisphere by a 26 gauge needle with a micrometer syringe under nembutal anesthesia. Whole brain irradiation was performed at 7 days after injection of the tumor cells and the radiation doses were 2,000 and 20,000 rads, respectively. The feature of x-rays were 200 kVp, 20 mA, 0.5 mm Cu + 0.5 mm Al filtration and TSD 20 cm. The dose-rate was 340 - 360 R/min. The articles of this study were as follows: a) Determination of LD 50 values for the mice, tumor-bearing in the brain or non-tumor-bearing; and b) Observation of clinical features and gross autopsy findings of the mice following irradiation. The LD 50 values for 2,000 rad irradiation in the tumor-bearing or non-tumor-bearing mice were 10.9 and 11.4 days, respectively. LD 50 values of 3.7 days and 4.3 days were the results for the tumor-bearing and non-tumor-bearing mice irradiated by 20,000 rad, respectively. On the other hand, the LD 50 value for the control group, i.e. non-irradiated mice, was 6.7 days. At postmortem examinations, gastrointestinal bleeding was observed frequently in mice bearing tumor in the brain. Whole brain irradiation is effective to prolong the life of tumor-bearing mice. However, in some instances, deaths have occurred earlier in tumor-bearing mice compared to the control group. (author)

Stereotactic irradiation for metastatic brain tumor

International Nuclear Information System (INIS)

Nomura, Ryutaro

2017-01-01

First, this paper reviewed the latest findings of stereotactic irradiation (STI) for metastatic brain tumors. Then, it described the results of randomized controlled trials for single or a few (2-4) metastasis in the following comparison tests: (1) comparison between whole brain radiotherapy (WBRT) alone group and (WBRT + STI) group, (2) comparison between STI alone group and (STI + WBRT) group, (3) comparison between STI alone group and (tumorectomy + WBRT) group, (4) comparison between (STI + WBRT) group and (tumorectomy + WBRT) group, and (5) between (tumorectomy + WBRT) group and (tumorectomy + STI) group. Among these, STI alone without WBRT has obtained a certain consensus. Against multiple metastatic brain tumors of 5 or more, when considering cognitive impairment and QOL loss by adding WBRT, it is general consensus that STI alone may be sufficient. At the authors' institution, cyber knife (CK) was introduced in 2008 and nearly 300 stereotactic radiotherapy for metastatic brain tumors have been performed annually. By adopting a robot arm and development of a lesion tracking system, the positional correction against the deviation of the bone margin of the skull is guaranteed in real time to ensure accuracy during irradiation, and hypofractionated stereotactic irradiation becomes easier. (A.O.)

Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

Science.gov (United States)

Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

2014-01-01

The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

Automatic Lung Tumor Segmentation on PET/CT Images Using Fuzzy Markov Random Field Model

Directory of Open Access Journals (Sweden)

Yu Guo

2014-01-01

Full Text Available The combination of positron emission tomography (PET and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice’s similarity coefficient (DSC was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

Functional imaging for brain tumors (perfusion, DTI and MR spectroscopy)

International Nuclear Information System (INIS)

Essig, M.; Giesel, F.; Stieltjes, B.; Weber, M.A.

2007-01-01

This contribution considers the possibilities involved with using functional methods in magnetic resonance imaging (MRI) diagnostics for brain tumors. Of the functional methods available, we discuss perfusion MRI (PWI), diffusion MRI (DWI and DTI) and MR spectroscopy (H-MRS). In cases of brain tumor, PWI aids in grading and better differentiation in diagnostics as well as for pre-therapeutic planning. In addition, the course of treatment, both after chemo- as well as radiotherapy in combination with surgical treatment, can be optimized. PWI allows better estimates of biological activity and aggressiveness in low grade brain tumors, and in the case of WHO grade II astrocytoma showing anaplastically transformed tumor areas, allows more rapid visualization and a better prediction of the course of the disease than conventional MRI diagnostics. Diffusion MRI, due to the directional dependence of the diffusion, can illustrate the course and direction of the nerve fibers, as well as reconstructing the nerve tracts in the cerebrum, pons and cerebellum 3-dimensionally. Diffusion imaging can be used for describing brain tumors, for evaluating contralateral involvement and the course of the nerve fibers near the tumor. Due to its operator dependence, DTI based fiber tracking for defining risk structures is controversial. DWI can also not differentiate accurately between cystic and necrotic brain tumors, or between metastases and brain abscesses. H-MRS provides information on cell membrane metabolism, neuronal integrity and the function of neuronal structures, energy metabolism and the formation of tumors and brain tissue necroses. Diagnostic problems such as the differentiation between neoplastic and non-neoplastic lesions, grading cerebral glioma and distinguishing between primary brain tumors and metastases can be resolved. An additional contribution will discuss the control of the course of glial tumors after radiotherapy. (orig.)

Cathepsin D and Its Prognostic Value in Neuroepithelial Brain Tumors

OpenAIRE

Pigac, Biserka; Dmitrović, Branko; Marić, Svjetlana; Mašić, Silvija

2012-01-01

Expression of Cathepsin D (Cath D) in some primary neuroepithelial brain tumors and its prognostic value were studied. The research included 65 samples of human primary neuroepithelial brain tumors. There were 50 glial tumors (10 diffuse astrocytomas (DA), 15 anaplastic astrocytomas (AA), 25 glioblastomas (GB), 15 embryonic tumors (15 medulloblastomas (MB) as well as 5 samples of normal brain tissue. Immunohistochemical method was applied to monitor diffuse positive reaction in the cytoplasm ...

Three-dimensional lung tumor segmentation from x-ray computed tomography using sparse field active models.

Science.gov (United States)

Awad, Joseph; Owrangi, Amir; Villemaire, Lauren; O'Riordan, Elaine; Parraga, Grace; Fenster, Aaron

2012-02-01

Manual segmentation of lung tumors is observer dependent and time-consuming but an important component of radiology and radiation oncology workflow. The objective of this study was to generate an automated lung tumor measurement tool for segmentation of pulmonary metastatic tumors from x-ray computed tomography (CT) images to improve reproducibility and decrease the time required to segment tumor boundaries. The authors developed an automated lung tumor segmentation algorithm for volumetric image analysis of chest CT images using shape constrained Otsu multithresholding (SCOMT) and sparse field active surface (SFAS) algorithms. The observer was required to select the tumor center and the SCOMT algorithm subsequently created an initial surface that was deformed using level set SFAS to minimize the total energy consisting of mean separation, edge, partial volume, rolling, distribution, background, shape, volume, smoothness, and curvature energies. The proposed segmentation algorithm was compared to manual segmentation whereby 21 tumors were evaluated using one-dimensional (1D) response evaluation criteria in solid tumors (RECIST), two-dimensional (2D) World Health Organization (WHO), and 3D volume measurements. Linear regression goodness-of-fit measures (r(2) = 0.63, p < 0.0001; r(2) = 0.87, p < 0.0001; and r(2) = 0.96, p < 0.0001), and Pearson correlation coefficients (r = 0.79, p < 0.0001; r = 0.93, p < 0.0001; and r = 0.98, p < 0.0001) for 1D, 2D, and 3D measurements, respectively, showed significant correlations between manual and algorithm results. Intra-observer intraclass correlation coefficients (ICC) demonstrated high reproducibility for algorithm (0.989-0.995, 0.996-0.997, and 0.999-0.999) and manual measurements (0.975-0.993, 0.985-0.993, and 0.980-0.992) for 1D, 2D, and 3D measurements, respectively. The intra-observer coefficient of variation (CV%) was low for algorithm (3.09%-4.67%, 4.85%-5.84%, and 5

Automated fetal brain segmentation from 2D MRI slices for motion correction.

Science.gov (United States)

Keraudren, K; Kuklisova-Murgasova, M; Kyriakopoulou, V; Malamateniou, C; Rutherford, M A; Kainz, B; Hajnal, J V; Rueckert, D

2014-11-01

Motion correction is a key element for imaging the fetal brain in-utero using Magnetic Resonance Imaging (MRI). Maternal breathing can introduce motion, but a larger effect is frequently due to fetal movement within the womb. Consequently, imaging is frequently performed slice-by-slice using single shot techniques, which are then combined into volumetric images using slice-to-volume reconstruction methods (SVR). For successful SVR, a key preprocessing step is to isolate fetal brain tissues from maternal anatomy before correcting for the motion of the fetal head. This has hitherto been a manual or semi-automatic procedure. We propose an automatic method to localize and segment the brain of the fetus when the image data is acquired as stacks of 2D slices with anatomy misaligned due to fetal motion. We combine this segmentation process with a robust motion correction method, enabling the segmentation to be refined as the reconstruction proceeds. The fetal brain localization process uses Maximally Stable Extremal Regions (MSER), which are classified using a Bag-of-Words model with Scale-Invariant Feature Transform (SIFT) features. The segmentation process is a patch-based propagation of the MSER regions selected during detection, combined with a Conditional Random Field (CRF). The gestational age (GA) is used to incorporate prior knowledge about the size and volume of the fetal brain into the detection and segmentation process. The method was tested in a ten-fold cross-validation experiment on 66 datasets of healthy fetuses whose GA ranged from 22 to 39 weeks. In 85% of the tested cases, our proposed method produced a motion corrected volume of a relevant quality for clinical diagnosis, thus removing the need for manually delineating the contours of the brain before motion correction. Our method automatically generated as a side-product a segmentation of the reconstructed fetal brain with a mean Dice score of 93%, which can be used for further processing. Copyright �

Study of perifocal low-density area in metastatic brain tumor

Energy Technology Data Exchange (ETDEWEB)

Suzuki, R; Okada, K; Hiratsuka, H; Inaba, Y [Tokyo Medical and Dental Univ. (Japan). School of Medicine; Tsuyumu, M

1980-04-01

It is well known that vasogenic brain edema often develops in brain tumors, head injuries, and inflammatory brain lesions. In order to investigate the development and resolution of vasogenic brain edema, some CT findings of metastatic brain tumors were studied in detail. 20 cases of metastatic brain tumors of the past three years were examined by means of a CT scan. In almost all the cases there was a perifocal low-density area (PFL) in the CT findings. In the tumors which were cystic and/or located in the infratentorial space, PFL was not present or, if present, only slightly so. On the contrary, in the tumors which were nodular and/or in the supratentorial space, PFL was present extensively. In the supratentorial metastasis, PFL seemed to be restricted within the white matter and not to involve the gray matter nor such midline structures as basal ganglia and corpus callosum. Besides, PFL was always in contact with the lateral ventricular wall. These results show that PFL in the metastatic tumors resembles in shape the experimental cold-induced brain edema in cats. PFL is presumed to represent vasogenic brain edema; these findings support the hypothesis that the main mechanism of the resolution of vasogenic brain edema is the drainage of the edema fluid into the ventricular CSF.

Interphone study - on mobile phones and brain tumors

International Nuclear Information System (INIS)

2010-01-01

Interphone study is the largest study on mobile phone use and risk of brain tumors that have been implemented. The study does not provide reliable answers to whether there is an increased risk of brain tumors using the mobile phone, but is an important contribution. (AG)

Proton MRS imaging in pediatric brain tumors

Energy Technology Data Exchange (ETDEWEB)

Zarifi, Maria [Aghia Sophia Children' s Hospital, Department of Radiology, Athens (Greece); Tzika, A.A. [Harvard Medical School, Department of Surgery, Massachusetts General Hospital, Boston, MA (United States); Shriners Burn Hospital, Boston, MA (United States)

2016-06-15

Magnetic resonance (MR) techniques offer a noninvasive, non-irradiating yet sensitive approach to diagnosing and monitoring pediatric brain tumors. Proton MR spectroscopy (MRS), as an adjunct to MRI, is being more widely applied to monitor the metabolic aspects of brain cancer. In vivo MRS biomarkers represent a promising advance and may influence treatment choice at both initial diagnosis and follow-up, given the inherent difficulties of sequential biopsies to monitor therapeutic response. When combined with anatomical or other types of imaging, MRS provides unique information regarding biochemistry in inoperable brain tumors and can complement neuropathological data, guide biopsies and enhance insight into therapeutic options. The combination of noninvasively acquired prognostic information and the high-resolution anatomical imaging provided by conventional MRI is expected to surpass molecular analysis and DNA microarray gene profiling, both of which, although promising, depend on invasive biopsy. This review focuses on recent data in the field of MRS in children with brain tumors. (orig.)

Assessing the scale of tumor heterogeneity by complete hierarchical segmentation of MRI

International Nuclear Information System (INIS)

Gensheimer, Michael F; Ermoian, Ralph P; Hawkins, Douglas S; Trister, Andrew D

2015-01-01

In many cancers, intratumoral heterogeneity has been found in histology, genetic variation and vascular structure. We developed an algorithm to interrogate different scales of heterogeneity using clinical imaging. We hypothesize that heterogeneity of perfusion at coarse scale may correlate with treatment resistance and propensity for disease recurrence. The algorithm recursively segments the tumor image into increasingly smaller regions. Each dividing line is chosen so as to maximize signal intensity difference between the two regions. This process continues until the tumor has been divided into single voxels, resulting in segments at multiple scales. For each scale, heterogeneity is measured by comparing each segmented region to the adjacent region and calculating the difference in signal intensity histograms. Using digital phantom images, we showed that the algorithm is robust to image artifacts and various tumor shapes. We then measured the primary tumor scales of contrast enhancement heterogeneity in MRI of 18 rhabdomyosarcoma patients. Using Cox proportional hazards regression, we explored the influence of heterogeneity parameters on relapse-free survival. Coarser scale of maximum signal intensity heterogeneity was prognostic of shorter survival (p = 0.05). By contrast, two fractal parameters and three Haralick texture features were not prognostic. In summary, our algorithm produces a biologically motivated segmentation of tumor regions and reports the amount of heterogeneity at various distance scales. If validated on a larger dataset, this prognostic imaging biomarker could be useful to identify patients at higher risk for recurrence and candidates for alternative treatment. (paper)

Prediction of tumor-brain adhesion in intracranial meningiomas by MR imaging and DSA

International Nuclear Information System (INIS)

Takeguchi, Takashi; Miki, Hitoshi; Shimizu, Teruhiko; Kikuchi, Keiichi; Mochizuki, Teruhito; Ohue, Shiro; Ohnishi, Takanori

2003-01-01

The purpose of this study was to evaluate the usefulness of MRI (magnetic resonance imaging) and DSA (digital subtraction angiography) by using preoperative MRI and DSA findings in the examination of meningiomas before excision. In particular, we focused on their usefulness in predicting tumor-brain adhesion during surgery. The subjects were 36 patients with intracranial meningioma who underwent tumor excision at which time neurosurgeons examined the tumor-brain adhesion. Two neurosurgeons evaluated the degree of tumor-brain adhesion from operation records and videotapes recorded during surgery. Two neuroradiologists retrospectively evaluated the preoperative MRI findings including tumor diameter, signal intensity of the tumor parenchyma obtained with T 2 -weighted imaging (T 2 WI), characteristics of the tumor-brain interface, and degree of peritumoral brain edema. The vascular supply was also evaluated from the preoperative DSA findings. The relationship between these MRI and DSA findings and the degree of tumor-brain adhesion during surgery as classified by the neurosurgeons was statistically analyzed. The degree of peritumoral brain edema and the shapes and characteristics of the tumor-brain interface, including the findings of FLAIR (fluid-attenuated inversion recovery) imaging and vascular supply observed by DSA, were significantly correlated with tumor-brain adhesion. In particular, the shapes and characteristics of the tumor-brain interface as observed by T 1 -weighted imaging (T 1 WI), T2WI, and FLAIR, respectively, as well as the vascular supply observed by DSA, were closely correlated with the degree of tumor-brain adhesion encountered during surgery. According to these results, we developed a method of predicting tumor-brain adhesion that considers the shape of the tumor-brain interface revealed by MRI and the vascular supply revealed by DSA. We retrospectively examined the findings of MRI and DSA performed before excision of meningioma and clarified

4D segmentation of brain MR images with constrained cortical thickness variation.

Directory of Open Access Journals (Sweden)

Li Wang

Full Text Available Segmentation of brain MR images plays an important role in longitudinal investigation of developmental, aging, disease progression changes in the cerebral cortex. However, most existing brain segmentation methods consider multiple time-point images individually and thus cannot achieve longitudinal consistency. For example, cortical thickness measured from the segmented image will contain unnecessary temporal variations, which will affect the time related change pattern and eventually reduce the statistical power of analysis. In this paper, we propose a 4D segmentation framework for the adult brain MR images with the constraint of cortical thickness variations. Specifically, we utilize local intensity information to address the intensity inhomogeneity, spatial cortical thickness constraint to maintain the cortical thickness being within a reasonable range, and temporal cortical thickness variation constraint in neighboring time-points to suppress the artificial variations. The proposed method has been tested on BLSA dataset and ADNI dataset with promising results. Both qualitative and quantitative experimental results demonstrate the advantage of the proposed method, in comparison to other state-of-the-art 4D segmentation methods.

Pediatric brain tumors of neuroepithelial tissue

International Nuclear Information System (INIS)

Papanagiotou, P.; Politi, M.; Bergmann, M.; Pekrun, A.; Juergens, K.U.

2014-01-01

Tumors of neuroepithelial tissue represent the largest group of pediatric brain tumors by far and has therefore been divided into several discrete tumor subtypes each corresponding to a specific component of the neuropil. The neuropil contains several subtypes of glial cells, including astrocytes, oligodendrocytes, ependymal cells and modified ependymal cells that form the choroid plexus. This review discusses the imaging aspects of the most common pediatric tumors of neuroepithelial tissue. (orig.) [de

Adaptive region-growing with maximum curvature strategy for tumor segmentation in 18F-FDG PET

Science.gov (United States)

Tan, Shan; Li, Laquan; Choi, Wookjin; Kang, Min Kyu; D'Souza, Warren D.; Lu, Wei

2017-07-01

Accurate tumor segmentation in PET is crucial in many oncology applications. We developed an adaptive region-growing (ARG) algorithm with a maximum curvature strategy (ARG_MC) for tumor segmentation in PET. The ARG_MC repeatedly applied a confidence connected region-growing algorithm with increasing relaxing factor f. The optimal relaxing factor (ORF) was then determined at the transition point on the f-volume curve, where the volume just grew from the tumor into the surrounding normal tissues. The ARG_MC along with five widely used algorithms were tested on a phantom with 6 spheres at different signal to background ratios and on two clinic datasets including 20 patients with esophageal cancer and 11 patients with non-Hodgkin lymphoma (NHL). The ARG_MC did not require any phantom calibration or any a priori knowledge of the tumor or PET scanner. The identified ORF varied with tumor types (mean ORF  =  9.61, 3.78 and 2.55 respectively for the phantom, esophageal cancer, and NHL datasets), and varied from one tumor to another. For the phantom, the ARG_MC ranked the second in segmentation accuracy with an average Dice similarity index (DSI) of 0.86, only slightly worse than Daisne’s adaptive thresholding method (DSI  =  0.87), which required phantom calibration. For both the esophageal cancer dataset and the NHL dataset, the ARG_MC had the highest accuracy with an average DSI of 0.87 and 0.84, respectively. The ARG_MC was robust to parameter settings and region of interest selection, and it did not depend on scanners, imaging protocols, or tumor types. Furthermore, the ARG_MC made no assumption about the tumor size or tumor uptake distribution, making it suitable for segmenting tumors with heterogeneous FDG uptake. In conclusion, the ARG_MC was accurate, robust and easy to use, it provides a highly potential tool for PET tumor segmentation in clinic.

Quality of radiomic features in glioblastoma multiforme: Impact of semi-automated tumor segmentation software

International Nuclear Information System (INIS)

Lee, Myung Eun; Kim, Jong Hyo; Woo, Bo Yeong; Ko, Micheal D.; Jamshidi, Neema

2017-01-01

The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant. The use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics

Histopathological studies on the irradiated brain tumors

International Nuclear Information System (INIS)

Narita, Tadao

1980-01-01

Of 43 cases of irradiated brain tumor, histological findings showed extensive necrosis or disappearance of the neoplasm, considered to be attributable to radiation treatment, in 30 (70%). Extensive necrosis of the tumor in areas exposed to radiation was found in 16 treated cases (37.2%). The histopathology of massive necrosis was that of simple coagulative necrosis, sometimes with marked vascular alterations and extravasation of fibrinoid material into the necrotic tissue. Necrosis was almost always incomplete, and foci of residual tumors were found at the periphery of the tumors. The terminal picture in cases of massive necrosis was often that of widespread intra- and extracranial metastasis. Almost complete disappearance of the tumor was observed in some cases with subsequent diffuse degenerative changes in the brain parenchyma exposed to radiation. In 5 cases of irradiated tumors, autopsy findings suggested that the growth of the primary tumor might have been restricted. And in 5 cases tumor cytology revealed the marked presence of a large number of multinucleated, bizarre giant cells with evidence of degeneration in both the cytoplasm and the nucleus. Multifocal necrosis of the brain, with axonal swelling and sponginess of the tissue, was observed in two patients following combined radiation and antineoplastic chemotherapy. Diffuse loss and degeneration of nerve cells of the cerebral cortex in pseudo-laminar fashion was observed in 7 patients with or without bilateral necrosis of the globus pallidus. Histological findings revealed typical anoxic encephalopathy. (J.P.N.)

Histopathological studies on the irradiated brain tumors

Energy Technology Data Exchange (ETDEWEB)

Narita, T [Gunma Univ., Maebashi (Japan).School of Medicine

1980-01-01

Of 43 cases of irradiated brain tumor, histological findings showed extensive necrosis or disappearance of the neoplasm, considered to be attributable to radiation treatment, in 30 (70%). Extensive necrosis of the tumor in areas exposed to radiation was found in 16 treated cases (37.2%). The histopathology of massive necrosis was that of simple coagulative necrosis, sometimes with marked vascular alterations and extravasation of fibrinoid material into the necrotic tissue. Necrosis was almost always incomplete, and foci of residual tumors were found at the periphery of the tumors. The terminal picture in cases of massive necrosis was often that of widespread intra- and extracranial metastasis. Almost complete disappearance of the tumor was observed in some cases with subsequent diffuse degenerative changes in the brain parenchyma exposed to radiation. In 5 cases of irradiated tumors, autopsy findings suggested that the growth of the primary tumor might have been restricted. And in 5 cases tumor cytology revealed the marked presence of a large number of multinucleated, bizarre giant cells with evidence of degeneration in both the cytoplasm and the nucleus. Multifocal necrosis of the brain, with axonal swelling and sponginess of the tissue, was observed in two patients following combined radiation and antineoplastic chemotherapy. Diffuse loss and degeneration of nerve cells of the cerebral cortex in pseudo-laminar fashion was observed in 7 patients with or without bilateral necrosis of the globus pallidus. Histological findings revealed typical anoxic encephalopathy.

Brain Tumor Trials Collaborative | Center for Cancer Research

Science.gov (United States)

Brain Tumor Trials Collaborative In Pursuit of a Cure The mission of the BTTC is to develop and perform state-of-the-art clinical trials in a collaborative and collegial environment, advancing treatments for patients with brain tumors, merging good scientific method with concern for patient well-being and outcome.

Beyond Survival - Cognition after Pediatric Brain Tumor

OpenAIRE

Tonning Olsson, Ingrid

2015-01-01

Background: Pediatric Brain Tumor (PBT) survivors suffer from cognitive sequelae, especially within the areas of cognitive tempo, attention, executive function and memory. The cognitive difficulties are often accentuated over the years, but knowledge about the long term trajectory is still scarce. Aim: The aim of this thesis was to examine cognitive sequelae after Pediatric Brain Tumor (PBT); risk factors, common difficulties, development and neuroimaging correlates. Methods: In study...

heuristically improved bayesian segmentation of brain mr images

African Journals Online (AJOL)

Brainweb as a simulated brain MRI dataset is used in evaluating the proposed algorithm. ..... neighboring system can improve the segmentation power of the algorithm. ... tuning and learning of fuzzy knowledge bases, World Scientific. Pub Co ...

Therapy of malignant brain tumors

International Nuclear Information System (INIS)

Jellinger, K.

