Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.

Science.gov (United States)

Marx, Mirko; Ehrhardt, Jan; Werner, René; Schlemmer, Heinz-Peter; Handels, Heinz

2014-05-01

Four-dimensional CT imaging is widely used to account for motion-related effects during radiotherapy planning of lung cancer patients. However, 4D CT often contains motion artifacts, cannot be used to measure motion variability, and leads to higher dose exposure. In this article, we propose using 4D MRI to acquire motion information for the radiotherapy planning process. From the 4D MRI images, we derive a time-continuous model of the average patient-specific respiratory motion, which is then applied to simulate 4D CT data based on a static 3D CT. The idea of the motion model is to represent the average lung motion over a respiratory cycle by cyclic B-spline curves. The model generation consists of motion field estimation in the 4D MRI data by nonlinear registration, assigning respiratory phases to the motion fields, and applying a B-spline approximation on a voxel-by-voxel basis to describe the average voxel motion over a breathing cycle. To simulate a patient-specific 4D CT based on a static CT of the patient, a multi-modal registration strategy is introduced to transfer the motion model from MRI to the static CT coordinates. Differences between model-based estimated and measured motion vectors are on average 1.39 mm for amplitude-based binning of the 4D MRI data of three patients. In addition, the MRI-to-CT registration strategy is shown to be suitable for the model transformation. The application of our 4D MRI-based motion model for simulating 4D CT images provides advantages over standard 4D CT (less motion artifacts, radiation-free). This makes it interesting for radiotherapy planning.

Mitigation of motion artifacts in CBCT of lung tumors based on tracked tumor motion during CBCT acquisition

International Nuclear Information System (INIS)

Lewis, John H; Li Ruijiang; Jia Xun; Watkins, W Tyler; Song, William Y; Jiang, Steve B; Lou, Yifei

2011-01-01

An algorithm capable of mitigating respiratory motion blurring artifacts in cone-beam computed tomography (CBCT) lung tumor images based on the motion of the tumor during the CBCT scan is developed. The tumor motion trajectory and probability density function (PDF) are reconstructed from the acquired CBCT projection images using a recently developed algorithm Lewis et al (2010 Phys. Med. Biol. 55 2505-22). Assuming that the effects of motion blurring can be represented by convolution of the static lung (or tumor) anatomy with the motion PDF, a cost function is defined, consisting of a data fidelity term and a total variation regularization term. Deconvolution is performed through iterative minimization of this cost function. The algorithm was tested on digital respiratory phantom, physical respiratory phantom and patient data. A clear qualitative improvement is evident in the deblurred images as compared to the motion-blurred images for all cases. Line profiles show that the tumor boundaries are more accurately and clearly represented in the deblurred images. The normalized root-mean-squared error between the images used as ground truth and the motion-blurred images are 0.29, 0.12 and 0.30 in the digital phantom, physical phantom and patient data, respectively. Deblurring reduces the corresponding values to 0.13, 0.07 and 0.19. Application of a -700 HU threshold to the digital phantom results in tumor dimension measurements along the superior-inferior axis of 2.8, 1.8 and 1.9 cm in the motion-blurred, ground truth and deblurred images, respectively. Corresponding values for the physical phantom are 3.4, 2.7 and 2.7 cm. A threshold of -500 HU applied to the patient case gives measurements of 3.1, 1.6 and 1.7 cm along the SI axis in the CBCT, 4DCT and deblurred images, respectively. This technique could provide more accurate information about a lung tumor's size and shape on the day of treatment.

Residual motion of lung tumors in end-of-inhale respiratory gated radiotherapy based on external surrogates

International Nuclear Information System (INIS)

Berbeco, Ross I.; Nishioka, Seiko; Shirato, Hiroki; Jiang, Steve B.

2006-01-01

It has been noted that some lung tumors exhibit large periodic motion due to respiration. To limit the amount of dose to healthy lung tissues, many clinics have begun gating radiotherapy treatment using externally placed surrogates. It has been observed by several institutions that the end-of-exhale (EOE) tumor position is more reproducible than other phases of the breathing cycle, so the gating window is often set there. From a treatment planning perspective, end-of-inhale (EOI) phase might be preferred for gating because the expanded lungs will further decrease the healthy tissue within the treatment field. We simulate gated treatment at the EOI phase, using a set of recently measured internal/external anatomy patient data. This paper attempts to answer three questions: (1) How much is the tumor residual motion when we use an external surrogate gating window at EOI? (2) How could we reduce the residual motion in the EOI gating window? (3) Is there a preference for amplitude- versus phase-based gating at EOI? We found that under free breathing conditions the residual motion of the tumors is much larger for EOI phase than for EOE phase. The mean values of residual motion at EOI were found to be 2.2 and 2.7 mm for amplitude- and phase-based gating, respectively, and, at EOE, 1.0 and 1.2 mm for amplitude- and phase-based gating, respectively. However, we note that the residual motion in the EOI gating window is correlated well with the reproducibility of the external surface position in the EOI phase. Using the results of a published breath-coaching study, we deduce that the residual motion of a lung tumor at EOI would approach that at EOE, with the same duty cycle (30%), under breath-coaching conditions. Additionally, we found that under these same conditions, phase-based gating approaches the same residual motion as amplitude-based gating, going from a 28% difference to 11%, for the patient with the largest difference between the two gating modalities. We conclude

Internal Motion Estimation by Internal-external Motion Modeling for Lung Cancer Radiotherapy.

Science.gov (United States)

Chen, Haibin; Zhong, Zichun; Yang, Yiwei; Chen, Jiawei; Zhou, Linghong; Zhen, Xin; Gu, Xuejun

2018-02-27

The aim of this study is to develop an internal-external correlation model for internal motion estimation for lung cancer radiotherapy. Deformation vector fields that characterize the internal-external motion are obtained by respectively registering the internal organ meshes and external surface meshes from the 4DCT images via a recently developed local topology preserved non-rigid point matching algorithm. A composite matrix is constructed by combing the estimated internal phasic DVFs with external phasic and directional DVFs. Principle component analysis is then applied to the composite matrix to extract principal motion characteristics, and generate model parameters to correlate the internal-external motion. The proposed model is evaluated on a 4D NURBS-based cardiac-torso (NCAT) synthetic phantom and 4DCT images from five lung cancer patients. For tumor tracking, the center of mass errors of the tracked tumor are 0.8(±0.5)mm/0.8(±0.4)mm for synthetic data, and 1.3(±1.0)mm/1.2(±1.2)mm for patient data in the intra-fraction/inter-fraction tracking, respectively. For lung tracking, the percent errors of the tracked contours are 0.06(±0.02)/0.07(±0.03) for synthetic data, and 0.06(±0.02)/0.06(±0.02) for patient data in the intra-fraction/inter-fraction tracking, respectively. The extensive validations have demonstrated the effectiveness and reliability of the proposed model in motion tracking for both the tumor and the lung in lung cancer radiotherapy.

Study of the ventilatory lung motion imaging in primary lung cancer

International Nuclear Information System (INIS)

Fujii, Tadashige; Tanaka, Masao; Yazaki, Yosikazu; Kitabayashi, Hiroshi; Sekiguchi, Morie.

1996-01-01

Using perfusion lung scintigrams with Tc-99m macroaggregated alubumin at maximal inspiration (I) and expiration (E), images of the ventilatory lung motion, which was calculated and delineated by an expression as (E-I)/I, were obtained in 84 cases with primary lung cancer, and its clinical significance in the diagnosis of primary lung cancer was studied. The image of (E-I)/I consisted of positive and negative components. The former visualized the motion of the regional intrapulmonary areas and the latter showed the motion of the lung border. The sum of positive (E-I)/I in the lung with the primary lesion which was lower than that in the contralateral lung, was significantly low in cases with hilar mass, pleural effusion and TNM classification of T3+T4. The sum of positive (E-I)/I in both lungs and vital capacity was relatively low in cases with hilar mass, pleural effusion, TNM classification of T3+T4 and M1. The distribution pattern of pulmonary perfusion and positive (E-I)/I was fairly matched in 48 cases, but mismatch was observed in 36 cases. In the image of negative (E-I)/I, decreased motion of the lung border including the diaphragm was shown in cases with pleural adhesion and thickening, pleural effusion, phrenic nerve palsy and other conditions with hypoventilation. This technique seems to be useful for the estimation of regional pulmonary function of pulmonary perfusion and lung motion, the extent and pathophysiology of primary lung cancer. (author)

Study of the ventilatory lung motion imaging in primary lung cancer

Energy Technology Data Exchange (ETDEWEB)

Fujii, Tadashige [Shinshu Univ., Matsumoto, Nagano (Japan). Shool of Allied Medical Sciences; Tanaka, Masao; Yazaki, Yosikazu; Kitabayashi, Hiroshi; Sekiguchi, Morie

1996-12-01

Using perfusion lung scintigrams with Tc-99m macroaggregated alubumin at maximal inspiration (I) and expiration (E), images of the ventilatory lung motion, which was calculated and delineated by an expression as (E-I)/I, were obtained in 84 cases with primary lung cancer, and its clinical significance in the diagnosis of primary lung cancer was studied. The image of (E-I)/I consisted of positive and negative components. The former visualized the motion of the regional intrapulmonary areas and the latter showed the motion of the lung border. The sum of positive (E-I)/I in the lung with the primary lesion which was lower than that in the contralateral lung, was significantly low in cases with hilar mass, pleural effusion and TNM classification of T3+T4. The sum of positive (E-I)/I in both lungs and vital capacity was relatively low in cases with hilar mass, pleural effusion, TNM classification of T3+T4 and M1. The distribution pattern of pulmonary perfusion and positive (E-I)/I was fairly matched in 48 cases, but mismatch was observed in 36 cases. In the image of negative (E-I)/I, decreased motion of the lung border including the diaphragm was shown in cases with pleural adhesion and thickening, pleural effusion, phrenic nerve palsy and other conditions with hypoventilation. This technique seems to be useful for the estimation of regional pulmonary function of pulmonary perfusion and lung motion, the extent and pathophysiology of primary lung cancer. (author)

Frequency filtering based analysis on the cardiac induced lung tumor motion and its impact on the radiotherapy management

International Nuclear Information System (INIS)

Chen, Ting; Qin, Songbing; Xu, Xiaoting; Jabbour, Salma K.; Haffty, Bruce G.; Yue, Ning J.

2014-01-01

Purpose/objectives: Lung tumor motion may be impacted by heartbeat in addition to respiration. This study seeks to quantitatively analyze heart-motion-induced tumor motion and to evaluate its impact on lung cancer radiotherapy. Methods/materials: Fluoroscopy images were acquired for 30 lung cancer patients. Tumor, diaphragm, and heart were delineated on selected fluoroscopy frames, and their motion was tracked and converted into temporal signals based on deformable registration propagation. The clinical relevance of heart impact was evaluated using the dose volumetric histogram of the redefined target volumes. Results: Correlation was found between tumor and cardiac motion for 23 patients. The heart-induced motion amplitude ranged from 0.2 to 2.6 mm. The ratio between heart-induced tumor motion and the tumor motion was inversely proportional to the amplitude of overall tumor motion. When the heart motion impact was integrated, there was an average 9% increase in internal target volumes for 17 patients. Dose coverage decrease was observed on redefined planning target volume in simulated SBRT plans. Conclusions: The tumor motion of thoracic cancer patients is influenced by both heart and respiratory motion. The cardiac impact is relatively more significant for tumor with less motion, which may lead to clinically significant uncertainty in radiotherapy for some patients

Simulation of lung motions using an artificial neural network

International Nuclear Information System (INIS)

Laurent, R.; Henriet, J.; Sauget, M.; Gschwind, R.; Makovicka, L.; Salomon, M.; Nguyen, F.

2011-01-01

Purpose. A way to improve the accuracy of lung radiotherapy for a patient is to get a better understanding of its lung motion. Indeed, thanks to this knowledge it becomes possible to follow the displacements of the clinical target volume (CTV) induced by the lung breathing. This paper presents a feasibility study of an original method to simulate the positions of points in patient's lung at all breathing phases. Patients and methods. This method, based on an artificial neural network, allowed learning the lung motion on real cases and then to simulate it for new patients for which only the beginning and the end breathing data are known. The neural network learning set is made up of more than 600 points. These points, shared out on three patients and gathered on a specific lung area, were plotted by a MD. Results. - The first results are promising: an average accuracy of 1 mm is obtained for a spatial resolution of 1 x 1 x 2.5 mm 3 . Conclusion. We have demonstrated that it is possible to simulate lung motion with accuracy using an artificial neural network. As future work we plan to improve the accuracy of our method with the addition of new patient data and a coverage of the whole lungs. (authors)

Biomechanical interpretation of a free-breathing lung motion model

International Nuclear Information System (INIS)

Zhao Tianyu; White, Benjamin; Lamb, James; Low, Daniel A; Moore, Kevin L; Yang Deshan; Mutic, Sasa; Lu Wei

2011-01-01

The purpose of this paper is to develop a biomechanical model for free-breathing motion and compare it to a published heuristic five-dimensional (5D) free-breathing lung motion model. An ab initio biomechanical model was developed to describe the motion of lung tissue during free breathing by analyzing the stress–strain relationship inside lung tissue. The first-order approximation of the biomechanical model was equivalent to a heuristic 5D free-breathing lung motion model proposed by Low et al in 2005 (Int. J. Radiat. Oncol. Biol. Phys. 63 921–9), in which the motion was broken down to a linear expansion component and a hysteresis component. To test the biomechanical model, parameters that characterize expansion, hysteresis and angles between the two motion components were reported independently and compared between two models. The biomechanical model agreed well with the heuristic model within 5.5% in the left lungs and 1.5% in the right lungs for patients without lung cancer. The biomechanical model predicted that a histogram of angles between the two motion components should have two peaks at 39.8° and 140.2° in the left lungs and 37.1° and 142.9° in the right lungs. The data from the 5D model verified the existence of those peaks at 41.2° and 148.2° in the left lungs and 40.1° and 140° in the right lungs for patients without lung cancer. Similar results were also observed for the patients with lung cancer, but with greater discrepancies. The maximum-likelihood estimation of hysteresis magnitude was reported to be 2.6 mm for the lung cancer patients. The first-order approximation of the biomechanical model fit the heuristic 5D model very well. The biomechanical model provided new insights into breathing motion with specific focus on motion trajectory hysteresis.

[Simulation of lung motions using an artificial neural network].

Science.gov (United States)

Laurent, R; Henriet, J; Salomon, M; Sauget, M; Nguyen, F; Gschwind, R; Makovicka, L

2011-04-01

A way to improve the accuracy of lung radiotherapy for a patient is to get a better understanding of its lung motion. Indeed, thanks to this knowledge it becomes possible to follow the displacements of the clinical target volume (CTV) induced by the lung breathing. This paper presents a feasibility study of an original method to simulate the positions of points in patient's lung at all breathing phases. This method, based on an artificial neural network, allowed learning the lung motion on real cases and then to simulate it for new patients for which only the beginning and the end breathing data are known. The neural network learning set is made up of more than 600 points. These points, shared out on three patients and gathered on a specific lung area, were plotted by a MD. The first results are promising: an average accuracy of 1mm is obtained for a spatial resolution of 1 × 1 × 2.5mm(3). We have demonstrated that it is possible to simulate lung motion with accuracy using an artificial neural network. As future work we plan to improve the accuracy of our method with the addition of new patient data and a coverage of the whole lungs. Copyright © 2010 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Sensitivity of Tumor Motion Simulation Accuracy to Lung Biomechanical Modeling Approaches and Parameters

OpenAIRE

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing

2015-01-01

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional com...

Image-guided radiotherapy and motion management in lung cancer

DEFF Research Database (Denmark)

Korreman, Stine

2015-01-01

In this review, image guidance and motion management in radiotherapy for lung cancer is discussed. Motion characteristics of lung tumours and image guidance techniques to obtain motion information are elaborated. Possibilities for management of image guidance and motion in the various steps...

A Novel Markerless Technique to Evaluate Daily Lung Tumor Motion Based on Conventional Cone-Beam CT Projection Data

International Nuclear Information System (INIS)

Yang Yin; Zhong Zichun; Guo Xiaohu; Wang Jing; Anderson, John; Solberg, Timothy; Mao Weihua

2012-01-01

Purpose: In this study, we present a novel markerless technique, based on cone beam computed tomography (CBCT) raw projection data, to evaluate lung tumor daily motion. Method and Materials: The markerless technique, which uses raw CBCT projection data and locates tumors directly on every projection, consists of three steps. First, the tumor contour on the planning CT is used to create digitally reconstructed radiographs (DRRs) at every projection angle. Two sets of DRRs are created: one showing only the tumor, and another with the complete anatomy without the tumor. Second, a rigid two-dimensional image registration is performed to register the DRR set without the tumor to the CBCT projections. After the registration, the projections are subtracted from the DRRs, resulting in a projection dataset containing primarily tumor. Finally, a second registration is performed between the subtracted projection and tumor-only DRR. The methodology was evaluated using a chest phantom containing a moving tumor, and retrospectively in 4 lung cancer patients treated by stereotactic body radiation therapy. Tumors detected on projection images were compared with those from three-dimensional (3D) and four-dimensional (4D) CBCT reconstruction results. Results: Results in both static and moving phantoms demonstrate that the accuracy is within 1 mm. The subsequent application to 22 sets of CBCT scan raw projection data of 4 lung cancer patients includes about 11,000 projections, with the detected tumor locations consistent with 3D and 4D CBCT reconstruction results. This technique reveals detailed lung tumor motion and provides additional information than conventional 4D images. Conclusion: This technique is capable of accurately characterizing lung tumor motion on a daily basis based on a conventional CBCT scan. It provides daily verification of the tumor motion to ensure that these motions are within prior estimation and covered by the treatment planning volume.

A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion.

Science.gov (United States)

Yang, Y X; Teo, S-K; Van Reeth, E; Tan, C H; Tham, I W K; Poh, C L

2015-08-01

Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors' proposed approach. A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.

CT-guided thin needles percutaneous cryoablation (PCA) in patients with primary and secondary lung tumors: A preliminary experience

Energy Technology Data Exchange (ETDEWEB)

Pusceddu, Claudio, E-mail: clapusceddu@gmail.com [Division of Interventional Radiology, Department of Oncological Radiology, Businco Hospital, Regional Referral Center for Oncologic Diseases, Cagliari, Zip code 09100 (Italy); Sotgia, Barbara, E-mail: barbara.sotgia@gmail.com [Department of Oncological Radiology, Businco Hospital, Regional Referral Center for Oncological Diseases, Cagliari, Zip code 09100 (Italy); Fele, Rosa Maria, E-mail: rosellafele@tiscali.it [Department of Oncological Radiology, Businco Hospital, Regional Referral Center for Oncological Diseases, Cagliari, Zip code 09100 (Italy); Melis, Luca, E-mail: doclucamelis@tiscali.it [Department of Oncological Radiology, Businco Hospital, Regional Referral Center for Oncological Diseases, Cagliari, Zip code 09100 (Italy)

2013-05-15

Purpose: To report the data of our initial experience with CT-guided thin cryoprobes for percutaneous cryoablation (PCA) in patients with primary and secondary pulmonary tumors. Material and methods: CT-guided thin needles PCA was performed on 34 lung masses (11 NSCLC = 32%; 23 secondary lung malignancies = 68%) in 32 consecutive patients (24 men and 8 women; mean age 67 ± 10 years) not suitable for surgical resection. Lung masses were treated using two types of cryoprobes: IceRod and IceSeed able to obtain different size of iceball. The number of probes used ranged from 1 to 5 depending on the size of the tumor. After insertion of the cryoprobes into the lesion, the PCA were performed with two 2 (91%) or 3 (9%) cycles each of 12 min of freezing followed by a 4 min active thawing phase and a 4 min passive thawing phase for each one for all treatments. Results: All cryoablation sessions were successfully completed. All primary and metastatic lung tumors were ablated. No procedure-related deaths occurred. Morbidity consisted of 21% (7 of 34) pneumothorax and 3% (1 of 34) cases asymptomatic small pulmonary hemorrhage, respectively, all of CTCAE grade 1 (Common Terminology Criteria for Adverse Events). Low density of entire lesion, central necrosis and solid mass appearance were identify in 21 (62%), 7 (21%) and 6 (17%) of cryoablated tumors, respectively. No lymphadenopathy developed in the region of treated lesions. Technical success (complete lack of enhancement) was achieved in 82%, 97% and 91% of treated lesions at 1-, 3- and 6-months CT follow-up scan, respectively (p < .000). Comparing the tumor longest diameter between the baseline and at 6 month CT images, technical success was revealed in 92% cases (p < .000). Conclusion: Our preliminary experience suggests that PCA is a feasible treatment option. Well-designed clinical trials with a larger patient population are necessary to further investigate the long-term results and prognostic factors.

Shape-correlated deformation statistics for respiratory motion prediction in 4D lung

Science.gov (United States)

Liu, Xiaoxiao; Oguz, Ipek; Pizer, Stephen M.; Mageras, Gig S.

2010-02-01

4D image-guided radiation therapy (IGRT) for free-breathing lungs is challenging due to the complicated respiratory dynamics. Effective modeling of respiratory motion is crucial to account for the motion affects on the dose to tumors. We propose a shape-correlated statistical model on dense image deformations for patient-specic respiratory motion estimation in 4D lung IGRT. Using the shape deformations of the high-contrast lungs as the surrogate, the statistical model trained from the planning CTs can be used to predict the image deformation during delivery verication time, with the assumption that the respiratory motion at both times are similar for the same patient. Dense image deformation fields obtained by diffeomorphic image registrations characterize the respiratory motion within one breathing cycle. A point-based particle optimization algorithm is used to obtain the shape models of lungs with group-wise surface correspondences. Canonical correlation analysis (CCA) is adopted in training to maximize the linear correlation between the shape variations of the lungs and the corresponding dense image deformations. Both intra- and inter-session CT studies are carried out on a small group of lung cancer patients and evaluated in terms of the tumor location accuracies. The results suggest potential applications using the proposed method.

A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion

Energy Technology Data Exchange (ETDEWEB)

Yang, Y. X.; Van Reeth, E.; Poh, C. L., E-mail: clpoh@ntu.edu.sg [School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore 637459 (Singapore); Teo, S.-K. [Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore 138632 (Singapore); Tan, C. H. [Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433 (Singapore); Tham, I. W. K. [Department of Radiation Oncology, National University Cancer Institute, Singapore 119082 (Singapore)

2015-08-15

Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors’ proposed approach. Methods: A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors’ proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters.

Science.gov (United States)

Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing

2015-11-21

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.

An externally and internally deformable, programmable lung motion phantom

Energy Technology Data Exchange (ETDEWEB)

Cheung, Yam; Sawant, Amit, E-mail: amit.sawant@utsouthwestern.edu [UT Southwestern Medical Center, University of Texas, Dallas, Texas 75390 (United States)

2015-05-15

Purpose: Most clinically deployed strategies for respiratory motion management in lung radiotherapy (e.g., gating and tracking) use external markers that serve as surrogates for tumor motion. However, typical lung phantoms used to validate these strategies are based on a rigid exterior and a rigid or a deformable-interior. Such designs do not adequately represent respiration because the thoracic anatomy deforms internally as well as externally. In order to create a closer approximation of respiratory motion, the authors describe the construction and experimental testing of an externally as well as internally deformable, programmable lung phantom. Methods: The outer shell of a commercially available lung phantom (RS-1500, RSD, Inc.) was used. The shell consists of a chest cavity with a flexible anterior surface, and embedded vertebrae, rib-cage and sternum. A custom-made insert was designed using a piece of natural latex foam block. A motion platform was programmed with sinusoidal and ten patient-recorded lung tumor trajectories. The platform was used to drive a rigid foam “diaphragm” that compressed/decompressed the phantom interior. Experimental characterization comprised of determining the reproducibility and the external–internal correlation of external and internal marker trajectories extracted from kV x-ray fluoroscopy. Experiments were conducted to illustrate three example applications of the phantom—(i) validating the geometric accuracy of the VisionRT surface photogrammetry system; (ii) validating an image registration tool, NiftyReg; and (iii) quantifying the geometric error due to irregular motion in four-dimensional computed tomography (4DCT). Results: The phantom correctly reproduced sinusoidal and patient-derived motion, as well as realistic respiratory motion-related effects such as hysteresis. The reproducibility of marker trajectories over multiple runs for sinusoidal as well as patient traces, as characterized by fluoroscopy, was within 0

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters

International Nuclear Information System (INIS)

Tehrani, Joubin Nasehi; Wang, Jing; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu

2015-01-01

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney–Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney–Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney–Rivlin material model along left-right, anterior–posterior, and superior–inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation. (paper)

Characterization of free breathing patterns with 5D lung motion model

Energy Technology Data Exchange (ETDEWEB)

Zhao Tianyu; Lu Wei; Yang Deshan; Mutic, Sasa; Noel, Camille E.; Parikh, Parag J.; Bradley, Jeffrey D.; Low, Daniel A. [Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri 63110 (United States)

2009-11-15

Purpose: To determine the quiet respiration breathing motion model parameters for lung cancer and nonlung cancer patients. Methods: 49 free breathing patient 4DCT image datasets (25 scans, cine mode) were collected with simultaneous quantitative spirometry. A cross-correlation registration technique was employed to track the lung tissue motion between scans. The registration results were applied to a lung motion model: X-vector=X-vector{sub 0}+{alpha}-vector{beta}-vector f, where X-vector is the position of a piece of tissue located at reference position X-vector{sub 0} during a reference breathing phase (zero tidal volume v, zero airflow f). {alpha}-vector is a parameter that characterizes the motion due to air filling (motion as a function of tidal volume v) and {beta}-vector is the parameter that accounts for the motion due to the imbalance of dynamical stress distributions during inspiration and exhalation that causes lung motion hysteresis (motion as a function of airflow f). The parameters {alpha}-vector and {beta}-vector together provide a quantitative characterization of breathing motion that inherently includes the complex hysteresis interplay. The {alpha}-vector and {beta}-vector distributions were examined for each patient to determine overall general patterns and interpatient pattern variations. Results: For 44 patients, the greatest values of |{alpha}-vector| were observed in the inferior and posterior lungs. For the rest of the patients, |{alpha}-vector| reached its maximum in the anterior lung in three patients and the lateral lung in two patients. The hysteresis motion {beta}-vector had greater variability, but for the majority of patients, |{beta}-vector| was largest in the lateral lungs. Conclusions: This is the first report of the three-dimensional breathing motion model parameters for a large cohort of patients. The model has the potential for noninvasively predicting lung motion. The majority of patients exhibited similar |{alpha}-vector| maps

Toward in vivo lung's tissue incompressibility characterization for tumor motion modeling in radiation therapy

International Nuclear Information System (INIS)

Shirzadi, Zahra; Sadeghi-Naini, Ali; Samani, Abbas

2013-01-01

Purpose: A novel technique is proposed to characterize lung tissue incompressibility variation during respiration. Estimating lung tissue incompressibility parameter variations resulting from air content variation throughout respiration is critical for computer assisted tumor motion tracking. Continuous tumor motion is a major challenge in lung cancer radiotherapy, especially with external beam radiotherapy. If not accounted for, this motion may lead to areas of radiation overdosage for normal tissue. Given the unavailability of imaging modality that can be used effectively for real-time lung tumor tracking, computer assisted approach based on tissue deformation estimation can be a good alternative. This approach involves lung biomechanical model where its fidelity depends on input tissue properties. This investigation shows that considering variable tissue incompressibility parameter is very important for predicting tumor motion accurately, hence improving the lung radiotherapy outcome. Methods: First, an in silico lung phantom study was conducted to demonstrate the importance of employing variable Poisson's ratio for tumor motion predication. After it was established that modeling this variability is critical for accurate tumor motion prediction, an optimization based technique was developed to estimate lung tissue Poisson's ratio as a function of respiration cycle time. In this technique, the Poisson's ratio and lung pressure value were varied systematically until optimal values were obtained, leading to maximum similarity between acquired and simulated 4D CT lung images. This technique was applied in an ex vivo porcine lung study where simulated images were constructed using the end exhale CT image and deformation fields obtained from the lung's FE modeling of each respiration time increment. To model the tissue, linear elastic and Marlow hyperelastic material models in conjunction with variable Poisson's ratio were used. Results: The phantom study showed that

Personalizes lung motion simulation fore external radiotherapy using an artificial neural network

International Nuclear Information System (INIS)

Laurent, R.