1987-01-01

The tumors of the brain claim for a separate position in scientific medicine regarding biology, morphology, features of clinical manifestation, diagnostics and therapy. During the past years due to rapid progress in medical biotechnics the situation of the neuroclinician in front of brain tumors has been dramatically changed. The prerequisites for early and accurate diagnosis as well as for successful treatment also of malignant neoplasms have increased and remarkably improved. At the same time the information necessary for an appropriate pragmatic use of the available cognitive methods and therapeutic means increased along the same scale. These facts necessitate the preparation of publications in which the state of the art is presented in possible completeness, systematic order and proper dis-posability for rational management and therapeutic strategies. The primary aim of the present book is to serve these purposes. With 8 chapters, two of them are indexed for INIS, the collective of competent authors deal on the biology, pathology and immunology of malignant brain tumors of adults and of children including relevant basic and recent data of experimental research; further on the available methods of therapy: neurosurgery, radiology and chemotherapy, the fundamental principals of their efficacy and the differing models of single respective combined application, in comprehensive critical form. 111 figs

Therapy of malignant brain tumors

Energy Technology Data Exchange (ETDEWEB)

Jellinger, K [ed.

1987-01-01

The tumors of the brain claim for a separate position in scientific medicine regarding biology, morphology, features of clinical manifestation, diagnostics and therapy. During the past years due to rapid progress in medical biotechnics the situation of the neuroclinician in front of brain tumors has been dramatically changed. The prerequisites for early and accurate diagnosis as well as for successful treatment also of malignant neoplasms have increased and remarkably improved. At the same time the information necessary for an appropriate pragmatic use of the available cognitive methods and therapeutic means increased along the same scale. These facts necessitate the preparation of publications in which the state of the art is presented in possible completeness, systematic order and proper dis-posability for rational management and therapeutic strategies. The primary aim of the present book is to serve these purposes. With 8 chapters, two of them are indexed for INIS, the collective of competent authors deal on the biology, pathology and immunology of malignant brain tumors of adults and of children including relevant basic and recent data of experimental research; further on the available methods of therapy: neurosurgery, radiology and chemotherapy, the fundamental principals of their efficacy and the differing models of single respective combined application, in comprehensive critical form. 111 figs.

Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains.

Science.gov (United States)

Bricq, S; Collet, Ch; Armspach, J P

2008-12-01

In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images is of interest for many brain disorders. However, due to several factors such as noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue classification remains a challenging task. In this paper, we present a unifying framework for unsupervised segmentation of multimodal brain MR images including partial volume effect, bias field correction, and information given by a probabilistic atlas. Here-proposed method takes into account neighborhood information using a Hidden Markov Chain (HMC) model. Due to the limited resolution of imaging devices, voxels may be composed of a mixture of different tissue types, this partial volume effect is included to achieve an accurate segmentation of brain tissues. Instead of assigning each voxel to a single tissue class (i.e., hard classification), we compute the relative amount of each pure tissue class in each voxel (mixture estimation). Further, a bias field estimation step is added to the proposed algorithm to correct intensity inhomogeneities. Furthermore, atlas priors were incorporated using probabilistic brain atlas containing prior expectations about the spatial localization of different tissue classes. This atlas is considered as a complementary sensor and the proposed method is extended to multimodal brain MRI without any user-tunable parameter (unsupervised algorithm). To validate this new unifying framework, we present experimental results on both synthetic and real brain images, for which the ground truth is available. Comparison with other often used techniques demonstrates the accuracy and the robustness of this new Markovian segmentation scheme.

Segmentation of corpus callosum using diffusion tensor imaging: validation in patients with glioblastoma

International Nuclear Information System (INIS)

Nazem-Zadeh, Mohammad-Reza; Saksena, Sona; Babajani-Fermi, Abbas; Jiang, Quan; Soltanian-Zadeh, Hamid; Rosenblum, Mark; Mikkelsen, Tom; Jain, Rajan

2012-01-01

This paper presents a three-dimensional (3D) method for segmenting corpus callosum in normal subjects and brain cancer patients with glioblastoma. Nineteen patients with histologically confirmed treatment naïve glioblastoma and eleven normal control subjects underwent DTI on a 3T scanner. Based on the information inherent in diffusion tensors, a similarity measure was proposed and used in the proposed algorithm. In this algorithm, diffusion pattern of corpus callosum was used as prior information. Subsequently, corpus callosum was automatically divided into Witelson subdivisions. We simulated the potential rotation of corpus callosum under tumor pressure and studied the reproducibility of the proposed segmentation method in such cases. Dice coefficients, estimated to compare automatic and manual segmentation results for Witelson subdivisions, ranged from 94% to 98% for control subjects and from 81% to 95% for tumor patients, illustrating closeness of automatic and manual segmentations. Studying the effect of corpus callosum rotation by different Euler angles showed that although segmentation results were more sensitive to azimuth and elevation than skew, rotations caused by brain tumors do not have major effects on the segmentation results. The proposed method and similarity measure segment corpus callosum by propagating a hyper-surface inside the structure (resulting in high sensitivity), without penetrating into neighboring fiber bundles (resulting in high specificity)

Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose–volume histograms

International Nuclear Information System (INIS)

Conson, Manuel; Cella, Laura; Pacelli, Roberto; Comerci, Marco; Liuzzi, Raffaele; Salvatore, Marco; Quarantelli, Mario

2014-01-01

Purpose: To implement and evaluate a magnetic resonance imaging atlas-based automated segmentation (MRI-ABAS) procedure for cortical and sub-cortical grey matter areas definition, suitable for dose-distribution analyses in brain tumor patients undergoing radiotherapy (RT). Patients and methods: 3T-MRI scans performed before RT in ten brain tumor patients were used. The MRI-ABAS procedure consists of grey matter classification and atlas-based regions of interest definition. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm was applied to structures manually delineated by four experts to generate the standard reference. Performance was assessed comparing multiple geometrical metrics (including Dice Similarity Coefficient – DSC). Dosimetric parameters from dose–volume-histograms were also generated and compared. Results: Compared with manual delineation, MRI-ABAS showed excellent reproducibility [median DSC ABAS = 1 (95% CI, 0.97–1.0) vs. DSC MANUAL = 0.90 (0.73–0.98)], acceptable accuracy [DSC ABAS = 0.81 (0.68–0.94) vs. DSC MANUAL = 0.90 (0.76–0.98)], and an overall 90% reduction in delineation time. Dosimetric parameters obtained using MRI-ABAS were comparable with those obtained by manual contouring. Conclusions: The speed, reproducibility, and robustness of the process make MRI-ABAS a valuable tool for investigating radiation dose–volume effects in non-target brain structures providing additional standardized data without additional time-consuming procedures

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

Directory of Open Access Journals (Sweden)

Yan Liu

Full Text Available Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS treatment planning. In this work, we developed a deep learning convolutional neural network (CNN algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.

Radionuclidr diagnosis of brain tumors, brain inflammatory and traumatic lesions

International Nuclear Information System (INIS)

Badmaev, K.N.; Mel'kishev, V.F.; Dement'ev, E.V.; Svetlova, N.L.

1982-01-01

A complex of problems of radionuclide diagnosis of central nervous system diseases including tumors, traumas, vascular lessons, inflammatory processes is considered. The principles, technique and results of radionuclide xintigraphy of a tumor, depending on its localization are given. Radioindication of brain tumours in the operation is given

Quality of radiomic features in glioblastoma multiforme: Impact of semi-automated tumor segmentation software

Energy Technology Data Exchange (ETDEWEB)

Lee, Myung Eun; Kim, Jong Hyo [Center for Medical-IT Convergence Technology Research, Advanced Institutes of Convergence Technology, Seoul National University, Suwon (Korea, Republic of); Woo, Bo Yeong [Dept. of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Suwon (Korea, Republic of); Ko, Micheal D.; Jamshidi, Neema [Dept. of Radiological Sciences, University of California, Los Angeles, Los Angeles (United States)

2017-06-15

The purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software. MR images of 45 GBM patients (29 males, 16 females) were downloaded from The Cancer Imaging Archive, in which post-contrast T1-weighted imaging and fluid-attenuated inversion recovery MR sequences were used. Two raters independently segmented the tumors using two semi-automated segmentation tools (TumorPrism3D and 3D Slicer). Regions of interest corresponding to contrast-enhancing lesion, necrotic portions, and non-enhancing T2 high signal intensity component were segmented for each tumor. A total of 180 imaging features were extracted, and their quality was evaluated in terms of stability, normalized dynamic range (NDR), and redundancy, using intra-class correlation coefficients, cluster consensus, and Rand Statistic. Our study results showed that most of the radiomic features in GBM were highly stable. Over 90% of 180 features showed good stability (intra-class correlation coefficient [ICC] ≥ 0.8), whereas only 7 features were of poor stability (ICC < 0.5). Most first order statistics and morphometric features showed moderate-to-high NDR (4 > NDR ≥1), while above 35% of the texture features showed poor NDR (< 1). Features were shown to cluster into only 5 groups, indicating that they were highly redundant. The use of semi-automated software tools provided sufficiently reliable tumor segmentation and feature stability; thus helping to overcome the inherent inter-rater and intra-rater variability of user intervention. However, certain aspects of feature quality, including NDR and redundancy, need to be assessed for determination of representative signature features before further development of radiomics.

Orotracheal administration of contrast agents: a new protocol for brain tumor targeting.

Science.gov (United States)

Bianchi, Andrea; Moncelet, Damien; Lux, François; Plissonneau, Marie; Rizzitelli, Silvia; Ribot, Emeline Julie; Tassali, Nawal; Bouchaud, Véronique; Tillement, Olivier; Voisin, Pierre; Crémillieux, Yannick

2015-06-01

The development of new non-invasive diagnostic and therapeutic approaches is of paramount importance in order to improve the outcome of patients with glioblastoma (GBM). In this work we investigated a completely non-invasive pre-clinical protocol to effectively target and detect brain tumors through the orotracheal route, using ultra-small nanoparticles (USRPs) and MRI. A mouse model of GBM was developed. In vivo MRI acquisitions were performed before and after intravenous or orotracheal administration of the nanoparticles to identify and segment the tumor. The accumulation of the nanoparticles in neoplastic lesions was assessed ex vivo through fluorescence microscopy. Before the administration of contrast agents, MR images allowed the identification of the presence of abnormal brain tissue in 73% of animals. After orotracheal or intravenous administration of USRPs, in all the mice an excellent co-localization of the position of the tumor with MRI and histology was observed. The elimination time of the USRPs from the tumor after the orotracheal administration was approximately 70% longer compared with intravenous injection. MRI and USRPs were shown to be powerful imaging tools able to detect, quantify and longitudinally monitor the development of GBMs. The absence of ionizing radiation and high resolution of MRI, along with the complete non-invasiveness and good reproducibility of the proposed protocol, make this technique potentially translatable to humans. To our knowledge, this is the first time that the advantages of a needle-free orotracheal administration route have been demonstrated for the investigation of the pathomorphological changes due to GBMs. Copyright © 2015 John Wiley & Sons, Ltd.

Imaging of brain tumors with histological correlations. 2. ed.

Energy Technology Data Exchange (ETDEWEB)

Drevelegas, Antonios (ed.)

2011-07-01

This volume provides a deeper understanding of the diagnosis of brain tumors by correlating radiographic imaging features with the underlying pathological abnormalities. All modern imaging modalities are used to complete a diagnostic overview of brain tumors with emphasis on recent advances in diagnostic neuroradiology. High-quality illustrations depicting common and uncommon imaging characteristics of a wide range of brain tumors are presented and analysed, drawing attention to the ways in which these characteristics reflect different aspects of pathology. Important theoretical considerations are also discussed. Since the first edition, chapters have been revised and updated and new material has been added, including detailed information on the clinical application of functional MRI and diffusion tensor imaging. Radiologists and other clinicians interested in the current diagnostic approach to brain tumors will find this book to be an invaluable and enlightening clinical tool. (orig.)

Delayed radiation necrosis of the brain simulating a brain tumor

International Nuclear Information System (INIS)

Ikeda, Hiroya; Kanai, Nobuhiro; Kamikawa, Kiyoo

1976-01-01

Two cases of delayed radiation necrosis of the brain are reported. Case 1 was a 50-year-old man who had right hemiparesis and disorientation 26 months after Linac irradiation (5,000 rad), preceded by an operation for right maxillar carcinoma. A left carotid angiogram demonstrated a left temporal mass lesion, extending to the frontal lobe. Case 2 was a 41-year-old man who had previously had an operation for right intraorbital plasmocytoma, followed by two Co irradiations (6,400 rad, and 5,000 rad). He had the signs and symptoms of intracranial hypertension 36 months after his last irradiation. A left carotid angiogram demonstrated a left temporal mass lesion. Both cases were treated by administration of steroid hormone (which alleviated the signs and symptoms) and by temporal lobectomy. Microscopic examinations showed necrosis of the brain tissues associated with hyaline degeneration of blood vessel walls and perivascular cell infiltration. The signs and symptoms of intracranial hypertension subsided postoperatively. Thirteen other cases the same as ours were collected from literature. They showed the signs and symptoms simulating a brain tumor (like a metastatic brain tumor) after irradiation to extracranial malignant tumors. Diagnosis of radiation necrosis was made by operation or autopsy. A follow-up for a long time is necessary, because the pathological changes in the brain may be progressive and extending in some cases, although decompressive operations for mass lesions give excellent results. (auth.)

Peritumoral edema associated with metastatic brain tumor

International Nuclear Information System (INIS)

Shirotani, Toshiki; Takiguchi, Hiroshi; Shima, Katsuji; Chigasaki, Hiroo; Tajima, Atsushi; Watanabe, Satoru.

1992-01-01

Computed tomographic (CT) examinations were performed in 94 lesions of 50 patients with metastatic brain tumors. Peritumoral edema (A E ) and tumor area (A T ) were measured using the planimetric method on the CT scan films that demonstrated maximum size of the tumor. Then, the volume of the peritumoral edema (V E ) and the surface area of the tumor (S T ) were claculated from these data. Eighty-three brain lesions from lung cancers were subdivided into 49 adenocarcinomas, 11 squamous cell carcinomas, 16 small cell carcinomas and 7 large cell carcinomas. Eleven metastatic tumors from breast cancers were all adenocarcinomas. There was statistical correlation between the surface area of tumor and the volume of the peritumoral edema for the adenocarcinoma (r=0.4043, p E /S T ratios in small cell carcinomas were smaller then those in non-small cell carcinomas, when the volume of the tumor was larger than 10 mm 3 . Accordingly, we suggest that the volume of the peritumoral edema in the small cell carcinoma is generally smaller than that in others. (author)

Clinical results of BNCT for malignant brain tumors in children

International Nuclear Information System (INIS)

Nakagawa, Yoshinobu; Kageji, Teruyoshi; Mizobuchi, Yoshifumi; Kumada, Hiroaki; Nakagawa, Yoshiaki

2009-01-01

It is very difficult to treat the patients with malignant brain tumor in children, especially under 3 years, because the conventional irradiation cannot be applied due to the damage of normal brain tissue. However, boron neutron capture therapy (BNCT) has tumor selectivity such that it can make damage only in tumor cells. We evaluated the clinical results and courses in patients with malignant glioma under 15 years. Among 183 patients with brain tumors treated by our group using BSH-based intra-operative BNCT, 23 patients were under 15 years. They included 4 patients under 3 years. There were 3 glioblastomas (GBM), 6 anaplastic astrocytomas(AAS), 7 primitive neuroectodermal tumors (PNET), 6 pontine gliomas and 1 anaplastic ependymoma. All GBM and PNET patients died due to CSF and/or CNS dissemination without local tumor regrowth. All pontine glioma patients died due to regrowth of the tumor. Four of 6 anaplastic astrocytoma and 1 anaplastic ependymoma patients alive without tumor recurrence. BNCT can be applied to malignant brain tumors in children, especially under 3 years instead of conventional radiation. Although it can achieve the local control in the primary site, it cannot prevent CSF dissemination in patients with glioblastoma.

Application of 31P MR spectroscopy to the brain tumors

International Nuclear Information System (INIS)

Ha, Dong Ho; Choi, Sun Seob; Oh, Jong Young; Yoon, Seong Kuk; Kang, Myong Jin; Kim, Ki Uk

2013-01-01

To evaluate the clinical feasibility and obtain useful parameters of 3 1P magnetic resonance spectroscopy (MRS) study for making the differential diagnosis of brain tumors. Twenty-eight patients with brain tumorous lesions (22 cases of brain tumor and 6 cases of abscess) and 11 normal volunteers were included. The patients were classified into the astrocytoma group, lymphoma group, metastasis group and the abscess group. We obtained the intracellular pH and the metabolite ratios of phosphomonoesters/phosophodiesters (PME/PDE), PME/inorganic phosphate (Pi), PDE/Pi, PME/adenosine triphosphate (ATP), PDE/ATP, PME/phosphocreatine (PCr), PDE/PCr, PCr/ATP, PCr/Pi, and ATP/Pi, and evaluated the statistical significances. The brain tumors had a tendency of alkalization (pH = 7.28 ± 0.27, p = 0.090), especially the pH of the lymphoma was significantly increased (pH = 7.45 ± 0.32, p = 0.013). The brain tumor group showed increased PME/PDE ratio compared with that in the normal control group (p 0.012). The ratios of PME/PDE, PDE/Pi, PME/PCr and PDE/PCr showed statistically significant differences between each brain lesion groups (p 1 'P MRS, and the pH, PME/PDE, PDE/Pi, PME/PCr, and PDE/PCr ratios are helpful for differentiating among the different types of brain tumors.

FDTD analysis of a noninvasive hyperthermia system for brain tumors.

Science.gov (United States)

Yacoob, Sulafa M; Hassan, Noha S

2012-08-14

Hyperthermia is considered one of the new therapeutic modalities for cancer treatment and is based on the difference in thermal sensitivity between healthy tissues and tumors. During hyperthermia treatment, the temperature of the tumor is raised to 40-45°C for a definite period resulting in the destruction of cancer cells. This paper investigates design, modeling and simulation of a new non-invasive hyperthermia applicator system capable of effectively heating deep seated as well as superficial brain tumors using inexpensive, simple, and easy to fabricate components without harming surrounding healthy brain tissues. The proposed hyperthermia applicator system is composed of an air filled partial half ellipsoidal chamber, a patch antenna, and a head model with an embedded tumor at an arbitrary location. The irradiating antenna is placed at one of the foci of the hyperthermia chamber while the center of the brain tumor is placed at the other focus. The finite difference time domain (FDTD) method is used to compute both the SAR patterns and the temperature distribution in three different head models due to two different patch antennas at a frequency of 915 MHz. The obtained results suggest that by using the proposed noninvasive hyperthermia system it is feasible to achieve sufficient and focused energy deposition and temperature rise to therapeutic values in deep seated as well as superficial brain tumors without harming surrounding healthy tissue. The proposed noninvasive hyperthermia system proved suitable for raising the temperature in tumors embedded in the brain to therapeutic values by carefully selecting the systems components. The operator of the system only needs to place the center of the brain tumor at a pre-specified location and excite the antenna at a single frequency of 915 MHz. Our study may provide a basis for a clinical applicator prototype capable of heating brain tumors.

Brain Tumor Segmentation Based on Random Forest

Directory of Open Access Journals (Sweden)

László Lefkovits

2016-09-01

Full Text Available In this article we present a discriminative model for tumor detection from multimodal MR images. The main part of the model is built around the random forest (RF classifier. We created an optimization algorithm able to select the important features for reducing the dimensionality of data. This method is also used to find out the training parameters used in the learning phase. The algorithm is based on random feature properties for evaluating the importance of the variable, the evolution of learning errors and the proximities between instances. The detection performances obtained have been compared with the most recent systems, offering similar results.

Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software.

Science.gov (United States)

Abdolmohammadi, Jamil; Shafiee, Mohsen; Faeghi, Fariborz; Arefan, Douman; Zali, Alireza; Motiei-Langroudi, Rouzbeh; Farshidfar, Zahra; Nazarlou, Ali Kiani; Tavakkoli, Ali; Yarham, Mohammad

2016-08-01

Timely diagnosis of brain tumors could considerably affect the process of patient treatment. To do so, para-clinical methods, particularly MRI, cannot be ignored. MRI has so far answered significant questions regarding tumor characteristics, as well as helping neurosurgeons. In order to detect the tumor cellularity, neuro-surgeons currently have to sample specimens by biopsy and then send them to the pathology unit. The aim of this study is to determine the tumor cellularity in the brain. In this cross-sectional study, 32 patients (18 males and 14 females from 18-77 y/o) were admitted to the neurosurgery department of Shohada-E Tajrish Hospital in Tehran, Iran from April 2012 to February 2014. In addition to routine pulse sequences, T2W Multi echo pulse sequences were taken and the images were analyzed using the MATLAB software to determine the brain tumor cellularity, compared with the biopsy. These findings illustrate the need for more T2 relaxation time decreases, the higher classes of tumors will stand out in the designed table. In this study, the results show T2 relaxation time with a 85% diagnostic weight, compared with the biopsy, to determine the brain tumor cellularity (p<0.05). Our results indicate that the T2 relaxation time feature is the best method to distinguish and present the degree of intra-axial brain tumors cellularity (85% accuracy compared to biopsy). The use of more data is recommended in order to increase the percent accuracy of this techniques.

Pet imaging of peripheral benzodiazepine binding sites in brain tumors

International Nuclear Information System (INIS)

Junck, L.; Jewett, D.M.; Olsen, J.M.; Kilbourn, M.R.; Koeppe, R.A.; Young, A.B.; Greenberg, H.S.; Kuhl, D.E.

1991-01-01

Studies in vitro have shown that the peripheral-type benzodiazepine binding site (PBBS) is present in moderate to high density on malignant gliomas as well as in areas of reactive gliosis, but in low density in normal brain. PK 11195 is an isoquinoline derivative that binds selectively to the PBBS but not to the central benzodiazepine receptor. We have used [ 11 C]PK 11195 with positron emission tomography (PET) to study brain tumors and cerebral infarcts. Preliminary results showed that, in 13 of 18 patients with astrocytomas, [ 11 C]PK 11195 radioactivity was increased in tumor compared to remote brain and that the concentration ratios of tumor-to-remote brain were higher for high grade astrocytomas than for low grade astrocytomas. Pharmacokinetic analysis suggests that the increased activity in tumor probably does not result from alterations in blood flow or vascular permeability. Patients with lymphoma, meningioma, medulloblastoma, brain metastasis, and neurosarcoidosis have also shown increased radioactivity in tumor. Among eight patients with acute and subacute cerebral infarcts, activity in the infarct was increased in seven and was often greatest at the periphery. We conclude that [ 11 C]PK 11195 is a promising radiopharmaceutical for further investigation of brain tumors as well as diseases characterized by reactive gliosis

Automated lung tumor segmentation for whole body PET volume based on novel downhill region growing

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Ballangan, Cherry; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Feng, Dagan

2010-03-01

We propose an automated lung tumor segmentation method for whole body PET images based on a novel downhill region growing (DRG) technique, which regards homogeneous tumor hotspots as 3D monotonically decreasing functions. The method has three major steps: thoracic slice extraction with K-means clustering of the slice features; hotspot segmentation with DRG; and decision tree analysis based hotspot classification. To overcome the common problem of leakage into adjacent hotspots in automated lung tumor segmentation, DRG employs the tumors' SUV monotonicity features. DRG also uses gradient magnitude of tumors' SUV to improve tumor boundary definition. We used 14 PET volumes from patients with primary NSCLC for validation. The thoracic region extraction step achieved good and consistent results for all patients despite marked differences in size and shape of the lungs and the presence of large tumors. The DRG technique was able to avoid the problem of leakage into adjacent hotspots and produced a volumetric overlap fraction of 0.61 +/- 0.13 which outperformed four other methods where the overlap fraction varied from 0.40 +/- 0.24 to 0.59 +/- 0.14. Of the 18 tumors in 14 NSCLC studies, 15 lesions were classified correctly, 2 were false negative and 15 were false positive.

Automated and Semiautomated Segmentation of Rectal Tumor Volumes on Diffusion-Weighted MRI: Can It Replace Manual Volumetry?

International Nuclear Information System (INIS)

Heeswijk, Miriam M. van; Lambregts, Doenja M.J.; Griethuysen, Joost J.M. van; Oei, Stanley; Rao, Sheng-Xiang; Graaff, Carla A.M. de; Vliegen, Roy F.A.; Beets, Geerard L.; Papanikolaou, Nikos; Beets-Tan, Regina G.H.