2011-01-01

The development of new techniques in the field of external radiotherapy opens new ways of gaining accuracy in dose distribution, in particular through the knowledge of individual lung motion. The numeric simulation NEMOSIS (Neural Network Motion Simulation System) we describe is based on artificial neural networks (ANN) and allows, in addition to determining motion in a personalized way, to reduce the necessary initial doses to determine it. In the first part, we will present current treatment options, lung motion as well as existing simulation or estimation methods. The second part describes the artificial neural network used and the steps for defining its parameters. An accurate evaluation of our approach was carried out on original patient data. The obtained results are compared with an existing motion estimated method. The extremely short computing time, in the range of milliseconds for the generation of one respiratory phase, would allow its use in clinical routine. Modifications to NEMOSIS in order to meet the requirements for its use in external radiotherapy are described, and a study of the motion of tumor outlines is carried out. This work lays the basis for lung motion simulation with ANNs and validates our approach. Its real time implementation coupled to its predication accuracy makes NEMOSIS promising tool for the simulation of motion synchronized with breathing. (author)

Audiovisual Biofeedback Improves Cine–Magnetic Resonance Imaging Measured Lung Tumor Motion Consistency

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Lee, Danny [Radiation Physics Laboratory, Sydney Medical School, The University of Sydney, Sidney, NSW (Australia); Greer, Peter B. [School of Mathematical and Physical Sciences, The University of Newcastle, Newcastle, NSW (Australia); Department of Radiation Oncology, Calvary Mater Newcastle, Newcastle, NSW (Australia); Ludbrook, Joanna; Arm, Jameen; Hunter, Perry [Department of Radiation Oncology, Calvary Mater Newcastle, Newcastle, NSW (Australia); Pollock, Sean; Makhija, Kuldeep; O' brien, Ricky T. [Radiation Physics Laboratory, Sydney Medical School, The University of Sydney, Sidney, NSW (Australia); Kim, Taeho [Radiation Physics Laboratory, Sydney Medical School, The University of Sydney, Sidney, NSW (Australia); Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia (United States); Keall, Paul, E-mail: paul.keall@sydney.edu.au [Radiation Physics Laboratory, Sydney Medical School, The University of Sydney, Sidney, NSW (Australia)

2016-03-01

Purpose: To assess the impact of an audiovisual (AV) biofeedback on intra- and interfraction tumor motion for lung cancer patients. Methods and Materials: Lung tumor motion was investigated in 9 lung cancer patients who underwent a breathing training session with AV biofeedback before 2 3T magnetic resonance imaging (MRI) sessions. The breathing training session was performed to allow patients to become familiar with AV biofeedback, which uses a guiding wave customized for each patient according to a reference breathing pattern. In the first MRI session (pretreatment), 2-dimensional cine-MR images with (1) free breathing (FB) and (2) AV biofeedback were obtained, and the second MRI session was repeated within 3-6 weeks (mid-treatment). Lung tumors were directly measured from cine-MR images using an auto-segmentation technique; the centroid and outlier motions of the lung tumors were measured from the segmented tumors. Free breathing and AV biofeedback were compared using several metrics: intra- and interfraction tumor motion consistency in displacement and period, and the outlier motion ratio. Results: Compared with FB, AV biofeedback improved intrafraction tumor motion consistency by 34% in displacement (P=.019) and by 73% in period (P<.001). Compared with FB, AV biofeedback improved interfraction tumor motion consistency by 42% in displacement (P<.046) and by 74% in period (P=.005). Compared with FB, AV biofeedback reduced the outlier motion ratio by 21% (P<.001). Conclusions: These results demonstrated that AV biofeedback significantly improved intra- and interfraction lung tumor motion consistency for lung cancer patients. These results demonstrate that AV biofeedback can facilitate consistent tumor motion, which is advantageous toward achieving more accurate medical imaging and radiation therapy procedures.

Audiovisual Biofeedback Improves Cine–Magnetic Resonance Imaging Measured Lung Tumor Motion Consistency

International Nuclear Information System (INIS)

Lee, Danny; Greer, Peter B.; Ludbrook, Joanna; Arm, Jameen; Hunter, Perry; Pollock, Sean; Makhija, Kuldeep; O'brien, Ricky T.; Kim, Taeho; Keall, Paul

2016-01-01

Purpose: To assess the impact of an audiovisual (AV) biofeedback on intra- and interfraction tumor motion for lung cancer patients. Methods and Materials: Lung tumor motion was investigated in 9 lung cancer patients who underwent a breathing training session with AV biofeedback before 2 3T magnetic resonance imaging (MRI) sessions. The breathing training session was performed to allow patients to become familiar with AV biofeedback, which uses a guiding wave customized for each patient according to a reference breathing pattern. In the first MRI session (pretreatment), 2-dimensional cine-MR images with (1) free breathing (FB) and (2) AV biofeedback were obtained, and the second MRI session was repeated within 3-6 weeks (mid-treatment). Lung tumors were directly measured from cine-MR images using an auto-segmentation technique; the centroid and outlier motions of the lung tumors were measured from the segmented tumors. Free breathing and AV biofeedback were compared using several metrics: intra- and interfraction tumor motion consistency in displacement and period, and the outlier motion ratio. Results: Compared with FB, AV biofeedback improved intrafraction tumor motion consistency by 34% in displacement (P=.019) and by 73% in period (P<.001). Compared with FB, AV biofeedback improved interfraction tumor motion consistency by 42% in displacement (P<.046) and by 74% in period (P=.005). Compared with FB, AV biofeedback reduced the outlier motion ratio by 21% (P<.001). Conclusions: These results demonstrated that AV biofeedback significantly improved intra- and interfraction lung tumor motion consistency for lung cancer patients. These results demonstrate that AV biofeedback can facilitate consistent tumor motion, which is advantageous toward achieving more accurate medical imaging and radiation therapy procedures.

SU-G-JeP3-04: Estimating 4D CBCT from Prior Information and Extremely Limited Angle Projections Using Structural PCA and Weighted Free-Form Deformation

International Nuclear Information System (INIS)

Harris, W; Yin, F; Zhang, Y; Ren, L

2016-01-01

Purpose: To investigate the feasibility of using structure-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. Methods: A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion-model extracted by global PCA and a free-form deformation (GMM-FD) technique, using data fidelity constraint and the deformation energy minimization. In this study, a new structural-PCA method was developed to build a structural motion-model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respirational changes from planning 4D-CT to onboard volume. The estimation accuracy was evaluated by the Volume-Percent-Difference (VPD)/Center-of-Mass-Shift (COMS) between lesions in the estimated and “ground-truth” on board 4D-CBCT. Results: Among 6 different XCAT scenarios corresponding to respirational and anatomical changes from planning CT to on-board using single 30° on-board projections, the VPD/COMS for SMM-WFD was reduced to 10.64±3.04%/1.20±0.45mm from 21.72±9.24%/1.80±0.53mm for GMM-FD. Using 15° orthogonal projections, the VPD/COMS was

SU-G-JeP3-04: Estimating 4D CBCT from Prior Information and Extremely Limited Angle Projections Using Structural PCA and Weighted Free-Form Deformation

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Harris, W; Yin, F; Zhang, Y; Ren, L [Duke University Medical Center, Durham, NC (United States)

2016-06-15

Purpose: To investigate the feasibility of using structure-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. Methods: A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion-model extracted by global PCA and a free-form deformation (GMM-FD) technique, using data fidelity constraint and the deformation energy minimization. In this study, a new structural-PCA method was developed to build a structural motion-model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respirational changes from planning 4D-CT to onboard volume. The estimation accuracy was evaluated by the Volume-Percent-Difference (VPD)/Center-of-Mass-Shift (COMS) between lesions in the estimated and “ground-truth” on board 4D-CBCT. Results: Among 6 different XCAT scenarios corresponding to respirational and anatomical changes from planning CT to on-board using single 30° on-board projections, the VPD/COMS for SMM-WFD was reduced to 10.64±3.04%/1.20±0.45mm from 21.72±9.24%/1.80±0.53mm for GMM-FD. Using 15° orthogonal projections, the VPD/COMS was

Assessment of Respiration-Induced Motion and Its Impact on Treatment Outcome for Lung Cancer

Directory of Open Access Journals (Sweden)

Yan Wang

2013-01-01

Full Text Available This study presented the analysis of free-breathing lung tumor motion characteristics using GE 4DCT and Varian RPM systems. Tumor respiratory movement was found to be associated with GTV size, the superior-inferior tumor location in the lung, and the attachment degree to rigid structure (e.g., chest wall, vertebrae, or mediastinum, with tumor location being the most important factor among the other two. Improved outcomes in survival and local control of 43 lung cancer patients were also reported. Consideration of respiration-induced motion based on 4DCT for lung cancer yields individualized margin and more accurate and safe target coverage and thus can potentially improve treatment outcome.

A comparison of tumor motion characteristics between early stage and locally advanced stage lung cancers

International Nuclear Information System (INIS)

Yu, Z. Henry; Lin, Steven H.; Balter, Peter; Zhang Lifei; Dong Lei

2012-01-01

Purpose: With the increasing use of conformal radiation therapy methods for non-small cell lung cancer (NSCLC), it is necessary to accurately determine respiratory-induced tumor motion. The purpose of this study is to analyze and compare the motion characteristics of early and locally advanced stage NSCLC tumors in a large population and correlate tumor motion with position, volume, and diaphragm motion. Methods and materials: A total of 191 (94 early stage, 97 locally advanced) non-small cell lung tumors were analyzed for this study. Each patient received a four-dimensional CT scan prior to receiving radiation treatment. A soft-tissue-based rigid registration algorithm was used to track the tumor motion. Tumor volumes were determined based on the gross tumor volume delineated by physicians in the end of expiration phase. Tumor motion characteristics were correlated with their standardized tumor locations, lobe location, and clinical staging. Diaphragm motion was calculated by subtracting the diaphragm location between the expiration and the inspiration phases. Results: Median, max, and 95th percentile of tumor motion for early stage tumors were 5.9 mm, 31.0 mm, and 20.0 mm, which were 1.2 mm, 12 mm, and 7 mm more than those in locally advanced NSCLC, respectively. The range of motion at 95th percentile is more than 50% larger in early stage lung cancer group than in the locally advanced lung cancer group. Early stage tumors in the lower lobe showed the largest motion with a median motion of 9.2 mm, while upper/mid-lobe tumors exhibited a median motion of 3.3 mm. Tumor volumes were not correlated with motion. Conclusion: The range of tumor motion differs depending on tumor location and staging of NSCLC. Early stage tumors are more mobile than locally advanced stage NSCLC. These factors should be considered for general motion management strategies when 4D simulation is not performed on individual basis.

Design and analysis of a tendon-based computed tomography-compatible robot with remote center of motion for lung biopsy.

Science.gov (United States)

Yang, Yunpeng; Jiang, Shan; Yang, Zhiyong; Yuan, Wei; Dou, Huaisu; Wang, Wei; Zhang, Daguang; Bian, Yuan

2017-04-01

Nowadays, biopsy is a decisive method of lung cancer diagnosis, whereas lung biopsy is time-consuming, complex and inaccurate. So a computed tomography-compatible robot for rapid and precise lung biopsy is developed in this article. According to the actual operation process, the robot is divided into two modules: 4-degree-of-freedom position module for location of puncture point is appropriate for patient's almost all positions and 3-degree-of-freedom tendon-based orientation module with remote center of motion is compact and computed tomography-compatible to orientate and insert needle automatically inside computed tomography bore. The workspace of the robot surrounds patient's thorax, and the needle tip forms a cone under patient's skin. A new error model of the robot based on screw theory is proposed in view of structure error and actuation error, which are regarded as screw motions. Simulation is carried out to verify the precision of the error model contrasted with compensation via inverse kinematics. The results of insertion experiment on specific phantom prove the feasibility of the robot with mean error of 1.373 mm in laboratory environment, which is accurate enough to replace manual operation.

Evaluation of imaging of the ventilatory lung motion in pulmonary diseases

International Nuclear Information System (INIS)

Fujii, Tadashige; Kanai, Hisakata; Tanaka, Masao; Hirayama, Jiro; Handa, Kenjiro

1988-01-01

Using perfusion lung scintigram with 99m Tc-macroaggregated albumin at maximal expiration (E) and inspiration (I), images of the motion of the regional pulmonary areas and lung margins during ventilation ((E-I)/I) was obtained in patients with various respiratory diseases. The image of (E-I)/I consisted of positive and negative components. The former component visualized the motion of the regional pulmonary areas that corresponded with the ventilatory amplitude of the videodensigram. The sum of the positive component of (E-I)/I in both lungs correlated with the vital capacity (n = 50, r = 0.62). It was 163.5 ± 52.5 in cases with a vital capacity of more than 3.01, 94.1 ± 61.5 in primary lung cancer, 89.2 ± 44.7 in chronic obstructive lung diseases and 69.0 ± 27.5 in diffuse interstitial pneumonia. The distribution pattern of pulmonary perfusion and the positive component of (E-I)/I matched fairly in many cases, but did not match in some cases. The negative component of (E-I)/I demonstrated the ventilatory motion of the lung margin and its decreased activity was shown in cases with hypoventilation of various causes including pleural diseases. The sum of the negative component of (E-I)/I in the both lungs correlated with the vital capacity (n = 50, r = 0.44). These results suggest that this technique is useful to estimate the regional pulmonary ventilatioin and motion of the lung margins. (author)

Development of motion image prediction method using principal component analysis

International Nuclear Information System (INIS)

Chhatkuli, Ritu Bhusal; Demachi, Kazuyuki; Kawai, Masaki; Sakakibara, Hiroshi; Kamiaka, Kazuma

2012-01-01

Respiratory motion can induce the limit in the accuracy of area irradiated during lung cancer radiation therapy. Many methods have been introduced to minimize the impact of healthy tissue irradiation due to the lung tumor motion. The purpose of this research is to develop an algorithm for the improvement of image guided radiation therapy by the prediction of motion images. We predict the motion images by using principal component analysis (PCA) and multi-channel singular spectral analysis (MSSA) method. The images/movies were successfully predicted and verified using the developed algorithm. With the proposed prediction method it is possible to forecast the tumor images over the next breathing period. The implementation of this method in real time is believed to be significant for higher level of tumor tracking including the detection of sudden abdominal changes during radiation therapy. (author)

Reproducible simulation of respiratory motion in porcine lung explants

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Biederer, J. [Dept. of Diagnostic Radiology, Univ. Hospital Schleswig-Holstein, Campus Kiel (Germany); Dept. of Radiology, German Cancer Research Center, Heidelberg (Germany); Plathow, C. [Dept. of Diagnostic Radiology, Eberhard-Karls-Univ. Tuebingen (Germany); Dept. of Radiology, German Cancer Research Center, Heidelberg (Germany); Schoebinger, M.; Meinzer, H.P. [Dept. of Medical and Biological Informatics, German Cancer Research Center, Heidelberg (Germany); Tetzlaff, R.; Puderbach, M.; Zaporozhan, J.; Kauczor, H.U. [Dept. of Radiology, German Cancer Research Center, Heidelberg (Germany); Bolte, H.; Heller, M. [Dept. of Diagnostic Radiology, Univ. Hospital Schleswig-Holstein, Campus Kiel (Germany)

2006-11-15

Purpose: To develop a model for exactly reproducible respiration motion simulations of animal lung explants inside an MR-compatible chest phantom. Materials and Methods: The materials included a piston pump and a flexible silicone reconstruction of a porcine diaphragm and were used in combination with an established MR-compatible chest phantom for porcine heart-lung preparations. The rhythmic inflation and deflation of the diaphragm at the bottom of the artificial thorax with water (1-1.5 L) induced lung tissue displacement resembling diaphragmatic breathing. This system was tested on five porcine heart-lung preparations using 1.5T MRI with transverse and coronal 3D-GRE (TR/TE=3.63/1.58, 256 x 256 matrix, 350 mm FOV, 4 mm slices) and half Fourier T2-FSE (TR/TE=545/29, 256 x 192, 350 mm, 6 mm) as well as multiple row detector CT (16 x 1 mm collimation, pitch 1.5, FOV 400 mm, 120 mAs) acquired at five fixed inspiration levels. Dynamic CT scans and coronal MRI with dynamic 2D-GRE and 2D-SS-GRE sequences (image frequencies of 10/sec and 3/sec, respectively) were acquired during continuous 'breathing' (7/minute). The position of the piston pump was visually correlated with the respiratory motion visible through the transparent wall of the phantom and with dynamic displays of CT and MR images. An elastic body splines analysis of the respiratory motion was performed using CT data. Results: Visual evaluation of MRI and CT showed three-dimensional movement of the lung tissue throughout the respiration cycle. Local tissue displacement inside the lung explants was documented with motion maps calculated from CT. The maximum displacement at the top of the diaphragm (mean 26.26 [SD 1.9] mm on CT and 27.16 [SD 1.5] mm on MRI, respectively [p=0.25; Wilcoxon test]) was in the range of tidal breathing in human patients. Conclusion: The chest phantom with a diaphragmatic pump is a promising platform for multi-modality imaging studies of the effects of respiratory lung

Reproducible simulation of respiratory motion in porcine lung explants

International Nuclear Information System (INIS)

Biederer, J.; Plathow, C.; Schoebinger, M.; Meinzer, H.P.; Tetzlaff, R.; Puderbach, M.; Zaporozhan, J.; Kauczor, H.U.; Bolte, H.; Heller, M.

2006-01-01

Purpose: To develop a model for exactly reproducible respiration motion simulations of animal lung explants inside an MR-compatible chest phantom. Materials and Methods: The materials included a piston pump and a flexible silicone reconstruction of a porcine diaphragm and were used in combination with an established MR-compatible chest phantom for porcine heart-lung preparations. The rhythmic inflation and deflation of the diaphragm at the bottom of the artificial thorax with water (1-1.5 L) induced lung tissue displacement resembling diaphragmatic breathing. This system was tested on five porcine heart-lung preparations using 1.5T MRI with transverse and coronal 3D-GRE (TR/TE=3.63/1.58, 256 x 256 matrix, 350 mm FOV, 4 mm slices) and half Fourier T2-FSE (TR/TE=545/29, 256 x 192, 350 mm, 6 mm) as well as multiple row detector CT (16 x 1 mm collimation, pitch 1.5, FOV 400 mm, 120 mAs) acquired at five fixed inspiration levels. Dynamic CT scans and coronal MRI with dynamic 2D-GRE and 2D-SS-GRE sequences (image frequencies of 10/sec and 3/sec, respectively) were acquired during continuous 'breathing' (7/minute). The position of the piston pump was visually correlated with the respiratory motion visible through the transparent wall of the phantom and with dynamic displays of CT and MR images. An elastic body splines analysis of the respiratory motion was performed using CT data. Results: Visual evaluation of MRI and CT showed three-dimensional movement of the lung tissue throughout the respiration cycle. Local tissue displacement inside the lung explants was documented with motion maps calculated from CT. The maximum displacement at the top of the diaphragm (mean 26.26 [SD 1.9] mm on CT and 27.16 [SD 1.5] mm on MRI, respectively [p=0.25; Wilcoxon test]) was in the range of tidal breathing in human patients. Conclusion: The chest phantom with a diaphragmatic pump is a promising platform for multi-modality imaging studies of the effects of respiratory lung motion. (orig.)

Statistical analysis of target motion in gated lung stereotactic body radiation therapy

International Nuclear Information System (INIS)

Zhao Bo; Yang Yong; Li Tianfang; Li Xiang; Heron, Dwight E; Huq, M Saiful

2011-01-01

An external surrogate-based respiratory gating technique is a useful method to reduce target margins for the treatment of a moving lung tumor. The success of this technique relies on a good correlation between the motion of the external markers and the internal tumor as well as the repeatability of the respiratory motion. In gated lung stereotactic body radiation therapy (SBRT), the treatment time for each fraction could exceed 30 min due to large fractional dose. Tumor motion may experience pattern changes such as baseline shift during such extended treatment time. The purpose of this study is to analyze tumor motion traces in actual treatment situations and to evaluate the effect of the target baseline shift in gated lung SBRT treatment. Real-time motion data for both the external markers and tumors from 51 lung SBRT treatments with Cyberknife Synchrony technology were analyzed in this study. The treatment time is typically greater than 30 min. The baseline shift was calculated with a rolling average window equivalent to ∼20 s and subtracted from that at the beginning. The magnitude of the baseline shift and its relationship with treatment time were investigated. Phase gating simulation was retrospectively performed on 12 carefully selected treatments with respiratory amplitude larger than 5 mm and regular phases. A customized gating window was defined for each individual treatment. It was found that the baseline shifts are specific to each patient and each fraction. Statistical analysis revealed that more than 69% treatments exhibited increased baseline shifts with the lapse of treatment time. The magnitude of the baseline shift could reach 5.3 mm during a 30 min treatment. Gating simulation showed that tumor excursion was caused mainly by the uncertainties in phase gating simulation and baseline shift, the latter being the primary factor. With a 5 mm gating window, 2 out of 12 treatments in the study group showed significant tumor excursion. Baseline shifts

Assessing breathing motion by shape matching of lung and diaphragm surfaces

Science.gov (United States)

Urschler, Martin; Bischof, Horst

2005-04-01

Studying complex thorax breating motion is an important research topic for accurate fusion of functional and anatomical data, radiotherapy planning or reduction of breathing motion artifacts. We investigate segmented CT lung, airway and diaphragm surfaces at several different breathing states between Functional Residual and Total Lung Capacity. In general, it is hard to robustly derive corresponding shape features like curvature maxima from lung and diaphragm surfaces since diaphragm and rib cage muscles tend to deform the elastic lung tissue such that e.g. ridges might disappear. A novel registration method based on the shape context approach for shape matching is presented where we extend shape context to 3D surfaces. The shape context approach was reported as a promising method for matching 2D shapes without relying on extracted shape features. We use the point correspondences for a non-rigid thin-plate-spline registration to get deformation fields that describe the movement of lung and diaphragm. Our validation consists of experiments on phantom and real sheep thorax data sets. Phantom experiments make use of shapes that are manipulated with known transformations that simulate breathing behaviour. Real thorax data experiments use a data set showing lungs and diaphragm at 5 distinct breathing states, where we compare subsets of the data sets and qualitatively and quantitatively asses the registration performance by using manually identified corresponding landmarks.

Effect of Audio Coaching on Correlation of Abdominal Displacement With Lung Tumor Motion

International Nuclear Information System (INIS)

Nakamura, Mitsuhiro; Narita, Yuichiro; Matsuo, Yukinori; Narabayashi, Masaru; Nakata, Manabu; Sawada, Akira; Mizowaki, Takashi; Nagata, Yasushi; Hiraoka, Masahiro

2009-01-01

Purpose: To assess the effect of audio coaching on the time-dependent behavior of the correlation between abdominal motion and lung tumor motion and the corresponding lung tumor position mismatches. Methods and Materials: Six patients who had a lung tumor with a motion range >8 mm were enrolled in the present study. Breathing-synchronized fluoroscopy was performed initially without audio coaching, followed by fluoroscopy with recorded audio coaching for multiple days. Two different measurements, anteroposterior abdominal displacement using the real-time positioning management system and superoinferior (SI) lung tumor motion by X-ray fluoroscopy, were performed simultaneously. Their sequential images were recorded using one display system. The lung tumor position was automatically detected with a template matching technique. The relationship between the abdominal and lung tumor motion was analyzed with and without audio coaching. Results: The mean SI tumor displacement was 10.4 mm without audio coaching and increased to 23.0 mm with audio coaching (p < .01). The correlation coefficients ranged from 0.89 to 0.97 with free breathing. Applying audio coaching, the correlation coefficients improved significantly (range, 0.93-0.99; p < .01), and the SI lung tumor position mismatches became larger in 75% of all sessions. Conclusion: Audio coaching served to increase the degree of correlation and make it more reproducible. In addition, the phase shifts between tumor motion and abdominal displacement were improved; however, all patients breathed more deeply, and the SI lung tumor position mismatches became slightly larger with audio coaching than without audio coaching.

Decision tree and PCA-based fault diagnosis of rotating machinery

Science.gov (United States)

Sun, Weixiang; Chen, Jin; Li, Jiaqing

2007-04-01

After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

Impact of PET - CT motion correction in minimising the gross tumour volume in non-small cell lung cancer

Directory of Open Access Journals (Sweden)

Michael Masoomi

2013-10-01

Full Text Available AbstractObjective: To investigate the impact of respiratory motion on localization, and quantification lung lesions for the Gross Tumour Volume utilizing an in-house developed Auto3Dreg programme and dynamic NURBS-based cardiac-torso digitised phantom (NCAT. Methods: Respiratory motion may result in more than 30% underestimation of the SUV values of lung, liver and kidney tumour lesions. The motion correction technique adopted in this study was an image-based motion correction approach using, an in-house developed voxel-intensity-based and a multi-resolution multi-optimisation (MRMO algorithm. All the generated frames were co-registered to a reference frame using a time efficient scheme. The NCAT phantom was used to generate CT attenuation maps and activity distribution volumes for the lung regions. Quantitative assessment including Region of Interest (ROI, image fidelity and image correlation techniques, as well as semi-quantitative line profile analysis and qualitatively overlaying non-motion and motion corrected image frames were performed. Results: the largest transformation was observed in the Z-direction. The greatest translation was for the frame 3, end inspiration, and the smallest for the frame 5 which was closet frame to the reference frame at 67% expiration. Visual assessment of the lesion sizes, 20-60mm at 3 different locations, apex, mid and base of lung showed noticeable improvement for all the foci and their locations. The maximum improvements for the image fidelity were from 0.395 to 0.930 within the lesion volume of interest. The greatest improvement in activity concentration underestimation, post motion correction, was 7% below the true activity for the 20 mm lesion. The discrepancies in activity underestimation were reduced with increasing the lesion sizes. Overlay activity distribution on the attenuation map showed improved localization of the PET metabolic information to the anatomical CT images. Conclusion: The respiratory

A 4DCT imaging-based breathing lung model with relative hysteresis

Energy Technology Data Exchange (ETDEWEB)

Miyawaki, Shinjiro; Choi, Sanghun [IIHR – Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A. [Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [IIHR – Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Mechanical and Industrial Engineering, The University of Iowa, 3131 Seamans Center, Iowa City, IA 52242 (United States)

2016-12-01

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.

MO-B-201-02: Motion Management for Proton Lung SBR

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Flampouri, S. [University of Florida Proton Therapy Institute (United States)

2016-06-15

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and

MO-B-201-02: Motion Management for Proton Lung SBR

International Nuclear Information System (INIS)

Flampouri, S.

2016-01-01

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and

Principal component analysis-based imaging angle determination for 3D motion monitoring using single-slice on-board imaging.

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Chen, Ting; Zhang, Miao; Jabbour, Salma; Wang, Hesheng; Barbee, David; Das, Indra J; Yue, Ning

2018-04-10

Through-plane motion introduces uncertainty in three-dimensional (3D) motion monitoring when using single-slice on-board imaging (OBI) modalities such as cine MRI. We propose a principal component analysis (PCA)-based framework to determine the optimal imaging plane to minimize the through-plane motion for single-slice imaging-based motion monitoring. Four-dimensional computed tomography (4DCT) images of eight thoracic cancer patients were retrospectively analyzed. The target volumes were manually delineated at different respiratory phases of 4DCT. We performed automated image registration to establish the 4D respiratory target motion trajectories for all patients. PCA was conducted using the motion information to define the three principal components of the respiratory motion trajectories. Two imaging planes were determined perpendicular to the second and third principal component, respectively, to avoid imaging with the primary principal component of the through-plane motion. Single-slice images were reconstructed from 4DCT in the PCA-derived orthogonal imaging planes and were compared against the traditional AP/Lateral image pairs on through-plane motion, residual error in motion monitoring, absolute motion amplitude error and the similarity between target segmentations at different phases. We evaluated the significance of the proposed motion monitoring improvement using paired t test analysis. The PCA-determined imaging planes had overall less through-plane motion compared against the AP/Lateral image pairs. For all patients, the average through-plane motion was 3.6 mm (range: 1.6-5.6 mm) for the AP view and 1.7 mm (range: 0.6-2.7 mm) for the Lateral view. With PCA optimization, the average through-plane motion was 2.5 mm (range: 1.3-3.9 mm) and 0.6 mm (range: 0.2-1.5 mm) for the two imaging planes, respectively. The absolute residual error of the reconstructed max-exhale-to-inhale motion averaged 0.7 mm (range: 0.4-1.3 mm, 95% CI: 0.4-1.1 mm) using

A Morphing Technique Applied to Lung Motions in Radiotherapy: Preliminary Results

Directory of Open Access Journals (Sweden)

R. Laurent

2010-01-01

Full Text Available Organ motion leads to dosimetric uncertainties during a patient’s treatment. Much work has been done to quantify the dosimetric effects of lung movement during radiation treatment. There is a particular need for a good description and prediction of organ motion. To describe lung motion more precisely, we have examined the possibility of using a computer technique: a morphing algorithm. Morphing is an iterative method which consists of blending one image into another image. To evaluate the use of morphing, Four Dimensions Computed Tomography (4DCT acquisition of a patient was performed. The lungs were automatically segmented for different phases, and morphing was performed using the end-inspiration and the end-expiration phase scans only. Intermediate morphing files were compared with 4DCT intermediate images. The results showed good agreement between morphing images and 4DCT images: fewer than 2 % of the 512 by 256 voxels were wrongly classified as belonging/not belonging to a lung section. This paper presents preliminary results, and our morphing algorithm needs improvement. We can infer that morphing offers considerable advantages in terms of radiation protection of the patient during the diagnosis phase, handling of artifacts, definition of organ contours and description of organ motion.