2016-01-01

Purpose: Diffusion-weighted imaging (DWI) tumor volumetry is promising for rectal cancer response assessment, but an important drawback is that manual per-slice tumor delineation can be highly time consuming. This study investigated whether manual DWI-volumetry can be reproduced using a (semi)automated segmentation approach. Methods and Materials: Seventy-nine patients underwent magnetic resonance imaging (MRI) that included DWI (highest b value [b1000 or b1100]) before and after chemoradiation therapy (CRT). Tumor volumes were assessed on b1000 (or b1100) DWI before and after CRT by means of (1) automated segmentation (by 2 inexperienced readers), (2) semiautomated segmentation (manual adjustment of the volumes obtained by method 1 by 2 radiologists), and (3) manual segmentation (by 2 radiologists); this last assessment served as the reference standard. Intraclass correlation coefficients (ICC) and Dice similarity indices (DSI) were calculated to evaluate agreement between different methods and observers. Measurement times (from a radiologist's perspective) were recorded for each method. Results: Tumor volumes were not significantly different among the 3 methods, either before or after CRT (P=.08 to .92). ICCs compared to manual segmentation were 0.80 to 0.91 and 0.53 to 0.66 before and after CRT, respectively, for the automated segmentation and 0.91 to 0.97 and 0.61 to 0.75, respectively, for the semiautomated method. Interobserver agreement (ICC) pre and post CRT was 0.82 and 0.59 for automated segmentation, 0.91 and 0.73 for semiautomated segmentation, and 0.91 and 0.75 for manual segmentation, respectively. Mean DSI between the automated and semiautomated method were 0.83 and 0.58 pre-CRT and post-CRT, respectively; DSI between the automated and manual segmentation were 0.68 and 0.42 and 0.70 and 0.41 between the semiautomated and manual segmentation, respectively. Median measurement time for the radiologists was 0 seconds (pre- and post-CRT) for the

Automated and Semiautomated Segmentation of Rectal Tumor Volumes on Diffusion-Weighted MRI: Can It Replace Manual Volumetry?

Energy Technology Data Exchange (ETDEWEB)

Heeswijk, Miriam M. van [Department of Radiology, Maastricht University Medical Centre, Maastricht (Netherlands); Department of Surgery, Maastricht University Medical Centre, Maastricht (Netherlands); Lambregts, Doenja M.J., E-mail: d.lambregts@nki.nl [Department of Radiology, Maastricht University Medical Centre, Maastricht (Netherlands); Department of Radiology, The Netherlands Cancer Institute, Amsterdam (Netherlands); Griethuysen, Joost J.M. van [GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht (Netherlands); Department of Radiology, The Netherlands Cancer Institute, Amsterdam (Netherlands); Oei, Stanley [Department of Radiology, Maastricht University Medical Centre, Maastricht (Netherlands); Rao, Sheng-Xiang [Department of Radiology, Maastricht University Medical Centre, Maastricht (Netherlands); Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai (China); Graaff, Carla A.M. de [Department of Radiology, Maastricht University Medical Centre, Maastricht (Netherlands); Vliegen, Roy F.A. [Atrium Medical Centre Parkstad/Zuyderland Medical Centre, Heerlen (Netherlands); Beets, Geerard L. [GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht (Netherlands); Department of Surgery, The Netherlands Cancer Institute, Amsterdam (Netherlands); Papanikolaou, Nikos [Laboratory of Computational Medicine, Institute of Computer Science, FORTH, Heraklion, Crete (Greece); Beets-Tan, Regina G.H. [GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht (Netherlands); Department of Radiology, The Netherlands Cancer Institute, Amsterdam (Netherlands)

2016-03-15

Purpose: Diffusion-weighted imaging (DWI) tumor volumetry is promising for rectal cancer response assessment, but an important drawback is that manual per-slice tumor delineation can be highly time consuming. This study investigated whether manual DWI-volumetry can be reproduced using a (semi)automated segmentation approach. Methods and Materials: Seventy-nine patients underwent magnetic resonance imaging (MRI) that included DWI (highest b value [b1000 or b1100]) before and after chemoradiation therapy (CRT). Tumor volumes were assessed on b1000 (or b1100) DWI before and after CRT by means of (1) automated segmentation (by 2 inexperienced readers), (2) semiautomated segmentation (manual adjustment of the volumes obtained by method 1 by 2 radiologists), and (3) manual segmentation (by 2 radiologists); this last assessment served as the reference standard. Intraclass correlation coefficients (ICC) and Dice similarity indices (DSI) were calculated to evaluate agreement between different methods and observers. Measurement times (from a radiologist's perspective) were recorded for each method. Results: Tumor volumes were not significantly different among the 3 methods, either before or after CRT (P=.08 to .92). ICCs compared to manual segmentation were 0.80 to 0.91 and 0.53 to 0.66 before and after CRT, respectively, for the automated segmentation and 0.91 to 0.97 and 0.61 to 0.75, respectively, for the semiautomated method. Interobserver agreement (ICC) pre and post CRT was 0.82 and 0.59 for automated segmentation, 0.91 and 0.73 for semiautomated segmentation, and 0.91 and 0.75 for manual segmentation, respectively. Mean DSI between the automated and semiautomated method were 0.83 and 0.58 pre-CRT and post-CRT, respectively; DSI between the automated and manual segmentation were 0.68 and 0.42 and 0.70 and 0.41 between the semiautomated and manual segmentation, respectively. Median measurement time for the radiologists was 0 seconds (pre- and post-CRT) for the

Automated and Semiautomated Segmentation of Rectal Tumor Volumes on Diffusion-Weighted MRI: Can It Replace Manual Volumetry?

Science.gov (United States)

van Heeswijk, Miriam M; Lambregts, Doenja M J; van Griethuysen, Joost J M; Oei, Stanley; Rao, Sheng-Xiang; de Graaff, Carla A M; Vliegen, Roy F A; Beets, Geerard L; Papanikolaou, Nikos; Beets-Tan, Regina G H

2016-03-15

Diffusion-weighted imaging (DWI) tumor volumetry is promising for rectal cancer response assessment, but an important drawback is that manual per-slice tumor delineation can be highly time consuming. This study investigated whether manual DWI-volumetry can be reproduced using a (semi)automated segmentation approach. Seventy-nine patients underwent magnetic resonance imaging (MRI) that included DWI (highest b value [b1000 or b1100]) before and after chemoradiation therapy (CRT). Tumor volumes were assessed on b1000 (or b1100) DWI before and after CRT by means of (1) automated segmentation (by 2 inexperienced readers), (2) semiautomated segmentation (manual adjustment of the volumes obtained by method 1 by 2 radiologists), and (3) manual segmentation (by 2 radiologists); this last assessment served as the reference standard. Intraclass correlation coefficients (ICC) and Dice similarity indices (DSI) were calculated to evaluate agreement between different methods and observers. Measurement times (from a radiologist's perspective) were recorded for each method. Tumor volumes were not significantly different among the 3 methods, either before or after CRT (P=.08 to .92). ICCs compared to manual segmentation were 0.80 to 0.91 and 0.53 to 0.66 before and after CRT, respectively, for the automated segmentation and 0.91 to 0.97 and 0.61 to 0.75, respectively, for the semiautomated method. Interobserver agreement (ICC) pre and post CRT was 0.82 and 0.59 for automated segmentation, 0.91 and 0.73 for semiautomated segmentation, and 0.91 and 0.75 for manual segmentation, respectively. Mean DSI between the automated and semiautomated method were 0.83 and 0.58 pre-CRT and post-CRT, respectively; DSI between the automated and manual segmentation were 0.68 and 0.42 and 0.70 and 0.41 between the semiautomated and manual segmentation, respectively. Median measurement time for the radiologists was 0 seconds (pre- and post-CRT) for the automated method, 41 to 69 seconds (pre-CRT) and

A semiautomatic CT-based ensemble segmentation of lung tumors: comparison with oncologists' delineations and with the surgical specimen.

Science.gov (United States)

Rios Velazquez, Emmanuel; Aerts, Hugo J W L; Gu, Yuhua; Goldgof, Dmitry B; De Ruysscher, Dirk; Dekker, Andre; Korn, René; Gillies, Robert J; Lambin, Philippe

2012-11-01

To assess the clinical relevance of a semiautomatic CT-based ensemble segmentation method, by comparing it to pathology and to CT/PET manual delineations by five independent radiation oncologists in non-small cell lung cancer (NSCLC). For 20 NSCLC patients (stages Ib-IIIb) the primary tumor was delineated manually on CT/PET scans by five independent radiation oncologists and segmented using a CT based semi-automatic tool. Tumor volume and overlap fractions between manual and semiautomatic-segmented volumes were compared. All measurements were correlated with the maximal diameter on macroscopic examination of the surgical specimen. Imaging data are available on www.cancerdata.org. High overlap fractions were observed between the semi-automatically segmented volumes and the intersection (92.5±9.0, mean±SD) and union (94.2±6.8) of the manual delineations. No statistically significant differences in tumor volume were observed between the semiautomatic segmentation (71.4±83.2 cm(3), mean±SD) and manual delineations (81.9±94.1 cm(3); p=0.57). The maximal tumor diameter of the semiautomatic-segmented tumor correlated strongly with the macroscopic diameter of the primary tumor (r=0.96). Semiautomatic segmentation of the primary tumor on CT demonstrated high agreement with CT/PET manual delineations and strongly correlated with the macroscopic diameter considered as the "gold standard". This method may be used routinely in clinical practice and could be employed as a starting point for treatment planning, target definition in multi-center clinical trials or for high throughput data mining research. This method is particularly suitable for peripherally located tumors. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Training stem cells for treatment of malignant brain tumors

Institute of Scientific and Technical Information of China (English)

Shengwen; Calvin; Li; Mustafa; H; Kabeer; Long; T; Vu; Vic; Keschrumrus; Hong; Zhen; Yin; Brent; A; Dethlefs; Jiang; F; Zhong; John; H; Weiss; William; G; Loudon

2014-01-01

The treatment of malignant brain tumors remains a challenge. Stem cell technology has been applied in the treatment of brain tumors largely because of the ability of some stem cells to infiltrate into regions within the brain where tumor cells migrate as shown in preclinical studies. However, not all of these efforts can translate in the effective treatment that improves the quality of life for pa-tients. Here, we perform a literature review to identify the problems in the field. Given the lack of efficacy of most stem cell-based agents used in the treatment of malignant brain tumors, we found that stem cell distribution(i.e., only a fraction of stem cells applied capable of targeting tumors) are among the limiting factors. We provide guidelines for potential improvements in stem cell distribution. Specifically, we use an engineered tissue graft platform that replicates the in vivo microenvironment, and provide our data to validate that this culture platform is viable for producing stem cells that have better stem cell distribution than with the Petri dish culture system.

The impact of dietary isoflavonoids on malignant brain tumors

International Nuclear Information System (INIS)

Sehm, Tina; Fan, Zheng; Weiss, Ruth; Schwarz, Marc; Engelhorn, Tobias; Hore, Nirjhar; Doerfler, Arnd; Buchfelder, Michael; Eyüpoglu, IIker Y; Savaskan, Nic E

2014-01-01

Poor prognosis and limited therapeutic options render malignant brain tumors one of the most devastating diseases in clinical medicine. Current treatment strategies attempt to expand the therapeutic repertoire through the use of multimodal treatment regimens. It is here that dietary fibers have been recently recognized as a supportive natural therapy in augmenting the body's response to tumor growth. Here, we investigated the impact of isoflavonoids on primary brain tumor cells. First, we treated glioma cell lines and primary astrocytes with various isoflavonoids and phytoestrogens. Cell viability in a dose-dependent manner was measured for biochanin A (BCA), genistein (GST), and secoisolariciresinol diglucoside (SDG). Dose–response action for the different isoflavonoids showed that BCA is highly effective on glioma cells and nontoxic for normal differentiated brain tissues. We further investigated BCA in ex vivo and in vivo experimentations. Organotypic brain slice cultures were performed and treated with BCA. For in vivo experiments, BCA was intraperitoneal injected in tumor-implanted Fisher rats. Tumor size and edema were measured and quantified by magnetic resonance imaging (MRI) scans. In vascular organotypic glioma brain slice cultures (VOGIM) we found that BCA operates antiangiogenic and neuroprotective. In vivo MRI scans demonstrated that administered BCA as a monotherapy was effective in reducing significantly tumor-induced brain edema and showed a trend for prolonged survival. Our results revealed that dietary isoflavonoids, in particular BCA, execute toxicity toward glioma cells, antiangiogenic, and coevally neuroprotective properties, and therefore augment the range of state-of-the-art multimodal treatment approach

Obtention of tumor volumes in PET images stacks using techniques of colored image segmentation

International Nuclear Information System (INIS)

Vieira, Jose W.; Lopes Filho, Ferdinand J.; Vieira, Igor F.

2014-01-01

This work demonstrated step by step how to segment color images of the chest of an adult in order to separate the tumor volume without significantly changing the values of the components R (Red), G (Green) and B (blue) of the colors of the pixels. For having information which allow to build color map you need to segment and classify the colors present at appropriate intervals in images. The used segmentation technique is to select a small rectangle with color samples in a given region and then erase with a specific color called 'rubber' the other regions of image. The tumor region was segmented into one of the images available and the procedure is displayed in tutorial format. All necessary computational tools have been implemented in DIP (Digital Image Processing), software developed by the authors. The results obtained, in addition to permitting the construction the colorful map of the distribution of the concentration of activity in PET images will also be useful in future work to enter tumors in voxel phantoms in order to perform dosimetric assessments

Multi-phase simultaneous segmentation of tumor in lung 4D-CT data with context information.

Directory of Open Access Journals (Sweden)

Zhengwen Shen

Full Text Available Lung 4D computed tomography (4D-CT plays an important role in high-precision radiotherapy because it characterizes respiratory motion, which is crucial for accurate target definition. However, the manual segmentation of a lung tumor is a heavy workload for doctors because of the large number of lung 4D-CT data slices. Meanwhile, tumor segmentation is still a notoriously challenging problem in computer-aided diagnosis. In this paper, we propose a new method based on an improved graph cut algorithm with context information constraint to find a convenient and robust approach of lung 4D-CT tumor segmentation. We combine all phases of the lung 4D-CT into a global graph, and construct a global energy function accordingly. The sub-graph is first constructed for each phase. A context cost term is enforced to achieve segmentation results in every phase by adding a context constraint between neighboring phases. A global energy function is finally constructed by combining all cost terms. The optimization is achieved by solving a max-flow/min-cut problem, which leads to simultaneous and robust segmentation of the tumor in all the lung 4D-CT phases. The effectiveness of our approach is validated through experiments on 10 different lung 4D-CT cases. The comparison with the graph cut without context constraint, the level set method and the graph cut with star shape prior demonstrates that the proposed method obtains more accurate and robust segmentation results.

Gamma knife radiosurgery for metastatic brain tumors from lung cancer

Energy Technology Data Exchange (ETDEWEB)

Serizawa, Toru; Ono, Junichi; Iuchi, Toshihiko [Chiba Cardiovascular Center, Ichihara (Japan). Chiba Cancer Center] (and others)

2003-01-01

The purpose of this retrospective study is to evaluate the effectiveness of gamma knife radiosurgery (GKS) alone for metastatic brain tumors from lung cancer. Two hundred thirty-one consecutive patients with metastatic brain tumors from lung cancer filling the following 4 criteria were analyzed for this study; no prior brain tumor treatment, 25 or fewer lesions, a maximum 5 tumors with diameter of 2 cm or more, no surgically inaccessible tumor 3 cm or greater in diameter. According to the same treatment protocol, large tumors ({>=} 3 cm) were surgically removed and all the other small lesions (<3 cm) were treated with GKS. New lesions were treated with repeated GKS. The tumor-progression-free, overall, neurological, lowered-QOL (quality of life)-free and new-lesion-free survivals were calculated with the Kaplan-Meier method. The poor prognostic factors for each survival were also analyzed with the Cox's proportional hazard model. The tumor control rate at 1 year was 96.5%. The estimated median overall survival time was 7.7 months. The first-year survival rates were 83.0% in neurological survival and 76.0% in lowered-QOL-free survival. The new-lesion-free survival at 1 year was 27.9%. Multivariate analysis revealed significant poor prognostic factors for neurological and lowered-QOL-free survivals were carcinomatous meningitis and >10 brain lesions. This study suggests the results of GKS for metastatic brain tumors from lung cancer are quite satisfactory considering prevention of neurological death and maintenance of QOL. But cases with carcinomatous meningitis and/or >10 brain lesions are not good candidates for GKS alone. (author)

A study of perifocal low-density area in metastatic brain tumor

International Nuclear Information System (INIS)

Suzuki, Ryuta; Okada, Kodai; Hiratsuka, Hideo; Inaba, Yutaka; Tsuyumu, Matsutaira.

1980-01-01

It is well known that vasogenic brain edema often develops in brain tumors, head injuries, and inflammatory brain lesions. In order to investigate the development and resolution of vasogenic brain edema, some CT findings of metastatic brain tumors were studied in detail. 20 cases of metastatic brain tumors of the past three years were examined by means of a CT scan. In almost all the cases there was a perifocal low-density area (PFL) in the CT findings. In the tumors which were cystic and/or located in the infratentorial space, PFL was not present or, if present, only slightly so. On the contrary, in the tumors which were nodular and/or in the supratentorial space, PFL was present extensively. In the supratentorial metastasis, PFL seemed to be restricted within the white matter and not to involve the gray matter nor such midline structures as basal ganglia and corpus callosum. Besides, PFL was always in contact with the lateral ventricular wall. These results show that PFL in the metastatic tumors resembles in shape the experimental cold-induced brain edema in cats. PFL is presumed to represent vasogenic brain edema; these findings support the hypothesis that the main mechanism of the resolution of vasogenic brain edema is the drainage of the edema fluid into the ventricular CSF. (author)

Groupwise registration of MR brain images with tumors

Science.gov (United States)

Tang, Zhenyu; Wu, Yihong; Fan, Yong

2017-09-01

A novel groupwise image registration framework is developed for registering MR brain images with tumors. Our method iteratively estimates a normal-appearance counterpart for each tumor image to be registered and constructs a directed graph (digraph) of normal-appearance images to guide the groupwise image registration. Particularly, our method maps each tumor image to its normal appearance counterpart by identifying and inpainting brain tumor regions with intensity information estimated using a low-rank plus sparse matrix decomposition based image representation technique. The estimated normal-appearance images are groupwisely registered to a group center image guided by a digraph of images so that the total length of ‘image registration paths’ to be the minimum, and then the original tumor images are warped to the group center image using the resulting deformation fields. We have evaluated our method based on both simulated and real MR brain tumor images. The registration results were evaluated with overlap measures of corresponding brain regions and average entropy of image intensity information, and Wilcoxon signed rank tests were adopted to compare different methods with respect to their regional overlap measures. Compared with a groupwise image registration method that is applied to normal-appearance images estimated using the traditional low-rank plus sparse matrix decomposition based image inpainting, our method achieved higher image registration accuracy with statistical significance (p  =  7.02  ×  10-9).

Fluorescent Nanoparticle Uptake for Brain Tumor Visualization

Directory of Open Access Journals (Sweden)

Rachel Tréhin

2006-04-01

Full Text Available Accurate delineation of tumor margins is vital to the successful surgical resection of brain tumors. We have previously developed a multimodal nanoparticle CLIO-Cy5.5, which is detectable by both magnetic resonance imaging and fluorescence, to assist in intraoperatively visualizing tumor boundaries. Here we examined the accuracy of tumor margin determination of orthotopic tumors implanted in hosts with differing immune responses to the tumor. Using a nonuser-based signal intensity method applied to fluorescent micrographs of 9L gliosarcoma green fluorescent protein (GFP tumors, mean overestimations of 2 and 24 µm were obtained using Cy5.5 fluorescence, compared to the true tumor margin determined by GFP fluorescence, in nude mice and rats, respectively. To resolve which cells internalized the nanoparticle and to quantitate degree of uptake, tumors were disaggregated and cells were analyzed by flow cytometry and fluorescence microscopy. Nanoparticle uptake was seen in both CD11b+ cells (representing activated microglia and macrophages and tumor cells in both animal models by both methods. CD11b+ cells were predominantly found at the tumor margin in both hosts, but were more pronounced at the margin in the rat model. Additional metastatic (CT26 colon and primary (Gli36 glioma brain tumor models likewise demonstrated that the nanoparticle was internalized both by tumor cells and by host cells. Together, these observations suggest that fluorescent nanoparticles provide an accurate method of tumor margin estimation based on a combination of tumor cell and host cell uptake for primary and metastatic tumors in animal model systems and offer potential for clinical translation.

Automatic segmentation of brain MRIs and mapping neuroanatomy across the human lifespan

Science.gov (United States)

Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Rueckert, Daniel; Aljabar, Paul; Hajnal, Joseph V.; Hammers, Alexander

2009-02-01

A robust model for the automatic segmentation of human brain images into anatomically defined regions across the human lifespan would be highly desirable, but such structural segmentations of brain MRI are challenging due to age-related changes. We have developed a new method, based on established algorithms for automatic segmentation of young adults' brains. We used prior information from 30 anatomical atlases, which had been manually segmented into 83 anatomical structures. Target MRIs came from 80 subjects (~12 individuals/decade) from 20 to 90 years, with equal numbers of men, women; data from two different scanners (1.5T, 3T), using the IXI database. Each of the adult atlases was registered to each target MR image. By using additional information from segmentation into tissue classes (GM, WM and CSF) to initialise the warping based on label consistency similarity before feeding this into the previous normalised mutual information non-rigid registration, the registration became robust enough to accommodate atrophy and ventricular enlargement with age. The final segmentation was obtained by combination of the 30 propagated atlases using decision fusion. Kernel smoothing was used for modelling the structural volume changes with aging. Example linear correlation coefficients with age were, for lateral ventricular volume, rmale=0.76, rfemale=0.58 and, for hippocampal volume, rmale=-0.6, rfemale=-0.4 (allρ<0.01).

CADrx for GBM Brain Tumors: Predicting Treatment Response from Changes in Diffusion-Weighted MRI

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Matthew S. Brown

2009-11-01

Full Text Available The goal of this study was to develop a computer-aided therapeutic response (CADrx system for early prediction of drug treatment response for glioblastoma multiforme (GBM brain tumors with diffusion weighted (DW MR images. In conventional Macdonald assessment, tumor response is assessed nine weeks or more post-treatment. However, we will investigate the ability of DW-MRI to assess response earlier, at five weeks post treatment. The apparent diffusion coefficient (ADC map, calculated from DW images, has been shown to reveal changes in the tumor’s microenvironment preceding morphologic tumor changes. ADC values in treated brain tumors could theoretically both increase due to the cell kill (and thus reduced cell density and decrease due to inhibition of edema. In this study, we investigated the effectiveness of features that quantify changes from pre- and post-treatment tumor ADC histograms to detect treatment response. There are three parts to this study: first, tumor regions were segmented on T1w contrast enhanced images by Otsu’s thresholding method, and mapped from T1w images onto ADC images by a 3D region of interest (ROI mapping tool using DICOM header information; second, ADC histograms of the tumor region were extracted from both pre- and five weeks post-treatment scans, and fitted by a two-component Gaussian mixture model (GMM. The GMM features as well as standard histogram-based features were extracted. Finally, supervised machine learning techniques were applied for classification of responders or non-responders. The approach was evaluated with a dataset of 85 patients with GBM under chemotherapy, in which 39 responded and 46 did not, based on tumor volume reduction. We compared adaBoost, random forest and support vector machine classification algorithms, using ten-fold cross validation, resulting in the best accuracy of 69.41% and the corresponding area under the curve (Az of 0.70.

Brain tumors and synchrotron radiation: Methodological developments in quantitative brain perfusion imaging and radiation therapy

International Nuclear Information System (INIS)

Adam, Jean-Francois

2005-01-01

High-grade gliomas are the most frequent type of primary brain tumors in adults. Unfortunately, the management of glioblastomas is still mainly palliative and remains a difficult challenge, despite advances in brain tumor molecular biology and in some emerging therapies. Synchrotron radiation opens fields for medical imaging and radiation therapy by using monochromatic intense x-ray beams. It is now well known that angiogenesis plays a critical role in the tumor growth process and that brain perfusion is representative of the tumor mitotic activity. Synchrotron radiation quantitative computed tomography (SRCT) is one of the most accurate techniques for measuring in vivo contrast agent concentration and thus computing precise and accurate absolute values of the brain perfusion key parameters. The methodological developments of SRCT absolute brain perfusion measurements as well as their preclinical validation are detailed in this thesis. In particular, absolute cerebral volume and blood brain barrier permeability high-resolution (pixel size 2 ) parametric maps were reported. In conventional radiotherapy, the treatment of these tumors remains a delicate challenge, because the damages to the surrounding normal brain tissue limit the amount of radiation that can be delivered. One strategy to overcome this limitation is to infuse an iodinated contrast agent to the patient during the irradiation. The contrast agent accumulates in the tumor, through the broken blood brain barrier, and the irradiation is performed with kilovoltage x rays, in tomography mode, the tumor being located at the center of rotation and the beam size adjusted to the tumor dimensions. The dose enhancement results from the photoelectric effect on the heavy element and from the irradiation geometry. Synchrotron beams, providing high intensity, tunable monochromatic x rays, are ideal for this treatment. The beam properties allow the selection of monochromatic irradiation, at the optimal energy, for a

The exciting potential of nanotherapy in brain-tumor targeted drug delivery approaches

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Vivek Agrahari

2017-01-01

Full Text Available Delivering therapeutics to the central nervous system (CNS and brain-tumor has been a major challenge. The current standard treatment approaches for the brain-tumor comprise of surgical resection followed by immunotherapy, radiotherapy, and chemotherapy. However, the current treatments are limited in providing significant benefits to the patients and despite recent technological advancements; brain-tumor is still challenging to treat. Brain-tumor therapy is limited by the lack of effective and targeted strategies to deliver chemotherapeutic agents across the blood-brain barrier (BBB. The BBB is the main obstacle that must be overcome to allow compounds to reach their targets in the brain. Recent advances have boosted the nanotherapeutic approaches in providing an attractive strategy in improving the drug delivery across the BBB and into the CNS. Compared to conventional formulations, nanoformulations offer significant advantages in CNS drug delivery approaches. Considering the above facts, in this review, the physiological/anatomical features of the brain-tumor and the BBB are briefly discussed. The drug transport mechanisms at the BBB are outlined. The approaches to deliver chemotherapeutic drugs across the CNS into the brain-tumor using nanocarriers are summarized. In addition, the challenges that need to be addressed in nanotherapeutic approaches for their enhanced clinical application in brain-tumor therapy are discussed.

Targeting Malignant Brain Tumors with Antibodies

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Rok Razpotnik

2017-09-01

Full Text Available Antibodies have been shown to be a potent therapeutic tool. However, their use for targeting brain diseases, including neurodegenerative diseases and brain cancers, has been limited, particularly because the blood–brain barrier (BBB makes brain tissue hard to access by conventional antibody-targeting strategies. In this review, we summarize new antibody therapeutic approaches to target brain tumors, especially malignant gliomas, as well as their potential drawbacks. Many different brain delivery platforms for antibodies have been studied such as liposomes, nanoparticle-based systems, cell-penetrating peptides (CPPs, and cell-based approaches. We have already shown the successful delivery of single-chain fragment variable (scFv with CPP as a linker between two variable domains in the brain. Antibodies normally face poor penetration through the BBB, with some variants sufficiently passing the barrier on their own. A “Trojan horse” method allows passage of biomolecules, such as antibodies, through the BBB by receptor-mediated transcytosis (RMT. Such examples of therapeutic antibodies are the bispecific antibodies where one binding specificity recognizes and binds a BBB receptor, enabling RMT and where a second binding specificity recognizes an antigen as a therapeutic target. On the other hand, cell-based systems such as stem cells (SCs are a promising delivery system because of their tumor tropism and ability to cross the BBB. Genetically engineered SCs can be used in gene therapy, where they express anti-tumor drugs, including antibodies. Different types and sources of SCs have been studied for the delivery of therapeutics to the brain; both mesenchymal stem cells (MSCs and neural stem cells (NSCs show great potential. Following the success in treatment of leukemias and lymphomas, the adoptive T-cell therapies, especially the chimeric antigen receptor-T cells (CAR-Ts, are making their way into glioma treatment as another type of cell

DCS-SVM: a novel semi-automated method for human brain MR image segmentation.

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Ahmadvand, Ali; Daliri, Mohammad Reza; Hajiali, Mohammadtaghi

2017-11-27

In this paper, a novel method is proposed which appropriately segments magnetic resonance (MR) brain images into three main tissues. This paper proposes an extension of our previous work in which we suggested a combination of multiple classifiers (CMC)-based methods named dynamic classifier selection-dynamic local training local Tanimoto index (DCS-DLTLTI) for MR brain image segmentation into three main cerebral tissues. This idea is used here and a novel method is developed that tries to use more complex and accurate classifiers like support vector machine (SVM) in the ensemble. This work is challenging because the CMC-based methods are time consuming, especially on huge datasets like three-dimensional (3D) brain MR images. Moreover, SVM is a powerful method that is used for modeling datasets with complex feature space, but it also has huge computational cost for big datasets, especially those with strong interclass variability problems and with more than two classes such as 3D brain images; therefore, we cannot use SVM in DCS-DLTLTI. Therefore, we propose a novel approach named "DCS-SVM" to use SVM in DCS-DLTLTI to improve the accuracy of segmentation results. The proposed method is applied on well-known datasets of the Internet Brain Segmentation Repository (IBSR) and promising results are obtained.

Yoga Therapy in Treating Patients With Malignant Brain Tumors

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2017-07-27

Adult Anaplastic Astrocytoma; Adult Anaplastic Ependymoma; Adult Anaplastic Meningioma; Adult Anaplastic Oligodendroglioma; Adult Brain Stem Glioma; Adult Choroid Plexus Tumor; Adult Diffuse Astrocytoma; Adult Ependymoblastoma; Adult Ependymoma; Adult Giant Cell Glioblastoma; Adult Glioblastoma; Adult Gliosarcoma; Adult Grade II Meningioma; Adult Medulloblastoma; Adult Meningeal Hemangiopericytoma; Adult Mixed Glioma; Adult Oligodendroglioma; Adult Papillary Meningioma; Adult Pineal Gland Astrocytoma; Adult Pineoblastoma; Adult Pineocytoma; Adult Supratentorial Primitive Neuroectodermal Tumor (PNET); Recurrent Adult Brain Tumor

"Facilitated" amino acid transport is upregulated in brain tumors.

Science.gov (United States)

Miyagawa, T; Oku, T; Uehara, H; Desai, R; Beattie, B; Tjuvajev, J; Blasberg, R

1998-05-01

The goal of this study was to determine the magnitude of "facilitated" amino acid transport across tumor and brain capillaries and to evaluate whether amino acid transporter expression is "upregulated" in tumor vessels compared to capillaries in contralateral brain tissue. Aminocyclopentane carboxylic acid (ACPC), a non-metabolized [14C]-labeled amino acid, and a reference molecule for passive vascular permeability, [67Ga]-gallium-diethylenetriaminepentaacetic acid (Ga-DTPA), were used in these studies. Two experimental rat gliomas were studied (C6 and RG2). Brain tissue was rapidly processed for double label quantitative autoradiography 10 minutes after intravenous injection of ACPC and Ga-DTPA. Parametric images of blood-to-brain transport (K1ACPC and K1Ga-DTPA, microL/min/g) produced from the autoradiograms and the histology were obtained from the same tissue section. These three images were registered in an image array processor; regions of interest in tumor and contralateral brain were defined on morphologic criteria (histology) and were transferred to the autoradiographic images to obtain mean values. The facilitated component of ACPC transport (deltaK1ACPC) was calculated from the K1ACPC and K1Ga-DTPA data, and paired comparisons between tumor and contralateral brain were performed. ACPC flux, K1ACPC, across normal brain capillaries (22.6 +/- 8.1 microL/g/min) was >200-fold greater than that of Ga-DTPA (0.09 +/- 0.04 microL/g/min), and this difference was largely (approximately 90%) due to facilitated ACPC transport. Substantially higher K1ACPC values compared to corresponding K1DTPA values were also measured in C6 and RG2 gliomas. The deltaK1ACPC values for C6 glioma were more than twice that of contralateral brain cortex. K1ACPC and deltaK1ACPC values for RG2 gliomas was not significantly higher than that of contralateral cortex, although a approximately 2-fold difference in facilitated transport is obtained after normalization for differences in capillary

A statistical method for lung tumor segmentation uncertainty in PET images based on user inference.

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Zheng, Chaojie; Wang, Xiuying; Feng, Dagan

2015-01-01

PET has been widely accepted as an effective imaging modality for lung tumor diagnosis and treatment. However, standard criteria for delineating tumor boundary from PET are yet to develop largely due to relatively low quality of PET images, uncertain tumor boundary definition, and variety of tumor characteristics. In this paper, we propose a statistical solution to segmentation uncertainty on the basis of user inference. We firstly define the uncertainty segmentation band on the basis of segmentation probability map constructed from Random Walks (RW) algorithm; and then based on the extracted features of the user inference, we use Principle Component Analysis (PCA) to formulate the statistical model for labeling the uncertainty band. We validated our method on 10 lung PET-CT phantom studies from the public RIDER collections [1] and 16 clinical PET studies where tumors were manually delineated by two experienced radiologists. The methods were validated using Dice similarity coefficient (DSC) to measure the spatial volume overlap. Our method achieved an average DSC of 0.878 ± 0.078 on phantom studies and 0.835 ± 0.039 on clinical studies.

Combination radiotherapy in an orthotopic mouse brain tumor model.

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Kramp, Tamalee R; Camphausen, Kevin

2012-03-06

Glioblastoma multiforme (GBM) are the most common and aggressive adult primary brain tumors. In recent years there has been substantial progress in the understanding of the mechanics of tumor invasion, and direct intracerebral inoculation of tumor provides the opportunity of observing the invasive process in a physiologically appropriate environment. As far as human brain tumors are concerned, the orthotopic models currently available are established either by stereotaxic injection of cell suspensions or implantation of a solid piece of tumor through a complicated craniotomy procedure. In our technique we harvest cells from tissue culture to create a cell suspension used to implant directly into the brain. The duration of the surgery is approximately 30 minutes, and as the mouse needs to be in a constant surgical plane, an injectable anesthetic is used. The mouse is placed in a stereotaxic jig made by Stoetling (figure 1). After the surgical area is cleaned and prepared, an incision is made; and the bregma is located to determine the location of the craniotomy. The location of the craniotomy is 2 mm to the right and 1 mm rostral to the bregma. The depth is 3 mm from the surface of the skull, and cells are injected at a rate of 2 μl every 2 minutes. The skin is sutured with 5-0 PDS, and the mouse is allowed to wake up on a heating pad. From our experience, depending on the cell line, treatment can take place from 7-10 days after surgery. Drug delivery is dependent on the drug composition. For radiation treatment the mice are anesthetized, and put into a custom made jig. Lead covers the mouse's body and exposes only the brain of the mouse. The study of tumorigenesis and the evaluation of new therapies for GBM require accurate and reproducible brain tumor animal models. Thus we use this orthotopic brain model to study the interaction of the microenvironment of the brain and the tumor, to test the effectiveness of different therapeutic agents with and without

Why does Jack, and not Jill, break his crown? Sex disparity in brain tumors.

Science.gov (United States)

Sun, Tao; Warrington, Nicole M; Rubin, Joshua B

2012-01-25

It is often reported that brain tumors occur more frequently in males, and that males suffer a worse outcome from brain tumors than females. If correct, these observations suggest that sex plays a fundamental role in brain tumor biology. The following review of the literature regarding primary and metastatic brain tumors, reveals that brain tumors do occur more frequently in males compared to females regardless of age, tumor histology, or region of the world. Sexually dimorphic mechanisms that might control tumor cell biology, as well as immune and brain microenvironmental responses to cancer, are explored as the basis for this sex disparity. Elucidating the mechanisms by which sex chromosomes and sex hormones impact on brain tumorigenesis and progression will advance our understanding of basic cancer biology and is likely to be essential for optimizing the care of brain tumor patients.

Assisted Care Options (Brain Tumors)

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... you with relief from the symptoms, pain, and stress of your brain tumor, while improving quality of life for both you and your family. Palliative care specialists work together as a team to provide an extra ...

Why does Jack, and not Jill, break his crown? Sex disparity in brain tumors

OpenAIRE

Sun, Tao; Warrington, Nicole M; Rubin, Joshua B

2012-01-01

Abstract It is often reported that brain tumors occur more frequently in males, and that males suffer a worse outcome from brain tumors than females. If correct, these observations suggest that sex plays a fundamental role in brain tumor biology. The following review of the literature regarding primary and metastatic brain tumors, reveals that brain tumors do occur more frequently in males compared to females regardless of age, tumor histology, or region of the world. Sexually dimorphic mecha...

Awake Craniotomy for Tumor Resection: Further Optimizing Therapy of Brain Tumors.

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Mehdorn, H Maximilian; Schwartz, Felix; Becker, Juliane

2017-01-01

In recent years more and more data have emerged linking the most radical resection to prolonged survival in patients harboring brain tumors. Since total tumor resection could increase postoperative morbidity, many methods have been suggested to reduce the risk of postoperative neurological deficits: awake craniotomy with the possibility of continuous patient-surgeon communication is one of the possibilities of finding out how radical a tumor resection can possibly be without causing permanent harm to the patient.In 1994 we started to perform awake craniotomy for glioma resection. In 2005 the use of intraoperative high-field magnetic resonance imaging (MRI) was included in the standard tumor therapy protocol. Here we review our experience in performing awake surgery for gliomas, gained in 219 patients.Patient selection by the operating surgeon and a neuropsychologist is of primary importance: the patient should feel as if they are part of the surgical team fighting against the tumor. The patient will undergo extensive neuropsychological testing, functional MRI, and fiber tractography in order to define the relationship between the tumor and the functionally relevant brain areas. Attention needs to be given at which particular time during surgery the intraoperative MRI is performed. Results from part of our series (without and with ioMRI scan) are presented.

NMR relaxation times in human brain tumors (preliminary results)

International Nuclear Information System (INIS)

Benoist, L.; Certaines, J. de; Chatel, M.; Menault, F.

1981-01-01

Since the early work of Damadian in 1971, proton NMR studies of tumors has been well documented. Present study concerns the spin-lattice T 1 and spin-spin T 2 relaxation times of normal dog brain according to the histological differentiation and of 35 human benignant or malignant tumors. The results principally show T 2 important variations between white and gray substance in normal brain but no discrimination between malignant and benignant tumors [fr

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

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Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

FDTD analysis of a noninvasive hyperthermia system for brain tumors

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Yacoob Sulafa M

2012-08-01

Full Text Available Abstract Background Hyperthermia is considered one of the new therapeutic modalities for cancer treatment and is based on the difference in thermal sensitivity between healthy tissues and tumors. During hyperthermia treatment, the temperature of the tumor is raised to 40–45°C for a definite period resulting in the destruction of cancer cells. This paper investigates design, modeling and simulation of a new non-invasive hyperthermia applicator system capable of effectively heating deep seated as well as superficial brain tumors using inexpensive, simple, and easy to fabricate components without harming surrounding healthy brain tissues. Methods The proposed hyperthermia applicator system is composed of an air filled partial half ellipsoidal chamber, a patch antenna, and a head model with an embedded tumor at an arbitrary location. The irradiating antenna is placed at one of the foci of the hyperthermia chamber while the center of the brain tumor is placed at the other focus. The finite difference time domain (FDTD method is used to compute both the SAR patterns and the temperature distribution in three different head models due to two different patch antennas at a frequency of 915 MHz. Results The obtained results suggest that by using the proposed noninvasive hyperthermia system it is feasible to achieve sufficient and focused energy deposition and temperature rise to therapeutic values in deep seated as well as superficial brain tumors without harming surrounding healthy tissue. Conclusions The proposed noninvasive hyperthermia system proved suitable for raising the temperature in tumors embedded in the brain to therapeutic values by carefully selecting the systems components. The operator of the system only needs to place the center of the brain tumor at a pre-specified location and excite the antenna at a single frequency of 915 MHz. Our study may provide a basis for a clinical applicator prototype capable of heating brain tumors.

Family History of Cancer in Benign Brain Tumor Subtypes Versus Gliomas

Energy Technology Data Exchange (ETDEWEB)

Ostrom, Quinn T. [Department of Anthropology, Case Western Reserve University, Cleveland, OH (United States); McCulloh, Christopher [Case Western Reserve University School of Medicine, Cleveland, OH (United States); Chen, Yanwen; Devine, Karen; Wolinsky, Yingli, E-mail: qto@case.edu [Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH (United States)

2012-02-28

Purpose: Family history is associated with gliomas, but this association has not been established for benign brain tumors. Using information from newly diagnosed primary brain tumor patients, we describe patterns of family cancer histories in patients with benign brain tumors and compare those to patients with gliomas. Methods: Newly diagnosed primary brain tumor patients were identified as part of the Ohio Brain Tumor Study. Each patient was asked to participate in a telephone interview about personal medical history, family history of cancer, and other exposures. Information was available from 33 acoustic neuroma (65%), 78 meningioma (65%), 49 pituitary adenoma (73.1%), and 152 glioma patients (58.2%). The association between family history of cancer and each subtype was compared with gliomas using unconditional logistic regression models generating odds ratios (ORs) and 95% confidence intervals. Results: There was no significant difference in family history of cancer between patients with glioma and benign subtypes. Conclusion: The results suggest that benign brain tumor may have an association with family history of cancer. More studies are warranted to disentangle the potential genetic and/or environmental causes for these diseases.

Family History of Cancer in Benign Brain Tumor Subtypes Versus Gliomas

International Nuclear Information System (INIS)

Ostrom, Quinn T.; McCulloh, Christopher; Chen, Yanwen; Devine, Karen; Wolinsky, Yingli

2012-01-01

Purpose: Family history is associated with gliomas, but this association has not been established for benign brain tumors. Using information from newly diagnosed primary brain tumor patients, we describe patterns of family cancer histories in patients with benign brain tumors and compare those to patients with gliomas. Methods: Newly diagnosed primary brain tumor patients were identified as part of the Ohio Brain Tumor Study. Each patient was asked to participate in a telephone interview about personal medical history, family history of cancer, and other exposures. Information was available from 33 acoustic neuroma (65%), 78 meningioma (65%), 49 pituitary adenoma (73.1%), and 152 glioma patients (58.2%). The association between family history of cancer and each subtype was compared with gliomas using unconditional logistic regression models generating odds ratios (ORs) and 95% confidence intervals. Results: There was no significant difference in family history of cancer between patients with glioma and benign subtypes. Conclusion: The results suggest that benign brain tumor may have an association with family history of cancer. More studies are warranted to disentangle the potential genetic and/or environmental causes for these diseases.

Family history of cancer in benign brain tumor subtypes versus gliomas

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Quinn eOstrom

2012-02-01

Full Text Available Purpose: Family history is associated with gliomas, but this association has not ben established for benign brain tumors. Using information from newly diagnosed primary brain tumor patients, we describe patterns of family cancer histories in patients with benign brain tumors and compare those to patients with gliomas. Methods: Newly diagnosed primary brain tumor patients were identified as part of the Ohio Brain Tumor Study (OBTS. Each patient was asked to participate in a telephone interview about personal medical history, family history of cancer, and other exposures. Information was available from 33 acoustic neuroma (65%, 78 meningioma (65%, 49 pituitary adenoma (73.1% and 152 glioma patients (58.2%. The association between family history of cancer and each subtype was compared with gliomas using unconditional logistic regression models generating odds ratios (ORs and 95% confidence intervals (95% CI. Results: There was no significant difference in family history of cancer between patients with glioma and benign subtypes. Conclusions: The results suggest that benign brain tumor may have an association with family history of cancer. More studies are warranted to disentangle the potential genetic and/or environmental causes for these diseases.

Diagnosis and prognosis of brain tumors in clinical trials

NARCIS (Netherlands)

T.S. Gorlia (Thierry)

2013-01-01

textabstractAccording to the Central Brain Registry Of The United States (CBTRUS) statistical report (February 2012) the incidence rate of all primary non malignant and malignant brain and central nervous system tumors is 19.89 cases per 100.000 (11.58 for non-malignant tumors and 7.31 for malignant

Why does Jack, and not Jill, break his crown? Sex disparity in brain tumors

Directory of Open Access Journals (Sweden)

Sun Tao

2012-01-01

Full Text Available Abstract It is often reported that brain tumors occur more frequently in males, and that males suffer a worse outcome from brain tumors than females. If correct, these observations suggest that sex plays a fundamental role in brain tumor biology. The following review of the literature regarding primary and metastatic brain tumors, reveals that brain tumors do occur more frequently in males compared to females regardless of age, tumor histology, or region of the world. Sexually dimorphic mechanisms that might control tumor cell biology, as well as immune and brain microenvironmental responses to cancer, are explored as the basis for this sex disparity. Elucidating the mechanisms by which sex chromosomes and sex hormones impact on brain tumorigenesis and progression will advance our understanding of basic cancer biology and is likely to be essential for optimizing the care of brain tumor patients.

Cellular characterization of the peritumoral edema zone in malignant brain tumors

International Nuclear Information System (INIS)

Engelhorn, T.; Schwarz, M.A.; Savaskan, N.E.

2009-01-01

Brain edema is a hallmark of human malignant brain tumors and contributes to the clinical course and outcome of brain tumor patients. The so-called perifocal edema or brain swelling imposes in T2-weighted MR scans as high intensity areas surrounding the bulk tumor mass. The mechanisms of this increased fluid attraction and the cellular composition of the microenvironment are only partially understood. In this study, we focus on imaging perifocal edema in orthotopically implanted gliomas in rodents and correlate perifocal edema with immunohistochemical markers. We identified that areas of perifocal edema not only include the tumor invasion zone, but also are associated with increased glial fibrillary acidic protein (GFAP) and aquaporin-4 expression surrounding the bulk tumor mass. Moreover, a high number of activated microglial cells expressing CD11b and macrophage migration inhibitory factor (MIF) accumulate at the tumor border. Thus, the area of perifocal edema is mainly dominated by reactive changes of vital brain tissue. These data corroborate that perifocal edema identified in T2-weighted MR scans are characterized with alterations in glial cell distribution and marker expression forming an inflammatory tumor microenvironment. (author)

Preclinical models to study the impact of the blood-brain barrier in brain tumor chemotherapy

NARCIS (Netherlands)

Vries, N.A. de

2009-01-01

High-grade gliomas, in particular Glioblastoma Multiforme (GBM), are the most common primary brain tumors in adults and among the deadliest of human cancers. Their location and the extensively infiltrative character of tumor cells into surrounding normal brain structures is an impediment for all

Radiotherapy for pediatric brain stem tumors

International Nuclear Information System (INIS)

Shcherbenko, O.I.; Parkhomenko, R.A.; Govorina, E.V.; Zelinskaya, N.I.; Ardatova, G.V.; Nechaeva, V.N.

2000-01-01

The immediate and short-term results of gamma therapy of brain stem tumors in 24 children were evaluated. All the patients were able to sustain treatment due to adjuvant support with dehydrating and hormonal drugs, and beneficial clinical effect was recorded in 80%. However, magnetic resonance tomography showed no decrease in tumor size. Tumor growth relapsed 3-8 months after radiotherapy. Although total dose ranged 60-72 Gy in 19 patients, there was no clinical evidence of radiation injury [ru

Tumor cell killing effect of boronated dipeptide. Boromethylglycylphenylalanine on boron neutron capture therapy for malignant brain tumors

International Nuclear Information System (INIS)

Takagaki, Masao; Ono, Koji; Masunaga, Shinichiro; Kinashi, Yuko; Kobayashi, Toru; Oda, Yoshifumi; Kikuchi, Haruhiko; Spielvogel, B.F.