Simulation of range imaging-based estimation of respiratory lung motion. Influence of noise, signal dimensionality and sampling patterns.

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Wilms, M; Werner, R; Blendowski, M; Ortmüller, J; Handels, H

2014-01-01

A major problem associated with the irradiation of thoracic and abdominal tumors is respiratory motion. In clinical practice, motion compensation approaches are frequently steered by low-dimensional breathing signals (e.g., spirometry) and patient-specific correspondence models, which are used to estimate the sought internal motion given a signal measurement. Recently, the use of multidimensional signals derived from range images of the moving skin surface has been proposed to better account for complex motion patterns. In this work, a simulation study is carried out to investigate the motion estimation accuracy of such multidimensional signals and the influence of noise, the signal dimensionality, and different sampling patterns (points, lines, regions). A diffeomorphic correspondence modeling framework is employed to relate multidimensional breathing signals derived from simulated range images to internal motion patterns represented by diffeomorphic non-linear transformations. Furthermore, an automatic approach for the selection of optimal signal combinations/patterns within this framework is presented. This simulation study focuses on lung motion estimation and is based on 28 4D CT data sets. The results show that the use of multidimensional signals instead of one-dimensional signals significantly improves the motion estimation accuracy, which is, however, highly affected by noise. Only small differences exist between different multidimensional sampling patterns (lines and regions). Automatically determined optimal combinations of points and lines do not lead to accuracy improvements compared to results obtained by using all points or lines. Our results show the potential of multidimensional breathing signals derived from range images for the model-based estimation of respiratory motion in radiation therapy.

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery

International Nuclear Information System (INIS)

Rottmann, Joerg; Berbeco, Ross; Keall, Paul

2013-01-01

Purpose: To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient.Methods: 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps.Results: Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm.Conclusions: The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery

Energy Technology Data Exchange (ETDEWEB)

Rottmann, Joerg; Berbeco, Ross [Brigham and Women' s Hospital, Dana Farber-Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States); Keall, Paul [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, Sydney NSW 2006 (Australia)

2013-09-15

Purpose: To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient.Methods: 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps.Results: Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error <1.0 mm [root mean square (rms) error of 0.3 mm] was observed. The tracking rms accuracy on BEV images from a lung SBRT patient (≈20 mm tumor motion range) is 1.0 mm.Conclusions: The authors demonstrate for the first time real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.

Characteristics and Validation Techniques for PCA-Based Gene-Expression Signatures

Directory of Open Access Journals (Sweden)

Anders E. Berglund

2017-01-01

Full Text Available Background. Many gene-expression signatures exist for describing the biological state of profiled tumors. Principal Component Analysis (PCA can be used to summarize a gene signature into a single score. Our hypothesis is that gene signatures can be validated when applied to new datasets, using inherent properties of PCA. Results. This validation is based on four key concepts. Coherence: elements of a gene signature should be correlated beyond chance. Uniqueness: the general direction of the data being examined can drive most of the observed signal. Robustness: if a gene signature is designed to measure a single biological effect, then this signal should be sufficiently strong and distinct compared to other signals within the signature. Transferability: the derived PCA gene signature score should describe the same biology in the target dataset as it does in the training dataset. Conclusions. The proposed validation procedure ensures that PCA-based gene signatures perform as expected when applied to datasets other than those that the signatures were trained upon. Complex signatures, describing multiple independent biological components, are also easily identified.

PCA3 and PCA3-Based Nomograms Improve Diagnostic Accuracy in Patients Undergoing First Prostate Biopsy

Directory of Open Access Journals (Sweden)

Virginie Vlaeminck-Guillem

2013-08-01

Full Text Available While now recognized as an aid to predict repeat prostate biopsy outcome, the urinary PCA3 (prostate cancer gene 3 test has also been recently advocated to predict initial biopsy results. The objective is to evaluate the performance of the PCA3 test in predicting results of initial prostate biopsies and to determine whether its incorporation into specific nomograms reinforces its diagnostic value. A prospective study included 601 consecutive patients addressed for initial prostate biopsy. The PCA3 test was performed before ≥12-core initial prostate biopsy, along with standard risk factor assessment. Diagnostic performance of the PCA3 test was evaluated. The three available nomograms (Hansen’s and Chun’s nomograms, as well as the updated Prostate Cancer Prevention Trial risk calculator; PCPT were applied to the cohort, and their predictive accuracies were assessed in terms of biopsy outcome: the presence of any prostate cancer (PCa and high-grade prostate cancer (HGPCa. The PCA3 score provided significant predictive accuracy. While the PCPT risk calculator appeared less accurate; both Chun’s and Hansen’s nomograms provided good calibration and high net benefit on decision curve analyses. When applying nomogram-derived PCa probability thresholds ≤30%, ≤6% of HGPCa would have been missed, while avoiding up to 48% of unnecessary biopsies. The urinary PCA3 test and PCA3-incorporating nomograms can be considered as reliable tools to aid in the initial biopsy decision.

Adaptive PCA based fault diagnosis scheme in imperial smelting process.

Science.gov (United States)

Hu, Zhikun; Chen, Zhiwen; Gui, Weihua; Jiang, Bin

2014-09-01

In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Markerless gating for lung cancer radiotherapy based on machine learning techniques

International Nuclear Information System (INIS)

Lin Tong; Li Ruijiang; Tang Xiaoli; Jiang, Steve B; Dy, Jennifer G

2009-01-01

In lung cancer radiotherapy, radiation to a mobile target can be delivered by respiratory gating, for which we need to know whether the target is inside or outside a predefined gating window at any time point during the treatment. This can be achieved by tracking one or more fiducial markers implanted inside or near the target, either fluoroscopically or electromagnetically. However, the clinical implementation of marker tracking is limited for lung cancer radiotherapy mainly due to the risk of pneumothorax. Therefore, gating without implanted fiducial markers is a promising clinical direction. We have developed several template-matching methods for fluoroscopic marker-less gating. Recently, we have modeled the gating problem as a binary pattern classification problem, in which principal component analysis (PCA) and support vector machine (SVM) are combined to perform the classification task. Following the same framework, we investigated different combinations of dimensionality reduction techniques (PCA and four nonlinear manifold learning methods) and two machine learning classification methods (artificial neural networks-ANN and SVM). Performance was evaluated on ten fluoroscopic image sequences of nine lung cancer patients. We found that among all combinations of dimensionality reduction techniques and classification methods, PCA combined with either ANN or SVM achieved a better performance than the other nonlinear manifold learning methods. ANN when combined with PCA achieves a better performance than SVM in terms of classification accuracy and recall rate, although the target coverage is similar for the two classification methods. Furthermore, the running time for both ANN and SVM with PCA is within tolerance for real-time applications. Overall, ANN combined with PCA is a better candidate than other combinations we investigated in this work for real-time gated radiotherapy.

A study of tumor motion management in the conformal radiotherapy of lung cancer

International Nuclear Information System (INIS)

Burnett, Stuart S.C.; Sixel, Katharina E.; Cheung, Patrick C.F.; Hoisak, Jeremy D.P.

2008-01-01

Purpose: To assess the benefit derived from the reduction of planning target volumes (PTVs) afforded by tumor motion management in treatment planning for lung cancer. Methods: We use a simple formula that combines measurements of tumor motion and set-up error for 7 patients to determine PTVs based on the following scenarios: standard uniform 15 mm margin, individualized PTVs (no gating), spirometry-based gating, and active breath-control (ABC). We compare the percent volumes of lung receiving at least 20 Gy (V20) for a standard prescription, and the maximum tolerated doses (MTDs) at fixed V20. In anticipation of improvements in set-up accuracy, we repeat the analysis assuming a reduced set-up margin of 3 mm. Results: Relative to the standard, the average percent reductions in V20 (±1 standard deviation) for the ungated and gated scenarios are 17 ± 5 and 21 ± 8; the percent gains in MTD are 25 ± 12 and 33 ± 11, respectively. For the 3 mm set-up margin, the corresponding results for V20 are 28 ± 7 and 36 ± 7, and for MTD are 57 ± 23 and 79 ± 31. Conclusions: Any form of motion management provides a benefit over the use of a standard margin. The benefit derived from gating compared to the use of ungated individualized PTVs increases with tumor mobility but is generally modest. While motion management may benefit patients with highly mobile tumors, we expect efforts to reduce set-up error to be of greater overall significance. The practical limit for lung PTV margins is likely around 4-5 mm, provided set-up error can be reduced sufficiently

Real-time soft tissue motion estimation for lung tumors during radiotherapy delivery.

Science.gov (United States)

Rottmann, Joerg; Keall, Paul; Berbeco, Ross

2013-09-01

To provide real-time lung tumor motion estimation during radiotherapy treatment delivery without the need for implanted fiducial markers or additional imaging dose to the patient. 2D radiographs from the therapy beam's-eye-view (BEV) perspective are captured at a frame rate of 12.8 Hz with a frame grabber allowing direct RAM access to the image buffer. An in-house developed real-time soft tissue localization algorithm is utilized to calculate soft tissue displacement from these images in real-time. The system is tested with a Varian TX linear accelerator and an AS-1000 amorphous silicon electronic portal imaging device operating at a resolution of 512 × 384 pixels. The accuracy of the motion estimation is verified with a dynamic motion phantom. Clinical accuracy was tested on lung SBRT images acquired at 2 fps. Real-time lung tumor motion estimation from BEV images without fiducial markers is successfully demonstrated. For the phantom study, a mean tracking error real-time markerless lung tumor motion estimation from BEV images alone. The described system can operate at a frame rate of 12.8 Hz and does not require prior knowledge to establish traceable landmarks for tracking on the fly. The authors show that the geometric accuracy is similar to (or better than) previously published markerless algorithms not operating in real-time.

Movie prediction of lung tumor for precise chasing radiation therapy

International Nuclear Information System (INIS)

Chhatkuli, Ritu Bhusal; Demachi, Kazuyuki; Kawai, Masaki; Sakakibara, Hiroshi; Uesaka, Mitsuru

2012-01-01

In recent years, precision for radiation therapy is a major challenge in the field of cancer treatment. When it comes to a moving organ like lungs, limiting the radiation to the target and sparing the surrounding healthy tissue is always a concern. It can induce the limit in the accuracy of area irradiated during lung cancer radiation therapy. Many methods have been introduced to compensate the motion in order to reduce the effect of radiation to healthy tissue due to respiratory motion. The motion of lung along with the tumor makes it very difficult to spare the healthy tissue during radiation therapy. The fear of this unintended damage to the neighboring tissue often limits the dose that can be applied to the tumor. The purpose of this research is the prediction of future motion images for the improvement of tumor tracking method. We predict the motion images by using principal component analysis (PCA) and multi-channel singular spectral analysis (MSSA) method. Time series x-ray images are used as training images. The motion images were successfully predicted and verified using the developed algorithm. The real time implementation of this method in future is believed to be significant for higher level of real time tumor tracking during radiation therapy. (author)

Real-time dynamic MR image reconstruction using compressed sensing and principal component analysis (CS-PCA): Demonstration in lung tumor tracking.

Science.gov (United States)

Dietz, Bryson; Yip, Eugene; Yun, Jihyun; Fallone, B Gino; Wachowicz, Keith

2017-08-01

This work presents a real-time dynamic image reconstruction technique, which combines compressed sensing and principal component analysis (CS-PCA), to achieve real-time adaptive radiotherapy with the use of a linac-magnetic resonance imaging system. Six retrospective fully sampled dynamic data sets of patients diagnosed with non-small-cell lung cancer were used to investigate the CS-PCA algorithm. Using a database of fully sampled k-space, principal components (PC's) were calculated to aid in the reconstruction of undersampled images. Missing k-space data were calculated by projecting the current undersampled k-space data onto the PC's to generate the corresponding PC weights. The weighted PC's were summed together, and the missing k-space was iteratively updated. To gain insight into how the reconstruction might proceed at lower fields, 6× noise was added to the 3T data to investigate how the algorithm handles noisy data. Acceleration factors ranging from 2 to 10× were investigated using CS-PCA and Split Bregman CS for comparison. Metrics to determine the reconstruction quality included the normalized mean square error (NMSE), as well as the dice coefficients (DC) and centroid displacement of the tumor segmentations. Our results demonstrate that CS-PCA performed superior than CS alone. The CS-PCA patient averaged DC for 3T and 6× noise added data remained above 0.9 for acceleration factors up to 10×. The patient averaged NMSE gradually increased with increasing acceleration; however, it remained below 0.06 up to an acceleration factor of 10× for both 3T and 6× noise added data. The CS-PCA reconstruction speed ranged from 5 to 20 ms (Intel i7-4710HQ CPU @ 2.5 GHz), depending on the chosen parameters. A real-time reconstruction technique was developed for adaptive radiotherapy using a Linac-MRI system. Our CS-PCA algorithm can achieve tumor contours with DC greater than 0.9 and NMSE less than 0.06 at acceleration factors of up to, and including, 10×. The

Applications of PCA and SVM-PSO Based Real-Time Face Recognition System

Directory of Open Access Journals (Sweden)

Ming-Yuan Shieh

2014-01-01

Full Text Available This paper incorporates principal component analysis (PCA with support vector machine-particle swarm optimization (SVM-PSO for developing real-time face recognition systems. The integrated scheme aims to adopt the SVM-PSO method to improve the validity of PCA based image recognition systems on dynamically visual perception. The face recognition for most human-robot interaction applications is accomplished by PCA based method because of its dimensionality reduction. However, PCA based systems are only suitable for processing the faces with the same face expressions and/or under the same view directions. Since the facial feature selection process can be considered as a problem of global combinatorial optimization in machine learning, the SVM-PSO is usually used as an optimal classifier of the system. In this paper, the PSO is used to implement a feature selection, and the SVMs serve as fitness functions of the PSO for classification problems. Experimental results demonstrate that the proposed method simplifies features effectively and obtains higher classification accuracy.

SU-G-JeP1-06: Correlation of Lung Tumor Motion with Tumor Location Using Electromagnetic Tracking

Energy Technology Data Exchange (ETDEWEB)

Muccigrosso, D; Maughan, N; Parikh, P [Washington University School of Medicine, Saint Louis, MO (United States); Schultejans, H; Bera, R [Lindbergh High School, St. Louis, MO (United States)

2016-06-15

Purpose: It is well known that lung tumors move with respiration. However, most measurements of lung tumor motion have studied long treatment times with intermittent imaging; those populations may not necessarily represent conventional LINAC patients. We summarized the correlation between tumor motion and location in a multi-institutional trial with electromagnetic tracking, and identified the patient cohort that would most benefit from respiratory gating. Methods: Continuous electromagnetic transponder data (Varian Medical, Seattle, WA) of lung tumor motion was collected from 14 patients (214 total fractions) across 3 institutions during external beam radiation therapy in a prospective clinical trial (NCT01396551). External intervention from the clinician, such as couch shifts, instructed breath-holds, and acquisition pauses, were manually removed from the 10 Hz tracking data according to recorded notes. The average three-dimensional displacement from the breathing cycle’s end-expiratory to end-inhalation phases (peak-to-peak distance) of the transponders’ isocenter was calculated for each patient’s treatment. A weighted average of each isocenter was used to assess the effects of location on motion. A total of 14 patients were included in this analysis, grouped by their transponders’ location in the lung: upper, medial, and lower. Results: 8 patients had transponders in the upper lung, and 3 patients each in the medial lobe and lower lung. The weighted average ± standard deviation of all peak-to-peak distances for each group was: 1.04 ± 0.39 cm in the lower lung, 0.56 ± 0.14 cm in the medial lung, and 0.30 ± 0.06 cm in the upper lung. Conclusion: Tumors in the lower lung are most susceptible to excessive motion and daily variation, and would benefit most from continuous motion tracking and gating. Those in the medial lobe might be at moderate risk. The upper lobes have limited motion. These results can guide different motion management strategies

Parallel GPU implementation of iterative PCA algorithms.

Science.gov (United States)

Andrecut, M

2009-11-01

Principal component analysis (PCA) is a key statistical technique for multivariate data analysis. For large data sets, the common approach to PCA computation is based on the standard NIPALS-PCA algorithm, which unfortunately suffers from loss of orthogonality, and therefore its applicability is usually limited to the estimation of the first few components. Here we present an algorithm based on Gram-Schmidt orthogonalization (called GS-PCA), which eliminates this shortcoming of NIPALS-PCA. Also, we discuss the GPU (Graphics Processing Unit) parallel implementation of both NIPALS-PCA and GS-PCA algorithms. The numerical results show that the GPU parallel optimized versions, based on CUBLAS (NVIDIA), are substantially faster (up to 12 times) than the CPU optimized versions based on CBLAS (GNU Scientific Library).

TU-F-17A-03: An Analytical Respiratory Perturbation Model for Lung Motion Prediction

International Nuclear Information System (INIS)

Li, G; Yuan, A; Wei, J

2014-01-01

Purpose: Breathing irregularity is common, causing unreliable prediction in tumor motion for correlation-based surrogates. Both tidal volume (TV) and breathing pattern (BP=ΔVthorax/TV, where TV=ΔVthorax+ΔVabdomen) affect lung motion in anterior-posterior and superior-inferior directions. We developed a novel respiratory motion perturbation (RMP) model in analytical form to account for changes in TV and BP in motion prediction from simulation to treatment. Methods: The RMP model is an analytical function of patient-specific anatomic and physiologic parameters. It contains a base-motion trajectory d(x,y,z) derived from a 4-dimensional computed tomography (4DCT) at simulation and a perturbation term Δd(ΔTV,ΔBP) accounting for deviation at treatment from simulation. The perturbation is dependent on tumor-specific location and patient-specific anatomy. Eleven patients with simulation and treatment 4DCT images were used to assess the RMP method in motion prediction from 4DCT1 to 4DCT2, and vice versa. For each patient, ten motion trajectories of corresponding points in the lower lobes were measured in both 4DCTs: one served as the base-motion trajectory and the other as the ground truth for comparison. In total, 220 motion trajectory predictions were assessed. The motion discrepancy between two 4DCTs for each patient served as a control. An established 5D motion model was used for comparison. Results: The average absolute error of RMP model prediction in superior-inferior direction is 1.6±1.8 mm, similar to 1.7±1.6 mm from the 5D model (p=0.98). Some uncertainty is associated with limited spatial resolution (2.5mm slice thickness) and temporal resolution (10-phases). Non-corrected motion discrepancy between two 4DCTs is 2.6±2.7mm, with the maximum of ±20mm, and correction is necessary (p=0.01). Conclusion: The analytical motion model predicts lung motion with accuracy similar to the 5D model. The analytical model is based on physical relationships, requires no

Principal Component Analysis Based Two-Dimensional (PCA-2D) Correlation Spectroscopy: PCA Denoising for 2D Correlation Spectroscopy

International Nuclear Information System (INIS)

Jung, Young Mee

2003-01-01

Principal component analysis based two-dimensional (PCA-2D) correlation analysis is applied to FTIR spectra of polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation. Substantial amount of artificial noise were added to the experimental data to demonstrate the practical noise-suppressing benefit of PCA-2D technique. 2D correlation analysis of the reconstructed data matrix from PCA loading vectors and scores successfully extracted only the most important features of synchronicity and asynchronicity without interference from noise or insignificant minor components. 2D correlation spectra constructed with only one principal component yield strictly synchronous response with no discernible a asynchronous features, while those involving at least two or more principal components generated meaningful asynchronous 2D correlation spectra. Deliberate manipulation of the rank of the reconstructed data matrix, by choosing the appropriate number and type of PCs, yields potentially more refined 2D correlation spectra

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY

Science.gov (United States)

YÜCEL, MERYEM A.; SELB, JULIETTE; COOPER, ROBERT J.; BOAS, DAVID A.

2014-01-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson’s correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson’s correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data. PMID:25360181

TARGETED PRINCIPLE COMPONENT ANALYSIS: A NEW MOTION ARTIFACT CORRECTION APPROACH FOR NEAR-INFRARED SPECTROSCOPY.

Science.gov (United States)

Yücel, Meryem A; Selb, Juliette; Cooper, Robert J; Boas, David A

2014-03-01

As near-infrared spectroscopy (NIRS) broadens its application area to different age and disease groups, motion artifacts in the NIRS signal due to subject movement is becoming an important challenge. Motion artifacts generally produce signal fluctuations that are larger than physiological NIRS signals, thus it is crucial to correct for them before obtaining an estimate of stimulus evoked hemodynamic responses. There are various methods for correction such as principle component analysis (PCA), wavelet-based filtering and spline interpolation. Here, we introduce a new approach to motion artifact correction, targeted principle component analysis (tPCA), which incorporates a PCA filter only on the segments of data identified as motion artifacts. It is expected that this will overcome the issues of filtering desired signals that plagues standard PCA filtering of entire data sets. We compared the new approach with the most effective motion artifact correction algorithms on a set of data acquired simultaneously with a collodion-fixed probe (low motion artifact content) and a standard Velcro probe (high motion artifact content). Our results show that tPCA gives statistically better results in recovering hemodynamic response function (HRF) as compared to wavelet-based filtering and spline interpolation for the Velcro probe. It results in a significant reduction in mean-squared error (MSE) and significant enhancement in Pearson's correlation coefficient to the true HRF. The collodion-fixed fiber probe with no motion correction performed better than the Velcro probe corrected for motion artifacts in terms of MSE and Pearson's correlation coefficient. Thus, if the experimental study permits, the use of a collodion-fixed fiber probe may be desirable. If the use of a collodion-fixed probe is not feasible, then we suggest the use of tPCA in the processing of motion artifact contaminated data.

BEM-based simulation of lung respiratory deformation for CT-guided biopsy.

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Chen, Dong; Chen, Weisheng; Huang, Lipeng; Feng, Xuegang; Peters, Terry; Gu, Lixu

2017-09-01

Accurate and real-time prediction of the lung and lung tumor deformation during respiration are important considerations when performing a peripheral biopsy procedure. However, most existing work focused on offline whole lung simulation using 4D image data, which is not applicable in real-time image-guided biopsy with limited image resources. In this paper, we propose a patient-specific biomechanical model based on the boundary element method (BEM) computed from CT images to estimate the respiration motion of local target lesion region, vessel tree and lung surface for the real-time biopsy guidance. This approach applies pre-computation of various BEM parameters to facilitate the requirement for real-time lung motion simulation. The resulting boundary condition at end inspiratory phase is obtained using a nonparametric discrete registration with convex optimization, and the simulation of the internal tissue is achieved by applying a tetrahedron-based interpolation method depend on expert-determined feature points on the vessel tree model. A reference needle is tracked to update the simulated lung motion during biopsy guidance. We evaluate the model by applying it for respiratory motion estimations of ten patients. The average symmetric surface distance (ASSD) and the mean target registration error (TRE) are employed to evaluate the proposed model. Results reveal that it is possible to predict the lung motion with ASSD of [Formula: see text] mm and a mean TRE of [Formula: see text] mm at largest over the entire respiratory cycle. In the CT-/electromagnetic-guided biopsy experiment, the whole process was assisted by our BEM model and final puncture errors in two studies were 3.1 and 2.0 mm, respectively. The experiment results reveal that both the accuracy of simulation and real-time performance meet the demands of clinical biopsy guidance.

SU-E-J-01: 3D Fluoroscopic Image Estimation From Patient-Specific 4DCBCT-Based Motion Models

International Nuclear Information System (INIS)

Dhou, S; Hurwitz, M; Lewis, J; Mishra, P

2014-01-01

Purpose: 3D motion modeling derived from 4DCT images, taken days or weeks before treatment, cannot reliably represent patient anatomy on the day of treatment. We develop a method to generate motion models based on 4DCBCT acquired at the time of treatment, and apply the model to estimate 3D time-varying images (referred to as 3D fluoroscopic images). Methods: Motion models are derived through deformable registration between each 4DCBCT phase, and principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated based on cone-beam projections simulating kV treatment imaging. PCA coefficients are optimized iteratively through comparison of these cone-beam projections and projections estimated based on the motion model. Digital phantoms reproducing ten patient motion trajectories, and a physical phantom with regular and irregular motion derived from measured patient trajectories, are used to evaluate the method in terms of tumor localization, and the global voxel intensity difference compared to ground truth. Results: Experiments included: 1) assuming no anatomic or positioning changes between 4DCT and treatment time; and 2) simulating positioning and tumor baseline shifts at the time of treatment compared to 4DCT acquisition. 4DCBCT were reconstructed from the anatomy as seen at treatment time. In case 1) the tumor localization error and the intensity differences in ten patient were smaller using 4DCT-based motion model, possible due to superior image quality. In case 2) the tumor localization error and intensity differences were 2.85 and 0.15 respectively, using 4DCT-based motion models, and 1.17 and 0.10 using 4DCBCT-based models. 4DCBCT performed better due to its ability to reproduce daily anatomical changes. Conclusion: The study showed an advantage of 4DCBCT-based motion models in the context of 3D fluoroscopic images estimation. Positioning and tumor baseline shift uncertainties were mitigated by the 4DCBCT-based

Comparison of lung tumor motion measured using a model-based 4DCT technique and a commercial protocol.

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O'Connell, Dylan; Shaverdian, Narek; Kishan, Amar U; Thomas, David H; Dou, Tai H; Lewis, John H; Lamb, James M; Cao, Minsong; Tenn, Stephen; Percy, Lee P; Low, Daniel A

2017-11-11

To compare lung tumor motion measured with a model-based technique to commercial 4-dimensional computed tomography (4DCT) scans and describe a workflow for using model-based 4DCT as a clinical simulation protocol. Twenty patients were imaged using a model-based technique and commercial 4DCT. Tumor motion was measured on each commercial 4DCT dataset and was calculated on model-based datasets for 3 breathing amplitude percentile intervals: 5th to 85th, 5th to 95th, and 0th to 100th. Internal target volumes (ITVs) were defined on the 4DCT and 5th to 85th interval datasets and compared using Dice similarity. Images were evaluated for noise and rated by 2 radiation oncologists for artifacts. Mean differences in tumor motion magnitude between commercial and model-based images were 0.47 ± 3.0, 1.63 ± 3.17, and 5.16 ± 4.90 mm for the 5th to 85th, 5th to 95th, and 0th to 100th amplitude intervals, respectively. Dice coefficients between ITVs defined on commercial and 5th to 85th model-based images had a mean value of 0.77 ± 0.09. Single standard deviation image noise was 11.6 ± 9.6 HU in the liver and 6.8 ± 4.7 HU in the aorta for the model-based images compared with 57.7 ± 30 and 33.7 ± 15.4 for commercial 4DCT. Mean model error within the ITV regions was 1.71 ± 0.81 mm. Model-based images exhibited reduced presence of artifacts at the tumor compared with commercial images. Tumor motion measured with the model-based technique using the 5th to 85th percentile breathing amplitude interval corresponded more closely to commercial 4DCT than the 5th to 95th or 0th to 100th intervals, which showed greater motion on average. The model-based technique tended to display increased tumor motion when breathing amplitude intervals wider than 5th to 85th were used because of the influence of unusually deep inhalations. These results suggest that care must be taken in selecting the appropriate interval during image generation when using model-based 4DCT methods. Copyright © 2017

Audiovisual biofeedback improves the correlation between internal/external surrogate motion and lung tumor motion.

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Lee, Danny; Greer, Peter B; Paganelli, Chiara; Ludbrook, Joanna Jane; Kim, Taeho; Keall, Paul

2018-03-01

Breathing management can reduce breath-to-breath (intrafraction) and day-by-day (interfraction) variability in breathing motion while utilizing the respiratory motion of internal and external surrogates for respiratory guidance. Audiovisual (AV) biofeedback, an interactive personalized breathing motion management system, has been developed to improve reproducibility of intra- and interfraction breathing motion. However, the assumption of the correlation of respiratory motion between surrogates and tumors is not always verified during medical imaging and radiation treatment. Therefore, the aim of the study was to test the hypothesis that the correlation of respiratory motion between surrogates and tumors is the same under free breathing without guidance (FB) and with AV biofeedback guidance for voluntary motion management. For 13 lung cancer patients receiving radiotherapy, 2D coronal and sagittal cine-MR images were acquired across two MRI sessions (pre- and mid-treatment) with two breathing conditions: (a) FB and (b) AV biofeedback, totaling 88 patient measurements. Simultaneously, the external respiratory motion of the abdomen was measured. The internal respiratory motion of the diaphragm and lung tumor was retrospectively measured from 2D coronal and sagittal cine-MR images. The correlation of respiratory motion between surrogates and tumors was calculated using Pearson's correlation coefficient for: (a) abdomen to tumor (abdomen-tumor) and (b) diaphragm to tumor (diaphragm-tumor). The correlations were compared between FB and AV biofeedback using several metrics: abdomen-tumor and diaphragm-tumor correlations with/without ≥5 mm tumor motion range and with/without adjusting for phase shifts between the signals. Compared to FB, AV biofeedback improved abdomen-tumor correlation by 11% (p = 0.12) from 0.53 to 0.59 and diaphragm-tumor correlation by 13% (p = 0.02) from 0.55 to 0.62. Compared to FB, AV biofeedback improved abdomen-tumor correlation by 17% (p = 0

Evaluation of tumor localization in respiration motion-corrected cone-beam CT: prospective study in lung.

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Dzyubak, Oleksandr; Kincaid, Russell; Hertanto, Agung; Hu, Yu-Chi; Pham, Hai; Rimner, Andreas; Yorke, Ellen; Zhang, Qinghui; Mageras, Gig S

2014-10-01

Target localization accuracy of cone-beam CT (CBCT) images used in radiation treatment of respiratory disease sites is affected by motion artifacts (blurring and streaking). The authors have previously reported on a method of respiratory motion correction in thoracic CBCT at end expiration (EE). The previous retrospective study was limited to examination of reducing motion artifacts in a small number of patient cases. They report here on a prospective study in a larger group of lung cancer patients to evaluate respiratory motion-corrected (RMC)-CBCT ability to improve lung tumor localization accuracy and reduce motion artifacts in Linac-mounted CBCT images. A second study goal examines whether the motion correction derived from a respiration-correlated CT (RCCT) at simulation yields similar tumor localization accuracy at treatment. In an IRB-approved study, 19 lung cancer patients (22 tumors) received a RCCT at simulation, and on one treatment day received a RCCT, a respiratory-gated CBCT at end expiration, and a 1-min CBCT. A respiration monitor of abdominal displacement was used during all scans. In addition to a CBCT reconstruction without motion correction, the motion correction method was applied to the same 1-min scan. Projection images were sorted into ten bins based on abdominal displacement, and each bin was reconstructed to produce ten intermediate CBCT images. Each intermediate CBCT was deformed to the end expiration state using a motion model derived from RCCT. The deformed intermediate CBCT images were then added to produce a final RMC-CBCT. In order to evaluate the second study goal, the CBCT was corrected in two ways, one using a model derived from the RCCT at simulation [RMC-CBCT(sim)], the other from the RCCT at treatment [RMC-CBCT(tx)]. Image evaluation compared uncorrected CBCT, RMC-CBCT(sim), and RMC-CBCT(tx). The gated CBCT at end expiration served as the criterion standard for comparison. Using automatic rigid image registration, each CBCT was

How does knee pain affect trunk and knee motion during badminton forehand lunges?

Science.gov (United States)

Huang, Ming-Tung; Lee, Hsing-Hsan; Lin, Cheng-Feng; Tsai, Yi-Ju; Liao, Jen-Chieh

2014-01-01

Badminton requires extensive lower extremity movement and a precise coordination of the upper extremity and trunk movements. Accordingly, this study investigated motions of the trunk and the knee, control of dynamic stability and muscle activation patterns of individuals with and without knee pain. Seventeen participants with chronic knee pain and 17 healthy participants participated in the study and performed forehand forward and backward diagonal lunges. This study showed that those with knee pain exhibited smaller knee motions in frontal and horizontal planes during forward lunge but greater knee motions in sagittal plane during backward lunge. By contrast, in both tasks, the injured group showed a smaller value on the activation level of the paraspinal muscles in pre-impact phase, hip-shoulder separation angle, trunk forward inclination range and peak centre of mass (COM) velocity. Badminton players with knee pain adopt a more conservative movement pattern of the knee to minimise recurrence of knee pain. The healthy group exhibit better weight-shifting ability due to a greater control of the trunk and knee muscles. Training programmes for badminton players with knee pain should be designed to improve both the neuromuscular control and muscle strength of the core muscles and the knee extensor with focus on the backward lunge motion.

Volatilization from PCA steel alloy

Energy Technology Data Exchange (ETDEWEB)

Hagrman, D.L.; Smolik, G.R.; McCarthy, K.A.; Petti, D.A.

1996-08-01

The mobilizations of key components from Primary Candidate Alloy (PCA) steel alloy have been measured with laboratory-scale experiments. The experiments indicate most of the mobilization from PCA steel is due to oxide formation and spalling but that the spalled particles are large enough to settle rapidly. Based on the experiments, models for the volatization of iron, manganese, and cobalt from PCA steel in steam and molybdenum from PCA steel in air have been derived.

Estimation of lung motion fields in 4D CT data by variational non-linear intensity-based registration: A comparison and evaluation study

International Nuclear Information System (INIS)

Werner, René; Schmidt-Richberg, Alexander; Handels, Heinz; Ehrhardt, Jan

2014-01-01

Accurate and robust estimation of motion fields in respiration-correlated CT (4D CT) images, usually performed by non-linear registration of the temporal CT frames, is a precondition for the analysis of patient-specific breathing dynamics and subsequent image-supported diagnostics and treatment planning. In this work, we present a comprehensive comparison and evaluation study of non-linear registration variants applied to the task of lung motion estimation in thoracic 4D CT data. In contrast to existing multi-institutional comparison studies (e.g. MIDRAS and EMPIRE10), we focus on the specific but common class of variational intensity-based non-parametric registration and analyze the impact of the different main building blocks of the underlying optimization problem: the distance measure to be minimized, the regularization approach and the transformation space considered during optimization. In total, 90 different combinations of building block instances are compared. Evaluated on proprietary and publicly accessible 4D CT images, landmark-based registration errors (TRE) between 1.14 and 1.20 mm for the most accurate registration variants demonstrate competitive performance of the applied general registration framework compared to other state-of-the-art approaches for lung CT registration. Although some specific trends can be observed, effects of interchanging individual instances of the building blocks on the TRE are in general rather small (no single outstanding registration variant existing); the same level of accuracy is, however, associated with significantly different degrees of motion field smoothness and computational demands. Consequently, the building block combination of choice will depend on application-specific requirements on motion field characteristics. (paper)

Model-based respiratory motion compensation for emission tomography image reconstruction

International Nuclear Information System (INIS)

Reyes, M; Malandain, G; Koulibaly, P M; Gonzalez-Ballester, M A; Darcourt, J

2007-01-01

In emission tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations, imprecise diagnosis, impairing of fusion with other modalities, etc. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested, which lead to improvements over the spatial activity distribution in lungs lesions, but which have the disadvantages of requiring additional instrumentation or the need of discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion compensation directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the maximum likelihood expectation maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data

Evaluation of tumor localization in respiration motion-corrected cone-beam CT: Prospective study in lung

Energy Technology Data Exchange (ETDEWEB)

Dzyubak, Oleksandr; Kincaid, Russell; Hertanto, Agung; Hu, Yu-Chi; Pham, Hai; Yorke, Ellen; Zhang, Qinghui; Mageras, Gig S., E-mail: magerasg@mskcc.org [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York 10065 (United States); Rimner, Andreas [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, New York 10065 (United States)

2014-10-15

Purpose: Target localization accuracy of cone-beam CT (CBCT) images used in radiation treatment of respiratory disease sites is affected by motion artifacts (blurring and streaking). The authors have previously reported on a method of respiratory motion correction in thoracic CBCT at end expiration (EE). The previous retrospective study was limited to examination of reducing motion artifacts in a small number of patient cases. They report here on a prospective study in a larger group of lung cancer patients to evaluate respiratory motion-corrected (RMC)-CBCT ability to improve lung tumor localization accuracy and reduce motion artifacts in Linac-mounted CBCT images. A second study goal examines whether the motion correction derived from a respiration-correlated CT (RCCT) at simulation yields similar tumor localization accuracy at treatment. Methods: In an IRB-approved study, 19 lung cancer patients (22 tumors) received a RCCT at simulation, and on one treatment day received a RCCT, a respiratory-gated CBCT at end expiration, and a 1-min CBCT. A respiration monitor of abdominal displacement was used during all scans. In addition to a CBCT reconstruction without motion correction, the motion correction method was applied to the same 1-min scan. Projection images were sorted into ten bins based on abdominal displacement, and each bin was reconstructed to produce ten intermediate CBCT images. Each intermediate CBCT was deformed to the end expiration state using a motion model derived from RCCT. The deformed intermediate CBCT images were then added to produce a final RMC-CBCT. In order to evaluate the second study goal, the CBCT was corrected in two ways, one using a model derived from the RCCT at simulation [RMC-CBCT(sim)], the other from the RCCT at treatment [RMC-CBCT(tx)]. Image evaluation compared uncorrected CBCT, RMC-CBCT(sim), and RMC-CBCT(tx). The gated CBCT at end expiration served as the criterion standard for comparison. Using automatic rigid image

Assessing Respiration-Induced Tumor Motion and Internal Target Volume Using Four-Dimensional Computed Tomography for Radiotherapy of Lung Cancer

International Nuclear Information System (INIS)

Liu, H. Helen; Balter, Peter; Tutt, Teresa; Choi, Bum; Zhang, Joy; Wang, Catherine; Chi, Melinda; Luo Dershan; Pan Tinsu; Hunjan, Sandeep; Starkschall, George; Rosen, Isaac; Prado, Karl; Liao Zhongxing; Chang, Joe; Komaki, Ritsuko; Cox, James D.; Mohan, Radhe; Dong Lei

2007-01-01

Purpose: To assess three-dimensional tumor motion caused by respiration and internal target volume (ITV) for radiotherapy of lung cancer. Methods and Materials: Respiration-induced tumor motion was analyzed for 166 tumors from 152 lung cancer patients, 57.2% of whom had Stage III or IV non-small-cell lung cancer. All patients underwent four-dimensional computed tomography (4DCT) during normal breathing before treatment. The expiratory phase of 4DCT images was used as the reference set to delineate gross tumor volume (GTV). Gross tumor volumes on other respiratory phases and resulting ITVs were determined using rigid-body registration of 4DCT images. The association of GTV motion with various clinical and anatomic factors was analyzed statistically. Results: The proportions of tumors that moved >0.5 cm along the superior-inferior (SI), lateral, and anterior-posterior (AP) axes during normal breathing were 39.2%, 1.8%, and 5.4%, respectively. For 95% of the tumors, the magnitude of motion was less than 1.34 cm, 0.40 cm, and 0.59 cm along the SI, lateral, and AP directions. The principal component of tumor motion was in the SI direction, with only 10.8% of tumors moving >1.0 cm. The tumor motion was found to be associated with diaphragm motion, the SI tumor location in the lung, size of the GTV, and disease T stage. Conclusions: Lung tumor motion is primarily driven by diaphragm motion. The motion of locally advanced lung tumors is unlikely to exceed 1.0 cm during quiet normal breathing except for small lesions located in the lower half of the lung

The singular value filter: a general filter design strategy for PCA-based signal separation in medical ultrasound imaging.

Science.gov (United States)

Mauldin, F William; Lin, Dan; Hossack, John A

2011-11-01

A general filtering method, called the singular value filter (SVF), is presented as a framework for principal component analysis (PCA) based filter design in medical ultrasound imaging. The SVF approach operates by projecting the original data onto a new set of bases determined from PCA using singular value decomposition (SVD). The shape of the SVF weighting function, which relates the singular value spectrum of the input data to the filtering coefficients assigned to each basis function, is designed in accordance with a signal model and statistical assumptions regarding the underlying source signals. In this paper, we applied SVF for the specific application of clutter artifact rejection in diagnostic ultrasound imaging. SVF was compared to a conventional PCA-based filtering technique, which we refer to as the blind source separation (BSS) method, as well as a simple frequency-based finite impulse response (FIR) filter used as a baseline for comparison. The performance of each filter was quantified in simulated lesion images as well as experimental cardiac ultrasound data. SVF was demonstrated in both simulation and experimental results, over a wide range of imaging conditions, to outperform the BSS and FIR filtering methods in terms of contrast-to-noise ratio (CNR) and motion tracking performance. In experimental mouse heart data, SVF provided excellent artifact suppression with an average CNR improvement of 1.8 dB with over 40% reduction in displacement tracking error. It was further demonstrated from simulation and experimental results that SVF provided superior clutter rejection, as reflected in larger CNR values, when filtering was achieved using complex pulse-echo received data and non-binary filter coefficients.

MO-G-18C-03: Evaluation of Deformable Image Registration for Lung Motion Estimation Using Hyperpolarized Gas Tagging MRI

International Nuclear Information System (INIS)

Huang, Q; Zhang, Y; Liu, Y; Hu, L; Yin, F; Cai, J; Miller, W

2014-01-01

Purpose: Hyperpolarized gas (HP) tagging MRI is a novel imaging technique for direct measurement of lung motion during breathing. This study aims to quantitatively evaluate the accuracy of deformable image registration (DIR) in lung motion estimation using HP tagging MRI as references. Methods: Three healthy subjects were imaged using the HP MR tagging, as well as a high-resolution 3D proton MR sequence (TrueFISP) at the end-of-inhalation (EOI) and the end-of-exhalation (EOE). Ground truth of lung motion and corresponding displacement vector field (tDVF) was derived from HP tagging MRI by manually tracking the displacement of tagging grids between EOI and EOE. Seven different DIR methods were applied to the high-resolution TrueFISP MR images (EOI and EOE) to generate the DIR-based DVFs (dDVF). The DIR methods include Velocity (VEL), MIM, Mirada, multi-grid B-spline from Elastix (MGB) and 3 other algorithms from DIRART toolbox (Double Force Demons (DFD), Improved Lucas-Kanade (ILK), and Iterative Optical Flow (IOF)). All registrations were performed by independent experts. Target registration error (TRE) was calculated as tDVF – dDVF. Analysis was performed for the entire lungs, and separately for the upper and lower lungs. Results: Significant differences between tDVF and dDVF were observed. Besides the DFD and IOF algorithms, all other dDVFs showed similarity in deformation magnitude distribution but away from the ground truth. The average TRE for entire lung ranged 2.5−23.7mm (mean=8.8mm), depending on the DIR method and subject's breathing amplitude. Larger TRE (13.3–23.7mm) was found in subject with larger breathing amplitude of 45.6mm. TRE was greater in lower lung (2.5−33.9 mm, mean=12.4mm) than that in upper lung (2.5−11.9 mm, mean=5.8mm). Conclusion: Significant differences were observed in lung motion estimation between the HP gas tagging MRI method and the DIR methods, especially when lung motion is large. Large variation among different

MO-G-18C-03: Evaluation of Deformable Image Registration for Lung Motion Estimation Using Hyperpolarized Gas Tagging MRI

Energy Technology Data Exchange (ETDEWEB)

Huang, Q; Zhang, Y [Duke University, Durham, NC (United States); Liu, Y [Duke University (United States); Hu, L; Yin, F; Cai, J [Duke University Medical Center, Durham, NC (United States); Miller, W [University of Virginia, Charlottesville, VA (United States)

2014-06-15

Purpose: Hyperpolarized gas (HP) tagging MRI is a novel imaging technique for direct measurement of lung motion during breathing. This study aims to quantitatively evaluate the accuracy of deformable image registration (DIR) in lung motion estimation using HP tagging MRI as references. Methods: Three healthy subjects were imaged using the HP MR tagging, as well as a high-resolution 3D proton MR sequence (TrueFISP) at the end-of-inhalation (EOI) and the end-of-exhalation (EOE). Ground truth of lung motion and corresponding displacement vector field (tDVF) was derived from HP tagging MRI by manually tracking the displacement of tagging grids between EOI and EOE. Seven different DIR methods were applied to the high-resolution TrueFISP MR images (EOI and EOE) to generate the DIR-based DVFs (dDVF). The DIR methods include Velocity (VEL), MIM, Mirada, multi-grid B-spline from Elastix (MGB) and 3 other algorithms from DIRART toolbox (Double Force Demons (DFD), Improved Lucas-Kanade (ILK), and Iterative Optical Flow (IOF)). All registrations were performed by independent experts. Target registration error (TRE) was calculated as tDVF – dDVF. Analysis was performed for the entire lungs, and separately for the upper and lower lungs. Results: Significant differences between tDVF and dDVF were observed. Besides the DFD and IOF algorithms, all other dDVFs showed similarity in deformation magnitude distribution but away from the ground truth. The average TRE for entire lung ranged 2.5−23.7mm (mean=8.8mm), depending on the DIR method and subject's breathing amplitude. Larger TRE (13.3–23.7mm) was found in subject with larger breathing amplitude of 45.6mm. TRE was greater in lower lung (2.5−33.9 mm, mean=12.4mm) than that in upper lung (2.5−11.9 mm, mean=5.8mm). Conclusion: Significant differences were observed in lung motion estimation between the HP gas tagging MRI method and the DIR methods, especially when lung motion is large. Large variation among different

Avoiding Optimal Mean ℓ2,1-Norm Maximization-Based Robust PCA for Reconstruction.

Science.gov (United States)

Luo, Minnan; Nie, Feiping; Chang, Xiaojun; Yang, Yi; Hauptmann, Alexander G; Zheng, Qinghua

2017-04-01

Robust principal component analysis (PCA) is one of the most important dimension-reduction techniques for handling high-dimensional data with outliers. However, most of the existing robust PCA presupposes that the mean of the data is zero and incorrectly utilizes the average of data as the optimal mean of robust PCA. In fact, this assumption holds only for the squared [Formula: see text]-norm-based traditional PCA. In this letter, we equivalently reformulate the objective of conventional PCA and learn the optimal projection directions by maximizing the sum of projected difference between each pair of instances based on [Formula: see text]-norm. The proposed method is robust to outliers and also invariant to rotation. More important, the reformulated objective not only automatically avoids the calculation of optimal mean and makes the assumption of centered data unnecessary, but also theoretically connects to the minimization of reconstruction error. To solve the proposed nonsmooth problem, we exploit an efficient optimization algorithm to soften the contributions from outliers by reweighting each data point iteratively. We theoretically analyze the convergence and computational complexity of the proposed algorithm. Extensive experimental results on several benchmark data sets illustrate the effectiveness and superiority of the proposed method.

Evaluation of image guided motion management methods in lung cancer radiotherapy

International Nuclear Information System (INIS)

Zhuang, Ling; Yan, Di; Liang, Jian; Ionascu, Dan; Mangona, Victor; Yang, Kai; Zhou, Jun

2014-01-01

Purpose: To evaluate the accuracy and reliability of three target localization methods for image guided motion management in lung cancer radiotherapy. Methods: Three online image localization methods, including (1) 2D method based on 2D cone beam (CB) projection images, (2) 3D method using 3D cone beam CT (CBCT) imaging, and (3) 4D method using 4D CBCT imaging, have been evaluated using a moving phantom controlled by (a) 1D theoretical breathing motion curves and (b) 3D target motion patterns obtained from daily treatment of 3 lung cancer patients. While all methods are able to provide target mean position (MP), the 2D and 4D methods can also provide target motion standard deviation (SD) and excursion (EX). For each method, the detected MP/SD/EX values are compared to the analytically calculated actual values to calculate the errors. The MP errors are compared among three methods and the SD/EX errors are compared between the 2D and 4D methods. In the theoretical motion study (a), the dependency of MP/SD/EX error on EX is investigated with EX varying from 2.0 cm to 3.0 cm with an increment step of 0.2 cm. In the patient motion study (b), the dependency of MP error on target sizes (2.0 cm and 3.0 cm), motion patterns (four motions per patient) and EX variations is investigated using multivariant linear regression analysis. Results: In the theoretical motion study (a), the MP detection errors are −0.2 ± 0.2, −1.5 ± 1.1, and −0.2 ± 0.2 mm for 2D, 3D, and 4D methods, respectively. Both the 2D and 4D methods could accurately detect motion pattern EX (error < 1.2 mm) and SD (error < 1.0 mm). In the patient motion study (b), MP detection error vector (mm) with the 2D method (0.7 ± 0.4) is found to be significantly less than with the 3D method (1.7 ± 0.8,p < 0.001) and the 4D method (1.4 ± 1.0, p < 0.001) using paired t-test. However, no significant difference is found between the 4D method and the 3D method. Based on multivariant linear regression analysis, the

Evaluation of image guided motion management methods in lung cancer radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Zhuang, Ling [Department of Radiation Oncology, Wayne State University School of Medicine, 4100 John R, Detroit, Michigan 48201 (United States); Yan, Di; Liang, Jian; Ionascu, Dan; Mangona, Victor; Yang, Kai; Zhou, Jun, E-mail: jun.zhou@beaumont.edu [Department of Radiation Oncology, William Beaumont Hospital, 3601 West Thirteen Mile Road, Royal Oak, Michigan 48073 (United States)

2014-03-15

Purpose: To evaluate the accuracy and reliability of three target localization methods for image guided motion management in lung cancer radiotherapy. Methods: Three online image localization methods, including (1) 2D method based on 2D cone beam (CB) projection images, (2) 3D method using 3D cone beam CT (CBCT) imaging, and (3) 4D method using 4D CBCT imaging, have been evaluated using a moving phantom controlled by (a) 1D theoretical breathing motion curves and (b) 3D target motion patterns obtained from daily treatment of 3 lung cancer patients. While all methods are able to provide target mean position (MP), the 2D and 4D methods can also provide target motion standard deviation (SD) and excursion (EX). For each method, the detected MP/SD/EX values are compared to the analytically calculated actual values to calculate the errors. The MP errors are compared among three methods and the SD/EX errors are compared between the 2D and 4D methods. In the theoretical motion study (a), the dependency of MP/SD/EX error on EX is investigated with EX varying from 2.0 cm to 3.0 cm with an increment step of 0.2 cm. In the patient motion study (b), the dependency of MP error on target sizes (2.0 cm and 3.0 cm), motion patterns (four motions per patient) and EX variations is investigated using multivariant linear regression analysis. Results: In the theoretical motion study (a), the MP detection errors are −0.2 ± 0.2, −1.5 ± 1.1, and −0.2 ± 0.2 mm for 2D, 3D, and 4D methods, respectively. Both the 2D and 4D methods could accurately detect motion pattern EX (error < 1.2 mm) and SD (error < 1.0 mm). In the patient motion study (b), MP detection error vector (mm) with the 2D method (0.7 ± 0.4) is found to be significantly less than with the 3D method (1.7 ± 0.8,p < 0.001) and the 4D method (1.4 ± 1.0, p < 0.001) using paired t-test. However, no significant difference is found between the 4D method and the 3D method. Based on multivariant linear regression analysis, the

SU-E-J-29: Audiovisual Biofeedback Improves Tumor Motion Consistency for Lung Cancer Patients

International Nuclear Information System (INIS)

Lee, D; Pollock, S; Makhija, K; Keall, P; Greer, P; Arm, J; Hunter, P; Kim, T

2014-01-01

Purpose: To investigate whether the breathing-guidance system: audiovisual (AV) biofeedback improves tumor motion consistency for lung cancer patients. This will minimize respiratory-induced tumor motion variations across cancer imaging and radiotherapy procedues. This is the first study to investigate the impact of respiratory guidance on tumor motion. Methods: Tumor motion consistency was investigated with five lung cancer patients (age: 55 to 64), who underwent a training session to get familiarized with AV biofeedback, followed by two MRI sessions across different dates (pre and mid treatment). During the training session in a CT room, two patient specific breathing patterns were obtained before (Breathing-Pattern-1) and after (Breathing-Pattern-2) training with AV biofeedback. In each MRI session, four MRI scans were performed to obtain 2D coronal and sagittal image datasets in free breathing (FB), and with AV biofeedback utilizing Breathing-Pattern-2. Image pixel values of 2D images after the normalization of 2D images per dataset and Gaussian filter per image were used to extract tumor motion using image pixel values. The tumor motion consistency of the superior-inferior (SI) direction was evaluated in terms of an average tumor motion range and period. Results: Audiovisual biofeedback improved tumor motion consistency by 60% (p value = 0.019) from 1.0±0.6 mm (FB) to 0.4±0.4 mm (AV) in SI motion range, and by 86% (p value < 0.001) from 0.7±0.6 s (FB) to 0.1±0.2 s (AV) in period. Conclusion: This study demonstrated that audiovisual biofeedback improves both breathing pattern and tumor motion consistency for lung cancer patients. These results suggest that AV biofeedback has the potential for facilitating reproducible tumor motion towards achieving more accurate medical imaging and radiation therapy procedures

SU-E-J-29: Audiovisual Biofeedback Improves Tumor Motion Consistency for Lung Cancer Patients

Energy Technology Data Exchange (ETDEWEB)

Lee, D; Pollock, S; Makhija, K; Keall, P [The University of Sydney, Camperdown, NSW (Australia); Greer, P [The University of Newcastle, Newcastle, NSW (Australia); Calvary Mater Newcastle Hospital, Newcastle, NSW (Australia); Arm, J; Hunter, P [Calvary Mater Newcastle Hospital, Newcastle, NSW (Australia); Kim, T [The University of Sydney, Camperdown, NSW (Australia); University of Virginia Health System, Charlottesville, VA (United States)

2014-06-01

Purpose: To investigate whether the breathing-guidance system: audiovisual (AV) biofeedback improves tumor motion consistency for lung cancer patients. This will minimize respiratory-induced tumor motion variations across cancer imaging and radiotherapy procedues. This is the first study to investigate the impact of respiratory guidance on tumor motion. Methods: Tumor motion consistency was investigated with five lung cancer patients (age: 55 to 64), who underwent a training session to get familiarized with AV biofeedback, followed by two MRI sessions across different dates (pre and mid treatment). During the training session in a CT room, two patient specific breathing patterns were obtained before (Breathing-Pattern-1) and after (Breathing-Pattern-2) training with AV biofeedback. In each MRI session, four MRI scans were performed to obtain 2D coronal and sagittal image datasets in free breathing (FB), and with AV biofeedback utilizing Breathing-Pattern-2. Image pixel values of 2D images after the normalization of 2D images per dataset and Gaussian filter per image were used to extract tumor motion using image pixel values. The tumor motion consistency of the superior-inferior (SI) direction was evaluated in terms of an average tumor motion range and period. Results: Audiovisual biofeedback improved tumor motion consistency by 60% (p value = 0.019) from 1.0±0.6 mm (FB) to 0.4±0.4 mm (AV) in SI motion range, and by 86% (p value < 0.001) from 0.7±0.6 s (FB) to 0.1±0.2 s (AV) in period. Conclusion: This study demonstrated that audiovisual biofeedback improves both breathing pattern and tumor motion consistency for lung cancer patients. These results suggest that AV biofeedback has the potential for facilitating reproducible tumor motion towards achieving more accurate medical imaging and radiation therapy procedures.

A margin-based analysis of the dosimetric impact of motion on step-and-shoot IMRT lung plans

International Nuclear Information System (INIS)

Waghorn, Benjamin J; Shah, Amish P; Rineer, Justin M; Langen, Katja M; Meeks, Sanford L

2014-01-01

Intrafraction motion during step-and-shoot (SNS) IMRT is known to affect the target dosimetry by a combination of dose blurring and interplay effects. These effects are typically managed by adding a margin around the target. A quantitative analysis was performed, assessing the relationship between target motion, margin size, and target dosimetry with the goal of introducing new margin recipes. A computational algorithm was used to calculate 1,174 motion-encoded dose distributions and DVHs within the patient’s CT dataset. Sinusoidal motion tracks were used simulating intrafraction motion for nine lung tumor patients, each with multiple margin sizes. D 95% decreased by less than 3% when the maximum target displacement beyond the margin experienced motion less than 5 mm in the superior-inferior direction and 15 mm in the anterior-posterior direction. For target displacements greater than this, D 95% decreased rapidly. Targets moving in excess of 5 mm outside the margin can cause significant changes to the target. D 95% decreased by up to 20% with target motion 10 mm outside the margin, with underdosing primarily limited to the target periphery. Multi-fractionated treatments were found to exacerbate target under-coverage. Margins several millimeters smaller than the maximum target displacement provided acceptable motion protection, while also allowing for reduced normal tissue morbidity

Therapy monitoring using dynamic MRI: Analysis of lung motion and intrathoracic tumor mobility before and after radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Plathow, Christian [Eberhard-Karls University Tuebingen, Department of Diagnostic Radiology, Tuebingen (Germany); German Cancer Research Center, Department of Radiology, Heidelberg (Germany); Hof, Holger; Kuhn, Sabine [University of Heidelberg, Department of Radiation Therapy, Clinic for Thoracic Diseases, Heidelberg (Germany); Puderbach, Michael; Ley, Sebastian; Biederer, Juergen; Kauczor, Hans-Ulrich [German Cancer Research Center, Department of Radiology, Heidelberg (Germany); Claussen, Claus D.; Schaefer, Juergen [Eberhard-Karls University Tuebingen, Department of Diagnostic Radiology, Tuebingen (Germany); Huber, Peter E. [University of Heidelberg, Department of Radiation Therapy, Clinic for Thoracic Diseases, Heidelberg (Germany); German Cancer Research Center, Department of Radiation Oncology, Heidelberg (Germany); Tuengerthal, Siegfried [University of Heidelberg, Department of Radiology, Heidelberg (Germany)

2006-09-15

A frequent side effect after radiotherapy of lung tumors is a decrease of pulmonary function accompanied by dyspnea due to developing lung fibrosis. The aim of this study was to monitor lung motion as a correlate of pulmonary function and intrathoracic tumor mobility before and after radiotherapy (RT) using dynamic MRI (dMRI). Thirty-five patients with stage I non-small-cell lung carcinoma were examined using dMRI (trueFISP; three images/s). Tumors were divided into T1 and T2 tumors of the upper, middle and lower lung region (LR). Maximum craniocaudal (CC) lung dimensions and tumor mobility in three dimensions were monitored. Vital capacity (VC) was measured and correlated using spirometry. Before RT, the maximum CC motion of the tumor-bearing hemithorax was 5.2{+-}0.9 cm if the tumor was located in the lower LR (middle LR: 5.5{+-}0.8 cm; upper LR: 6.0{+-}0.6 cm). After RT, lung motion was significantly reduced in the lower LR (P<0.05). Before RT, the maximum CC tumor mobility was significantly higher in tumors of the lower LR 2.5{+-}0.6 vs. 2.0{+-}0.3 cm (middle LR; P<0.05) vs. 0.7{+-}0.2 cm (upper LR; P<0.01). After RT, tumor mobility was significantly reduced in the lower LR (P<0.01) and in T2 tumor patients (P<0.05). VC showed no significant changes. dMRI is capable of monitoring changes in lung motion that were not suspected from spirometry. This might make the treatment of side effects possible at a very early stage. Changes of lung motion and tumor mobility are highly dependent on the tumor localization and tumor diameter. (orig.)