1994-01-01

The killing effect of Boron Neutron Capture Therapy; BNCT, is dependant on the boron concentration ratio of tumor to normal brain (T/N ratio), and also that of tumor to blood (T/B ratio). The clinical boron carrier of boro-captate (BSH) showed the large T/N ratio of ca. 8, however the T/B ratio was around 1, which indicated nonselective accumulation into tumor. Indeed high boron concentration of blood restrict the neutron irradiation dose in order to circumvent the normal endothelial damage, especially in the case of deeply seated tumor. Phenylalanine analogue of para borono-phenylalanine (BPA) is an effective boron carrier on BNCT for malignant melanoma. For the BNCT on brain tumors, however, BPA concentration in normal brain was reported to be intolerably high. In order to improve the T/N ratio of BPA in brain, therefore, a dipeptide of boromethylglycylphenylalanine (BMGP) was synthesized deriving from trimethylglycine conjugated with BPA. It is expected to be selectively accumulated into tumor with little uptake into normal brain. Because a dipeptide might not pass through the normal blood brain barrier (BBB). Its killing effect on cultured glioma cell, T98G, and its distribution in rat brain bearing 9L glioma have been investigated in this paper. The BNCT effect of BMGP on cultured cells was nearly triple in comparison with DL-BPA. The neutron dose yielding 1% survival ratio were 7x10 12 nvt for BMGP and 2x10 13 nvt for BPA respectively on BNCT after boron loading for 16 hrs in the same B-10 concentration of 20ppm. Quantitative study of boron concentration via the α-auto radiography and the prompt gamma ray assay on 9L brain tumor rats revealed that T/N ratio and T/B ratio are 12.0 and 3.0 respectively. Those values are excellent for BNCT use. (author)

Bleomycin treatment of brain tumors: an evaluation

DEFF Research Database (Denmark)

Linnert, Mette; Gehl, Julie

2009-01-01

Bleomycin has been used in the treatment of brain tumors for over 30 years. Currently, we are evaluating electrochemotherapy (the use of electric pulses to enhance uptake of bleomycin) for patients with secondary brain tumors. We, therefore, reviewed the literature with specific reference...... fever, headaches, nausea and vomiting, lethargy, and peritumoral edema. Out of 189 patients treated from 1973 to 2007, only five patients (3%) had severe and six patients (3%) had moderate adverse effects. One death was directly related to this treatment, where very high doses were used. Two patients...

Study of automated segmentation of the cerebellum and brainstem on brain MR images

International Nuclear Information System (INIS)

Hayashi, Norio; Matsuura, Yukihiro; Sanada, Shigeru; Suzuki, Masayuki

2005-01-01

MR imaging is an important method for diagnosing abnormalities of the brain. This paper presents an automated method to segment the cerebellum and brainstem for brain MR images. MR images were obtained from 10 normal subjects (male 4, female 6; 22-75 years old, average 31.0 years) and 15 patients with brain atrophy (male 3, female 12; 62-85 years of age, average 76.0 years). The automated method consisted of the following four steps: segmentation of the brain on original images, detection of an upper plane of the cerebellum using the Hough transform, correction of the plane using three-dimensional (3D) information, and segmentation of the cerebellum and brainstem using the plane. The results indicated that the regions obtained by the automated method were visually similar to those obtained by a manual method. The average rates of coincidence between the automated method and manual method were 83.0±9.0% in normal subjects and 86.4±3.6% in patients. (author)

Increased expression of aquaporin-4 in human traumatic brain injury and brain tumors

Institute of Scientific and Technical Information of China (English)

HuaHu; Wei-PingZhang; LeiZhang; ZhongChen; Er-QingWei

2004-01-01

Aquaporin-4 (AQP4) is one of the aquaporins (AQPs), a water channel family. In the brain, AQP4 is expressed in astroeyte foot processes, and plays an important role in water homeostasis and in the formation of brain edema. In our study, AQP4 expression in human brain specimens from patients with traumatic brain injury or different brain tumors was detected

Factors affecting intellectual outcome in pediatric brain tumor patients

International Nuclear Information System (INIS)

Ellenberg, L.; McComb, J.G.; Siegel, S.E.; Stowe, S.

1987-01-01

A prospective study utilizing repeated intellectual testing was undertaken in 73 children with brain tumors consecutively admitted to Childrens Hospital of Los Angeles over a 3-year period to determine the effect of tumor location, extent of surgical resection, hydrocephalus, age of the child, radiation therapy, and chemotherapy on cognitive outcome. Forty-three patients were followed for at least two sequential intellectual assessments and provide the data for this study. Children with hemispheric tumors had the most general cognitive impairment. The degree of tumor resection, adequately treated hydrocephalus, and chemotherapy had no bearing on intellectual outcome. Age of the child affected outcome mainly as it related to radiation. Whole brain radiation therapy was associated with cognitive decline. This was especially true in children below 7 years of age, who experienced a very significant loss of function after whole brain radiation therapy

[Neuronavigator-guided microsurgery for resection of brain tumors].

Science.gov (United States)

Zhang, Xiang; Zhang, Jianning; Fei, Zhou; Wu, Jingwen; Fu, Luoan; Qu, Yan; Liu, Weiping; Wang, Zhanxiang; Yang, Lisun; He, Xiaosheng; Zhen, Haining; Gao, Dakuan; Cao, Weidong; Liang, Jingwen

2002-02-25

To study locating accuracy for the brain tumors and their peri-structures by the neuronavigator and elucidate the microsurgical effects. 65 patients with intracranial tumors were microsurgically treated by the application of Stealth Station and Vector Vision system. The treatment effects were summarized and the neuronavigational accuracy was discussed. After mean fiducial error (MFE) and sustained accuracy (SA) were satisfied. Total tumor removal was achieved in 63 cases (97.0%), subtotal removal in 2 cases (3.0%). The neurological functions were improved in 56 cases (86.2%), unchanged obviously in 9 cases (13.8%). No case deteriorated and died in the group. Navigation systems are reliable and accurate in making microneurosurgical plans for brain tumors. And they can provide tracing of the tumor in the operation and guide the operator's manipulation. The techniques, which help total removal of the tumors and reduce the postoperative complications, are very useful in guarantee operation effects.

Improving Brain Magnetic Resonance Image (MRI Segmentation via a Novel Algorithm based on Genetic and Regional Growth

Directory of Open Access Journals (Sweden)

Javadpour A.

2016-06-01

Full Text Available Background: Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging. Objective: This study describes a new method for brain Magnetic Resonance Image (MRI segmentation via a novel algorithm based on genetic and regional growth. Methods: Among medical imaging methods, brains MRI segmentation is important due to high contrast of non-intrusive soft tissue and high spatial resolution. Size variations of brain tissues are often accompanied by various diseases such as Alzheimer’s disease. As our knowledge about the relation between various brain diseases and deviation of brain anatomy increases, MRI segmentation is exploited as the first step in early diagnosis. In this paper, regional growth method and auto-mate selection of initial points by genetic algorithm is used to introduce a new method for MRI segmentation. Primary pixels and similarity criterion are automatically by genetic algorithms to maximize the accuracy and validity in image segmentation. Results: By using genetic algorithms and defining the fixed function of image segmentation, the initial points for the algorithm were found. The proposed algorithms are applied to the images and results are manually selected by regional growth in which the initial points were compared. The results showed that the proposed algorithm could reduce segmentation error effectively. Conclusion: The study concluded that the proposed algorithm could reduce segmentation error effectively and help us to diagnose brain diseases.

Brain tumor initiating cells adapt to restricted nutrition through preferential glucose uptake.

Science.gov (United States)

Flavahan, William A; Wu, Qiulian; Hitomi, Masahiro; Rahim, Nasiha; Kim, Youngmi; Sloan, Andrew E; Weil, Robert J; Nakano, Ichiro; Sarkaria, Jann N; Stringer, Brett W; Day, Bryan W; Li, Meizhang; Lathia, Justin D; Rich, Jeremy N; Hjelmeland, Anita B

2013-10-01

Like all cancers, brain tumors require a continuous source of energy and molecular resources for new cell production. In normal brain, glucose is an essential neuronal fuel, but the blood-brain barrier limits its delivery. We now report that nutrient restriction contributes to tumor progression by enriching for brain tumor initiating cells (BTICs) owing to preferential BTIC survival and to adaptation of non-BTICs through acquisition of BTIC features. BTICs outcompete for glucose uptake by co-opting the high affinity neuronal glucose transporter, type 3 (Glut3, SLC2A3). BTICs preferentially express Glut3, and targeting Glut3 inhibits BTIC growth and tumorigenic potential. Glut3, but not Glut1, correlates with poor survival in brain tumors and other cancers; thus, tumor initiating cells may extract nutrients with high affinity. As altered metabolism represents a cancer hallmark, metabolic reprogramming may maintain the tumor hierarchy and portend poor prognosis.

A novel algorithm for segmentation of brain MR images

International Nuclear Information System (INIS)

Sial, M.Y.; Yu, L.; Chowdhry, B.S.; Rajput, A.Q.K.; Bhatti, M.I.

2006-01-01

Accurate and fully automatic segmentation of brain from magnetic resonance (MR) scans is a challenging problem that has received an enormous amount of . attention lately. Many researchers have applied various techniques however a standard fuzzy c-means algorithm has produced better results compared to other methods. In this paper, we present a modified fuzzy c-means (FCM) based algorithm for segmentation of brain MR images. Our algorithm is formulated by modifying the objective function of the standard FCM and uses a special spread method to get a smooth and slow varying bias field This method has the advantage that it can be applied at an early stage in an automated data analysis before a tissue model is available. The results on MRI images show that this method provides better results compared to standard FCM algorithms. (author)

Automated Segmentation of in Vivo and Ex Vivo Mouse Brain Magnetic Resonance Images

Directory of Open Access Journals (Sweden)

Alize E.H. Scheenstra

2009-01-01

Full Text Available Segmentation of magnetic resonance imaging (MRI data is required for many applications, such as the comparison of different structures or time points, and for annotation purposes. Currently, the gold standard for automated image segmentation is nonlinear atlas-based segmentation. However, these methods are either not sufficient or highly time consuming for mouse brains, owing to the low signal to noise ratio and low contrast between structures compared with other applications. We present a novel generic approach to reduce processing time for segmentation of various structures of mouse brains, in vivo and ex vivo. The segmentation consists of a rough affine registration to a template followed by a clustering approach to refine the rough segmentation near the edges. Compared with manual segmentations, the presented segmentation method has an average kappa index of 0.7 for 7 of 12 structures in in vivo MRI and 11 of 12 structures in ex vivo MRI. Furthermore, we found that these results were equal to the performance of a nonlinear segmentation method, but with the advantage of being 8 times faster. The presented automatic segmentation method is quick and intuitive and can be used for image registration, volume quantification of structures, and annotation.

Treatment optimization of a brain tumor in BNCT by Monte Carlo method

International Nuclear Information System (INIS)

Nejat, S.; Binesh, A.; Karimian, A.

2012-01-01

Brain cancers are one of the most important diseases. BNCT (Boron Neutron Capture Therapy) is used to brain tumor treatment. In this method the 1 0B (n,α) 7 Li reaction is used. The purpose of this study is absorbed dose evaluation of tumoral and healthy parts of brain. To achieve this aim the brain was simulated by a cylindrical phantom with the dimensions of 20 cm in diameter and height. In BNCT treatment the BSH (Na 2 B 12 H 11 SH) is injected to the human body and absorbed in the healthy and tumoral parts by the ratios of 18 and 65 ppm respectively. So in this research the absorption of BSH in tumoral and healthy parts of brain was considered as the mentioned ratio. Then the neutron with the energy range of 50 eV - 10 keV was exposed to the brain and maximum absorbed dose in healthy and tumoral parts of brain were calculated for a cylindrical tumor with the thickness of about 1 cm which was considered in 5.5 cm depth of brain. This research showed the suitable energy to treat this tumor by BNCT is interval 4 keV- 6keV. The average of dose which is met with healthy and tumor tissue was gained for 6 keV energy of brain 1.18x10 -12 cGy/n and 5.98x10 -12 cGy/n respectively. Maximum of dose which is met with healthy tissue was 4.3 Gy which is much less than standard amount 12.6 Gy. Therefore BNCT method is known as an effective way in the therapy of this kind of tumor. (authors)

The Brain's Cutting-Room Floor: Segmentation of Narrative Cinema

Science.gov (United States)

Zacks, Jeffrey M.; Speer, Nicole K.; Swallow, Khena M.; Maley, Corey J.

2010-01-01

Observers segment ongoing activity into meaningful events. Segmentation is a core component of perception that helps determine memory and guide planning. The current study tested the hypotheses that event segmentation is an automatic component of the perception of extended naturalistic activity, and that the identification of event boundaries in such activities results in part from processing changes in the perceived situation. Observers may identify boundaries between events as a result of processing changes in the observed situation. To test this hypothesis and study this potential mechanism, we measured brain activity while participants viewed an extended narrative film. Large transient responses were observed when the activity was segmented, and these responses were mediated by changes in the observed activity, including characters and their interactions, interactions with objects, spatial location, goals, and causes. These results support accounts that propose event segmentation is automatic and depends on processing meaningful changes in the perceived situation; they are the first to show such effects for extended naturalistic human activity. PMID:20953234

Utility of 99mTc-GHA Brain SPECT in the grading of brain tumors

International Nuclear Information System (INIS)

Bhattacharya, Anish; Mittal, B.R.; Kumar, Ashok

2004-01-01

Full text: Brain tumors are of diverse histological types, the most common being derived from glial tissue. The clinical management and prognosis of brain tumor patients is dependent on accurate neuro-pathologic diagnosis and grading. Radiological imaging is not always a good modality for assessing the exact nature and grade of a malignant tumor. Magnetic resonance imaging (MRI) has a very high soft tissue resolution and is helpful in classifying the grade of tumor. Radionuclide imaging techniques that can reveal metabolic activity within tumor cells are very helpful in predicting the degree of malignancy. Usefulness of Tl-201 SPECT and FDG PET studies have been widely reported to evaluate malignant lesions by measuring increased regional glucose metabolism and amino acid uptake. 99mTc-GHA (Glucoheptonate), more or less analogous to 18F-FDG, may show increased glucose metabolism and help in grading tumors. This study was carried out to determine the utility of 99mTc-GHA SPECT for grading cerebral gliomas. Nineteen patients (12M, 7F) aged 22 to 51 years (36.1 ± 8.3) diagnosed clinically and radiologically to have a brain tumor were evaluated with 99mTc-GHA brain SPECT. All the patients had undergone CT/ MRI examination prior to the brain SPECT study. No patient had undergone surgery, radiation therapy or chemotherapy before the imaging studies. Brain SPECT was performed twice, i.e 40 min and 3 hours after intravenous administration of 20 mCi of Tc99m-GHA under a dual head SPECT gamma camera (Ecam, Siemens), with a low energy high-resolution collimator. A total of 128 frames of 30 seconds each, 64 per detector, were acquired in 128 x 128 matrix, with 360-degree rotation in step and shoot mode. Reconstruction of the SPECT data was done using standard software. Abnormal concentration of tracer at the tumor site was compared to normal uptake on the contralateral side, and ratios obtained for early (40 min) and delayed (3 hours) uptake of tracer. Retention ratio (RR), a

Characterization of a sequential pipeline approach to automatic tissue segmentation from brain MR Images

International Nuclear Information System (INIS)

Hou, Zujun; Huang, Su

2008-01-01

Quantitative analysis of gray matter and white matter in brain magnetic resonance imaging (MRI) is valuable for neuroradiology and clinical practice. Submission of large collections of MRI scans to pipeline processing is increasingly important. We characterized this process and suggest several improvements. To investigate tissue segmentation from brain MR images through a sequential approach, a pipeline that consecutively executes denoising, skull/scalp removal, intensity inhomogeneity correction and intensity-based classification was developed. The denoising phase employs a 3D-extension of the Bayes-Shrink method. The inhomogeneity is corrected by an improvement of the Dawant et al.'s method with automatic generation of reference points. The N3 method has also been evaluated. Subsequently the brain tissue is segmented into cerebrospinal fluid, gray matter and white matter by a generalized Otsu thresholding technique. Intensive comparisons with other sequential or iterative methods have been carried out using simulated and real images. The sequential approach with judicious selection on the algorithm selection in each stage is not only advantageous in speed, but also can attain at least as accurate segmentation as iterative methods under a variety of noise or inhomogeneity levels. A sequential approach to tissue segmentation, which consecutively executes the wavelet shrinkage denoising, scalp/skull removal, inhomogeneity correction and intensity-based classification was developed to automatically segment the brain tissue into CSF, GM and WM from brain MR images. This approach is advantageous in several common applications, compared with other pipeline methods. (orig.)

WE-E-17A-06: Assessing the Scale of Tumor Heterogeneity by Complete Hierarchical Segmentation On MRI

International Nuclear Information System (INIS)

Gensheimer, M; Trister, A; Ermoian, R; Hawkins, D

2014-01-01

Purpose: In many cancers, intratumoral heterogeneity exists in vascular and genetic structure. We developed an algorithm which uses clinical imaging to interrogate different scales of heterogeneity. We hypothesize that heterogeneity of perfusion at large distance scales may correlate with propensity for disease recurrence. We applied the algorithm to initial diagnosis MRI of rhabdomyosarcoma patients to predict recurrence. Methods: The Spatial Heterogeneity Analysis by Recursive Partitioning (SHARP) algorithm recursively segments the tumor image. The tumor is repeatedly subdivided, with each dividing line chosen to maximize signal intensity difference between the two subregions. This process continues to the voxel level, producing segments at multiple scales. Heterogeneity is measured by comparing signal intensity histograms between each segmented region and the adjacent region. We measured the scales of contrast enhancement heterogeneity of the primary tumor in 18 rhabdomyosarcoma patients. Using Cox proportional hazards regression, we explored the influence of heterogeneity parameters on relapse-free survival (RFS). To compare with existing methods, fractal and Haralick texture features were also calculated. Results: The complete segmentation produced by SHARP allows extraction of diverse features, including the amount of heterogeneity at various distance scales, the area of the tumor with the most heterogeneity at each scale, and for a given point in the tumor, the heterogeneity at different scales. 10/18 rhabdomyosarcoma patients suffered disease recurrence. On contrast-enhanced MRI, larger scale of maximum signal intensity heterogeneity, relative to tumor diameter, predicted for shorter RFS (p=0.05). Fractal dimension, fractal fit, and three Haralick features did not predict RFS (p=0.09-0.90). Conclusion: SHARP produces an automatic segmentation of tumor regions and reports the amount of heterogeneity at various distance scales. In rhabdomyosarcoma, RFS was

Pathophysiological aspects of malignant brain tumors studied with positron emission tomography

International Nuclear Information System (INIS)

Jarden, J.O.

1994-01-01

To further understand the control of brain tumor fluid balance and pH, the following studies were undertaken. The transport of a water soluble molecule across the brain and tumor capillary endothelium was studied during glucocorticoid and radiation treatment. The brain and brain-tumor acidity (pH) was evaluated as a single measurement in patients receiving a low maintenance dose of glucocorticoid. Transport changes and pH were measured in 61 patients with cerebral tumors using 82 Rubidium ( 82 Rb) and 11 C-Dimethyloxa-zolidindione ( 11 C-DMO), respectively, and Positron Emission Tomography (PET). Supplementary studies of tumor and contralateral brain blood flow and blood volume using the C 15 O 2 /PET and C 15 O/PET technique, respectively, were included to validate the 82 Rb/PET model and obtain further information. A total of 125 PET scans were performed. Supplementary studies were undertaken to estimate delay of blood registration and form distribution of arterial blood isotope activity curves. Blood-to-tumor barrier transport was outlined at baseline and at 6 and 24 hours after the start of glucocorticoid treatment, finding a significant decrease in the transpfort. Radiation treatment (2-6 gray) did not alter the blood-to-tumor barrier transport when restudied within one hour in patients receiving glucocorticoid. The pH in brain tumors was as high as 6.88-7.26, suggesting that tumors are more alkalotic than the normal brain. The permeability surface area product and the permeability coefficient were determined form the 82 Rb/PET transport and C 15 O 2 /PET flow studies. Baseline permeability values were comparable to the literature values both for 82 Rb and potassium. No difference in tissue blood volume was seen between 82 Rb/PET and C 15 O/PET models and was of the same magnitude in the tumor and the contralateral tissue. Aspects of tumor alkalosis, tumor edema production, glucocorticoid edema clearance, and relationship between the anti-edema effect of

Emerging Techniques in Brain Tumor Imaging: What Radiologists Need to Know

Energy Technology Data Exchange (ETDEWEB)

Kim, Minjae; Kim, Ho Sung [Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505 (Korea, Republic of)

2016-11-01

Among the currently available brain tumor imaging, advanced MR imaging techniques, such as diffusion-weighted MR imaging and perfusion MR imaging, have been used for solving diagnostic challenges associated with conventional imaging and for monitoring the brain tumor treatment response. Further development of advanced MR imaging techniques and postprocessing methods may contribute to predicting the treatment response to a specific therapeutic regimen, particularly using multi-modality and multiparametric imaging. Over the next few years, new imaging techniques, such as amide proton transfer imaging, will be studied regarding their potential use in quantitative brain tumor imaging. In this review, the pathophysiologic considerations and clinical validations of these promising techniques are discussed in the context of brain tumor characterization and treatment response.

Automatic segmentation of tumor-laden lung volumes from the LIDC database

Science.gov (United States)

O'Dell, Walter G.

2012-03-01

The segmentation of the lung parenchyma is often a critical pre-processing step prior to application of computer-aided detection of lung nodules. Segmentation of the lung volume can dramatically decrease computation time and reduce the number of false positive detections by excluding from consideration extra-pulmonary tissue. However, while many algorithms are capable of adequately segmenting the healthy lung, none have been demonstrated to work reliably well on tumor-laden lungs. Of particular challenge is to preserve tumorous masses attached to the chest wall, mediastinum or major vessels. In this role, lung volume segmentation comprises an important computational step that can adversely affect the performance of the overall CAD algorithm. An automated lung volume segmentation algorithm has been developed with the goals to maximally exclude extra-pulmonary tissue while retaining all true nodules. The algorithm comprises a series of tasks including intensity thresholding, 2-D and 3-D morphological operations, 2-D and 3-D floodfilling, and snake-based clipping of nodules attached to the chest wall. It features the ability to (1) exclude trachea and bowels, (2) snip large attached nodules using snakes, (3) snip small attached nodules using dilation, (4) preserve large masses fully internal to lung volume, (5) account for basal aspects of the lung where in a 2-D slice the lower sections appear to be disconnected from main lung, and (6) achieve separation of the right and left hemi-lungs. The algorithm was developed and trained to on the first 100 datasets of the LIDC image database.

(18)F-Fluorodeoxyglucose PET/Computed Tomography for Primary Brain Tumors

DEFF Research Database (Denmark)

Antonsen Segtnan, Eivind; Hess, Søren; Grupe, Peter

2015-01-01

Structural imaging with computed tomography (CT) and MR imaging is the mainstay in primary diagnosis of primary brain tumors, but these modalities depend on morphologic appearance and an intact blood-brain barrier, and important aspects of tumor biology are not addressed. Such issues may...

Neuropathological biomarker candidates in brain tumors: key issues for translational efficiency.

Science.gov (United States)

Hainfellner, J A; Heinzl, H

2010-01-01

Brain tumors comprise a large spectrum of rare malignancies in children and adults that are often associated with severe neurological symptoms and fatal outcome. Neuropathological tumor typing provides both prognostic and predictive tissue information which is the basis for optimal postoperative patient management and therapy. Molecular biomarkers may extend and refine prognostic and predictive information in a brain tumor case, providing more individualized and optimized treatment options. In the recent past a few neuropathological brain tumor biomarkers have translated smoothly into clinical use whereas many candidates show protracted translation. We investigated the causes of protracted translation of candidate brain tumor biomarkers. Considering the research environment from personal, social and systemic perspectives we identified eight determinants of translational success: methodology, funding, statistics, organization, phases of research, cooperation, self-reflection, and scientific progeny. Smoothly translating biomarkers are associated with low degrees of translational complexity whereas biomarkers with protracted translation are associated with high degrees. Key issues for translational efficiency of neuropathological brain tumor biomarker research seem to be related to (i) the strict orientation to the mission of medical research, that is the improval of medical practice as primordial purpose of research, (ii) definition of research priorities according to clinical needs, and (iii) absorption of translational complexities by means of operatively beneficial standards. To this end, concrete actions should comprise adequate scientific education of young investigators, and shaping of integrative diagnostics and therapy research both on the local level and the level of influential international brain tumor research platforms.