Therapy monitoring using dynamic MRI: Analysis of lung motion and intrathoracic tumor mobility before and after radiotherapy

International Nuclear Information System (INIS)

Plathow, Christian; Hof, Holger; Kuhn, Sabine; Puderbach, Michael; Ley, Sebastian; Biederer, Juergen; Kauczor, Hans-Ulrich; Claussen, Claus D.; Schaefer, Juergen; Huber, Peter E.; Tuengerthal, Siegfried

2006-01-01

A frequent side effect after radiotherapy of lung tumors is a decrease of pulmonary function accompanied by dyspnea due to developing lung fibrosis. The aim of this study was to monitor lung motion as a correlate of pulmonary function and intrathoracic tumor mobility before and after radiotherapy (RT) using dynamic MRI (dMRI). Thirty-five patients with stage I non-small-cell lung carcinoma were examined using dMRI (trueFISP; three images/s). Tumors were divided into T1 and T2 tumors of the upper, middle and lower lung region (LR). Maximum craniocaudal (CC) lung dimensions and tumor mobility in three dimensions were monitored. Vital capacity (VC) was measured and correlated using spirometry. Before RT, the maximum CC motion of the tumor-bearing hemithorax was 5.2±0.9 cm if the tumor was located in the lower LR (middle LR: 5.5±0.8 cm; upper LR: 6.0±0.6 cm). After RT, lung motion was significantly reduced in the lower LR (P<0.05). Before RT, the maximum CC tumor mobility was significantly higher in tumors of the lower LR 2.5±0.6 vs. 2.0±0.3 cm (middle LR; P<0.05) vs. 0.7±0.2 cm (upper LR; P<0.01). After RT, tumor mobility was significantly reduced in the lower LR (P<0.01) and in T2 tumor patients (P<0.05). VC showed no significant changes. dMRI is capable of monitoring changes in lung motion that were not suspected from spirometry. This might make the treatment of side effects possible at a very early stage. Changes of lung motion and tumor mobility are highly dependent on the tumor localization and tumor diameter. (orig.)

SU-F-T-560: Measurement of Dose Blurring Effect Due to Respiratory Motion for Lung Stereotactic Body Radiation Therapy (SBRT) Using Monte Carlo Based Calculation Algorithm

International Nuclear Information System (INIS)

Badkul, R; Pokhrel, D; Jiang, H; Lominska, C; Wang, F; Ramanjappa, T

2016-01-01

Purpose: Intra-fractional tumor motion due to respiration may potentially compromise dose delivery for SBRT of lung tumors. Even sufficient margins are used to ensure there is no geometric miss of target volume, there is potential dose blurring effect may present due to motion and could impact the tumor coverage if motions are larger. In this study we investigated dose blurring effect of open fields as well as Lung SBRT patients planned using 2 non-coplanar dynamic conformal arcs(NCDCA) and few conformal beams(CB) calculated with Monte Carlo (MC) based algorithm utilizing phantom with 2D-diode array(MapCheck) and ion-chamber. Methods: SBRT lung patients were planned on Brainlab-iPlan system using 4D-CT scan and ITV were contoured on MIP image set and verified on all breathing phase image sets to account for breathing motion and then 5mm margin was applied to generate PTV. Plans were created using two NCDCA and 4-5 CB 6MV photon calculated using XVMC MC-algorithm. 3 SBRT patients plans were transferred to phantom with MapCheck and 0.125cc ion-chamber inserted in the middle of phantom to calculate dose. Also open field 3×3, 5×5 and 10×10 were calculated on this phantom. Phantom was placed on motion platform with varying motion from 5, 10, 20 and 30 mm with duty cycle of 4 second. Measurements were carried out for open fields as well 3 patients plans at static and various degree of motions. MapCheck planar dose and ion-chamber reading were collected and compared with static measurements and computed values to evaluate the dosimetric effect on tumor coverage due to motion. Results: To eliminate complexity of patients plan 3 simple open fields were also measured to see the dose blurring effect with the introduction of motion. All motion measured ionchamber values were normalized to corresponding static value. For open fields 5×5 and 10×10 normalized central axis ion-chamber values were 1.00 for all motions but for 3×3 they were 1 up to 10mm motion and 0.97 and 0

Differential Motion Between Mediastinal Lymph Nodes and Primary Tumor in Radically Irradiated Lung Cancer Patients

International Nuclear Information System (INIS)

Schaake, Eva E.; Rossi, Maddalena M.G.; Buikhuisen, Wieneke A.; Burgers, Jacobus A.; Smit, Adrianus A.J.; Belderbos, José S.A.; Sonke, Jan-Jakob

2014-01-01

Purpose/Objective: In patients with locally advanced lung cancer, planning target volume margins for mediastinal lymph nodes and tumor after a correction protocol based on bony anatomy registration typically range from 1 to 1.5 cm. Detailed information about lymph node motion variability and differential motion with the primary tumor, however, is lacking from large series. In this study, lymph node and tumor position variability were analyzed in detail and correlated to the main carina to evaluate possible margin reduction. Methods and Materials: Small gold fiducial markers (0.35 × 5 mm) were placed in the mediastinal lymph nodes of 51 patients with non-small cell lung cancer during routine diagnostic esophageal or bronchial endoscopic ultrasonography. Four-dimensional (4D) planning computed tomographic (CT) and daily 4D cone beam (CB) CT scans were acquired before and during radical radiation therapy (66 Gy in 24 fractions). Each CBCT was registered in 3-dimensions (bony anatomy) and 4D (tumor, marker, and carina) to the planning CT scan. Subsequently, systematic and random residual misalignments of the time-averaged lymph node and tumor position relative to the bony anatomy and carina were determined. Additionally, tumor and lymph node respiratory amplitude variability was quantified. Finally, required margins were quantified by use of a recipe for dual targets. Results: Relative to the bony anatomy, systematic and random errors ranged from 0.16 to 0.32 cm for the markers and from 0.15 to 0.33 cm for the tumor, but despite similar ranges there was limited correlation (0.17-0.71) owing to differential motion. A large variability in lymph node amplitude between patients was observed, with an average motion of 0.56 cm in the cranial-caudal direction. Margins could be reduced by 10% (left-right), 27% (cranial-caudal), and 10% (anteroposterior) for the lymph nodes and −2%, 15%, and 7% for the tumor if an online carina registration protocol replaced a

In Vivo Imaging of Experimental Melanoma Tumors using the Novel Radiotracer 68Ga-NODAGA-Procainamide (PCA).

Science.gov (United States)

Kertész, István; Vida, András; Nagy, Gábor; Emri, Miklós; Farkas, Antal; Kis, Adrienn; Angyal, János; Dénes, Noémi; Szabó, Judit P; Kovács, Tünde; Bai, Péter; Trencsényi, György

2017-01-01

The most aggressive form of skin cancer is the malignant melanoma. Because of its high metastatic potential the early detection of primary melanoma tumors and metastases using non-invasive PET imaging determines the outcome of the disease. Previous studies have already shown that benzamide derivatives, such as procainamide (PCA) specifically bind to melanin pigment. The aim of this study was to synthesize and investigate the melanin specificity of the novel 68 Ga-labeled NODAGA-PCA molecule in vitro and in vivo using PET techniques. Procainamide (PCA) was conjugated with NODAGA chelator and was labeled with Ga-68 ( 68 Ga-NODAGA-PCA). The melanin specificity of 68 Ga-NODAGA-PCA was tested in vitro , ex vivo and in vivo using melanotic B16-F10 and amelanotic Melur melanoma cell lines. By subcutaneous and intravenous injection of melanoma cells tumor-bearing mice were prepared, on which biodistribution studies and small animal PET/CT scans were performed for 68 Ga-NODAGA-PCA and 18 FDG tracers. 68 Ga-NODAGA-PCA was produced with high specific activity (14.9±3.9 GBq/µmol) and with excellent radiochemical purity (98%PCA uptake of B16-F10 cells was significantly ( p ≤0.01) higher than Melur cells. Ex vivo biodistribution and in vivo PET/CT studies using subcutaneous and metastatic tumor models showed significantly ( p ≤0.01) higher 68 Ga-NODAGA-PCA uptake in B16-F10 primary tumors and lung metastases in comparison with amelanotic Melur tumors. In experiments where 18 FDG and 68 Ga-NODAGA-PCA uptake of B16-F10 tumors was compared, we found that the tumor-to-muscle (T/M) and tumor-to-lung (T/L) ratios were significantly ( p ≤0.05 and p ≤0.01) higher using 68 Ga-NODAGA-PCA than the 18 FDG accumulation. Our novel radiotracer 68 Ga-NODAGA-PCA showed specific binding to the melanin producing experimental melanoma tumors. Therefore, 68 Ga-NODAGA-PCA is a suitable diagnostic radiotracer for the detection of melanoma tumors and metastases in vivo .

Dosimetric effect of intrafraction tumor motion in phase gated lung stereotactic body radiotherapy

International Nuclear Information System (INIS)

Zhao Bo; Yang Yong; Li Tianfang; Li Xiang; Heron, Dwight E.; Huq, M. Saiful

2012-01-01

Purpose: A major concern for lung intensity modulated radiation therapy delivery is the deviation of actually delivered dose distribution from the planned one due to simultaneous movements of multileaf collimator (MLC) leaves and tumor. For gated lung stereotactic body radiotherapy treatment (SBRT), the situation becomes even more complicated because of SBRT's characteristics such as fewer fractions, smaller target volume, higher dose rate, and extended fractional treatment time. The purpose of this work is to investigate the dosimetric effect of intrafraction tumor motion during gated lung SBRT delivery by reconstructing the delivered dose distribution with real-time tumor motion considered. Methods: The tumor motion data were retrieved from six lung patients. Each of them received three fractions of stereotactic radiotherapy treatments with Cyberknife Synchrony (Accuray, Sunnyvale, CA). Phase gating through an external surrogate was simulated with a gating window of 5 mm. The resulting residual tumor motion curves during gating (beam-on) were retrieved. Planning target volume (PTV) was defined as physician-contoured clinical target volume (CTV) surrounded by an isotropic 5 mm margin. Each patient was prescribed with 60 Gy/3 fractions. The authors developed an algorithm to reconstruct the delivered dose with tumor motion. The DMLC segments, mainly leaf position and segment weighting factor, were recalculated according to the probability density function of tumor motion curve. The new DMLC sequence file was imported back to treatment planning system to reconstruct the dose distribution. Results: Half of the patients in the study group experienced PTV D95% deviation up to 26% for fractional dose and 14% for total dose. CTV mean dose dropped by 1% with tumor motion. Although CTV is almost covered by prescribed dose with 5 mm margin, qualitative comparison on the dose distributions reveals that CTV is on the verge of underdose. The discrepancy happens due to tumor

The relation between respiratory motion artifact correction and lung standardized uptake value

International Nuclear Information System (INIS)

Yin Lijie; Liu Xiaojian; Liu Jie; Xu Rui; Yan Jue

2014-01-01

PET/CT is playing an important role in disease diagnosis and therapeutic evaluation. But the respiratory motion artifact may bring trouble in diagnosis and therapy. There are many methods to correct the respiratory motion artifact. Respiratory gated PET/CT is applied most extensively of them. Using respiratory gated PET/CT to correct respiratory motion artifact can increase the maximum standardized uptake value of lung lesion obviously, thereby improving the quality of image and accuracy of diagnosis. (authors)

PCA-based bootstrap confidence interval tests for gene-disease association involving multiple SNPs

Directory of Open Access Journals (Sweden)

Xue Fuzhong

2010-01-01

Full Text Available Abstract Background Genetic association study is currently the primary vehicle for identification and characterization of disease-predisposing variant(s which usually involves multiple single-nucleotide polymorphisms (SNPs available. However, SNP-wise association tests raise concerns over multiple testing. Haplotype-based methods have the advantage of being able to account for correlations between neighbouring SNPs, yet assuming Hardy-Weinberg equilibrium (HWE and potentially large number degrees of freedom can harm its statistical power and robustness. Approaches based on principal component analysis (PCA are preferable in this regard but their performance varies with methods of extracting principal components (PCs. Results PCA-based bootstrap confidence interval test (PCA-BCIT, which directly uses the PC scores to assess gene-disease association, was developed and evaluated for three ways of extracting PCs, i.e., cases only(CAES, controls only(COES and cases and controls combined(CES. Extraction of PCs with COES is preferred to that with CAES and CES. Performance of the test was examined via simulations as well as analyses on data of rheumatoid arthritis and heroin addiction, which maintains nominal level under null hypothesis and showed comparable performance with permutation test. Conclusions PCA-BCIT is a valid and powerful method for assessing gene-disease association involving multiple SNPs.

Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging.

Science.gov (United States)

Zhou, Ruixi; Huang, Wei; Yang, Yang; Chen, Xiao; Weller, Daniel S; Kramer, Christopher M; Kozerke, Sebastian; Salerno, Michael

2018-02-01

Cardiovascular magnetic resonance (CMR) stress perfusion imaging provides important diagnostic and prognostic information in coronary artery disease (CAD). Current clinical sequences have limited temporal and/or spatial resolution, and incomplete heart coverage. Techniques such as k-t principal component analysis (PCA) or k-t sparcity and low rank structure (SLR), which rely on the high degree of spatiotemporal correlation in first-pass perfusion data, can significantly accelerate image acquisition mitigating these problems. However, in the presence of respiratory motion, these techniques can suffer from significant degradation of image quality. A number of techniques based on non-rigid registration have been developed. However, to first approximation, breathing motion predominantly results in rigid motion of the heart. To this end, a simple robust motion correction strategy is proposed for k-t accelerated and compressed sensing (CS) perfusion imaging. A simple respiratory motion compensation (MC) strategy for k-t accelerated and compressed-sensing CMR perfusion imaging to selectively correct respiratory motion of the heart was implemented based on linear k-space phase shifts derived from rigid motion registration of a region-of-interest (ROI) encompassing the heart. A variable density Poisson disk acquisition strategy was used to minimize coherent aliasing in the presence of respiratory motion, and images were reconstructed using k-t PCA and k-t SLR with or without motion correction. The strategy was evaluated in a CMR-extended cardiac torso digital (XCAT) phantom and in prospectively acquired first-pass perfusion studies in 12 subjects undergoing clinically ordered CMR studies. Phantom studies were assessed using the Structural Similarity Index (SSIM) and Root Mean Square Error (RMSE). In patient studies, image quality was scored in a blinded fashion by two experienced cardiologists. In the phantom experiments, images reconstructed with the MC strategy had higher

Measurement of lung tumor motion using respiration-correlated CT

International Nuclear Information System (INIS)

Mageras, Gig S.; Pevsner, Alex; Yorke, Ellen D.; Rosenzweig, Kenneth E.; Ford, Eric C.; Hertanto, Agung; Larson, Steven M.; Lovelock, D. Michael; Erdi, Yusuf E.; Nehmeh, Sadek A.; Humm, John L.; Ling, C. Clifton

2004-01-01

Purpose: We investigate the characteristics of lung tumor motion measured with respiration-correlated computed tomography (RCCT) and examine the method's applicability to radiotherapy planning and treatment. Methods and materials: Six patients treated for non-small-cell lung carcinoma received a helical single-slice computed tomography (CT) scan with a slow couch movement (1 mm/s), while simultaneously respiration is recorded with an external position-sensitive monitor. Another 6 patients receive a 4-slice CT scan in a cine mode, in which sequential images are acquired for a complete respiratory cycle at each couch position while respiration is recorded. The images are retrospectively resorted into different respiration phases as measured with the external monitor (4-slice data) or patient surface displacement observed in the images (single-slice data). The gross tumor volume (GTV) in lung is delineated at one phase and serves as a visual guide for delineation at other phases. Interfractional GTV variation is estimated by scaling diaphragm position variations measured in gated radiographs at treatment with the ratio of GTV:diaphragm displacement observed in the RCCT data. Results: Seven out of 12 patients show GTV displacement with respiration of more than 1 cm, primarily in the superior-inferior (SI) direction; 2 patients show anterior-posterior displacement of more than 1 cm. In all cases, extremes in GTV position in the SI direction are consistent with externally measured extremes in respiration. Three patients show evidence of hysteresis in GTV motion, in which the tumor trajectory is displaced 0.2 to 0.5 cm anteriorly during expiration relative to inspiration. Significant (>1 cm) expansion of the GTV in the SI direction with respiration is observed in 1 patient. Estimated intrafractional GTV motion for gated treatment at end expiration is 0.6 cm or less in all cases; however; interfraction variation estimates (systematic plus random) are more than 1 cm in 3

Potential for Interfraction Motion to Increase Esophageal Toxicity in Lung SBRT

OpenAIRE

Pham, Anthony Hoai-Nam; Yorke, Ellen; Rimner, Andreas; Wu, Abraham Jing-Ching

2017-01-01

Purpose: To characterize the effect of the relative motion of esophagus and tumor on radiation doses to the esophagus in patients treated with stereotactic body radiation therapy for central lung tumors. Methods and Materials: Fifty fractions of stereotactic body radiation therapy in 10 patients with lung tumors within 2.5 cm of the esophagus were reviewed. The esophagus was delineated on each treatment’s cone-beam computed tomography scan and compared to its position on the planning scan. Do...

MO-B-201-01: Overcoming the Challenges of Motion Management in Current Lung SBRT Practice

Energy Technology Data Exchange (ETDEWEB)

Shang, C. [Boca Raton Regional Hospital (United States)

2016-06-15

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and

MO-B-201-01: Overcoming the Challenges of Motion Management in Current Lung SBRT Practice

International Nuclear Information System (INIS)

Shang, C.

2016-01-01

The motion management in stereotactic body radiation therapy (SBRT) is a key to success for a SBRT program, and still an on-going challenging task. A major factor is that moving structures behave differently than standing structures when examined by imaging modalities, and thus require special considerations and employments. Understanding the motion effects to these different imaging processes is a prerequisite for a decent motion management program. The commonly used motion control techniques to physically restrict tumor motion, if adopted correctly, effectively increase the conformity and accuracy of hypofractionated treatment. The effective application of such requires one to understand the mechanics of the application and the related physiology especially related to respiration. The image-guided radiation beam control, or tumor tracking, further realized the endeavor for precision-targeting. During tumor tracking, the respiratory motion is often constantly monitored by non-ionizing beam sources using the body surface as its surrogate. This then has to synchronize with the actual internal tumor motion. The latter is often accomplished by stereo X-ray imaging or similar techniques. With these advanced technologies, one may drastically reduce the treated volume and increase the clinicians’ confidence for a high fractional ablative radiation dose. However, the challenges in implementing the motion management may not be trivial and is dependent on each clinic case. This session of presentations is intended to provide an overview of the current techniques used in managing the tumor motion in SBRT, specifically for routine lung SBRT, proton based treatments, and newly-developed MR guided RT. Learning Objectives: Through this presentation, the audience will understand basic roles of commonly used imaging modalities for lung cancer studies; familiarize the major advantages and limitations of each discussed motion control methods; familiarize the major advantages and

A PCA3 gene-based transcriptional amplification system targeting primary prostate cancer

OpenAIRE

Neveu, Bertrand; Jain, Pallavi; T?tu, Bernard; Wu, Lily; Fradet, Yves; Pouliot, Fr?d?ric

2015-01-01

Targeting specifically primary prostate cancer (PCa) cells for immune therapy, gene therapy or molecular imaging is of high importance. The PCA3 long non-coding RNA is a unique PCa biomarker and oncogene that has been widely studied. This gene has been mainly exploited as an accurate diagnostic urine biomarker for PCa detection. In this study, the PCA3 promoter was introduced into a new transcriptional amplification system named the 3-Step Transcriptional Amplification System (PCA3-3STA) and ...

Performance evaluation of PCA-based spike sorting algorithms.

Science.gov (United States)

Adamos, Dimitrios A; Kosmidis, Efstratios K; Theophilidis, George

2008-09-01

Deciphering the electrical activity of individual neurons from multi-unit noisy recordings is critical for understanding complex neural systems. A widely used spike sorting algorithm is being evaluated for single-electrode nerve trunk recordings. The algorithm is based on principal component analysis (PCA) for spike feature extraction. In the neuroscience literature it is generally assumed that the use of the first two or most commonly three principal components is sufficient. We estimate the optimum PCA-based feature space by evaluating the algorithm's performance on simulated series of action potentials. A number of modifications are made to the open source nev2lkit software to enable systematic investigation of the parameter space. We introduce a new metric to define clustering error considering over-clustering more favorable than under-clustering as proposed by experimentalists for our data. Both the program patch and the metric are available online. Correlated and white Gaussian noise processes are superimposed to account for biological and artificial jitter in the recordings. We report that the employment of more than three principal components is in general beneficial for all noise cases considered. Finally, we apply our results to experimental data and verify that the sorting process with four principal components is in agreement with a panel of electrophysiology experts.

Analysis of Lung Tumor Motion in a Large Sample: Patterns and Factors Influencing Precise Delineation of Internal Target Volume

International Nuclear Information System (INIS)

Knybel, Lukas; Cvek, Jakub; Molenda, Lukas; Stieberova, Natalie; Feltl, David

2016-01-01

Purpose/Objective: To evaluate lung tumor motion during respiration and to describe factors affecting the range and variability of motion in patients treated with stereotactic ablative radiation therapy. Methods and Materials: Log file analysis from online respiratory tumor tracking was performed in 145 patients. Geometric tumor location in the lungs, tumor volume and origin (primary or metastatic), sex, and tumor motion amplitudes in the superior-inferior (SI), latero-lateral (LL), and anterior-posterior (AP) directions were recorded. Tumor motion variability during treatment was described using intrafraction/interfraction amplitude variability and tumor motion baseline changes. Tumor movement dependent on the tumor volume, position and origin, and sex were evaluated using statistical regression and correlation analysis. Results: After analysis of >500 hours of data, the highest rates of motion amplitudes, intrafraction/interfraction variation, and tumor baseline changes were in the SI direction (6.0 ± 2.2 mm, 2.2 ± 1.8 mm, 1.1 ± 0.9 mm, and −0.1 ± 2.6 mm). The mean motion amplitudes in the lower/upper geometric halves of the lungs were significantly different (P 15 mm were observed only in the lower geometric quarter of the lungs. Higher tumor motion amplitudes generated higher intrafraction variations (R=.86, P 3 mm indicated tumors contacting mediastinal structures or parietal pleura. On univariate analysis, neither sex nor tumor origin (primary vs metastatic) was an independent predictive factor of different movement patterns. Metastatic lesions in women, but not men, showed significantly higher mean amplitudes (P=.03) and variability (primary, 2.7 mm; metastatic, 4.9 mm; P=.002) than primary tumors. Conclusion: Online tracking showed significant irregularities in lung tumor movement during respiration. Motion amplitude was significantly lower in upper lobe tumors; higher interfraction amplitude variability indicated tumors in contact

Simulation of lung motions using an artificial neural network; Utilisation d'un reseau de neurones artificiels pour la simulation des mouvements pulmonaires

Energy Technology Data Exchange (ETDEWEB)

Laurent, R.; Henriet, J.; Sauget, M.; Gschwind, R.; Makovicka, L. [IRMA/ENISYS/FEMTO-ST, UMR 6174 CNRS, pole universitaire des Portes du Jura, BP 71427, 25211 Montbeliard cedex (France); Salomon, M. [AND/LIFC, universite de Franche-Comte, BP 527, rue Engel-Gros, 90016 Belfort cedex (France); Nguyen, F. [Service de radiotherapie, CHU Jean-Minjoz, 3, boulevard Fleming, 25030 Besancon cedex (France)

2011-04-15

Purpose. A way to improve the accuracy of lung radiotherapy for a patient is to get a better understanding of its lung motion. Indeed, thanks to this knowledge it becomes possible to follow the displacements of the clinical target volume (CTV) induced by the lung breathing. This paper presents a feasibility study of an original method to simulate the positions of points in patient's lung at all breathing phases. Patients and methods. This method, based on an artificial neural network, allowed learning the lung motion on real cases and then to simulate it for new patients for which only the beginning and the end breathing data are known. The neural network learning set is made up of more than 600 points. These points, shared out on three patients and gathered on a specific lung area, were plotted by a MD. Results. - The first results are promising: an average accuracy of 1 mm is obtained for a spatial resolution of 1 x 1 x 2.5 mm{sup 3}. Conclusion. We have demonstrated that it is possible to simulate lung motion with accuracy using an artificial neural network. As future work we plan to improve the accuracy of our method with the addition of new patient data and a coverage of the whole lungs. (authors)

Cost effectiveness analysis of screening in the early diagnosis of prostate cancer (PCA)

International Nuclear Information System (INIS)

Mueller-Lisse, U.G.; Mueller-Lisse, U.L.

2002-01-01

Purpose. The authors attempted to provide an overview of current concepts and the status of research in the field of cost effectiveness analysis (CEA) of screening for prostate cancer (PCA).Material and methods. Basic concepts and methods of CEA were reviewed. Examples of CEA-related studies of PCA were obtained from pertinent literature through medical databases.Results. Screening for PCA has so far been restricted to limited groups of health care recipients, usually within the framework of clinical trials. In those trials, screening for PCA usually results in higher numbers of PCAs being detected at lower average stages in a given population. As a consequence of screening, the rate of potentially curable PCAs increases. However, it has not yet been demonstrated that screening for PCA decreases PCA-related mortality or morbidity from metastatic PCA. On the other hand, additional costs are associated with the screening measure and with increased use of resources for diagnosis and treatment of the additional PCAs detected through screening.Conclusions. Throughout the European Union and North America, mass screening for PCA has not been implemented. This may chiefly be due to the current lack of information on long term benefits of PCA screening, particularly disease-specific survival. Currently, major studies are underway to assess the effects of PCA screening and its cost effectiveness. These studies include the US-American prostate, lung, colon and ovary trials (PLCO) and the European randomised study of Screening for Prostate Cancer (ERSPC). (orig.) [de

The application of the sinusoidal model to lung cancer patient respiratory motion

International Nuclear Information System (INIS)

George, R.; Vedam, S.S.; Chung, T.D.; Ramakrishnan, V.; Keall, P.J.

2005-01-01

Accurate modeling of the respiratory cycle is important to account for the effect of organ motion on dose calculation for lung cancer patients. The aim of this study is to evaluate the accuracy of a respiratory model for lung cancer patients. Lujan et al. [Med. Phys. 26(5), 715-720 (1999)] proposed a model, which became widely used, to describe organ motion due to respiration. This model assumes that the parameters do not vary between and within breathing cycles. In this study, first, the correlation of respiratory motion traces with the model f(t) as a function of the parameter n(n=1,2,3) was undertaken for each breathing cycle from 331 four-minute respiratory traces acquired from 24 lung cancer patients using three breathing types: free breathing, audio instruction, and audio-visual biofeedback. Because cos 2 and cos 4 had similar correlation coefficients, and cos 2 and cos 1 have a trigonometric relationship, for simplicity, the cos 1 value was consequently used for further analysis in which the variations in mean position (z 0 ), amplitude of motion (b) and period (τ) with and without biofeedback or instructions were investigated. For all breathing types, the parameter values, mean position (z 0 ), amplitude of motion (b), and period (τ) exhibited significant cycle-to-cycle variations. Audio-visual biofeedback showed the least variations for all three parameters (z 0 , b, and τ). It was found that mean position (z 0 ) could be approximated with a normal distribution, and the amplitude of motion (b) and period (τ) could be approximated with log normal distributions. The overall probability density function (pdf) of f(t) for each of the three breathing types was fitted with three models: normal, bimodal, and the pdf of a simple harmonic oscillator. It was found that the normal and the bimodal models represented the overall respiratory motion pdfs with correlation values from 0.95 to 0.99, whereas the range of the simple harmonic oscillator pdf correlation

Development of deformable moving lung phantom to simulate respiratory motion in radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Kim, Jina [Department of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul 137-701 (Korea, Republic of); Lee, Youngkyu [Department of Radiation Oncology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 137-701, Seoul (Korea, Republic of); Shin, Hunjoo [Department of Radiation Oncology, Inchoen St. Mary' s Hospital College of Medicine, The Catholic University of Korea, Incheon 403-720 (Korea, Republic of); Ji, Sanghoon [Field Robot R& D Group, Korea Institute of Industrial Technology, Ansan 426-910 (Korea, Republic of); Park, Sungkwang [Department of Radiation Oncology, Busan Paik Hospital, Inje University, Busan 614-735 (Korea, Republic of); Kim, Jinyoung [Department of Radiation Oncology, Haeundae Paik Hospital, Inje University, Busan 612-896 (Korea, Republic of); Jang, Hongseok [Department of Radiation Oncology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 137-701, Seoul (Korea, Republic of); Kang, Youngnam, E-mail: ynkang33@gmail.com [Department of Radiation Oncology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, 137-701, Seoul (Korea, Republic of)

2016-07-01

Radiation treatment requires high accuracy to protect healthy organs and destroy the tumor. However, tumors located near the diaphragm constantly move during treatment. Respiration-gated radiotherapy has significant potential for the improvement of the irradiation of tumor sites affected by respiratory motion, such as lung and liver tumors. To measure and minimize the effects of respiratory motion, a realistic deformable phantom is required for use as a gold standard. The purpose of this study was to develop and study the characteristics of a deformable moving lung (DML) phantom, such as simulation, tissue equivalence, and rate of deformation. The rate of change of the lung volume, target deformation, and respiratory signals were measured in this study; they were accurately measured using a realistic deformable phantom. The measured volume difference was 31%, which closely corresponds to the average difference in human respiration, and the target movement was − 30 to + 32 mm. The measured signals accurately described human respiratory signals. This DML phantom would be useful for the estimation of deformable image registration and in respiration-gated radiotherapy. This study shows that the developed DML phantom can exactly simulate the patient's respiratory signal and it acts as a deformable 4-dimensional simulation of a patient's lung with sufficient volume change.

Development of deformable moving lung phantom to simulate respiratory motion in radiotherapy

International Nuclear Information System (INIS)

Kim, Jina; Lee, Youngkyu; Shin, Hunjoo; Ji, Sanghoon; Park, Sungkwang; Kim, Jinyoung; Jang, Hongseok; Kang, Youngnam

2016-01-01

Radiation treatment requires high accuracy to protect healthy organs and destroy the tumor. However, tumors located near the diaphragm constantly move during treatment. Respiration-gated radiotherapy has significant potential for the improvement of the irradiation of tumor sites affected by respiratory motion, such as lung and liver tumors. To measure and minimize the effects of respiratory motion, a realistic deformable phantom is required for use as a gold standard. The purpose of this study was to develop and study the characteristics of a deformable moving lung (DML) phantom, such as simulation, tissue equivalence, and rate of deformation. The rate of change of the lung volume, target deformation, and respiratory signals were measured in this study; they were accurately measured using a realistic deformable phantom. The measured volume difference was 31%, which closely corresponds to the average difference in human respiration, and the target movement was − 30 to + 32 mm. The measured signals accurately described human respiratory signals. This DML phantom would be useful for the estimation of deformable image registration and in respiration-gated radiotherapy. This study shows that the developed DML phantom can exactly simulate the patient's respiratory signal and it acts as a deformable 4-dimensional simulation of a patient's lung with sufficient volume change.

Analysis of Lung Tumor Motion in a Large Sample: Patterns and Factors Influencing Precise Delineation of Internal Target Volume

Energy Technology Data Exchange (ETDEWEB)

Knybel, Lukas [Department of Oncology, University Hospital Ostrava, Ostrava (Czech Republic); VŠB-Technical University of Ostrava, Ostrava (Czech Republic); Cvek, Jakub, E-mail: Jakub.cvek@fno.cz [Department of Oncology, University Hospital Ostrava, Ostrava (Czech Republic); Molenda, Lukas; Stieberova, Natalie; Feltl, David [Department of Oncology, University Hospital Ostrava, Ostrava (Czech Republic)

2016-11-15

Purpose/Objective: To evaluate lung tumor motion during respiration and to describe factors affecting the range and variability of motion in patients treated with stereotactic ablative radiation therapy. Methods and Materials: Log file analysis from online respiratory tumor tracking was performed in 145 patients. Geometric tumor location in the lungs, tumor volume and origin (primary or metastatic), sex, and tumor motion amplitudes in the superior-inferior (SI), latero-lateral (LL), and anterior-posterior (AP) directions were recorded. Tumor motion variability during treatment was described using intrafraction/interfraction amplitude variability and tumor motion baseline changes. Tumor movement dependent on the tumor volume, position and origin, and sex were evaluated using statistical regression and correlation analysis. Results: After analysis of >500 hours of data, the highest rates of motion amplitudes, intrafraction/interfraction variation, and tumor baseline changes were in the SI direction (6.0 ± 2.2 mm, 2.2 ± 1.8 mm, 1.1 ± 0.9 mm, and −0.1 ± 2.6 mm). The mean motion amplitudes in the lower/upper geometric halves of the lungs were significantly different (P<.001). Motion amplitudes >15 mm were observed only in the lower geometric quarter of the lungs. Higher tumor motion amplitudes generated higher intrafraction variations (R=.86, P<.001). Interfraction variations and baseline changes >3 mm indicated tumors contacting mediastinal structures or parietal pleura. On univariate analysis, neither sex nor tumor origin (primary vs metastatic) was an independent predictive factor of different movement patterns. Metastatic lesions in women, but not men, showed significantly higher mean amplitudes (P=.03) and variability (primary, 2.7 mm; metastatic, 4.9 mm; P=.002) than primary tumors. Conclusion: Online tracking showed significant irregularities in lung tumor movement during respiration. Motion amplitude was significantly lower in upper lobe

Tracking lung tissue motion and expansion/compression with inverse consistent image registration and spirometry.

Science.gov (United States)

Christensen, Gary E; Song, Joo Hyun; Lu, Wei; El Naqa, Issam; Low, Daniel A

2007-06-01

Breathing motion is one of the major limiting factors for reducing dose and irradiation of normal tissue for conventional conformal radiotherapy. This paper describes a relationship between tracking lung motion using spirometry data and image registration of consecutive CT image volumes collected from a multislice CT scanner over multiple breathing periods. Temporal CT sequences from 5 individuals were analyzed in this study. The couch was moved from 11 to 14 different positions to image the entire lung. At each couch position, 15 image volumes were collected over approximately 3 breathing periods. It is assumed that the expansion and contraction of lung tissue can be modeled as an elastic material. Furthermore, it is assumed that the deformation of the lung is small over one-fifth of a breathing period and therefore the motion of the lung can be adequately modeled using a small deformation linear elastic model. The small deformation inverse consistent linear elastic image registration algorithm is therefore well suited for this problem and was used to register consecutive image scans. The pointwise expansion and compression of lung tissue was measured by computing the Jacobian of the transformations used to register the images. The logarithm of the Jacobian was computed so that expansion and compression of the lung were scaled equally. The log-Jacobian was computed at each voxel in the volume to produce a map of the local expansion and compression of the lung during the breathing period. These log-Jacobian images demonstrate that the lung does not expand uniformly during the breathing period, but rather expands and contracts locally at different rates during inhalation and exhalation. The log-Jacobian numbers were averaged over a cross section of the lung to produce an estimate of the average expansion or compression from one time point to the next and compared to the air flow rate measured by spirometry. In four out of five individuals, the average log

Tracking lung tissue motion and expansion/compression with inverse consistent image registration and spirometry

International Nuclear Information System (INIS)

Christensen, Gary E.; Song, Joo Hyun; Lu, Wei; Naqa, Issam El; Low, Daniel A.

2007-01-01

Breathing motion is one of the major limiting factors for reducing dose and irradiation of normal tissue for conventional conformal radiotherapy. This paper describes a relationship between tracking lung motion using spirometry data and image registration of consecutive CT image volumes collected from a multislice CT scanner over multiple breathing periods. Temporal CT sequences from 5 individuals were analyzed in this study. The couch was moved from 11 to 14 different positions to image the entire lung. At each couch position, 15 image volumes were collected over approximately 3 breathing periods. It is assumed that the expansion and contraction of lung tissue can be modeled as an elastic material. Furthermore, it is assumed that the deformation of the lung is small over one-fifth of a breathing period and therefore the motion of the lung can be adequately modeled using a small deformation linear elastic model. The small deformation inverse consistent linear elastic image registration algorithm is therefore well suited for this problem and was used to register consecutive image scans. The pointwise expansion and compression of lung tissue was measured by computing the Jacobian of the transformations used to register the images. The logarithm of the Jacobian was computed so that expansion and compression of the lung were scaled equally. The log-Jacobian was computed at each voxel in the volume to produce a map of the local expansion and compression of the lung during the breathing period. These log-Jacobian images demonstrate that the lung does not expand uniformly during the breathing period, but rather expands and contracts locally at different rates during inhalation and exhalation. The log-Jacobian numbers were averaged over a cross section of the lung to produce an estimate of the average expansion or compression from one time point to the next and compared to the air flow rate measured by spirometry. In four out of five individuals, the average log

Pre-processing data using wavelet transform and PCA based on ...

Indian Academy of Sciences (India)

Abazar Solgi

2017-07-14

Jul 14, 2017 ... Pre-processing data using wavelet transform and PCA based on support vector regression and gene expression programming for river flow simulation. Abazar Solgi1,*, Amir Pourhaghi1, Ramin Bahmani2 and Heidar Zarei3. 1. Department of Water Resources Engineering, Shahid Chamran University of ...

PcaO Positively Regulates pcaHG of the β-Ketoadipate Pathway in Corynebacterium glutamicum▿

OpenAIRE

Zhao, Ke-Xin; Huang, Yan; Chen, Xi; Wang, Nan-Xi; Liu, Shuang-Jiang

2010-01-01

We identified a new regulator, PcaO, which is involved in regulation of the protocatechuate (PCA) branch of the β-ketoadipate pathway in Corynebacterium glutamicum. PcaO is an atypical large ATP-binding LuxR family (LAL)-type regulator and does not have a Walker A motif. A mutant of C. glutamicum in which pcaO was disrupted (RES167ΔpcaO) was unable to grow on PCA, and growth on PCA was restored by complementation with pcaO. Both an enzymatic assay of PCA 3,4-dioxygenase activity (encoded by p...

Comparative study of PCA in classification of multichannel EMG signals.

Science.gov (United States)

Geethanjali, P

2015-06-01

Electromyographic (EMG) signals are abundantly used in the field of rehabilitation engineering in controlling the prosthetic device and significantly essential to find fast and accurate EMG pattern recognition system, to avoid intrusive delay. The main objective of this paper is to study the influence of Principal component analysis (PCA), a transformation technique, in pattern recognition of six hand movements using four channel surface EMG signals from ten healthy subjects. For this reason, time domain (TD) statistical as well as auto regression (AR) coefficients are extracted from the four channel EMG signals. The extracted statistical features as well as AR coefficients are transformed using PCA to 25, 50 and 75 % of corresponding original feature vector space. The classification accuracy of PCA transformed and non-PCA transformed TD statistical features as well as AR coefficients are studied with simple logistic regression (SLR), decision tree (DT) with J48 algorithm, logistic model tree (LMT), k nearest neighbor (kNN) and neural network (NN) classifiers in the identification of six different movements. The Kruskal-Wallis (KW) statistical test shows that there is a significant reduction (P PCA transformed features compared to non-PCA transformed features. SLR with non-PCA transformed time domain (TD) statistical features performs better in accuracy and computational power compared to other features considered in this study. In addition, the motion control of three drives for six movements of the hand is implemented with SLR using TD statistical features in off-line with TMSLF2407 digital signal controller (DSC).

Control of Respiratory Motion by Hypnosis Intervention during Radiotherapy of Lung Cancer I

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Rongmao Li

2013-01-01

Full Text Available The uncertain position of lung tumor during radiotherapy compromises the treatment effect. To effectively control respiratory motion during radiotherapy of lung cancer without any side effects, a novel control scheme, hypnosis, has been introduced in lung cancer treatment. In order to verify the suggested method, six volunteers were selected with a wide range of distribution of age, weight, and chest circumference. A set of experiments have been conducted for each volunteer, under the guidance of the professional hypnotist. All the experiments were repeated in the same environmental condition. The amplitude of respiration has been recorded under the normal state and hypnosis, respectively. Experimental results show that the respiration motion of volunteers in hypnosis has smaller and more stable amplitudes than in normal state. That implies that the hypnosis intervention can be an alternative way for respiratory control, which can effectively reduce the respiratory amplitude and increase the stability of respiratory cycle. The proposed method will find useful application in image-guided radiotherapy.

Control of Respiratory Motion by Hypnosis Intervention during Radiotherapy of Lung Cancer I

Science.gov (United States)

Deng, Jie; Xie, Yaoqin

2013-01-01

The uncertain position of lung tumor during radiotherapy compromises the treatment effect. To effectively control respiratory motion during radiotherapy of lung cancer without any side effects, a novel control scheme, hypnosis, has been introduced in lung cancer treatment. In order to verify the suggested method, six volunteers were selected with a wide range of distribution of age, weight, and chest circumference. A set of experiments have been conducted for each volunteer, under the guidance of the professional hypnotist. All the experiments were repeated in the same environmental condition. The amplitude of respiration has been recorded under the normal state and hypnosis, respectively. Experimental results show that the respiration motion of volunteers in hypnosis has smaller and more stable amplitudes than in normal state. That implies that the hypnosis intervention can be an alternative way for respiratory control, which can effectively reduce the respiratory amplitude and increase the stability of respiratory cycle. The proposed method will find useful application in image-guided radiotherapy. PMID:24093100

Surface EMG signals based motion intent recognition using multi-layer ELM

Science.gov (United States)

Wang, Jianhui; Qi, Lin; Wang, Xiao

2017-11-01

The upper-limb rehabilitation robot is regard as a useful tool to help patients with hemiplegic to do repetitive exercise. The surface electromyography (sEMG) contains motion information as the electric signals are generated and related to nerve-muscle motion. These sEMG signals, representing human's intentions of active motions, are introduced into the rehabilitation robot system to recognize upper-limb movements. Traditionally, the feature extraction is an indispensable part of drawing significant information from original signals, which is a tedious task requiring rich and related experience. This paper employs a deep learning scheme to extract the internal features of the sEMG signals using an advanced Extreme Learning Machine based auto-encoder (ELMAE). The mathematical information contained in the multi-layer structure of the ELM-AE is used as the high-level representation of the internal features of the sEMG signals, and thus a simple ELM can post-process the extracted features, formulating the entire multi-layer ELM (ML-ELM) algorithm. The method is employed for the sEMG based neural intentions recognition afterwards. The case studies show the adopted deep learning algorithm (ELM-AE) is capable of yielding higher classification accuracy compared to the Principle Component Analysis (PCA) scheme in 5 different types of upper-limb motions. This indicates the effectiveness and the learning capability of the ML-ELM in such motion intent recognition applications.

Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm.

Science.gov (United States)

Saba, Luca; Jain, Pankaj K; Suri, Harman S; Ikeda, Nobutaka; Araki, Tadashi; Singh, Bikesh K; Nicolaides, Andrew; Shafique, Shoaib; Gupta, Ajay; Laird, John R; Suri, Jasjit S

2017-06-01

Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the machine learning framework to select and retain dominant features, resulting in superior performance. This leads to more stability and reliability. The automated system uses offline image data along with the ground truth labels to generate the parameters, which are then used to transform the online grayscale features to predict the risk of stroke. A set of sixteen grayscale plaque features is computed. Utilizing the cross-validation protocol (K = 10), and the PCA cutoff of 0.995, the machine learning system is able to achieve an accuracy of 98.55 and 98.83%corresponding to the carotidfar wall and near wall plaques, respectively. The corresponding reliability of the system was 94.56 and 95.63%, respectively. The automated system was validated against the manual risk assessment system and the precision of merit for same cross-validation settings and PCA cutoffs are 98.28 and 93.92%for the far and the near wall, respectively.PCA-embedded morphology-based plaque characterization shows a powerful strategy for risk assessment and can be adapted in clinical settings.

A viscoelastic model of the correlation between respiratory lung tumour motion and an external abdominal signal

International Nuclear Information System (INIS)

Cavan, A.E.; Wilson, P.L.; Meyer, J.; Berbeco, R.I.

2010-01-01

Full text: Accuracy of radiotherapy treatment of lung cancer is limited by respiratory induced tumour motion. Compensation for this motion is required to increase treatment efficacy. The lung tumour motion is related to motion of an external abdominal marker, but a reliable model of this correlation is essential. Three viscoelastic systems were developed, in order to determine the best model and analyse its effectiveness on clinical data. Three 1D viscoelastic systems (a spring and dash pot in parallel, series and a combination) were developed and compared using a simulated breathing pattern. The most effective model was applied to 60 clinical data sets (consisting of co-ordinates of tumour and abdominal motion) from multiple treatment fractions of ten patients. The model was optimised for each data set, and efficacy determined by calculating the root mean square (RMS) error between the mo elled position and the actual tumour motion. Upon application to clinical data the parallel configuration achieved an average RMS error of 0.95 mm (superior-inferior direction). The model had patient specific parameters, and displayed good consistency over extended treatment periods. The model ha dled amplitude, frequency and baseline variations of the input signal, and phase shifts between tumour and abdominal motions. This study has shown that a viscoelastic model can be used to cor relate internal lung tumour motion with an external abdominal signal. The ability to handle breathing pattern in'egularities is comparable or better than previous models. Extending the model to a full 3D, pr dictive system could allow clinical implementation for radiotherapy.

Investigating the feasibility of rapid MRI for image-guided motion management in lung cancer radiotherapy.

Science.gov (United States)

Sawant, Amit; Keall, Paul; Pauly, Kim Butts; Alley, Marcus; Vasanawala, Shreyas; Loo, Billy W; Hinkle, Jacob; Joshi, Sarang

2014-01-01

Cycle-to-cycle variations in respiratory motion can cause significant geometric and dosimetric errors in the administration of lung cancer radiation therapy. A common limitation of the current strategies for motion management is that they assume a constant, reproducible respiratory cycle. In this work, we investigate the feasibility of using rapid MRI for providing long-term imaging of the thorax in order to better capture cycle-to-cycle variations. Two nonsmall-cell lung cancer patients were imaged (free-breathing, no extrinsic contrast, and 1.5 T scanner). A balanced steady-state-free-precession (b-SSFP) sequence was used to acquire cine-2D and cine-3D (4D) images. In the case of Patient 1 (right midlobe lesion, ~40 mm diameter), tumor motion was well correlated with diaphragmatic motion. In the case of Patient 2, (left upper-lobe lesion, ~60 mm diameter), tumor motion was poorly correlated with diaphragmatic motion. Furthermore, the motion of the tumor centroid was poorly correlated with the motion of individual points on the tumor boundary, indicating significant rotation and/or deformation. These studies indicate that image quality and acquisition speed of cine-2D MRI were adequate for motion monitoring. However, significant improvements are required to achieve comparable speeds for truly 4D MRI. Despite several challenges, rapid MRI offers a feasible and attractive tool for noninvasive, long-term motion monitoring.

WE-G-BRF-04: Robust Real-Time Volumetric Imaging Based On One Single Projection

International Nuclear Information System (INIS)

Xu, Y; Yan, H; Ouyang, L; Wang, J; Jiang, S; Jia, X; Zhou, L

2014-01-01

Purpose: Real-time volumetric imaging is highly desirable to provide instantaneous image guidance for lung radiation therapy. This study proposes a scheme to achieve this goal using one single projection by utilizing sparse learning and a principal component analysis (PCA) based lung motion model. Methods: A patient-specific PCA-based lung motion model is first constructed by analyzing deformable vector fields (DVFs) between a reference image and 4DCT images at each phase. At the training stage, we “learn” the relationship between the DVFs and the projection using sparse learning. Specifically, we first partition the projections into patches, and then apply sparse learning to automatically identify patches that best correlate with the principal components of the DVFs. Once the relationship is established, at the application stage, we first employ a patchbased intensity correction method to overcome the problem of different intensity scale between the calculated projection in the training stage and the measured projection in the application stage. The corrected projection image is then fed to the trained model to derive a DVF, which is applied to the reference image, yielding a volumetric image corresponding to the projection. We have validated our method through a NCAT phantom simulation case and one experiment case. Results: Sparse learning can automatically select those patches containing motion information, such as those around diaphragm. For the simulation case, over 98% of the lung region pass the generalized gamma test (10HU/1mm), indicating combined accuracy in both intensity and spatial domain. For the experimental case, the average tumor localization errors projected to the imager are 0.68 mm and 0.4 mm on the axial and tangential direction, respectively. Conclusion: The proposed method is capable of accurately generating a volumetric image using one single projection. It will potentially offer real-time volumetric image guidance to facilitate lung

WE-G-BRF-04: Robust Real-Time Volumetric Imaging Based On One Single Projection

Energy Technology Data Exchange (ETDEWEB)

Xu, Y [UT Southwestern Medical Center, Dallas, TX (United States); Southern Medical University, Guangzhou (China); Yan, H; Ouyang, L; Wang, J; Jiang, S; Jia, X [UT Southwestern Medical Center, Dallas, TX (United States); Zhou, L [Southern Medical University, Guangzhou (China)

2014-06-15

Purpose: Real-time volumetric imaging is highly desirable to provide instantaneous image guidance for lung radiation therapy. This study proposes a scheme to achieve this goal using one single projection by utilizing sparse learning and a principal component analysis (PCA) based lung motion model. Methods: A patient-specific PCA-based lung motion model is first constructed by analyzing deformable vector fields (DVFs) between a reference image and 4DCT images at each phase. At the training stage, we “learn” the relationship between the DVFs and the projection using sparse learning. Specifically, we first partition the projections into patches, and then apply sparse learning to automatically identify patches that best correlate with the principal components of the DVFs. Once the relationship is established, at the application stage, we first employ a patchbased intensity correction method to overcome the problem of different intensity scale between the calculated projection in the training stage and the measured projection in the application stage. The corrected projection image is then fed to the trained model to derive a DVF, which is applied to the reference image, yielding a volumetric image corresponding to the projection. We have validated our method through a NCAT phantom simulation case and one experiment case. Results: Sparse learning can automatically select those patches containing motion information, such as those around diaphragm. For the simulation case, over 98% of the lung region pass the generalized gamma test (10HU/1mm), indicating combined accuracy in both intensity and spatial domain. For the experimental case, the average tumor localization errors projected to the imager are 0.68 mm and 0.4 mm on the axial and tangential direction, respectively. Conclusion: The proposed method is capable of accurately generating a volumetric image using one single projection. It will potentially offer real-time volumetric image guidance to facilitate lung

External validation of a PCA-3-based nomogram for predicting prostate cancer and high-grade cancer on initial prostate biopsy.

Science.gov (United States)

Greene, Daniel J; Elshafei, Ahmed; Nyame, Yaw A; Kara, Onder; Malkoc, Ercan; Gao, Tianming; Jones, J Stephen

2016-08-01

The aim of this study was to externally validate a previously developed PCA3-based nomogram for the prediction of prostate cancer (PCa) and high-grade (intermediate and/or high-grade) prostate cancer (HGPCa) at the time of initial prostate biopsy. A retrospective review was performed on a cohort of 336 men from a large urban academic medical center. All men had serum PSA PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and abnormal finding on digital rectal exam (DRE). These variables were used to test the accuracy (concordance index) and calibration of a previously published PCA3 nomogram. Biopsy confirms PCa and HGPCa in 51.0% and 30.4% of validation patients, respectively. This differed from the original cohort in that it had significantly more PCa and HGPCA (51% vs. 44%, P = 0.019; and 30.4% vs. 19.1%, P PCa detection the concordance index was 75% and 77% for overall PCa and HGPCa, respectively. Calibration for overall PCa was good. This represents the first external validation of a PCA3-based prostate cancer predictive nomogram in a North American population. Prostate 76:1019-1023, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Investigating the Feasibility of Rapid MRI for Image-Guided Motion Management in Lung Cancer Radiotherapy

Directory of Open Access Journals (Sweden)

Amit Sawant

2014-01-01

Full Text Available Cycle-to-cycle variations in respiratory motion can cause significant geometric and dosimetric errors in the administration of lung cancer radiation therapy. A common limitation of the current strategies for motion management is that they assume a constant, reproducible respiratory cycle. In this work, we investigate the feasibility of using rapid MRI for providing long-term imaging of the thorax in order to better capture cycle-to-cycle variations. Two nonsmall-cell lung cancer patients were imaged (free-breathing, no extrinsic contrast, and 1.5 T scanner. A balanced steady-state-free-precession (b-SSFP sequence was used to acquire cine-2D and cine-3D (4D images. In the case of Patient 1 (right midlobe lesion, ~40 mm diameter, tumor motion was well correlated with diaphragmatic motion. In the case of Patient 2, (left upper-lobe lesion, ~60 mm diameter, tumor motion was poorly correlated with diaphragmatic motion. Furthermore, the motion of the tumor centroid was poorly correlated with the motion of individual points on the tumor boundary, indicating significant rotation and/or deformation. These studies indicate that image quality and acquisition speed of cine-2D MRI were adequate for motion monitoring. However, significant improvements are required to achieve comparable speeds for truly 4D MRI. Despite several challenges, rapid MRI offers a feasible and attractive tool for noninvasive, long-term motion monitoring.

Application of EOF/PCA-based methods in the post-processing of GRACE derived water variations

Science.gov (United States)

Forootan, Ehsan; Kusche, Jürgen

2010-05-01

Two problems that users of monthly GRACE gravity field solutions face are 1) the presence of correlated noise in the Stokes coefficients that increases with harmonic degree and causes ‘striping', and 2) the fact that different physical signals are overlaid and difficult to separate from each other in the data. These problems are termed the signal-noise separation problem and the signal-signal separation problem. Methods that are based on principal component analysis and empirical orthogonal functions (PCA/EOF) have been frequently proposed to deal with these problems for GRACE. However, different strategies have been applied to different (spatial: global/regional, spectral: global/order-wise, geoid/equivalent water height) representations of the GRACE level 2 data products, leading to differing results and a general feeling that PCA/EOF-based methods are to be applied ‘with care'. In addition, it is known that conventional EOF/PCA methods force separated modes to be orthogonal, and that, on the other hand, to either EOFs or PCs an arbitrary orthogonal rotation can be applied. The aim of this paper is to provide a common theoretical framework and to study the application of PCA/EOF-based methods as a signal separation tool due to post-process GRACE data products. In order to investigate and illustrate the applicability of PCA/EOF-based methods, we have employed them on GRACE level 2 monthly solutions based on the Center for Space Research, University of Texas (CSR/UT) RL04 products and on the ITG-GRACE03 solutions from the University of Bonn, and on various representations of them. Our results show that EOF modes do reveal the dominating annual, semiannual and also long-periodic signals in the global water storage variations, but they also show how choosing different strategies changes the outcome and may lead to unexpected results.

PEM-PCA: A Parallel Expectation-Maximization PCA Face Recognition Architecture

Directory of Open Access Journals (Sweden)

Kanokmon Rujirakul

2014-01-01

Full Text Available Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages’ complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.

PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.

Science.gov (United States)

Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar

2014-01-01

Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.