Growth of melanoma brain tumors monitored by photoacoustic microscopy

Science.gov (United States)

Staley, Jacob; Grogan, Patrick; Samadi, Abbas K.; Cui, Huizhong; Cohen, Mark S.; Yang, Xinmai

2010-07-01

Melanoma is a primary malignancy that is known to metastasize to the brain and often causes death. The ability to image the growth of brain melanoma in vivo can provide new insights into its evolution and response to therapies. In our study, we use a reflection mode photoacoustic microscopy (PAM) system to detect the growth of melanoma brain tumor in a small animal model. The melanoma tumor cells are implanted in the brain of a mouse at the beginning of the test. Then, PAM is used to scan the region of implantation in the mouse brain, and the growth of the melanoma is monitored until the death of the animal. It is demonstrated that PAM is capable of detecting and monitoring the brain melanoma growth noninvasively in vivo.

99mTc-MIBI-SPECT-studies in the evaluation of brain tumors

International Nuclear Information System (INIS)

Ambrus, E.; Pavics, L.; Gruenwald, F.; Barath, B.; Tiszlavicz, L.; Bender, H.; Menzel, C.; Almasi, L.; Lang, J.; Bodosi, M.; Biersack, H.J.; Csernay, L.

1994-01-01

Brain SPECT studies were performed 5 and 60 minutes after 99m Tc-MIBI administration in 41 patients with brain tumors confirmed by CT and surgical removal (13 meningeomas, 8 astrocytomas grades I-III, 10 glioblastomas, 10 metastases). 99m Tc-MIBI uptake was found in 32 out of 41 brain tumors. According to the semiquantitative SPECT analysis, the tumor/non tumor radios revealed a statistically significant difference in the early tracer uptake between meningeomas and astrocytomas (+4.73±2.91 vs -1.75±0.75, p 99m Tc-MIBI uptake and its changes with time. We concluded that the combination of an early and late 99m Tc-MIBI brain SPECT may be helpful in the non invasive histological classification of brain tumors and the determination of the grade of theirs malignancy. (orig.) [de

Fast CSF MRI for brain segmentation; Cross-validation by comparison with 3D T1-based brain segmentation methods.

Science.gov (United States)

van der Kleij, Lisa A; de Bresser, Jeroen; Hendrikse, Jeroen; Siero, Jeroen C W; Petersen, Esben T; De Vis, Jill B

2018-01-01

In previous work we have developed a fast sequence that focusses on cerebrospinal fluid (CSF) based on the long T2 of CSF. By processing the data obtained with this CSF MRI sequence, brain parenchymal volume (BPV) and intracranial volume (ICV) can be automatically obtained. The aim of this study was to assess the precision of the BPV and ICV measurements of the CSF MRI sequence and to validate the CSF MRI sequence by comparison with 3D T1-based brain segmentation methods. Ten healthy volunteers (2 females; median age 28 years) were scanned (3T MRI) twice with repositioning in between. The scan protocol consisted of a low resolution (LR) CSF sequence (0:57min), a high resolution (HR) CSF sequence (3:21min) and a 3D T1-weighted sequence (6:47min). Data of the HR 3D-T1-weighted images were downsampled to obtain LR T1-weighted images (reconstructed imaging time: 1:59 min). Data of the CSF MRI sequences was automatically segmented using in-house software. The 3D T1-weighted images were segmented using FSL (5.0), SPM12 and FreeSurfer (5.3.0). The mean absolute differences for BPV and ICV between the first and second scan for CSF LR (BPV/ICV: 12±9/7±4cc) and CSF HR (5±5/4±2cc) were comparable to FSL HR (9±11/19±23cc), FSL LR (7±4, 6±5cc), FreeSurfer HR (5±3/14±8cc), FreeSurfer LR (9±8, 12±10cc), and SPM HR (5±3/4±7cc), and SPM LR (5±4, 5±3cc). The correlation between the measured volumes of the CSF sequences and that measured by FSL, FreeSurfer and SPM HR and LR was very good (all Pearson's correlation coefficients >0.83, R2 .67-.97). The results from the downsampled data and the high-resolution data were similar. Both CSF MRI sequences have a precision comparable to, and a very good correlation with established 3D T1-based automated segmentations methods for the segmentation of BPV and ICV. However, the short imaging time of the fast CSF MRI sequence is superior to the 3D T1 sequence on which segmentation with established methods is performed.

Investigating Contingency Risk Factors of Brain Tumor in Children and Adolescents

Directory of Open Access Journals (Sweden)

A Nazemi

2014-12-01

Conclusion: According to research results, several preventable and predictable factors are linked to pediatric brain tumors. Therefore, children prone to brain tumors are recommended to be examined and screened for these risk factors.

Automatic segmentation of MR brain images of preterm infants using supervised classification

NARCIS (Netherlands)

Moeskops, Pim; Benders, Manon J N L; Chiţă, Sabina M.; Kersbergen, Karina J.; Groenendaal, Floris; de Vries, Linda S.; Viergever, Max A.; Isgum, Ivana

Preterm birth is often associated with impaired brain development. The state and expected progression of preterm brain development can be evaluated using quantitative assessment of MR images. Such measurements require accurate segmentation of different tissue types in those images.This paper

Automatic segmentation of MR brain images of preterm infants using supervised classification

NARCIS (Netherlands)

Moeskops, P.; Benders, M.J.N.L.; Chiţ, S.M.; Kersbergen, K.J.; Groenendaal, F.; de Vries, L.S.; Viergever, M.A.; Išgum, I.

Preterm birth is often associated with impaired brain development. The state and expected progression of preterm brain development can be evaluated using quantitative assessment of MR images. Such measurements require accurate segmentation of different tissue types in those images. This paper

Radiation treatment of brain tumors: Concepts and strategies

International Nuclear Information System (INIS)

Marks, J.E.

1989-01-01

Ionizing radiation has demonstrated clinical value for a multitude of CNS tumors. Application of the different physical modalities available has made it possible for the radiotherapist to concentrate the radiation in the region of the tumor with relative sparing of the surrounding normal tissues. Correlation of radiation dose with effect on cranial soft tissues, normal brain, and tumor has shown increasing effect with increasing dose. By using different physical modalities to alter the distribution of radiation dose, it is possible to increase the dose to the tumor and reduce the dose to the normal tissues. Alteration of the volume irradiated and the dose delivered to cranial soft tissues, normal brain, and tumor are strategies that have been effective in improving survival and decreasing complications. The quest for therapeutic gain using hyperbaric oxygen, neutrons, radiation sensitizers, chemotherapeutic agents, and BNCT has met with limited success. Both neoplastic and normal cells are affected simultaneously by all modalities of treatment, including ionizing radiation. Consequently, one is unable to totally depopulate a tumor without irreversibly damaging the normal tissues. In the case of radiation, it is the brain that limits delivery of curative doses, and in the case of chemical additives, it is other organ systems, such as bone marrow, liver, lung, kidneys, and peripheral nerves. Thus, the major obstacle in the treatment of malignant gliomas is our inability to preferentially affect the tumor with the modalities available. Until it is possible to directly target the neoplastic cell without affecting so many of the adjacent normal cells, the quest for therapeutic gain will go unrealized.72 references

Changing Epidemiology of Pediatric Brain Tumors

Directory of Open Access Journals (Sweden)

J Gordon Millichap

2009-07-01

Full Text Available Neurosurgeons at the Hospital for Sick Children, Toronto, Canada, analyzed and classified 1, 866 surgical pathology cases of brain tumors in children under age 19 years, treated 1980-2008.

hTe exciting potential of nanotherapy in brain-tumor targeted drug delivery approaches

Institute of Scientific and Technical Information of China (English)

Vivek Agrahari

2017-01-01

Delivering therapeutics to the central nervous system (CNS) and brain-tumor has been a major challenge. hTe current standard treatment approaches for the brain-tumor comprise of surgical resection followed by immunotherapy, radiotherapy, and chemotherapy. However, the current treatments are limited in provid-ing signiifcant beneifts to the patients and despite recent technological advancements; brain-tumor is still challenging to treat. Brain-tumor therapy is limited by the lack of effective and targeted strategies to deliver chemotherapeutic agents across the blood-brain barrier (BBB). hTe BBB is the main obstacle that must be overcome to allow compounds to reach their targets in the brain. Recent advances have boosted the nan-otherapeutic approaches in providing an attractive strategy in improving the drug delivery across the BBB and into the CNS. Compared to conventional formulations, nanoformulations offer signiifcant ad vantages in CNS drug delivery approaches. Considering the above facts, in this review, the physiological/anatomical features of the brain-tumor and the BBB are brielfy discussed. hTe drug transport mechanisms at the BBB are outlined. hTe approaches to deliver chemotherapeutic drugs across the CNS into the brain-tumor using nanocarriers are summarized. In addition, the challenges that need to be addressed in nanotherapeutic ap-proaches for their enhanced clinical application in brain-tumor therapy are discussed.

Automated Glioblastoma Segmentation Based on a Multiparametric Structured Unsupervised Classification

Science.gov (United States)

Juan-Albarracín, Javier; Fuster-Garcia, Elies; Manjón, José V.; Robles, Montserrat; Aparici, F.; Martí-Bonmatí, L.; García-Gómez, Juan M.

2015-01-01

Automatic brain tumour segmentation has become a key component for the future of brain tumour treatment. Currently, most of brain tumour segmentation approaches arise from the supervised learning standpoint, which requires a labelled training dataset from which to infer the models of the classes. The performance of these models is directly determined by the size and quality of the training corpus, whose retrieval becomes a tedious and time-consuming task. On the other hand, unsupervised approaches avoid these limitations but often do not reach comparable results than the supervised methods. In this sense, we propose an automated unsupervised method for brain tumour segmentation based on anatomical Magnetic Resonance (MR) images. Four unsupervised classification algorithms, grouped by their structured or non-structured condition, were evaluated within our pipeline. Considering the non-structured algorithms, we evaluated K-means, Fuzzy K-means and Gaussian Mixture Model (GMM), whereas as structured classification algorithms we evaluated Gaussian Hidden Markov Random Field (GHMRF). An automated postprocess based on a statistical approach supported by tissue probability maps is proposed to automatically identify the tumour classes after the segmentations. We evaluated our brain tumour segmentation method with the public BRAin Tumor Segmentation (BRATS) 2013 Test and Leaderboard datasets. Our approach based on the GMM model improves the results obtained by most of the supervised methods evaluated with the Leaderboard set and reaches the second position in the ranking. Our variant based on the GHMRF achieves the first position in the Test ranking of the unsupervised approaches and the seventh position in the general Test ranking, which confirms the method as a viable alternative for brain tumour segmentation. PMID:25978453

Multimodal Navigation in Endoscopic Transsphenoidal Resection of Pituitary Tumors using Image-based Vascular and Cranial Nerve Segmentation: A Prospective Validation Study

Science.gov (United States)

Dolati, Parviz; Eichberg, Daniel; Golby, Alexandra; Zamani, Amir; Laws, Edward

2016-01-01

Introduction Transsphenoidal surgery (TSS) is a well-known approach for the treatment of pituitary tumors. However, lateral misdirection and vascular damage, intraoperative CSF leakage, and optic nerve and vascular injuries are all well-known complications, and the risk of adverse events is more likely in less experienced hands. This prospective study was conducted to validate the accuracy of image-based segmentation in localization of neurovascular structures during TSS. Methods Twenty-five patients with pituitary tumors underwent preoperative 3TMRI, which included thin-sectioned 3D space T2, 3D Time of Flight and MPRAGE sequences. Images were reviewed by an expert independent neuroradiologist. Imaging sequences were loaded in BrainLab iPlanNet (16/25 cases) or Stryker (9/25 cases) image guidance platforms for segmentation and pre-operative planning. After patient registration into the neuronavigation system and subsequent surgical exposure, each segmented neural or vascular element was validated by manual placement of the navigation probe on or as close as possible to the target. The audible pulsations of the bilateral ICA were confirmed using a micro-Doppler probe. Results Pre-operative segmentation of the ICA and cavernous sinus matched with the intra-operative endoscopic and micro-Doppler findings in all cases (Dice Similarity Coefficient =1). This information reassured the surgeons with regard to the lateral extent of bone removal at the sellar floor and the limits of lateral exploration. Excellent correspondence between image-based segmentation and the endoscopic view was also evident at the surface of the tumor and at the tumor-normal gland interfaces. This assisted in preventing unnecessary removal of the normal pituitary gland. Image-guidance assisted the surgeons in localizing the optic nerve and chiasm in 64% of the cases and the diaphragma sella in 52% of cases, which helped to determine the limits of upward exploration and to decrease the risk of CSF

A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation - With Application to Tumor and Stroke

DEFF Research Database (Denmark)

Menze, Bjoern H.; Van Leemput, Koen; Lashkari, Danial

2016-01-01

jointly from the image data. It delineates lesion areas individually in each channel, allowing for differences in lesion appearance across modalities, an important feature of many brain tumor imaging sequences. We also propose discriminative model extensions to map the output of the generative model......), to estimate the label map for a new image. Our model augments the probabilistic atlas of the healthy tissues with a latent atlas of the lesion. We derive an estimation algorithm with closed-form EM update equations. The method extracts a latent atlas prior distribution and the lesion posterior distributions...

An epidemiologic survey on brain tumors in Kerman from 1997 to 2001

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Hamed Reihani kermani

2004-09-01

Full Text Available Central nervous system tumors contain neoplastic and nonneoplastic lesions. Incidence of brain tumors has increased in all age groups in recent 20 years. Developments of medical devices such as CT scan, MRI and varying of classification are important causes of this raising. The present study evaluates epidemiology of brain tumors from 1997 to 2001 in Kerman. In a cross sectional study all files of neurosurgery department, in Kerman Bahonar Hospital and from 1997 to 2001, were inquired. Variables such as age, sex and histological considerations were evaluated. A total of 338 tumors were studied. The most common tumor was glial (35%, and meningioma was the second common tumor (26.3%. The other tumors were anaplastic astrocytoma, astrocytoma, pituitary adenoma, aucostic neorinoma, medulloblastoma, ependymoma, choroid plexus carcinoma, craniopharyngioma, lymphoma, sarcoma and anaplastic ependymoma. There was statistical significant difference between tumors and sex and age (p<0.05. Age and sex distribution of brain tumors is compatible with other studies in many countries. These findings suggest that prevalence of brain tumors in Kerman has increased in recent years because of diagnostic methods have improved and other medical devices are available.

Sigma and opioid receptors in human brain tumors

International Nuclear Information System (INIS)

Thomas, G.E.; Szuecs, M.; Mamone, J.Y.; Bem, W.T.; Rush, M.D.; Johnson, F.E.; Coscia, C.J.

1990-01-01

Human brain tumors and nude mouse-borne human neuroblastomas and gliomas were analyzed for sigma and opioid receptor content. Sigma binding was assessed using [ 3 H] 1, 3-di-o-tolylguanidine (DTG), whereas opioid receptor subtypes were measured with tritiated forms of the following: μ, [D-ala 2 , mePhe 4 , gly-ol 5 ] enkephalin (DAMGE); κ, ethylketocyclazocine (EKC) or U69,593; δ, [D-pen 2 , D-pen 5 ] enkephalin (DPDPE) or [D-ala 2 , D-leu 5 ] enkephalin (DADLE) with μ suppressor present. Binding parameters were estimated by homologous displacement assays followed by analysis using the LIGAND program. Sigma binding was detected in 15 of 16 tumors examined with very high levels found in a brain metastasis from an adenocarcinoma of lung and a human neuroblastoma (SK-N-MC) passaged in nude mice. κ opioid receptor binding was detected in 4 of 4 glioblastoma multiforme specimens and 2 of 2 human astrocytoma cell lines tested but not in the other brain tumors analyzed

Improving the accuracy of brain tumor surgery via Raman-based technology.

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Hollon, Todd; Lewis, Spencer; Freudiger, Christian W; Sunney Xie, X; Orringer, Daniel A

2016-03-01

Despite advances in the surgical management of brain tumors, achieving optimal surgical results and identification of tumor remains a challenge. Raman spectroscopy, a laser-based technique that can be used to nondestructively differentiate molecules based on the inelastic scattering of light, is being applied toward improving the accuracy of brain tumor surgery. Here, the authors systematically review the application of Raman spectroscopy for guidance during brain tumor surgery. Raman spectroscopy can differentiate normal brain from necrotic and vital glioma tissue in human specimens based on chemical differences, and has recently been shown to differentiate tumor-infiltrated tissues from noninfiltrated tissues during surgery. Raman spectroscopy also forms the basis for coherent Raman scattering (CRS) microscopy, a technique that amplifies spontaneous Raman signals by 10,000-fold, enabling real-time histological imaging without the need for tissue processing, sectioning, or staining. The authors review the relevant basic and translational studies on CRS microscopy as a means of providing real-time intraoperative guidance. Recent studies have demonstrated how CRS can be used to differentiate tumor-infiltrated tissues from noninfiltrated tissues and that it has excellent agreement with traditional histology. Under simulated operative conditions, CRS has been shown to identify tumor margins that would be undetectable using standard bright-field microscopy. In addition, CRS microscopy has been shown to detect tumor in human surgical specimens with near-perfect agreement to standard H & E microscopy. The authors suggest that as the intraoperative application and instrumentation for Raman spectroscopy and imaging matures, it will become an essential component in the neurosurgical armamentarium for identifying residual tumor and improving the surgical management of brain tumors.

Statistical segmentation of multidimensional brain datasets

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Desco, Manuel; Gispert, Juan D.; Reig, Santiago; Santos, Andres; Pascau, Javier; Malpica, Norberto; Garcia-Barreno, Pedro

2001-07-01

This paper presents an automatic segmentation procedure for MRI neuroimages that overcomes part of the problems involved in multidimensional clustering techniques like partial volume effects (PVE), processing speed and difficulty of incorporating a priori knowledge. The method is a three-stage procedure: 1) Exclusion of background and skull voxels using threshold-based region growing techniques with fully automated seed selection. 2) Expectation Maximization algorithms are used to estimate the probability density function (PDF) of the remaining pixels, which are assumed to be mixtures of gaussians. These pixels can then be classified into cerebrospinal fluid (CSF), white matter and grey matter. Using this procedure, our method takes advantage of using the full covariance matrix (instead of the diagonal) for the joint PDF estimation. On the other hand, logistic discrimination techniques are more robust against violation of multi-gaussian assumptions. 3) A priori knowledge is added using Markov Random Field techniques. The algorithm has been tested with a dataset of 30 brain MRI studies (co-registered T1 and T2 MRI). Our method was compared with clustering techniques and with template-based statistical segmentation, using manual segmentation as a gold-standard. Our results were more robust and closer to the gold-standard.

Aerobic Glycolysis as a Marker of Tumor Aggressiveness: Preliminary Data in High Grade Human Brain Tumors

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Andrei G. Vlassenko

2015-01-01

Full Text Available Objectives. Glucose metabolism outside of oxidative phosphorylation, or aerobic glycolysis (AG, is a hallmark of active cancer cells that is not directly measured with standard 18F-fluorodeoxyglucose (FDG positron emission tomography (PET. In this study, we characterized tumor regions with elevated AG defined based on PET measurements of glucose and oxygen metabolism. Methods. Fourteen individuals with high-grade brain tumors underwent structural MR scans and PET measurements of cerebral blood flow (CBF, oxygen (CMRO2 and glucose (CMRGlu metabolism, and AG, using 15O-labeled CO, O2 and H2O, and FDG, and were compared to a normative cohort of 20 age-matched individuals. Results. Elevated AG was observed in most high-grade brain tumors and it was associated with decreased CMRO2 and CBF, but not with significant changes in CMRGlu. Elevated AG was a dramatic and early sign of tumor growth associated with decreased survival. AG changes associated with tumor growth were differentiated from the effects of nonneoplastic processes such as epileptic seizures. Conclusions. Our findings demonstrate that high-grade brain tumors exhibit elevated AG as a marker of tumor growth and aggressiveness. AG may detect areas of active tumor growth that are not evident on conventional FDG PET.

Spread of edema with brain tumors

International Nuclear Information System (INIS)

Hosoya, Takaaki

1987-01-01

Cerebral edema associated with brain tumors is visualized on CT as a hypodensity lesion involving mainly the white matter. The detailed features of its evolution were investigated in a review of CT examinations performed on 56 patients with brain tumors, with the following results. 1. The susceptibility to edema varied according to the types of fibers. Association fibers were more sensitive to edema than projection and commissural fibers. 2. The edema had a characteristic of spreading along not only the association fibers but also the projection and commissural fibers. 3. The spread of edema along the association fibers was interupted in sites of convergence of the fibers such as the external capsule and just beneath the central sulcus in the certrum semiovale. 4. In some cases with intra-axial tumors, the edema extended mainly in the projection and commissural fibers considered to be more resistant to it. For example, in cases with parietal and temporal intra-axial tumors, the posterior limb of the internal capsule was often more edematous than the external capsule. 5. The edema associated with meningioma had a characteristic of spreading mainly along the association fibers. When situated close to the corpus callosum, however, the commissural fibers were also involved. Edema extending mainly in the internal capsule, thus, was rarely observed in meningioma. 6. There was unique pattern of spread of edema in frontal tumors, which differentiated their CT pattern. Therefore, the location of the tumor could be correctly diagnosed by the pattern of the edema extension, even near the central sulcus or in the operculum region. (author)

Brain tumor radiosurgery. Current status and strategies to enhance the effect of radiosurgery

International Nuclear Information System (INIS)

Niranjan, A.; Lunsford, L.D.; Gobbel, G.T.; Kondziolka, D.; Maitz, A.; Flickinger, J.C.

2000-01-01

First, the current status of brain tumor radiosurgery is reviewed, and radiosurgery for brain tumors, including benign tumors, malignant tumors, primary glial tumors, and metastatic tumors, is described. Rapid developments in neuroimaging, stereotactic techniques, and robotic technology in the last decade have contributed to improved results and wider applications of radiosurgery. Radiosurgery has become the preferred management modality for many intracranial tumors, including schwannomas, meningiomas, and metastatic tumors. Although radiosurgery provides survival benefits in patients with diffuse malignant brain tumors, cure is still not possible. Microscopic tumor infiltration into surrounding normal tissue is the main cause of recurrence. Additional strategies are needed to specifically target tumor cells. Next, strategies to enhance the effect of radiosurgery are reviewed. Whereas the long-term clinical results of radiosurgery have established its role in the treatment of benign tumors, additional strategies are needed to improve cell killing in malignant brain tumors and to protect normal surrounding brain. The first strategy included the use of various agents to protect normal brain while delivering a high dose to the tumor cells, but finding an effective radioprotective agent has been problematic. Pentobarbital and 21-aminosteroid (21-AS) are presented as examples. The second strategy for radiation protection aimed at the repair of radiation-induced damage to the normal brain. The cause of radiation-induced breakdown of normal tissue is unclear. The white matter and the cerebral vasculature appear to be particularly susceptible to radiation. Oligodendrocytes and endothelial cells may be critical targets of radiation. The authors hypothesize that radiation-induced damage to these cell types can be repaired by neural stem cells. They also describe the use of tumor necrosis factor alpha (TNF-alpha) and neural stem cells as a means of enhancing the effect of

Intelligence Deficits in Chinese Patients with Brain Tumor: The Impact of Tumor Resection

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Chao Shen

2013-01-01

Full Text Available Background. Intelligence is much important for brain tumor patients after their operation, while the reports about surgical related intelligence deficits are not frequent. It is not only theoretically important but also meaningful for clinical practice. Methods. Wechsler Adult Intelligence Scale was employed to evaluate the intelligence of 103 patients with intracranial tumor and to compare the intelligence quotient (IQ, verbal IQ (VIQ, and performance IQ (PIQ between the intracerebral and extracerebral subgroups. Results. Although preoperative intelligence deficits appeared in all subgroups, IQ, VIQ, and PIQ were not found to have any significant difference between the intracerebral and extracerebral subgroups, but with VIQ lower than PIQ in all the subgroups. An immediate postoperative follow-up demonstrated a decline of IQ and PIQ in the extracerebral subgroup, but an improvement of VIQ in the right intracerebral subgroup. Pituitary adenoma resection exerted no effect on intelligence. In addition, age, years of education, and tumor size were found to play important roles. Conclusions. Brain tumors will impair IQ, VIQ, and PIQ. The extracerebral tumor resection can deteriorate IQ and PIQ. However, right intracerebral tumor resection is beneficial to VIQ, and transsphenoidal pituitary adenoma resection performs no effect on intelligence.

Straight trajectory planning for keyhole neurosurgery in sheep with automatic brain structures segmentation

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Favaro, Alberto; Lad, Akash; Formenti, Davide; Zani, Davide Danilo; De Momi, Elena

2017-03-01

In a translational neuroscience/neurosurgery perspective, sheep are considered good candidates to study because of the similarity between their brain and the human one. Automatic planning systems for safe keyhole neurosurgery maximize the probe/catheter distance from vessels and risky structures. This work consists in the development of a trajectories planner for straight catheters placement intended to be used for investigating the drug diffusivity mechanisms in sheep brain. Automatic brain segmentation of gray matter, white matter and cerebrospinal fluid is achieved using an online available sheep atlas. Ventricles, midbrain and cerebellum segmentation have been also carried out. The veterinary surgeon is asked to select a target point within the white matter to be reached by the probe and to define an entry area on the brain cortex. To mitigate the risk of hemorrhage during the insertion process, which can prevent the success of the insertion procedure, the trajectory planner performs a curvature analysis of the brain cortex and wipes out from the poll of possible entry points the sulci, as part of brain cortex where superficial blood vessels are naturally located. A limited set of trajectories is then computed and presented to the surgeon, satisfying an optimality criteria based on a cost function which considers the distance from critical brain areas and the whole trajectory length. The planner proved to be effective in defining rectilinear trajectories accounting for the safety constraints determined by the brain morphology. It also demonstrated a short computational time and good capability in segmenting gyri and sulci surfaces.

Localized 31P magnetic resonance spectroscopy of large pediatric brain tumors

International Nuclear Information System (INIS)

Sutton, L.N.; Lenkinski, R.E.; Cohen, B.H.; Packer, R.J.; Zimmerman, R.A.

1990-01-01

Fourteen children aged 1 week to 16 years, with a variety of large or superficial brain tumors, underwent localized in vivo 31 P magnetic resonance spectroscopy of their tumor. Quantitative spectral analysis was performed by measuring the area under individual peaks using a computer algorithm. In eight patients with histologically benign tumors the spectra were considered to be qualitatively indistinguishable from normal brain. The phosphocreatine/inorganic phosphate ratio (PCr/Pi) averaged 2.0. Five patients had histologically malignant tumors; qualitatively, four of these were considered to have abnormal spectra, showing a decrease in the PCr peak. The PCr/Pi ratio for this group averaged 0.85, which was significantly lower than that seen in the benign tumor group (p less than 0.05). No difference between the two groups was seen in adenosine triphosphate or phosphomonoesters. It is concluded that a specific metabolic fingerprint for childhood brain tumors may not exist, but that some malignant tumors show a pattern suggestive of ischemia

Development and Implementation of a Corriedale Ovine Brain Atlas for Use in Atlas-Based Segmentation.

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Kishan Andre Liyanage

Full Text Available Segmentation is the process of partitioning an image into subdivisions and can be applied to medical images to isolate anatomical or pathological areas for further analysis. This process can be done manually or automated by the use of image processing computer packages. Atlas-based segmentation automates this process by the use of a pre-labelled template and a registration algorithm. We developed an ovine brain atlas that can be used as a model for neurological conditions such as Parkinson's disease and focal epilepsy. 17 female Corriedale ovine brains were imaged in-vivo in a 1.5T (low-resolution MRI scanner. 13 of the low-resolution images were combined using a template construction algorithm to form a low-resolution template. The template was labelled to form an atlas and tested by comparing manual with atlas-based segmentations against the remaining four low-resolution images. The comparisons were in the form of similarity metrics used in previous segmentation research. Dice Similarity Coefficients were utilised to determine the degree of overlap between eight independent, manual and atlas-based segmentations, with values ranging from 0 (no overlap to 1 (complete overlap. For 7 of these 8 segmented areas, we achieved a Dice Similarity Coefficient of 0.5-0.8. The amygdala was difficult to segment due to its variable location and similar intensity to surrounding tissues resulting in Dice Coefficients of 0.0-0.2. We developed a low resolution ovine brain atlas with eight clinically relevant areas labelled. This brain atlas performed comparably to prior human atlases described in the literature and to intra-observer error providing an atlas that can be used to guide further research using ovine brains as a model and is hosted online for public access.

Irradiated large segment allografts in limb saving surgery for extremity tumor - Philippine experience

International Nuclear Information System (INIS)

Wang, E.H.M.; Agcaoili, N.; Turqueza, M.S.

1999-01-01

Limb saving surgery has only recently become an option in the Phillipines. This has given a better comprehension of oncologic principles and from the refinement of bone-reconstruction procedures. Foremost among the latter is the use of large segment bone allografts. Large-segment allografts (LSA) are available from the Tissue and Bone Bank of the University of the Philippines (UP). After harvest, these bones are processed at the Bank, radiation-sterilized at the Philippine Nuclear Research Institute, and then stored in a -80 degree C deep freezer. We present our 4-year experience (Jan 93 - Dec 96) with LSA for limb saving surgery in musculoskeletal tumors. All patients included had: (1) malignant or aggressive extremity tumors; (2) surgery performed by the UP - Musculoskeletal Tumor Unit (UP-MUST Unit); (3) reconstructions utilizing irradiated large-segment allografts from the UP Tissue and Bone Bank; and (4) follow-up of at least one year or until death. Tumors included osteosarcoma (6) giant cell tumors (11), and metastatic lesions (3). Age ranged from 16-64 years old; 13 males and 7 females. Bones involved were the femur (12) tibia (5) and humerus (3). Average defect length was 15 cm and surgeries performed were intercalary replacement (5), resection arthrodesis (11), hemicondylar allograft (3), and allograft-prosthesis-composite (1). Follow-up ranged was from 17- 60 months or until death. Fifteen (1 5) were alive with NED (no evidence of disease), 3 were dead (2 of disease 1 of other causes), and 2 were AWED (alive with evidence of disease). Functional evaluation using the criteria of the International Society of Limb Salvage (ISOLS) was performed on 18 patients. This averaged 27.5 out of 30 points (92%) for 15 patients. Many having returned to their previous work and recreation. The 3 failures were due to infections in 2 cases (both of whom opted for amputations but who have not been fit with prostheses), and a fracture (secondary to a fall) in one case. Limb

Analysis of Brain Tumors Due to the Usage of Mobile Phones

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SOOBIA SAEED

2017-07-01

Full Text Available The impact of cellular phone radiation on human health is the subject of current mindfulness and is an outcome of the huge increase in phone usage throughout the world. Phones use electromagnetic radiation in the microwave range. The issue is associated with wireless use for 50 minutes and above. The excessive use of mobile phone may cause brain tumors. Nowadays the most commonly developed brain tumor type is GBM (Glioblastoma in multiform and Malignant Astrocytoma. In this paper, we focus on the causes of brain tumor (cancer due to the cell phone as this increase in glucose metabolism. The aim of the study is to address the aforementioned problems associated with the cell phone. MATLAB programming to detect a brain tumor has been used. We have conducted MRI (Magnetic Resonance Imaging study to get the best images and results.

Analysis of brain tumors due to the usage of mobile phones

International Nuclear Information System (INIS)

Saeed, S.; Noor, S.A.; Shaikh, A.

2017-01-01

The impact of cellular phone radiation on human health is the subject of current mindfulness and is an outcome of the huge increase in phone usage throughout the world. Phones use electromagnetic radiation in the microwave range. The issue is associated with wireless use for 50 minutes and above. The excessive use of mobile phone may cause brain tumors. Nowadays the most commonly developed brain tumor type is GBM (Glioblastoma) in multiform and Malignant Astrocytoma. In this paper, we focus on the causes of brain tumor (cancer) due to the cell phone as this increase in glucose metabolism. The aim of the study is to address the aforementioned problems associated with the cell phone. MATLAB programming to detect a brain tumor has been used. We have conducted MRI (Magnetic Resonance Imaging) study to get the best images and results. (author)

Evolution of Brain Tumor and Stability of Geometric Invariants

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K. Tawbe

2008-01-01

Full Text Available This paper presents a method to reconstruct and to calculate geometric invariants on brain tumors. The geometric invariants considered in the paper are the volume, the area, the discrete Gauss curvature, and the discrete mean curvature. The volume of a tumor is an important aspect that helps doctors to make a medical diagnosis. And as doctors seek a stable calculation, we propose to prove the stability of some invariants. Finally, we study the evolution of brain tumor as a function of time in two or three years depending on patients with MR images every three or six months.

Genetic and modifying factors that determine the risk of brain tumors

DEFF Research Database (Denmark)

Montelli, Terezinha de Cresci Braga; Peraçoli, Maria Terezinha Serrão; Rogatto, Silvia Regina

2011-01-01

of tumor escape, CNS tumor immunology, immune defects that impair anti-tumor systemic immunity in brain tumor patients and local immuno-suppressive factors within CNS are also reviewed. New hope to treatment perspectives, as dendritic-cell-based vaccines is summarized too. Concluding, it seems well...... responses can alert immune system. However, it is necessary to clarify if individuals with both constitutional defects in immune functions and genetic instability have higher risk of developing brain tumors. Cytogenetic prospective studies and gene copy number variations analysis also must be performed...

Occupational risk factors for brain tumors. A case-referent death-certificate analysis

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Thomas, T.L.; Fontham, E.T.; Norman, S.A.; Stemhagen, A.; Hoover, R.N.

1986-04-01

Numerous studies have suggested that employment in the oil refining and chemical manufacturing industries may be associated with excess brain tumor risk. A case-referent study was undertaken to evaluate brain tumor risk by occupation and industry in three geographic areas (northern New Jersey, Philadelphia, and the Gulf Coast of Louisiana) with a heavy concentration of these industries. Seven hundred and eighteen white men dying from brain tumor at age 30 years or older were ascertained from death certificates for 1978-1981. The referents were men who died of other causes, excluding epilepsy and stroke. Usual occupation and industry were obtained from the death certificates, and the maximum likelihood estimates of the relative risk were calculated for specific industries and occupations. Small nonsignificant excess risks of brain tumors were seen among persons whose usual employment was in the petroleum refining, electrical equipment manufacturing, health services, and educational services industries. Compared with other white-collar professionals, health diagnosticians, teachers, and artists/designers had a significantly elevated brain tumor risk. Among blue-collar workers, the only group with a significantly elevated brain tumor risk was precision metal workers, who are exposed to metal dusts and fumes and substances used as coolants, lubricants, and degreasers.

Recent technological advances in pediatric brain tumor surgery.

Science.gov (United States)

Zebian, Bassel; Vergani, Francesco; Lavrador, José Pedro; Mukherjee, Soumya; Kitchen, William John; Stagno, Vita; Chamilos, Christos; Pettorini, Benedetta; Mallucci, Conor

2017-01-01

X-rays and ventriculograms were the first imaging modalities used to localize intracranial lesions including brain tumors as far back as the 1880s. Subsequent advances in preoperative radiological localization included computed tomography (CT; 1971) and MRI (1977). Since then, other imaging modalities have been developed for clinical application although none as pivotal as CT and MRI. Intraoperative technological advances include the microscope, which has allowed precise surgery under magnification and improved lighting, and the endoscope, which has improved the treatment of hydrocephalus and allowed biopsy and complete resection of intraventricular, pituitary and pineal region tumors through a minimally invasive approach. Neuronavigation, intraoperative MRI, CT and ultrasound have increased the ability of the neurosurgeon to perform safe and maximal tumor resection. This may be facilitated by the use of fluorescing agents, which help define the tumor margin, and intraoperative neurophysiological monitoring, which helps identify and protect eloquent brain.

Cytokine Gene Polymorphisms in Egyptian Cases with Brain Tumors

International Nuclear Information System (INIS)

Badr El-Din, N.K.; Abdel-Hady, E.K.; Salem, F.K.; Settin, A.; ALI, N.

2009-01-01

Background: Cytokines are proposed to play important roles in brain tumor biology as well as neuro degeneration or impaired neuronal function. Objectives: This work aimed to check the association of polymorphisms of cytokine genes in Egyptian cases with brain tumors. Methods: This work included 45 cases affected by brain tumors diagnosed as 24 benign and 21 malignant. Their median age was 45 years, and they were 20 males and 25 females. These cases were taken randomly from the Neurosurgery Department of Mansoura University Hospital, Egypt. Case genotypes were compared to 98 healthy unrelated controls from the same locality. DNA was amplified using PCR utilizing sequence specific primers (SSP) for detection of polymorphisms related to TNF-a-308 (G/A), IL-10-1082 (G/A), IL-6-174 (G/C) and IL-1Ra (VNTR) genes. Results: Cases affected with benign brain tumors showed a significant higher frequency of IL-10-1082 A/A [odds ratio (OR=8.0), p<0.001] and IL-6-174 C/C (OR=6.3, p=0.002) homozygous genotypes as compared to controls. Malignant cases, on the other hand, showed significantly higher frequency of IL-6-174 C/C (OR =4.8, p=0.002) homozygous genotype and TNF-a-308 A/A (OR=4.9, p<0.001) homozygous genotype when compared to controls. In the meantime, all cases showed no significant difference regarding the distribution of IL-1Ra VNTR genotype polymorphism compared to controls. Conclusions: Cytokine gene polymorphisms showed a pattern of association with brain tumors which may have potential impact on family counseling and disease management.

Local appearance features for robust MRI brain structure segmentation across scanning protocols

DEFF Research Database (Denmark)

Achterberg, H.C.; Poot, Dirk H. J.; van der Lijn, Fedde

2013-01-01

Segmentation of brain structures in magnetic resonance images is an important task in neuro image analysis. Several papers on this topic have shown the benefit of supervised classification based on local appearance features, often combined with atlas-based approaches. These methods require...... a representative annotated training set and therefore often do not perform well if the target image is acquired on a different scanner or with a different acquisition protocol than the training images. Assuming that the appearance of the brain is determined by the underlying brain tissue distribution...... with substantially different imaging protocols and on different scanners. While a combination of conventional appearance features trained on data from a different scanner with multiatlas segmentation performed poorly with an average Dice overlap of 0.698, the local appearance model based on the new acquisition...

Life satisfaction in adult survivors of childhood brain tumors.

Science.gov (United States)

Crom, Deborah B; Li, Zhenghong; Brinkman, Tara M; Hudson, Melissa M; Armstrong, Gregory T; Neglia, Joseph; Ness, Kirsten K

2014-01-01

Adult survivors of childhood brain tumors experience multiple, significant, lifelong deficits as a consequence of their malignancy and therapy. Current survivorship literature documents the substantial impact such impairments have on survivors' physical health and quality of life. Psychosocial reports detail educational, cognitive, and emotional limitations characterizing survivors as especially fragile, often incompetent, and unreliable in evaluating their circumstances. Anecdotal data suggest some survivors report life experiences similar to those of healthy controls. The aim of our investigation was to determine whether life satisfaction in adult survivors of childhood brain tumors differs from that of healthy controls and to identify potential predictors of life satisfaction in survivors. This cross-sectional study compared 78 brain tumor survivors with population-based matched controls. Chi-square tests, t tests, and linear regression models were used to investigate patterns of life satisfaction and identify potential correlates. Results indicated that life satisfaction of adult survivors of childhood brain tumors was similar to that of healthy controls. Survivors' general health expectations emerged as the primary correlate of life satisfaction. Understanding life satisfaction as an important variable will optimize the design of strategies to enhance participation in follow-up care, reduce suffering, and optimize quality of life in this vulnerable population. © 2014 by Association of Pediatric Hematology/Oncology Nurses.

Gamma knife treatment of pediatric brain tumors

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Kobayashi, Tatsuya; Kida, Yoshihisa; Tanaka, Takayuki; Oyama, Hirofumi (Komaki City Hospital, Hokkaido (Japan))

1994-02-01

Gamma knife radiosurgery was performed on 386 patients with intracranial lesions at Komaki City Hospital from May 1991 through December 1992. Forty three of the patients were under 15 years of age. Twenty six patients had arteriovenous malformations and 17 had brain tumors: 9 gliomas and 8 non-gliomatous tumors. The gliomas included 3 ependymomas, 2 benign astrocytomas, one ganglioglioma, one oligodendroglioma; one medulloblastoma and one glioblastoma multiforme. The non-gliomatous tumors included 3 pineal tumors, 2 craniopharyngiomas, 2 acoustic neurinomas, and one C-P angle epidermoid tumor. The male/female ratio was 12:5 and the mean diameter of the tumors was 19.3 mm. They were treated with a mean maximum dose of 32.5 Gy and a marginal dose of 17.1 Gy with a mean isocenter number of 4.9. The early results of single session treatment with Gamma knife of pediatric brain tumors were evaluated by repeated MRIs and changes of neurological signs during a mean follow-up period of 6.4 months. It was found that 5 of the 17 responded to treatment (29.5%), with partical response (PR) in 2 with craniopharyngioma and one with ganglioglioma. Central necrosis (CN) was present with optic glioma and one with neurinoma. In three patients (17.6%) the treatment was not effective. One with medulloblastoma and one with glioblastoma died at 4 and 6 months and the one with ependymoma was reoperated on after 3 months because of progression of the tumor (PG). The other nine patients (52.9%) were unchanged (NC). We must follow more patients to determine the effectiveness of gamma radiosurgery on these tumors. (author).

Expression and activity of the urokinase plasminogen activator system in canine primary brain tumors

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Rossmeisl JH

2017-04-01

Full Text Available John H Rossmeisl,1–3 Kelli Hall-Manning,4 John L Robertson,1,3,5 Jamie N King,1,2 Rafael V Davalos,3,5 Waldemar Debinski,3 Subbiah Elankumaran6,† 1Veterinary and Comparative Neuro-Oncology Laboratory, 2Department of Small Animal Clinical Sciences, 3The Brain Tumor Center of Excellence, Wake Forest Baptist Medical Center Comprehensive Cancer Center, Winston-Salem, NC, 4Virginia Tech Animal Laboratory Services, Virginia-Maryland College of Veterinary Medicine, 5Department of Biomedical Engineering and Mechanics, Virginia Tech-Wake Forest University School of Biomedical Engineering and Sciences, Virginia Tech, 6Department of Biomedical Sciences and Pathobiology, Virginia-Maryland College of Veterinary Medicine, Blacksburg, VA, USA†The authors regret to advise of the passing of Dr Subbiah Elankumaran prior to publicationBackground: The expression of the urokinase plasminogen activator receptor (uPAR, a glycosylphosphatidylinositol-anchored protein family member, and the activity of its ligand, urokinase-type plasminogen activator (uPA, have been associated with the invasive and metastatic potentials of a variety of human brain tumors through their regulation of extracellular matrix degradation. Domesticated dogs develop naturally occurring brain tumors that share many clinical, phenotypic, molecular, and genetic features with their human counterparts, which has prompted the use of the dogs with spontaneous brain tumors as models to expedite the translation of novel brain tumor therapeutics to humans. There is currently little known regarding the role of the uPA system in canine brain tumorigenesis. The objective of this study was to characterize the expression of uPAR and the activity of uPA in canine brain tumors as justification for the development of uPAR-targeted brain tumor therapeutics in dogs.Methods: We investigated the expression of uPAR in 37 primary canine brain tumors using immunohistochemistry, Western blotting, real

Characterization of TEM1/endosialin in human and murine brain tumors

International Nuclear Information System (INIS)

Carson-Walter, Eleanor B; Walter, Kevin A; Winans, Bethany N; Whiteman, Melissa C; Liu, Yang; Jarvela, Sally; Haapasalo, Hannu; Tyler, Betty M; Huso, David L; Johnson, Mahlon D

2009-01-01

TEM1/endosialin is an emerging microvascular marker of tumor angiogenesis. We characterized the expression pattern of TEM1/endosialin in astrocytic and metastatic brain tumors and investigated its role as a therapeutic target in human endothelial cells and mouse xenograft models. In situ hybridization (ISH), immunohistochemistry (IH) and immunofluorescence (IF) were used to localize TEM1/endosialin expression in grade II-IV astrocytomas and metastatic brain tumors on tissue microarrays. Changes in TEM1/endosialin expression in response to pro-angiogenic conditions were assessed in human endothelial cells grown in vitro. Intracranial U87MG glioblastoma (GBM) xenografts were analyzed in nude TEM1/endosialin knockout (KO) and wildtype (WT) mice. TEM1/endosialin was upregulated in primary and metastatic human brain tumors, where it localized primarily to the tumor vasculature and a subset of tumor stromal cells. Analysis of 275 arrayed grade II-IV astrocytomas demonstrated TEM1/endosialin expression in 79% of tumors. Robust TEM1/endosialin expression occurred in 31% of glioblastomas (grade IV astroctyomas). TEM1/endosialin expression was inversely correlated with patient age. TEM1/endosialin showed limited co-localization with CD31, αSMA and fibronectin in clinical specimens. In vitro, TEM1/endosialin was upregulated in human endothelial cells cultured in matrigel. Vascular Tem1/endosialin was induced in intracranial U87MG GBM xenografts grown in mice. Tem1/endosialin KO vs WT mice demonstrated equivalent survival and tumor growth when implanted with intracranial GBM xenografts, although Tem1/endosialin KO tumors were significantly more vascular than the WT counterparts. TEM1/endosialin was induced in the vasculature of high-grade brain tumors where its expression was inversely correlated with patient age. Although lack of TEM1/endosialin did not suppress growth of intracranial GBM xenografts, it did increase tumor vascularity. The cellular localization of TEM1

Targeting brain tumor cAMP: the case for sex-specific therapeutics

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Nicole M Warrington

2015-07-01

Full Text Available A relationship between cyclic adenosine 3’, 5’-monophosphate (cAMP levels and brain tumor biology has been evident for nearly as long as cAMP and its synthetase, adenylate cyclase (ADCY have been known. The importance of the pathway in brain tumorigenesis has been demonstrated in vitro and in multiple animal models. Recently, we provided human validation for a cooperating oncogenic role for cAMP in brain tumorigenesis when we found that SNPs in ADCY8 were correlated with glioma (brain tumor risk in individuals with Neurofibromatosis type 1 (NF1. Together, these studies provide a strong rationale for targeting cAMP in brain tumor therapy. However, the cAMP pathway is well known to be sexually dimorphic, and SNPs in ADCY8 affected glioma risk in a sex-specific fashion, elevating the risk for females while protecting males. The cAMP pathway can be targeted at multiple levels in the regulation of its synthesis and degradation. Sex differences in response to drugs that target cAMP regulators indicate that successful targeting of the cAMP pathway for brain tumor patients is likely to require matching specific mechanisms of drug action with patient sex.

Segmentation of Brain MRI Using SOM-FCM-Based Method and 3D Statistical Descriptors

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Andrés Ortiz

2013-01-01

Full Text Available Current medical imaging systems provide excellent spatial resolution, high tissue contrast, and up to 65535 intensity levels. Thus, image processing techniques which aim to exploit the information contained in the images are necessary for using these images in computer-aided diagnosis (CAD systems. Image segmentation may be defined as the process of parcelling the image to delimit different neuroanatomical tissues present on the brain. In this paper we propose a segmentation technique using 3D statistical features extracted from the volume image. In addition, the presented method is based on unsupervised vector quantization and fuzzy clustering techniques and does not use any a priori information. The resulting fuzzy segmentation method addresses the problem of partial volume effect (PVE and has been assessed using real brain images from the Internet Brain Image Repository (IBSR.

Quantitative imaging of magnesium distribution at single-cell resolution in brain tumors and infiltrating tumor cells with secondary ion mass spectrometry (SIMS)

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Chandra, Subhash; Parker, Dylan J.; Barth, Rolf F.; Pannullo, Susan C.

2016-01-01

Glioblastoma multiforme (GBM) is one of the deadliest forms of human brain tumors. The infiltrative pattern of growth of these tumors includes the spread of individual and/or clusters of tumor cells at some distance from the main tumor mass in parts of the brain protected by an intact blood-brain-barrier. Pathophysiological studies of GBM could be greatly enhanced by analytical techniques capable of in situ single-cell resolution measurements of infiltrating tumor cells. Magnesium homeostasis is an area of active investigation in high grade gliomas. In the present study, we have used the F98 rat glioma as a model of human GBM and an elemental/isotopic imaging technique of secondary ion mass spectrometry (SIMS), a CAMECA IMS-3f ion microscope, for studying Mg distributions with single-cell resolution in freeze-dried brain tissue cryosections. Quantitative observations were made on tumor cells in the main tumor mass, contiguous brain tissue, and infiltrating tumor cells in adjacent normal brain. The brain tissue contained a significantly lower total Mg concentration of 4.70 ± 0.93 mmol/Kg wet weight (mean ± SD) in comparison to 11.64 ± 1.96 mmol/Kg wet weight in tumor cells of the main tumor mass and 10.72 ± 1.76 mmol/Kg wet weight in infiltrating tumor cells (p<0.05). The nucleus of individual tumor cells contained elevated levels of bound Mg. These observations demonstrate enhanced Mg-influx and increased binding of Mg in tumor cells and provide strong support for further investigation of GBMs for altered Mg homeostasis and activation of Mg-transporting channels as possible therapeutic targets. PMID:26703785

The unique case-report of metachronous brain tumors of different histology

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А. М. Zaitsev

2013-01-01

Full Text Available  The case of unusual course of brain tumor process – metachronous development of breast cancer brain metastasis and then development of malignant glioma is reported. The surgical treatment for both tumors were performed with intraoperative fluorescence diagnosis and photodynamic therapy. Due to multimodality treatment the patient was alive for 15 months from diagnosis of IV stage breast cancer (brain metastasis. 

[Positron emission tomography in the diagnosis of recurrent growth of brain tumors].

Science.gov (United States)

Skvortsova, T Iu; Brodskaia, Z L; Rudas, M S; Mozhaev, S V; Gurchin, A F; Medvedev, S V

2005-01-01

The authors analyzed the results of 11C-methionine positron emission tomography (PET) in 101 patients with suspected recurrent brain tumor. The diagnosis was confirmed in 72 patients. The increased 11C-methionine uptake in the initial tumor area is considered to be a crucial PET evidence of a recurrent tumor. On the other hand, brain tissue histological changes associated with surgery, radiation, and chemotherapy were characterized by the low uptake of the tracer. The sensitivity and specificity of PET scanning in detecting tumor recurrence were found to be 95.8 and 96.5%, respectively. 11C-methionine PET is proposed as a reliable technique for early differentiating between a recurrent brain tumor and treatment-induced nonneoplastic changes.

Regional cerebral blood flow in various types of brain tumor. Effect of the space-occupying lesion on blood flow in brain tissue close to and remote from tumor site

DEFF Research Database (Denmark)

Kuroda, K; Skyhøj Olsen, T; Lassen, N A

1982-01-01

Regional cerebral blood flow (rCBF) was measured in 23 patients with brain tumors using the 133Xe intra-carotid injection method and a 254 channel gamma camera. The glioblastomas (4) and astrocytomas (4) all showed hyperemia in the tumor and tumor-near region. This was also seen in several...... meningiomas (4 of 7 cases) in which most of the tumor itself did not receive any isotope. Brain metastases (6) usually had a low flow in the tumor and tumor-near region. The glioblastomas tended to show markedly bending 133Xe wash-out curves pointing to pronounced heterogeneity of blood flow. Most of the flow...... maps, regardless of the tumor types, showed widespread abnormalities of rCBF not only in the tumor region but also in the region remote from the tumor. It is concluded that measurement of rCBF cannot yield accurate differential diagnostic information, but that the widespread derangement of the brain...

Microvessel organization and structure in experimental brain tumors: microvessel populations with distinctive structural and functional properties.

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Schlageter, K E; Molnar, P; Lapin, G D; Groothuis, D R

1999-11-01

We studied microvessel organization in five brain tumor models (ENU, MSV, RG-2, S635cl15, and D-54MG) and normal brain, including microvessel diameter (LMVD), intermicrovessel distance (IMVD), microvessel density (MVD), surface area (S(v)), and orientation. LMVD and IMVD were larger and MVD was lower in tumors than normal brain. S(v) in tumors overlapped normal brain values and orientation was random in both tumors and brain. ENU and RG-2 tumors and brain were studied by electron microscopy. Tumor microvessel wall was thicker than that of brain. ENU and normal brain microvessels were continuous and nonfenestrated. RG-2 microvessels contained fenestrations and endothelial gaps; the latter had a maximum major axis of 3.0 microm. Based on anatomic measurements, the pore area of RG-2 tumors was estimated at 7.4 x 10(-6) cm(2) g(-1) from fenestrations and 3.5 x 10(-5) cm(2) g(-1) from endothelial gaps. Increased permeability of RG-2 microvessels to macromolecules is most likely attributable to endothelial gaps. Three microvessel populations may occur in brain tumors: (1) continuous nonfenestrated, (2) continuous fenestrated, and (3) discontinuous (with or without fenestrations). The first group may be unique to brain tumors; the latter two are similar to microvessels found in systemic tumors. Since structure-function properties of brain tumor microvessels will affect drug delivery, studies of microvessel function should be incorporated into clinical trials of brain tumor therapy, especially those using macromolecules. Copyright 1999 Academic Press.

A neuropathology-based approach to epilepsy surgery in brain tumors and proposal for a new terminology use for long-term epilepsy-associated brain tumors

NARCIS (Netherlands)

Blumcke, Ingmar; Aronica, Eleonora; Urbach, Horst; Alexopoulos, Andreas; Gonzalez-Martinez, Jorge A.

2014-01-01

Every fourth patient submitted to epilepsy surgery suffers from a brain tumor. Microscopically, these neoplasms present with a wide-ranging spectrum of glial or glio-neuronal tumor subtypes. Gangliogliomas (GG) and dysembryoplastic neuroepithelial tumors (DNTs) are the most frequently recognized

Sigma and opioid receptors in human brain tumors

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Thomas, G.E.; Szuecs, M.; Mamone, J.Y.; Bem, W.T.; Rush, M.D.; Johnson, F.E.; Coscia, C.J. (St. Louis Univ. School of Medicine, MO (USA))

1990-01-01

Human brain tumors and nude mouse-borne human neuroblastomas and gliomas were analyzed for sigma and opioid receptor content. Sigma binding was assessed using ({sup 3}H) 1, 3-di-o-tolylguanidine (DTG), whereas opioid receptor subtypes were measured with tritiated forms of the following: {mu}, (D-ala{sup 2}, mePhe{sup 4}, gly-ol{sup 5}) enkephalin (DAMGE); {kappa}, ethylketocyclazocine (EKC) or U69,593; {delta}, (D-pen{sup 2}, D-pen{sup 5}) enkephalin (DPDPE) or (D-ala{sup 2}, D-leu{sup 5}) enkephalin (DADLE) with {mu} suppressor present. Binding parameters were estimated by homologous displacement assays followed by analysis using the LIGAND program. Sigma binding was detected in 15 of 16 tumors examined with very high levels found in a brain metastasis from an adenocarcinoma of lung and a human neuroblastoma (SK-N-MC) passaged in nude mice. {kappa} opioid receptor binding was detected in 4 of 4 glioblastoma multiforme specimens and 2 of 2 human astrocytoma cell lines tested but not in the other brain tumors analyzed.

Clinical study on brain tumors in the aged

International Nuclear Information System (INIS)

Teramoto, Akira; Manaka, Shinya; Takakura, Kintomo

1981-01-01

In order to investigate the clinical features and the prognosis of brain tumors in the aged, 132 cases over 60 years of age were studied from the consecutive series of 1,793 brain tumors in the University of Tokyo Hospital (1963 - 1979). The incidence of brain tumors in the aged was 7.4% on the whole, while it showed a significant increase from 4.8% (1960's) to 11.5% (the later half of 1970's). Histologically, meningiomas were the most common tumors (26%), followed by neurinomas (17%), pituitary adenomas (16%) and metastatic tumors (15%). Malignant gliomas were found more frequently than benign ones. There were more meningiomas as age advanced. The proportion and the number of meningioma cases has obviously increased in recent years when CT scanners became available. Symptoms of intracranial hypertention were found less frequently in aged patients although they were still common in cases of glioblastomas. The duration from onset to surgery was relatively long, especially in cases of neurinomas and pituitary adenomas. Two cases of astrocytomas belonged to the category of silent gliomas. Overall operative mortality rate was 10.6%, while it showed a marked decrease to 4.7% in the 1970's. Five-year survival rates were as follows: meningiomas (58%), pituitary adenomas (70%), neurinomas (80%), glioblastomas (20%) and astrocytomas (25%). As for functional prognoses, 30% of the patients showed poor states on ADL, mostly because of residual psychic disorders. (author)

Intracarotid injection of 195mPt-CDDP on rat brain tumors

International Nuclear Information System (INIS)

Ikawa, Eishi; Kamitani, Hideki; Hori, Tomokatsu; Akaboshi, Mitsuhiko.

1995-01-01

We began to try intracarotid injection of 195m Pt-CDDP on transplanted rats of C6 glioma. As a control, normal rats were also treated with intracarotid injection of 195m Pt-CDDP. After injection, the tumor, the normal brain of injected site, the brain of contralateral site, and the blood were sampled for the measurement of the Pt uptake. On normal rats, the ratio of the Pt uptake of the brain to that of the blood was highest in 20 minutes after injection. The ratio of the Pt uptake of the brain of injected site to that of the blood was almost same as that of the brain of contralateral site, so it seemed that the Pt uptake was not so enhanced with intracarotid injection on the normal brain. On the other hand, the ratio of the Pt uptake of the transplanted brain tumor to that of the blood was greatly higher than that of the normal brain. So it seemed that the intracarotid injection of CDDP may have some activities against brain tumors. This study was now started, so we continue this study further more. (author)

Identification of microRNA signature in different pediatric brain tumors.

Science.gov (United States)

Tantawy, Marwa; Elzayat, Mariam G; Yehia, Dina; Taha, Hala

2018-01-01

Understanding pediatric brain tumor biology is essential to help on disease stratification, and to find novel markers for early diagnosis. MicroRNA (miRNA) expression has been linked to clinical outcomes and tumor biology. Here, we aimed to detect the expression of different miRNAs in different pediatric brain tumor subtypes to discover biomarkers for early detection and develop novel therapies. Expression of 82 miRNAs was detected in 120 pediatric brain tumors from fixed-formalin paraffin-embedded tissues, low-grade glioma, high-grade glioma, ependymoma, and medulloblastoma, using quantitative real-time PCR. Low-expression of miR-221, miR-9, and miR-181c/d and over-expression of miR-101, miR-222, miR-139, miR-1827, and miR-34c was found in medulloblastoma; low expression of miR-10a and over-expression of miR-10b and miR-29a in ependymoma; low expression of miR-26a and overexpression of miR-19a/b, miR-24, miR-27a, miR- 584, and miR-527 in low-grade glioma. Cox regression showed differential miRNA expression between responders and non-responders. The most specific were miR-10a and miR-29a low expression in LGG non-responders, miR-135a and miR-146b over-expression in ependymoma non-responders, and miR-135b overexpression in medulloblastoma non-responders. MicroRNAs are differentially expressed in subtypes of brain tumors suggesting that they may help diagnosis. A greater understanding of aberrant miRNA in pediatric brain tumors may support development of novel therapies.

Measurement of P-31 MR relaxation times and concentrations in human brain and brain tumors

International Nuclear Information System (INIS)

Roth, K.; Naruse, S.; Hubesch, B.; Gober, I.; Lawry, T.; Boska, M.; Matson, G.B.; Weiner, M.W.

1987-01-01

Measurements of high-energy phosphates and pH were made in human brain and brain tumors using P-31 MR imaging. Using a Philips Gyroscan 1.5-T MRMRS, MR images were used to select a cuboidal volume of interest and P-31 MR spectra were obtained from that volume using the ISIS technique. An external quantitation standard was used. T 1 s were measured by inversion recovery. Quantitative values for metabolites were calculated using B 1 field plot of the head coil. The results for normal brain phosphates are as follows; adenosine triphosphate, 2.2 mM; phosphocreatin, 5.3 mM; inorganic phosphate, 1.6 mM. Preliminary studies with human brain tumors show a decrease of all phosphate compounds. These experiments are the first to quantitate metabolites in human brain

Comparison of resilience in adolescent survivors of brain tumors and healthy adolescents.

Science.gov (United States)

Chen, Chin-Mi; Chen, Yueh-Chih; Wong, Tai-Tong

2014-01-01

Resilience is essential for the psychological adjustment of adolescents experiencing difficulty. Comparing differences in resilience between adolescent survivors of brain tumors and healthy adolescents may help identify factors related to resilience in adolescents. The purpose of this study was to clarify how illness impacts the normative development of adolescent survivors of brain tumors by comparing them to healthy adolescents in terms of resilience and how it is affected by various health problems. This cross-sectional, case-control study used convenience sampling to recruit 13- to 18-year-old adolescent survivors of brain tumors and healthy adolescents matched by school level, gender, and living area. Data were collected by structured questionnaires. The sample included 60 adolescent survivors and 120 healthy adolescents. Participants in both groups were predominantly male adolescents (63.3%) and junior high school students (55%). The 2 groups did not differ significantly in resilience, but survivors without emotional problems had a higher mean resilience score than did healthy adolescents and survivors with emotional problems (F = 8.65, P adolescent survivors of brain tumors and healthy adolescents. In addition, the impact of emotional problems on resilience was more severe in brain tumor survivors than in healthy adolescents. Our results suggest that pediatric oncology nurses design interdisciplinary school-based interventions to reduce the impact of emotional problems on resilience in both healthy adolescents and those who survived brain tumors.

Brain tumors in children: long-term survival after radiation treatment

Energy Technology Data Exchange (ETDEWEB)

Jenkin, Derek; Greenberg, Mark; Hoffman, Harold; Hendrick, Bruce; Humphreys, Robin; Vatter, Annette

1995-02-01

Purpose: To determine the cause of death in children who survive more than 5 years after radiation treatment of a brain tumor. Methods and Material: Nine hundred and twelve consecutive children with a primary brain tumor irradiated at the Princess Margaret Hospital or Toronto-Bayview Regional Cancer Center from 1958 to 1991, were evaluated for long-term outcome. Results: Overall 10- and 20-year survival rates were 44% and 37%. Subsequent survival of 377 5-year survivors was, at an additional 10 and 20 years, 78% and 67%. Most (83%) deaths that occurred more than 5 years from diagnosis were a result of relapse of the original tumor. The 10-year survival rate subsequent to relapse was 9% when the first relapse occurred less than one year from diagnosis, 17% for 1-2 years, and 31% when the time to relapse was 3 years or greater. The cumulative actuarial incidence of, and death from, second malignant tumors at 30 years from diagnosis was 18% and 13%, respectively. Conclusions: Death later than 5 years from diagnosis of a brain tumor in children is common and is usually due to progressive disease in slowly evolving low grade tumors. Death from a second malignant tumor becomes more frequent than death from the original tumor after 15 years from diagnosis.

Fetal antigen 2 in primary and secondary brain tumors

DEFF Research Database (Denmark)

Rasmussen, H Boje; Teisner, B; Schrøder, H D

1991-01-01

Immunohistochemical deposition and distribution of fetal antigen 2 (FA2) was examined in normal brain tissue and in primary and metastatic tumors of the brain. In normal brain tissue FA2 was exclusively found linearly around the vessels, along pia and in arachnoidea. A similar localization was seen...

Awake craniotomy for brain tumor: indications, technique and benefits.

Science.gov (United States)

Dziedzic, Tomasz; Bernstein, Mark

2014-12-01

Increasing interest in the quality of life of patients after treatment of brain tumors has led to the exploration of methods that can improve intraoperative assessment of neurological status to avoid neurological deficits. The only method that can provide assessment of all eloquent areas of cerebral cortex and white matter is brain mapping during awake craniotomy. This method helps ensure that the quality of life and the neuro-oncological result of treatment are not compromised. Apart from the medical aspects of awake surgery, its economic issues are also favorable. Here, we review the main aspects of awake brain tumor surgery. Neurosurgical, neuropsychological, neurophysiological and anesthetic issues are briefly discussed.

Sequential computed tomographic imaging of a transplantable rabbit brain tumor

International Nuclear Information System (INIS)

Kumar, A.J.; Rosenbaum, A.E.; Beck, T.J.; Ahn, H.S.; Anderson, J.

1986-01-01

The accuracy of CT imaging in evaluating VX-2 tumor growth in the rabbit brain was assessed. CT scanning was performed in 5 outbred New Zealand white male rabbits before and at 4, 7, 9 and 13 (in 3 animals) days after surgical implantation of 3 x 10 5 viable VX-2 tumor cells in the frontoparietal lobes. The CT studies were correlated with gross pathology in each. The tumor was visualized with CT in all 5 rabbits by the 9th day post implantation when the tumor ranged in size from 4-6 x 3-4 x 2-3 mm. Between the 9th and 13th day, the tumor increased 6-fold in two rabbits and 12-fold in the third rabbit. CT is a useful technique to evaluate brain tumor growth in this model and should be valuable in documenting the efficacy of chemotherapy on tumor growth. (orig.)

Optimized performance of flight Plan during chemoembolization for hepatocellular carcinoma: Importance of the proportion of segmented tumor area

Energy Technology Data Exchange (ETDEWEB)

Joo, Seung Moon; Kim, Yong Pyo; Yum, Tae Jun; Eun, Na Lae; Lee, Da Hye; Lee, Kwang Hun [Dept. of Radiology, Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of)

2016-09-15

To evaluate retrospectively the clinical effectiveness of Flight Plan for Liver (FPFL), an automated tumor-feeding artery detection software in cone-beam CT angiography (CBCTA), in identifying tumor-feeding arteries for the treatment of hepatocellular carcinoma (HCC) using three different segmentation sensitivities. The study included 50 patients with 80 HCC nodules who received transarterial chemoembolization. Standard digital subtracted angiography (DSA) and CBCTA were systematically performed and analyzed. Three settings of the FPFL software for vascular tree segmentation were tested for each tumor: the default, Group D; adjusting the proportion of segmented tumor area between 30 to 50%, Group L; and between 50 to 80%, Group H. In total, 109 feeder vessels supplying 80 HCC nodules were identified. The negative predictive value of DSA, FPFL in groups D, L, and H was 56.8%, 87.7%, 94.2%, 98.5%, respectively. The accuracy of DSA, FPFL in groups D, L, and H was 62.6%, 86.8%, 93.4%, 95.6%, respectively. The sensitivity, negative predictive value (NPV), and accuracy of FPFL were higher in Group H than in Group D (p = 0.041, 0.034, 0.005). All three segmentation sensitivity groups showed higher specificity, positive predictive value, NPV, and accuracy of FPFL, as compared to DSA. FlightPlan for Liver is a valuable tool for increasing detection of HCC tumor feeding vessels, as compared to standard DSA analysis, particularly in small HCC. Manual adjustment of segmentation sensitivity improves the accuracy of FPFL.

Optimized Performance of FlightPlan during Chemoembolization for Hepatocellular Carcinoma: Importance of the Proportion of Segmented Tumor Area

Energy Technology Data Exchange (ETDEWEB)

Joo, Seung-Moon; Kim, Yong Pyo; Yum, Tae Jun; Eun, Na Lae; Lee, Dahye; Lee, Kwang-Hun [Department of Radiology, Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul 06273 (Korea, Republic of)

2016-11-01

To evaluate retrospectively the clinical effectiveness of FlightPlan for Liver (FPFL), an automated tumor-feeding artery detection software in cone-beam CT angiography (CBCTA), in identifying tumor-feeding arteries for the treatment of hepatocellular carcinoma (HCC) using three different segmentation sensitivities. The study included 50 patients with 80 HCC nodules who received transarterial chemoembolization. Standard digital subtracted angiography (DSA) and CBCTA were systematically performed and analyzed. Three settings of the FPFL software for vascular tree segmentation were tested for each tumor: the default, Group D; adjusting the proportion of segmented tumor area between 30 to 50%, Group L; and between 50 to 80%, Group H. In total, 109 feeder vessels supplying 80 HCC nodules were identified. The negative predictive value of DSA, FPFL in groups D, L, and H was 56.8%, 87.7%, 94.2%, 98.5%, respectively. The accuracy of DSA, FPFL in groups D, L, and H was 62.6%, 86.8%, 93.4%, 95.6%, respectively. The sensitivity, negative predictive value (NPV), and accuracy of FPFL were higher in Group H than in Group D (p = 0.041, 0.034, 0.005). All three segmentation sensitivity groups showed higher specificity, positive predictive value, NPV, and accuracy of FPFL, as compared to DSA. FlightPlan for Liver is a valuable tool for increasing detection of HCC tumor feeding vessels, as compared to standard DSA analysis, particularly in small HCC. Manual adjustment of segmentation sensitivity improves the accuracy of FPFL.

Label-free imaging of brain and brain tumor specimens with combined two-photon excited fluorescence and second harmonic generation microscopy

Science.gov (United States)

Jiang, Liwei; Wang, Xingfu; Wu, Zanyi; Du, Huiping; Wang, Shu; Li, Lianhuang; Fang, Na; Lin, Peihua; Chen, Jianxin; Kang, Dezhi; Zhuo, Shuangmu

2017-10-01

Label-free imaging techniques are gaining acceptance within the medical imaging field, including brain imaging, because they have the potential to be applied to intraoperative in situ identifications of pathological conditions. In this paper, we describe the use of two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) microscopy in combination for the label-free detection of brain and brain tumor specimens; gliomas. Two independently detecting channels were chosen to subsequently collect TPEF/SHG signals from the specimen to increase TPEF/SHG image contrasts. Our results indicate that the combined TPEF/SHG microscopic techniques can provide similar rat brain structural information and produce a similar resolution like conventional H&E staining in neuropathology; including meninges, cerebral cortex, white-matter structure corpus callosum, choroid plexus, hippocampus, striatum, and cerebellar cortex. It can simultaneously detect infiltrating human brain tumor cells, the extracellular matrix collagen fiber of connective stroma within brain vessels and collagen depostion in tumor microenvironments. The nuclear-to-cytoplasmic ratio and collagen content can be extracted as quantitative indicators for differentiating brain gliomas from healthy brain tissues. With the development of two-photon fiberscopes and microendoscope probes and their clinical applications, the combined TPEF and SHG microcopy may become an important multimodal, nonlinear optical imaging approach for real-time intraoperative histological diagnostics of residual brain tumors. These occur in various brain regions during ongoing surgeries through the method of simultaneously identifying tumor cells, and the change of tumor microenvironments, without the need for the removal biopsies and without the need for tissue labelling or fluorescent markers.

{sup 18}F-labeled RGD peptide: initial evaluation for imaging brain tumor angiogenesis

Energy Technology Data Exchange (ETDEWEB)

Chen Xiaoyuan; Park, Ryan; Shahinian, Anthony H.; Tohme, Michel; Khankaldyyan, Vazgen; Bozorgzadeh, Mohammed H.; Bading, James R.; Moats, Rex; Laug, Walter E.; Conti, Peter S. E-mail: pconti@usc.edu

2004-02-01

Brain tumors are highly angiogenesis dependent. The cell adhesion receptor integrin {alpha}{sub v}{beta}{sub 3} is overexpressed in glioma and activated endothelial cells and plays an important role in brain tumor growth, spread and angiogenesis. Suitably labeled {alpha}{sub v}{beta}{sub 3}-integrin antagonists may therefore be useful for imaging brain tumor associated angiogenesis. Cyclic RGD peptide c(RGDyK) was labeled with {sup 18}F via N-succinimidyl-4-[{sup 18}F]fluorobenzoate through the side-chain {epsilon}-amino group of the lysine residue. The radiotracer was evaluated in vivo for its tumor targeting efficacy and pharmacokinetics in subcutaneously implanted U87MG and orthotopically implanted U251T glioblastoma nude mouse models by means of microPET, quantitative autoradiography and direct tissue sampling. The N-4-[{sup 18}F]fluorobenzoyl-RGD ([{sup 18}F]FB-RGD) was produced in less than 2 h with 20-25% decay-corrected yields and specific activity of 230 GBq/{mu}mol at end of synthesis. The tracer showed very rapid blood clearance and both hepatobiliary and renal excretion. Tumor-to-muscle uptake ratio at 30 min was approximately 5 in the subcutaneous U87MG tumor model. MicroPET imaging with the orthotopic U251T brain tumor model revealed very high tumor-to-brain ratio, with virtually no uptake in the normal brain. Successful blocking of tumor uptake of [{sup 18}F]FB-RGD in the presence of excess amount of c(RGDyK) revealed receptor specific activity accumulation. Hence, N-4-[{sup 18}F]fluorobenzoyl labeled cyclic RGD peptide [{sup 18}F]FB-RGD is a potential tracer for imaging {alpha}{sub v}{beta}{sub 3}-integrin positive tumors in brain and other anatomic locations.