SU-C-BRF-05: Design and Geometric Validation of An Externally and Internally Deformable, Programmable Lung Motion Phantom

International Nuclear Information System (INIS)

Cheung, Y; Sawant, A

2014-01-01

Purpose: Most clinically-deployed strategies for respiratory motion management in lung radiotherapy (e.g., gating, tracking) use external markers that serve as surrogates for tumor motion. However, typical lung phantoms used to validate these strategies are rigid-exterior+rigid-interior or rigid-exterior+deformable-interior. Neither class adequately represents the human anatomy, which is deformable internally as well as externally. We describe the construction and experimental validation of a more realistic, externally- and internally-deformable, programmable lung phantom. Methods: The outer shell of a commercially-available lung phantom (RS- 1500, RSD Inc.) was used. The shell consists of a chest cavity with a flexible anterior surface, and embedded vertebrae, rib-cage and sternum. A 3-axis platform was programmed with sinusoidal and six patient-recorded lung tumor trajectories. The platform was used to drive a rigid foam ‘diaphragm’ that compressed/decompressed the phantom interior. Experimental characterization comprised of mapping the superior-inferior (SI) and anterior-posterior (AP) trajectories of external and internal radioopaque markers with kV x-ray fluoroscopy and correlating these with optical surface monitoring using the in-room VisionRT system. Results: The phantom correctly reproduced the programmed motion as well as realistic effects such as hysteresis. The reproducibility of marker trajectories over multiple runs for sinusoidal as well as patient traces, as characterized by fluoroscopy, was within 0.4 mm RMS error for internal as well as external markers. The motion trajectories of internal and external markers as measured by fluoroscopy were found to be highly correlated (R=0.97). Furthermore, motion trajectories of arbitrary points on the deforming phantom surface, as recorded by the VisionRT system also showed a high correlation with respect to the fluoroscopically-measured trajectories of internal markers (R=0.92). Conclusion: We have

Model selection for Gaussian kernel PCA denoising

DEFF Research Database (Denmark)

Jørgensen, Kasper Winther; Hansen, Lars Kai

2012-01-01

We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

SU-E-T-452: Impact of Respiratory Motion On Robustly-Optimized Intensity-Modulated Proton Therapy to Treat Lung Cancers

International Nuclear Information System (INIS)

Liu, W; Schild, S; Bues, M; Liao, Z; Sahoo, N; Park, P; Li, H; Li, Y; Li, X; Shen, J; Anand, A; Dong, L; Zhu, X; Mohan, R

2014-01-01

Purpose: We compared conventionally optimized intensity-modulated proton therapy (IMPT) treatment plans against the worst-case robustly optimized treatment plans for lung cancer. The comparison of the two IMPT optimization strategies focused on the resulting plans' ability to retain dose objectives under the influence of patient set-up, inherent proton range uncertainty, and dose perturbation caused by respiratory motion. Methods: For each of the 9 lung cancer cases two treatment plans were created accounting for treatment uncertainties in two different ways: the first used the conventional Method: delivery of prescribed dose to the planning target volume (PTV) that is geometrically expanded from the internal target volume (ITV). The second employed the worst-case robust optimization scheme that addressed set-up and range uncertainties through beamlet optimization. The plan optimality and plan robustness were calculated and compared. Furthermore, the effects on dose distributions of the changes in patient anatomy due to respiratory motion was investigated for both strategies by comparing the corresponding plan evaluation metrics at the end-inspiration and end-expiration phase and absolute differences between these phases. The mean plan evaluation metrics of the two groups were compared using two-sided paired t-tests. Results: Without respiratory motion considered, we affirmed that worst-case robust optimization is superior to PTV-based conventional optimization in terms of plan robustness and optimality. With respiratory motion considered, robust optimization still leads to more robust dose distributions to respiratory motion for targets and comparable or even better plan optimality [D95% ITV: 96.6% versus 96.1% (p=0.26), D5% - D95% ITV: 10.0% versus 12.3% (p=0.082), D1% spinal cord: 31.8% versus 36.5% (p =0.035)]. Conclusion: Worst-case robust optimization led to superior solutions for lung IMPT. Despite of the fact that robust optimization did not explicitly

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

Science.gov (United States)

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

SU-C-BRA-07: Variability of Patient-Specific Motion Models Derived Using Different Deformable Image Registration Algorithms for Lung Cancer Stereotactic Body Radiotherapy (SBRT) Patients

Energy Technology Data Exchange (ETDEWEB)

Dhou, S; Williams, C [Brigham and Women’s Hospital / Harvard Medical School, Boston, MA (United States); Ionascu, D [William Beaumont Hospital, Royal Oak, MI (United States); Lewis, J [University of California at Los Angeles, Los Angeles, CA (United States)

2016-06-15

Purpose: To study the variability of patient-specific motion models derived from 4-dimensional CT (4DCT) images using different deformable image registration (DIR) algorithms for lung cancer stereotactic body radiotherapy (SBRT) patients. Methods: Motion models are derived by 1) applying DIR between each 4DCT image and a reference image, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs, resulting in a motion model (a set of eigenvectors capturing the variations in the DVFs). Three DIR algorithms were used: 1) Demons, 2) Horn-Schunck, and 3) iterative optical flow. The motion models derived were compared using patient 4DCT scans. Results: Motion models were derived and the variations were evaluated according to three criteria: 1) the average root mean square (RMS) difference which measures the absolute difference between the components of the eigenvectors, 2) the dot product between the eigenvectors which measures the angular difference between the eigenvectors in space, and 3) the Euclidean Model Norm (EMN), which is calculated by summing the dot products of an eigenvector with the first three eigenvectors from the reference motion model in quadrature. EMN measures how well an eigenvector can be reconstructed using another motion model derived using a different DIR algorithm. Results showed that comparing to a reference motion model (derived using the Demons algorithm), the eigenvectors of the motion model derived using the iterative optical flow algorithm has smaller RMS, larger dot product, and larger EMN values than those of the motion model derived using Horn-Schunck algorithm. Conclusion: The study showed that motion models vary depending on which DIR algorithms were used to derive them. The choice of a DIR algorithm may affect the accuracy of the resulting model, and it is important to assess the suitability of the algorithm chosen for a particular application. This project was supported

SU-C-BRA-07: Variability of Patient-Specific Motion Models Derived Using Different Deformable Image Registration Algorithms for Lung Cancer Stereotactic Body Radiotherapy (SBRT) Patients

International Nuclear Information System (INIS)

Dhou, S; Williams, C; Ionascu, D; Lewis, J

2016-01-01

Purpose: To study the variability of patient-specific motion models derived from 4-dimensional CT (4DCT) images using different deformable image registration (DIR) algorithms for lung cancer stereotactic body radiotherapy (SBRT) patients. Methods: Motion models are derived by 1) applying DIR between each 4DCT image and a reference image, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs, resulting in a motion model (a set of eigenvectors capturing the variations in the DVFs). Three DIR algorithms were used: 1) Demons, 2) Horn-Schunck, and 3) iterative optical flow. The motion models derived were compared using patient 4DCT scans. Results: Motion models were derived and the variations were evaluated according to three criteria: 1) the average root mean square (RMS) difference which measures the absolute difference between the components of the eigenvectors, 2) the dot product between the eigenvectors which measures the angular difference between the eigenvectors in space, and 3) the Euclidean Model Norm (EMN), which is calculated by summing the dot products of an eigenvector with the first three eigenvectors from the reference motion model in quadrature. EMN measures how well an eigenvector can be reconstructed using another motion model derived using a different DIR algorithm. Results showed that comparing to a reference motion model (derived using the Demons algorithm), the eigenvectors of the motion model derived using the iterative optical flow algorithm has smaller RMS, larger dot product, and larger EMN values than those of the motion model derived using Horn-Schunck algorithm. Conclusion: The study showed that motion models vary depending on which DIR algorithms were used to derive them. The choice of a DIR algorithm may affect the accuracy of the resulting model, and it is important to assess the suitability of the algorithm chosen for a particular application. This project was supported

Petrology of Antarctic Eucrites PCA 91078 and PCA 91245

Science.gov (United States)

Howard, L. M.; Domanik, K. J.; Drake, M. J.; Mittlefehldt, D. W.

2002-01-01

Antarctic eucrites PCA 91078 and PCA 91245, are petrographically characterized and found to be unpaired, type 6, basaltic eucrites. Observed textures that provide insight into the petrogenesis of these meteorites are also discussed. Additional information is contained in the original extended abstract.

WE-G-BRD-02: Characterizing Information Loss in a Sparse-Sampling-Based Dynamic MRI Sequence (k-T BLAST) for Lung Motion Monitoring

International Nuclear Information System (INIS)

Arai, T; Nofiele, J; Sawant, A

2015-01-01

Purpose: Rapid MRI is an attractive, non-ionizing tool for soft-tissue-based monitoring of respiratory motion in thoracic and abdominal radiotherapy. One big challenge is to achieve high temporal resolution while maintaining adequate spatial resolution. K-t BLAST, sparse-sampling and reconstruction sequence based on a-priori information represents a potential solution. In this work, we investigated how much “true” motion information is lost as a-priori information is progressively added for faster imaging. Methods: Lung tumor motions in superior-inferior direction obtained from ten individuals were replayed into an in-house, MRI-compatible, programmable motion platform (50Hz refresh and 100microns precision). Six water-filled 1.5ml tubes were placed on it as fiducial markers. Dynamic marker motion within a coronal slice (FOV: 32×32cm"2, resolution: 0.67×0.67mm"2, slice-thickness: 5mm) was collected on 3.0T body scanner (Ingenia, Philips). Balanced-FFE (TE/TR: 1.3ms/2.5ms, flip-angle: 40degrees) was used in conjunction with k-t BLAST. Each motion was repeated four times as four k-t acceleration factors 1, 2, 5, and 16 (corresponding frame rates were 2.5, 4.7, 9.8, and 19.1Hz, respectively) were compared. For each image set, one average motion trajectory was computed from six marker displacements. Root mean square error (RMS) was used as a metric of spatial accuracy where measured trajectories were compared to original data. Results: Tumor motion was approximately 10mm. The mean(standard deviation) of respiratory rates over ten patients was 0.28(0.06)Hz. Cumulative distributions of tumor motion frequency spectra (0–25Hz) obtained from the patients showed that 90% of motion fell on 3.88Hz or less. Therefore, the frame rate must be a double or higher for accurate monitoring. The RMS errors over patients for k-t factors of 1, 2, 5, and 16 were.10(.04),.17(.04), .21(.06) and.26(.06)mm, respectively. Conclusions: K-t factor of 5 or higher can cover the high

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

Science.gov (United States)

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.

The PCa Tumor Microenvironment.

Science.gov (United States)

Sottnik, Joseph L; Zhang, Jian; Macoska, Jill A; Keller, Evan T

2011-12-01

The tumor microenvironment (TME) is a very complex niche that consists of multiple cell types, supportive matrix and soluble factors. Cells in the TME consist of both host cells that are present at tumor site at the onset of tumor growth and cells that are recruited in either response to tumor- or host-derived factors. PCa (PCa) thrives on crosstalk between tumor cells and the TME. Crosstalk results in an orchestrated evolution of both the tumor and microenvironment as the tumor progresses. The TME reacts to PCa-produced soluble factors as well as direct interaction with PCa cells. In return, the TME produces soluble factors, structural support and direct contact interactions that influence the establishment and progression of PCa. In this review, we focus on the host side of the equation to provide a foundation for understanding how different aspects of the TME contribute to PCa progression. We discuss immune effector cells, specialized niches, such as the vascular and bone marrow, and several key protein factors that mediate host effects on PCa. This discussion highlights the concept that the TME offers a potentially very fertile target for PCa therapy.

Using an external surrogate for predictor model training in real-time motion management of lung tumors

Energy Technology Data Exchange (ETDEWEB)

Rottmann, Joerg; Berbeco, Ross [Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States)

2014-12-15

Purpose: Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. Methods: The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal–external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Results: Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum

Circle of Willis Variants: Fetal PCA

Directory of Open Access Journals (Sweden)

Amir Shaban

2013-01-01

Full Text Available We sought to determine the prevalence of fetal posterior cerebral artery (fPCA and if fPCA was associated with specific stroke etiology and vessel territory affected. This paper is a retrospective review of prospectively identified patients with acute ischemic stroke from July 2008 to December 2010. We defined complete fPCA as absence of a P1 segment linking the basilar with the PCA and partial fPCA as small segment linking the basilar with the PCA. Patients without intracranial vascular imaging were excluded. We compared patients with complete fPCA, partial fPCA, and without fPCA in terms of demographics, stroke severity, distribution, and etiology and factored in whether the stroke was ipsilateral to the fPCA. Of the 536 included patients, 9.5% ( had complete fPCA and 15.1% ( had partial fPCA. Patients with complete fPCA were older and more often female than partial fPCA and no fPCA patients, and significant variation in TOAST classification was detected across groups (. Patients with complete fPCA had less small vessel and more large vessel strokes than patients with no fPCA and partial fPCA. Fetal PCA may predispose to stroke mechanism, but is not associated with vascular distribution, stroke severity, or early outcome.

Validity of clinical outcome measures to evaluate ankle range of motion during the weight-bearing lunge test.

Science.gov (United States)

Hall, Emily A; Docherty, Carrie L

2017-07-01

To determine the concurrent validity of standard clinical outcome measures compared to laboratory outcome measure while performing the weight-bearing lunge test (WBLT). Cross-sectional study. Fifty participants performed the WBLT to determine dorsiflexion ROM using four different measurement techniques: dorsiflexion angle with digital inclinometer at 15cm distal to the tibial tuberosity (°), dorsiflexion angle with inclinometer at tibial tuberosity (°), maximum lunge distance (cm), and dorsiflexion angle using a 2D motion capture system (°). Outcome measures were recorded concurrently during each trial. To establish concurrent validity, Pearson product-moment correlation coefficients (r) were conducted, comparing each dependent variable to the 2D motion capture analysis (identified as the reference standard). A higher correlation indicates strong concurrent validity. There was a high correlation between each measurement technique and the reference standard. Specifically the correlation between the inclinometer placement at 15cm below the tibial tuberosity (44.9°±5.5°) and the motion capture angle (27.0°±6.0°) was r=0.76 (p=0.001), between the inclinometer placement at the tibial tuberosity angle (39.0°±4.6°) and the motion capture angle was r=0.71 (p=0.001), and between the distance from the wall clinical measure (10.3±3.0cm) to the motion capture angle was r=0.74 (p=0.001). This study determined that the clinical measures used during the WBLT have a high correlation with the reference standard for assessing dorsiflexion range of motion. Therefore, obtaining maximum lunge distance and inclinometer angles are both valid assessments during the weight-bearing lunge test. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Automatic detection of optic disc based on PCA and mathematical morphology.

Science.gov (United States)

Morales, Sandra; Naranjo, Valery; Angulo, Us; Alcaniz, Mariano

2013-04-01

The algorithm proposed in this paper allows to automatically segment the optic disc from a fundus image. The goal is to facilitate the early detection of certain pathologies and to fully automate the process so as to avoid specialist intervention. The method proposed for the extraction of the optic disc contour is mainly based on mathematical morphology along with principal component analysis (PCA). It makes use of different operations such as generalized distance function (GDF), a variant of the watershed transformation, the stochastic watershed, and geodesic transformations. The input of the segmentation method is obtained through PCA. The purpose of using PCA is to achieve the grey-scale image that better represents the original RGB image. The implemented algorithm has been validated on five public databases obtaining promising results. The average values obtained (a Jaccard's and Dice's coefficients of 0.8200 and 0.8932, respectively, an accuracy of 0.9947, and a true positive and false positive fractions of 0.9275 and 0.0036) demonstrate that this method is a robust tool for the automatic segmentation of the optic disc. Moreover, it is fairly reliable since it works properly on databases with a large degree of variability and improves the results of other state-of-the-art methods.

Early Improper Motion Detection in Golf Swings Using Wearable Motion Sensors: The First Approach

Science.gov (United States)

Stančin, Sara; Tomažič, Sašo

2013-01-01

This paper presents an analysis of a golf swing to detect improper motion in the early phase of the swing. Led by the desire to achieve a consistent shot outcome, a particular golfer would (in multiple trials) prefer to perform completely identical golf swings. In reality, some deviations from the desired motion are always present due to the comprehensive nature of the swing motion. Swing motion deviations that are not detrimental to performance are acceptable. This analysis is conducted using a golfer's leading arm kinematic data, which are obtained from a golfer wearing a motion sensor that is comprised of gyroscopes and accelerometers. Applying the principal component analysis (PCA) to the reference observations of properly performed swings, the PCA components of acceptable swing motion deviations are established. Using these components, the motion deviations in the observations of other swings are examined. Any unacceptable deviations that are detected indicate an improper swing motion. Arbitrarily long observations of an individual player's swing sequences can be included in the analysis. The results obtained for the considered example show an improper swing motion in early phase of the swing, i.e., the first part of the backswing. An early detection method for improper swing motions that is conducted on an individual basis provides assistance for performance improvement. PMID:23752563

Quantification of organ motion based on an adaptive image-based scale invariant feature method

Energy Technology Data Exchange (ETDEWEB)

Paganelli, Chiara [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, piazza L. Da Vinci 32, Milano 20133 (Italy); Peroni, Marta [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, piazza L. Da Vinci 32, Milano 20133, Italy and Paul Scherrer Institut, Zentrum für Protonentherapie, WMSA/C15, CH-5232 Villigen PSI (Italy); Baroni, Guido; Riboldi, Marco [Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, piazza L. Da Vinci 32, Milano 20133, Italy and Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, strada Campeggi 53, Pavia 27100 (Italy)

2013-11-15

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application of contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT

Volume-monitored chest CT: a simplified method for obtaining motion-free images near full inspiratory and end expiratory lung volumes

Energy Technology Data Exchange (ETDEWEB)

Mueller, Kathryn S. [The Ohio State University College of Medicine, Columbus, OH (United States); Long, Frederick R. [Nationwide Children' s Hospital, The Children' s Radiological Institute, Columbus, OH (United States); Flucke, Robert L. [Nationwide Children' s Hospital, Department of Pulmonary Medicine, Columbus, OH (United States); Castile, Robert G. [The Research Institute at Nationwide Children' s Hospital, Center for Perinatal Research, Columbus, OH (United States)

2010-10-15

Lung inflation and respiratory motion during chest CT affect diagnostic accuracy and reproducibility. To describe a simple volume-monitored (VM) method for performing reproducible, motion-free full inspiratory and end expiratory chest CT examinations in children. Fifty-two children with cystic fibrosis (mean age 8.8 {+-} 2.2 years) underwent pulmonary function tests and inspiratory and expiratory VM-CT scans (1.25-mm slices, 80-120 kVp, 16-40 mAs) according to an IRB-approved protocol. The VM-CT technique utilizes instruction from a respiratory therapist, a portable spirometer and real-time documentation of lung volume on a computer. CT image quality was evaluated for achievement of targeted lung-volume levels and for respiratory motion. Children achieved 95% of vital capacity during full inspiratory imaging. For end expiratory scans, 92% were at or below the child's end expiratory level. Two expiratory exams were judged to be at suboptimal volumes. Two inspiratory (4%) and three expiratory (6%) exams showed respiratory motion. Overall, 94% of scans were performed at optimal volumes without respiratory motion. The VM-CT technique is a simple, feasible method in children as young as 4 years to achieve reproducible high-quality full inspiratory and end expiratory lung CT images. (orig.)

Radiotherapy of tumors under respiratory motion. Estimation of the motional velocity field and dose accumulation based on 4D image data

International Nuclear Information System (INIS)

Werner, Rene

2013-01-01

belong to the most precise methods currently available. In clinical practice, however, there exists the problem that many medical facilities are not equipped with 4D imaging devices. Further, 4D images still offer only a snapshot of the patient-specific motion range and potential motion variability may limit the conclusions that can be drawn from them. To address these aspects, in the next part of the thesis - based on the optimized methods for motion field estimation in 4D CT image data and further including statistical motion information and models, respectively - model-based approaches for motion field estimation and prediction are developed. First, a novel approach for statistical modeling of lung motion in a patient collective is presented, and methods for adapting the model for prediction of patient-specific motion patterns are provided. The latter allow, for instance, the estimation of respiratory lung and lung tumor motion for radiation therapy treatment planning, if no temporally resolved image sequences are available for the patient; this use case is demonstrated. Further, techniques of multivariate statistics are applied to account for variations of motion patterns by integrating additional information provided by motion indicators used in 4D radiation therapy (e.g. abdominal belts or spirometer measurements) for a patient-specific, situation-related adaption of the motion fields computed using 4D images and the methods for motion field estimation described before. In the last part of the thesis, the developed methods are finally applied for assessing and analyzing the dosimetric impact of respiratory motion during radiation therapy of lung tumors. Both 3D conformal radiotherapy and intensity modulated radiotherapy are modeled as treatment modalities. In the case of intensity modulated radiotherapy, short delivery times for single radiation fields lead to the risk that the corresponding dose contributions are not only subject to a motion-induced dose blurring

Thin-section CT of lung without ECG gating: 64-detector row CT can markedly reduce cardiac motion artifact which can simulate lung lesions

International Nuclear Information System (INIS)

Yanagawa, Masahiro; Tomiyama, Noriyuki; Sumikawa, Hiromitsu; Inoue, Atsuo; Daimon, Tadahisa; Honda, Osamu; Mihara, Naoki; Johkoh, Takeshi; Nakamura, Hironobu

2009-01-01

Purpose: Motion artifacts, which can mimic thickened bronchial wall and the cystic appearance of bronchiectasis, constitute a potential pitfall in the diagnosis of interstitial or bronchial disease. Therefore, purpose of our study was to evaluate whether 64-detector row CT (64-MDCT) enables a reduction in respiratory or cardiac motion artifacts in the lung area on thin-section CT without ECG gating, and to examine the correlation between cardiac motion artifact and heart rate. Materials and methods: Thirty-two patients with suspected diffuse lung disease, who underwent both 8- and 64-MDCT (gantry rotation time, 0.5 and 0.4 s, respectively), were included. The heart rates of an additional 155 patients were measured (range, 48-126 beats per minute; mean, 76 beats per minute) immediately prior to 64-MDCT, and compared to the degree of cardiac motion artifact. Two independent observers evaluated the following artifacts on a monitor without the knowledge of relevant clinical information: (1) artifacts on 8- and 64-MDCT images with 1.25-mm thickness and those on 64-MDCT images with 0.625-mm thickness in 32 patients; and (2) artifacts on 64-MDCT images with 0.625-mm thickness in 155 patients. Results: Interobserver agreement was good in evaluating artifacts on 8-MDCT images with 1.25-mm thickness (weighted Kappa test, κ = 0.61-0.71), and fair or poor in the other evaluations (κ < 0.31). Two observers stated that cardiac motion artifacts were more significant on 8-MDCT than on 64-MDCT in all 32 patients. Statistically significant differences were found at various checkpoints only in comparing artifacts between 8- and 64-MDCT for 1.25-mm thickness (Wilcoxon's signed-rank test, p < 0.0017). Cardiac motion artifacts on 64-MDCT had no significant correlation with heart rate (Spearman's correlation coefficient by rank test). Conclusion: The high temporal resolution of 64-MDCT appears to reduce cardiac motion artifact that can affect thin-section scans of the lung parenchyma

Thin-section CT of lung without ECG gating: 64-detector row CT can markedly reduce cardiac motion artifact which can simulate lung lesions

Energy Technology Data Exchange (ETDEWEB)

Yanagawa, Masahiro [Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871 (Japan)], E-mail: m-yanagawa@radiol.med.osaka-u.ac.jp; Tomiyama, Noriyuki; Sumikawa, Hiromitsu; Inoue, Atsuo [Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871 (Japan); Daimon, Tadahisa [Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871 (Japan); Department of Medicine, Division of Pulmonary Medicine, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi 329-0498 (Japan); Honda, Osamu [Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871 (Japan); Mihara, Naoki [Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871 (Japan); Department of Radiology, Osaka Advanced Medical Imaging Center, 5-20-1 Momoyamadai, Suita-city, Osaka 565-0854 (Japan); Johkoh, Takeshi [Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871 (Japan); Department of Medical Physics, Osaka University Graduate School of Medicine, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871 (Japan); Nakamura, Hironobu [Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871 (Japan)

2009-01-15

Purpose: Motion artifacts, which can mimic thickened bronchial wall and the cystic appearance of bronchiectasis, constitute a potential pitfall in the diagnosis of interstitial or bronchial disease. Therefore, purpose of our study was to evaluate whether 64-detector row CT (64-MDCT) enables a reduction in respiratory or cardiac motion artifacts in the lung area on thin-section CT without ECG gating, and to examine the correlation between cardiac motion artifact and heart rate. Materials and methods: Thirty-two patients with suspected diffuse lung disease, who underwent both 8- and 64-MDCT (gantry rotation time, 0.5 and 0.4 s, respectively), were included. The heart rates of an additional 155 patients were measured (range, 48-126 beats per minute; mean, 76 beats per minute) immediately prior to 64-MDCT, and compared to the degree of cardiac motion artifact. Two independent observers evaluated the following artifacts on a monitor without the knowledge of relevant clinical information: (1) artifacts on 8- and 64-MDCT images with 1.25-mm thickness and those on 64-MDCT images with 0.625-mm thickness in 32 patients; and (2) artifacts on 64-MDCT images with 0.625-mm thickness in 155 patients. Results: Interobserver agreement was good in evaluating artifacts on 8-MDCT images with 1.25-mm thickness (weighted Kappa test, {kappa} = 0.61-0.71), and fair or poor in the other evaluations ({kappa} < 0.31). Two observers stated that cardiac motion artifacts were more significant on 8-MDCT than on 64-MDCT in all 32 patients. Statistically significant differences were found at various checkpoints only in comparing artifacts between 8- and 64-MDCT for 1.25-mm thickness (Wilcoxon's signed-rank test, p < 0.0017). Cardiac motion artifacts on 64-MDCT had no significant correlation with heart rate (Spearman's correlation coefficient by rank test). Conclusion: The high temporal resolution of 64-MDCT appears to reduce cardiac motion artifact that can affect thin-section scans of

SU-G-BRA-10: Marker Free Lung Tumor Motion Tracking by An Active Contour Model On Cone Beam CT Projections for Stereotactic Body Radiation Therapy of Lung Cancer

International Nuclear Information System (INIS)

Chao, M; Yuan, Y; Lo, Y; Wei, J

2016-01-01

Purpose: To develop a novel strategy to extract the lung tumor motion from cone beam CT (CBCT) projections by an active contour model with interpolated respiration learned from diaphragm motion. Methods: Tumor tracking on CBCT projections was accomplished with the templates derived from planning CT (pCT). There are three major steps in the proposed algorithm: 1) The pCT was modified to form two CT sets: a tumor removed pCT and a tumor only pCT, the respective digitally reconstructed radiographs DRRtr and DRRto following the same geometry of the CBCT projections were generated correspondingly. 2) The DRRtr was rigidly registered with the CBCT projections on the frame-by-frame basis. Difference images between CBCT projections and the registered DRRtr were generated where the tumor visibility was appreciably enhanced. 3) An active contour method was applied to track the tumor motion on the tumor enhanced projections with DRRto as templates to initialize the tumor tracking while the respiratory motion was compensated for by interpolating the diaphragm motion estimated by our novel constrained linear regression approach. CBCT and pCT from five patients undergoing stereotactic body radiotherapy were included in addition to scans from a Quasar phantom programmed with known motion. Manual tumor tracking was performed on CBCT projections and was compared to the automatic tracking to evaluate the algorithm accuracy. Results: The phantom study showed that the error between the automatic tracking and the ground truth was within 0.2mm. For the patients the discrepancy between the calculation and the manual tracking was between 1.4 and 2.2 mm depending on the location and shape of the lung tumor. Similar patterns were observed in the frequency domain. Conclusion: The new algorithm demonstrated the feasibility to track the lung tumor from noisy CBCT projections, providing a potential solution to better motion management for lung radiation therapy.

SU-G-BRA-10: Marker Free Lung Tumor Motion Tracking by An Active Contour Model On Cone Beam CT Projections for Stereotactic Body Radiation Therapy of Lung Cancer

Energy Technology Data Exchange (ETDEWEB)

Chao, M; Yuan, Y; Lo, Y [The Mount Sinai Medical Center, New York, NY (United States); Wei, J [City College of New York, New York, NY (United States)

2016-06-15

Purpose: To develop a novel strategy to extract the lung tumor motion from cone beam CT (CBCT) projections by an active contour model with interpolated respiration learned from diaphragm motion. Methods: Tumor tracking on CBCT projections was accomplished with the templates derived from planning CT (pCT). There are three major steps in the proposed algorithm: 1) The pCT was modified to form two CT sets: a tumor removed pCT and a tumor only pCT, the respective digitally reconstructed radiographs DRRtr and DRRto following the same geometry of the CBCT projections were generated correspondingly. 2) The DRRtr was rigidly registered with the CBCT projections on the frame-by-frame basis. Difference images between CBCT projections and the registered DRRtr were generated where the tumor visibility was appreciably enhanced. 3) An active contour method was applied to track the tumor motion on the tumor enhanced projections with DRRto as templates to initialize the tumor tracking while the respiratory motion was compensated for by interpolating the diaphragm motion estimated by our novel constrained linear regression approach. CBCT and pCT from five patients undergoing stereotactic body radiotherapy were included in addition to scans from a Quasar phantom programmed with known motion. Manual tumor tracking was performed on CBCT projections and was compared to the automatic tracking to evaluate the algorithm accuracy. Results: The phantom study showed that the error between the automatic tracking and the ground truth was within 0.2mm. For the patients the discrepancy between the calculation and the manual tracking was between 1.4 and 2.2 mm depending on the location and shape of the lung tumor. Similar patterns were observed in the frequency domain. Conclusion: The new algorithm demonstrated the feasibility to track the lung tumor from noisy CBCT projections, providing a potential solution to better motion management for lung radiation therapy.

Performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches in VQ codebook generation for image compression

Science.gov (United States)

Tsai, Jinn-Tsong; Chou, Ping-Yi; Chou, Jyh-Horng

2015-11-01

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (LBG) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches. The PCA-EA-LBG approaches contain PCA-GA-LBG, PCA-PSO-LBG, PCA-HBMO-LBG, and PCA-FF-LBG, while the PCA-LBG-EA approaches contain PCA-LBG, PCA-LBG-GA, PCA-LBG-PSO, PCA-LBG-HBMO, and PCA-LBG-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-LBG used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for LBG to discover a codebook. The PCA-LBG approach is to use the PCA to select vectors as initial individuals for LBG to find a codebook. The PCA-LBG-EA used the final result of PCA-LBG as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-LBG first used global search and then applied local search skill, while in PCA-LBG-EA first used local search and then employed global search skill. The results verify that the PCA-EA-LBG indeed gain superior results compared to the PCA-LBG-EA, because the PCA-EA-LBG explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-LBG approaches in designing VQ codebooks outperform existing approaches shown in the literature.

Sequential combination of k-t principle component analysis (PCA) and partial parallel imaging: k-t PCA GROWL.

Science.gov (United States)

Qi, Haikun; Huang, Feng; Zhou, Hongmei; Chen, Huijun

2017-03-01

k-t principle component analysis (k-t PCA) is a distinguished method for high spatiotemporal resolution dynamic MRI. To further improve the accuracy of k-t PCA, a combination with partial parallel imaging (PPI), k-t PCA/SENSE, has been tested. However, k-t PCA/SENSE suffers from long reconstruction time and limited improvement. This study aims to improve the combination of k-t PCA and PPI on both reconstruction speed and accuracy. A sequential combination scheme called k-t PCA GROWL (GRAPPA operator for wider readout line) was proposed. The GRAPPA operator was performed before k-t PCA to extend each readout line into a wider band, which improved the condition of the encoding matrix in the following k-t PCA reconstruction. k-t PCA GROWL was tested and compared with k-t PCA and k-t PCA/SENSE on cardiac imaging. k-t PCA GROWL consistently resulted in better image quality compared with k-t PCA/SENSE at high acceleration factors for both retrospectively and prospectively undersampled cardiac imaging, with a much lower computation cost. The improvement in image quality became greater with the increase of acceleration factor. By sequentially combining the GRAPPA operator and k-t PCA, the proposed k-t PCA GROWL method outperformed k-t PCA/SENSE in both reconstruction speed and accuracy, suggesting that k-t PCA GROWL is a better combination scheme than k-t PCA/SENSE. Magn Reson Med 77:1058-1067, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

List-mode-based reconstruction for respiratory motion correction in PET using non-rigid body transformations

International Nuclear Information System (INIS)

Lamare, F; Carbayo, M J Ledesma; Cresson, T; Kontaxakis, G; Santos, A; Rest, C Cheze Le; Reader, A J; Visvikis, D

2007-01-01

Respiratory motion in emission tomography leads to reduced image quality. Developed correction methodology has been concentrating on the use of respiratory synchronized acquisitions leading to gated frames. Such frames, however, are of low signal-to-noise ratio as a result of containing reduced statistics. In this work, we describe the implementation of an elastic transformation within a list-mode-based reconstruction for the correction of respiratory motion over the thorax, allowing the use of all data available throughout a respiratory motion average acquisition. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List-mode-data-based PET-simulated frames were subsequently produced by combining the NCAT datasets with Monte Carlo simulation. A non-rigid registration algorithm based on B-spline basis functions was employed to derive transformation parameters accounting for the respiratory motion using the NCAT dynamic CT images. The displacement matrices derived were subsequently applied during the image reconstruction of the original emission list mode data. Two different implementations for the incorporation of the elastic transformations within the one-pass list mode EM (OPL-EM) algorithm were developed and evaluated. The corrected images were compared with those produced using an affine transformation of list mode data prior to reconstruction, as well as with uncorrected respiratory motion average images. Results demonstrate that although both correction techniques considered lead to significant improvements in accounting for respiratory motion artefacts in the lung fields, the elastic-transformation-based correction leads to a more uniform improvement across the lungs for different lesion sizes and locations

Simultaneous Estimation of Hydrochlorothiazide, Hydralazine Hydrochloride, and Reserpine Using PCA, NAS, and NAS-PCA.

Science.gov (United States)

Sharma, Chetan; Badyal, Pragya Nand; Rawal, Ravindra K

2015-01-01

In this study, new and feasible UV-visible spectrophotometric and multivariate spectrophotometric methods were described for the simultaneous determination of hydrochlorothiazide (HCTZ), hydralazine hydrochloride (H.HCl), and reserpine (RES) in combined pharmaceutical tablets. Methanol was used as a solvent for analysis and the whole UV region was scanned from 200-400 nm. The resolution was obtained by using multivariate methods such as the net analyte signal method (NAS), principal component analysis (PCA), and net analyte signal-principal component analysis (NAS-PCA) applied to the UV spectra of the mixture. The results obtained from all of the three methods were compared. NAS-PCA showed a lot of resolved data as compared to NAS and PCA. Thus, the NAS-PCA technique is a combination of NAS and PCA methods which is advantageous to obtain the information from overlapping results.

MRI-based measurements of respiratory motion variability and assessment of imaging strategies for radiotherapy planning

International Nuclear Information System (INIS)

Blackall, J M; Ahmad, S; Miquel, M E; McClelland, J R; Landau, D B; Hawkes, D J

2006-01-01

Respiratory organ motion has a significant impact on the planning and delivery of radiotherapy (RT) treatment for lung cancer. Currently widespread techniques, such as 4D-computed tomography (4DCT), cannot be used to measure variability of this motion from one cycle to the next. In this paper, we describe the use of fast magnetic resonance imaging (MRI) techniques to investigate the intra- and inter-cycle reproducibility of respiratory motion and also to estimate the level of errors that may be introduced into treatment delivery by using various breath-hold imaging strategies during lung RT planning. A reference model of respiratory motion is formed to enable comparison of different breathing cycles at any arbitrary position in the respiratory cycle. This is constructed by using free-breathing images from the inhale phase of a single breathing cycle, then co-registering the images, and thereby tracking landmarks. This reference model is then compared to alternative models constructed from images acquired during the exhale phase of the same cycle and the inhale phase of a subsequent cycle, to assess intra- and inter-cycle variability ('hysteresis' and 'reproducibility') of organ motion. The reference model is also compared to a series of models formed from breath-hold data at exhale and inhale. Evaluation of these models is carried out on data from ten healthy volunteers and five lung cancer patients. Free-breathing models show good levels of intra- and inter-cycle reproducibility across the tidal breathing range. Mean intra-cycle errors in the position of organ surface landmarks of 1.5(1.4)-3.5(3.3) mm for volunteers and 2.8(1.8)-5.2(5.2) mm for patients. Equivalent measures of inter-cycle variability across this range are 1.7(1.0)-3.9(3.3) mm for volunteers and 2.8(1.8)-3.3(2.2) mm for patients. As expected, models based on breath-hold sequences do not represent normal tidal motion as well as those based on free-breathing data, with mean errors of 4

Assessment of CF lung disease using motion corrected PROPELLER MRI: a comparison with CT

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Ciet, Pierluigi [General Hospital Ca' Foncello, Radiology Department, Treviso (Italy); Sophia Children' s Hospital, Pediatric Pulmonology Erasmus MC, Rotterdam (Netherlands); Erasmus MC, Radiology, Rotterdam (Netherlands); Serra, Goffredo; Catalano, Carlo [University of Rome ' ' Sapienza' ' , Radiology, Rome (Italy); Bertolo, Silvia; Morana, Giovanni [General Hospital Ca' Foncello, Radiology Department, Treviso (Italy); Spronk, Sandra [Erasmus MC, Radiology, Rotterdam (Netherlands); Erasmus MC, Epidemiology, Rotterdam (Netherlands); Ros, Mirco [Ca' Foncello Hospital, Pediatrics, Treviso (Italy); Fraioli, Francesco [University College London (UCL), Institute of Nuclear Medicine, London (United Kingdom); Quattrucci, Serena [University of Rome Sapienza, Pediatrics, Rome (Italy); Assael, M.B. [Azienda Ospedaliera di Verona, Verona CF Center, Verona (Italy); Pomerri, Fabio [University of Padova, Department of Medicine-DIMED, Padova (Italy); Tiddens, Harm A.W.M. [Sophia Children' s Hospital, Pediatric Pulmonology Erasmus MC, Rotterdam (Netherlands); Erasmus MC, Radiology, Rotterdam (Netherlands)

2016-03-15

To date, PROPELLER MRI, a breathing-motion-insensitive technique, has not been assessed for cystic fibrosis (CF) lung disease. We compared this technique to CT for assessing CF lung disease in children and adults. Thirty-eight stable CF patients (median 21 years, range 6-51 years, 22 female) underwent MRI and CT on the same day. Study protocol included respiratory-triggered PROPELLER MRI and volumetric CT end-inspiratory and -expiratory acquisitions. Two observers scored the images using the CF-MRI and CF-CT systems. Scores were compared with intra-class correlation coefficient (ICC) and Bland-Altman plots. The sensitivity and specificity of MRI versus CT were calculated. MRI sensitivity for detecting severe CF bronchiectasis was 0.33 (CI 0.09-0.57), while specificity was 100 % (CI 0.88-1). ICCs for bronchiectasis and trapped air were as follows: MRI-bronchiectasis (0.79); CT-bronchiectasis (0.85); MRI-trapped air (0.51); CT-trapped air (0.87). Bland-Altman plots showed an MRI tendency to overestimate the severity of bronchiectasis in mild CF disease and underestimate bronchiectasis in severe disease. Motion correction in PROPELLER MRI does not improve assessment of CF lung disease compared to CT. However, the good inter- and intra-observer agreement and the high specificity suggest that MRI might play a role in the short-term follow-up of CF lung disease (i.e. pulmonary exacerbations). (orig.)

Assessment of CF lung disease using motion corrected PROPELLER MRI: a comparison with CT

International Nuclear Information System (INIS)

Ciet, Pierluigi; Serra, Goffredo; Catalano, Carlo; Bertolo, Silvia; Morana, Giovanni; Spronk, Sandra; Ros, Mirco; Fraioli, Francesco; Quattrucci, Serena; Assael, M.B.; Pomerri, Fabio; Tiddens, Harm A.W.M.

2016-01-01

To date, PROPELLER MRI, a breathing-motion-insensitive technique, has not been assessed for cystic fibrosis (CF) lung disease. We compared this technique to CT for assessing CF lung disease in children and adults. Thirty-eight stable CF patients (median 21 years, range 6-51 years, 22 female) underwent MRI and CT on the same day. Study protocol included respiratory-triggered PROPELLER MRI and volumetric CT end-inspiratory and -expiratory acquisitions. Two observers scored the images using the CF-MRI and CF-CT systems. Scores were compared with intra-class correlation coefficient (ICC) and Bland-Altman plots. The sensitivity and specificity of MRI versus CT were calculated. MRI sensitivity for detecting severe CF bronchiectasis was 0.33 (CI 0.09-0.57), while specificity was 100 % (CI 0.88-1). ICCs for bronchiectasis and trapped air were as follows: MRI-bronchiectasis (0.79); CT-bronchiectasis (0.85); MRI-trapped air (0.51); CT-trapped air (0.87). Bland-Altman plots showed an MRI tendency to overestimate the severity of bronchiectasis in mild CF disease and underestimate bronchiectasis in severe disease. Motion correction in PROPELLER MRI does not improve assessment of CF lung disease compared to CT. However, the good inter- and intra-observer agreement and the high specificity suggest that MRI might play a role in the short-term follow-up of CF lung disease (i.e. pulmonary exacerbations). (orig.)

Initial clinical observations of intra- and interfractional motion variation in MR-guided lung SBRT.

Science.gov (United States)

Thomas, David H; Santhanam, Anand; Kishan, Amar U; Cao, Minsong; Lamb, James; Min, Yugang; O'Connell, Dylan; Yang, Yingli; Agazaryan, Nzhde; Lee, Percy; Low, Daniel

2018-02-01

To evaluate variations in intra- and interfractional tumour motion, and the effect on internal target volume (ITV) contour accuracy, using deformable image registration of real-time two-dimensional-sagittal cine-mode MRI acquired during lung stereotactic body radiation therapy (SBRT) treatments. Five lung tumour patients underwent free-breathing SBRT treatments on the ViewRay system, with dose prescribed to a planning target volume (defined as a 3-6 mm expansion of the 4DCT-ITV). Sagittal slice cine-MR images (3.5 × 3.5 mm 2 pixels) were acquired through the centre of the tumour at 4 frames per second throughout the treatments (3-4 fractions of 21-32 min). Tumour gross tumour volumes (GTVs) were contoured on the first frame of the MR cine and tracked for the first 20 min of each treatment using offline optical-flow based deformable registration implemented on a GPU cluster. A ground truth ITV (MR-ITV 20 min ) was formed by taking the union of tracked GTV contours. Pseudo-ITVs were generated from unions of the GTV contours tracked over 10 s segments of image data (MR-ITV 10 s ). Differences were observed in the magnitude of median tumour displacement between days of treatments. MR-ITV 10 s areas were as small as 46% of the MR-ITV 20 min . An ITV offers a "snapshot" of breathing motion for the brief period of time the tumour is imaged on a specific day. Real-time MRI over prolonged periods of time and over multiple treatment fractions shows that ITV size varies. Further work is required to investigate the dosimetric effect of these results. Advances in knowledge: Five lung tumour patients underwent free-breathing MRI-guided SBRT treatments, and their tumours tracked using deformable registration of cine-mode MRI. The results indicate that variability of both intra- and interfractional breathing amplitude should be taken into account during planning of lung radiotherapy.

Online prediction of respiratory motion: multidimensional processing with low-dimensional feature learning

International Nuclear Information System (INIS)

Ruan, Dan; Keall, Paul

2010-01-01

Accurate real-time prediction of respiratory motion is desirable for effective motion management in radiotherapy for lung tumor targets. Recently, nonparametric methods have been developed and their efficacy in predicting one-dimensional respiratory-type motion has been demonstrated. To exploit the correlation among various coordinates of the moving target, it is natural to extend the 1D method to multidimensional processing. However, the amount of learning data required for such extension grows exponentially with the dimensionality of the problem, a phenomenon known as the 'curse of dimensionality'. In this study, we investigate a multidimensional prediction scheme based on kernel density estimation (KDE) in an augmented covariate-response space. To alleviate the 'curse of dimensionality', we explore the intrinsic lower dimensional manifold structure and utilize principal component analysis (PCA) to construct a proper low-dimensional feature space, where kernel density estimation is feasible with the limited training data. Interestingly, the construction of this lower dimensional representation reveals a useful decomposition of the variations in respiratory motion into the contribution from semiperiodic dynamics and that from the random noise, as it is only sensible to perform prediction with respect to the former. The dimension reduction idea proposed in this work is closely related to feature extraction used in machine learning, particularly support vector machines. This work points out a pathway in processing high-dimensional data with limited training instances, and this principle applies well beyond the problem of target-coordinate-based respiratory-based prediction. A natural extension is prediction based on image intensity directly, which we will investigate in the continuation of this work. We used 159 lung target motion traces obtained with a Synchrony respiratory tracking system. Prediction performance of the low-dimensional feature learning-based

Gating treatment delivery QA based on a surrogate motion analysis

International Nuclear Information System (INIS)

Chojnowski, J.; Simpson, E.

2011-01-01

Full text: To develop a methodology to estimate intrafractional target position error during a phase-based gated treatment. Westmead Cancer Care Centre is using respiratory correlated phase-based gated beam delivery in the treatment of lung cancer. The gating technique is managed by the Varian Real-time Position Management (RPM) system, version 1.7.5. A 6-dot block is placed on the abdomen of the patient and acts as a surrogate for the target motion. During a treatment session, the motion of the surrogate can be recorded by RPM application. Analysis of the surrogate motion file by in-house developed software allows the intrafractional error of the treatment session to be computed. To validate the computed error, a simple test that involves the introduction of deliberate errors is performed. Errors of up to 1.1 cm are introduced to a metal marker placed on a surrogate using the Varian Breathing Phantom. The moving marker was scanned in prospective mode using a GE Lightspeed 16 CT scanner. Using the CT images, a difference of the marker position with and without introduced errors is compared to the calculated errors based on the surrogate motion. The average and standard deviation of a difference between calculated target position errors and measured introduced artificial errors of the marker position is 0.02 cm and 0.07 cm respectively. Conclusion The calculated target positional error based on surrogate motion analysis provides a quantitative measure of intrafractional target positional errors during treatment. Routine QA for gated treatment using surrogate motion analysis is relatively quick and simple.

Local respiratory motion correction for PET/CT imaging: Application to lung cancer

Energy Technology Data Exchange (ETDEWEB)

Lamare, F., E-mail: frederic.lamare@chu-bordeaux.fr; Fernandez, P. [INCIA, UMR 5287, University of Bordeaux, Talence F-33400, France and Nuclear Medicine Department, University Hospital, Bordeaux 33000 (France); Fayad, H.; Visvikis, D. [INSERM, UMR1101, LaTIM, Université de Bretagne Occidentale, Brest 29609 (France)

2015-10-15

Purpose: Despite multiple methodologies already proposed to correct respiratory motion in the whole PET imaging field of view (FOV), such approaches have not found wide acceptance in clinical routine. An alternative can be the local respiratory motion correction (LRMC) of data corresponding to a given volume of interest (VOI: organ or tumor). Advantages of LRMC include the use of a simple motion model, faster execution times, and organ specific motion correction. The purpose of this study was to evaluate the performance of LMRC using various motion models for oncology (lung lesion) applications. Methods: Both simulated (NURBS based 4D cardiac-torso phantom) and clinical studies (six patients) were used in the evaluation of the proposed LRMC approach. PET data were acquired in list-mode and synchronized with respiration. The implemented approach consists first in defining a VOI on the reconstructed motion average image. Gated PET images of the VOI are subsequently reconstructed using only lines of response passing through the selected VOI and are used in combination with a center of gravity or an affine/elastic registration algorithm to derive the transformation maps corresponding to the respiration effects. Those are finally integrated in the reconstruction process to produce a motion free image over the lesion regions. Results: Although the center of gravity or affine algorithm achieved similar performance for individual lesion motion correction, the elastic model, applied either locally or to the whole FOV, led to an overall superior performance. The spatial tumor location was altered by 89% and 81% for the elastic model applied locally or to the whole FOV, respectively (compared to 44% and 39% for the center of gravity and affine models, respectively). This resulted in similar associated overall tumor volume changes of 84% and 80%, respectively (compared to 75% and 71% for the center of gravity and affine models, respectively). The application of the nonrigid

The variability of tumor motion and respiration pattern in Stereotactic Body RadioTherapy(SBRT) for Lung cancer patients

Energy Technology Data Exchange (ETDEWEB)

Park, Hyun Joon; Bae, Sun Myeong; Baek, Geum Mun; Kang, Tae Young; Seo, Dong Rin [Dept. of Radiation Oncology, ASAN Medical Center, Seoul (Korea, Republic of)

2016-06-15

The purpose of this study is to evaluate the variability of tumor motion and respiration pattern in lung cancer patients undergoing Stereotactic Body RadioTherapy(SBRT) by using On-Board imager (OBI) system and Real-time Position Management (RPM) System. This study population consisted of 60 lung cancer patient treated with stereotactic body radiotherapy (48 Gy / 4 fractions). Of these, 30 were treated with gating (group 1) and 30 without gating(group2): typically the patients whose tumors showed three-dimensional respiratory motion > 10 mm were selected for gating. 4-dimensional Computed Tomography (4DCT). Cone Beam CT (CBCT) and Fluoroscopy images were used to measure the tumor motion. RPM system was used to evaluate the variability of respiration pattern on SBRT for group1. The mean difference of tumor motion among 4DCT, CBCT and Fluoroscopy images in the cranio-caudal direction was 2.3 mm in group 1, 2. The maximum difference was 12.5 mm in the group 1 and 8.5 mm in group 2. The number of treatment fractions that patient's respiration pattern was within Upper-Lower threshold on SBRT in group 2 was 31 fractions. A patient who exhibited the most unstable pattern exceeded 108 times in a fraction. Although many patients in group 1 and 2 kept the reproducibility of tumor motion within 5 mm during their treatment, some patients exhibited variability of tumor motion in the CBCT and Fluoroscopy images. It was possible to improve the accuracy of dose delivery in SBRT without gating for lung cancer patient by using RPM system.

Circle of Willis Variants: Fetal PCA

OpenAIRE

Amir Shaban; Karen C. Albright; Amelia K. Boehme; Sheryl Martin-Schild

2013-01-01

We sought to determine the prevalence of fetal posterior cerebral artery (fPCA) and if fPCA was associated with specific stroke etiology and vessel territory affected. This paper is a retrospective review of prospectively identified patients with acute ischemic stroke from July 2008 to December 2010. We defined complete fPCA as absence of a P1 segment linking the basilar with the PCA and partial fPCA as small segment linking the basilar with the PCA. Patients without intracranial vascular ima...

Effects of Respiratory Motion on Passively Scattered Proton Therapy Versus Intensity Modulated Photon Therapy for Stage III Lung Cancer: Are Proton Plans More Sensitive to Breathing Motion?

International Nuclear Information System (INIS)

Matney, Jason; Park, Peter C.; Bluett, Jaques; Chen, Yi Pei; Liu, Wei; Court, Laurence E.; Liao, Zhongxing; Li, Heng; Mohan, Radhe

2013-01-01

Purpose: To quantify and compare the effects of respiratory motion on paired passively scattered proton therapy (PSPT) and intensity modulated photon therapy (IMRT) plans; and to establish the relationship between the magnitude of tumor motion and the respiratory-induced dose difference for both modalities. Methods and Materials: In a randomized clinical trial comparing PSPT and IMRT, radiation therapy plans have been designed according to common planning protocols. Four-dimensional (4D) dose was computed for PSPT and IMRT plans for a patient cohort with respiratory motion ranging from 3 to 17 mm. Image registration and dose accumulation were performed using grayscale-based deformable image registration algorithms. The dose–volume histogram (DVH) differences (4D-3D [3D = 3-dimensional]) were compared for PSPT and IMRT. Changes in 4D-3D dose were correlated to the magnitude of tumor respiratory motion. Results: The average 4D-3D dose to 95% of the internal target volume was close to zero, with 19 of 20 patients within 1% of prescribed dose for both modalities. The mean 4D-3D between the 2 modalities was not statistically significant (P<.05) for all dose–volume histogram indices (mean ± SD) except the lung V5 (PSPT: +1.1% ± 0.9%; IMRT: +0.4% ± 1.2%) and maximum cord dose (PSPT: +1.5 ± 2.9 Gy; IMRT: 0.0 ± 0.2 Gy). Changes in 4D-3D dose were correlated to tumor motion for only 2 indices: dose to 95% planning target volume, and heterogeneity index. Conclusions: With our current margin formalisms, target coverage was maintained in the presence of respiratory motion up to 17 mm for both PSPT and IMRT. Only 2 of 11 4D-3D indices (lung V5 and spinal cord maximum) were statistically distinguishable between PSPT and IMRT, contrary to the notion that proton therapy will be more susceptible to respiratory motion. Because of the lack of strong correlations with 4D-3D dose differences in PSPT and IMRT, the extent of tumor motion was not an adequate predictor of potential

Effects of Respiratory Motion on Passively Scattered Proton Therapy Versus Intensity Modulated Photon Therapy for Stage III Lung Cancer: Are Proton Plans More Sensitive to Breathing Motion?

Energy Technology Data Exchange (ETDEWEB)

Matney, Jason; Park, Peter C. [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); The University of Texas Graduate School of Biomedical Sciences, Houston, Texas (United States); Bluett, Jaques [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Chen, Yi Pei [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); The University of Texas Graduate School of Biomedical Sciences, Houston, Texas (United States); Liu, Wei; Court, Laurence E. [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Liao, Zhongxing [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Li, Heng [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mohan, Radhe, E-mail: rmohan@mdanderson.org [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)

2013-11-01

Purpose: To quantify and compare the effects of respiratory motion on paired passively scattered proton therapy (PSPT) and intensity modulated photon therapy (IMRT) plans; and to establish the relationship between the magnitude of tumor motion and the respiratory-induced dose difference for both modalities. Methods and Materials: In a randomized clinical trial comparing PSPT and IMRT, radiation therapy plans have been designed according to common planning protocols. Four-dimensional (4D) dose was computed for PSPT and IMRT plans for a patient cohort with respiratory motion ranging from 3 to 17 mm. Image registration and dose accumulation were performed using grayscale-based deformable image registration algorithms. The dose–volume histogram (DVH) differences (4D-3D [3D = 3-dimensional]) were compared for PSPT and IMRT. Changes in 4D-3D dose were correlated to the magnitude of tumor respiratory motion. Results: The average 4D-3D dose to 95% of the internal target volume was close to zero, with 19 of 20 patients within 1% of prescribed dose for both modalities. The mean 4D-3D between the 2 modalities was not statistically significant (P<.05) for all dose–volume histogram indices (mean ± SD) except the lung V5 (PSPT: +1.1% ± 0.9%; IMRT: +0.4% ± 1.2%) and maximum cord dose (PSPT: +1.5 ± 2.9 Gy; IMRT: 0.0 ± 0.2 Gy). Changes in 4D-3D dose were correlated to tumor motion for only 2 indices: dose to 95% planning target volume, and heterogeneity index. Conclusions: With our current margin formalisms, target coverage was maintained in the presence of respiratory motion up to 17 mm for both PSPT and IMRT. Only 2 of 11 4D-3D indices (lung V5 and spinal cord maximum) were statistically distinguishable between PSPT and IMRT, contrary to the notion that proton therapy will be more susceptible to respiratory motion. Because of the lack of strong correlations with 4D-3D dose differences in PSPT and IMRT, the extent of tumor motion was not an adequate predictor of potential

Improved algorithms for the classification of rough rice using a bionic electronic nose based on PCA and the Wilks distribution.

Science.gov (United States)

Xu, Sai; Zhou, Zhiyan; Lu, Huazhong; Luo, Xiwen; Lan, Yubin

2014-03-19

Principal Component Analysis (PCA) is one of the main methods used for electronic nose pattern recognition. However, poor classification performance is common in classification and recognition when using regular PCA. This paper aims to improve the classification performance of regular PCA based on the existing Wilks Λ-statistic (i.e., combined PCA with the Wilks distribution). The improved algorithms, which combine regular PCA with the Wilks Λ-statistic, were developed after analysing the functionality and defects of PCA. Verification tests were conducted using a PEN3 electronic nose. The collected samples consisted of the volatiles of six varieties of rough rice (Zhongxiang1, Xiangwan13, Yaopingxiang, WufengyouT025, Pin 36, and Youyou122), grown in same area and season. The first two principal components used as analysis vectors cannot perform the rough rice varieties classification task based on a regular PCA. Using the improved algorithms, which combine the regular PCA with the Wilks Λ-statistic, many different principal components were selected as analysis vectors. The set of data points of the Mahalanobis distance between each of the varieties of rough rice was selected to estimate the performance of the classification. The result illustrates that the rough rice varieties classification task is achieved well using the improved algorithm. A Probabilistic Neural Networks (PNN) was also established to test the effectiveness of the improved algorithms. The first two principal components (namely PC1 and PC2) and the first and fifth principal component (namely PC1 and PC5) were selected as the inputs of PNN for the classification of the six rough rice varieties. The results indicate that the classification accuracy based on the improved algorithm was improved by 6.67% compared to the results of the regular method. These results prove the effectiveness of using the Wilks Λ-statistic to improve the classification accuracy of the regular PCA approach. The results

Memory Efficient PCA Methods for Large Group ICA.

Science.gov (United States)

Rachakonda, Srinivas; Silva, Rogers F; Liu, Jingyu; Calhoun, Vince D

2016-01-01

data analysis. Implications to other methods such as expectation maximization PCA (EM PCA) are also presented. Based on our results, general recommendations for efficient application of PCA methods are given according to problem size and available computational resources. MPOWIT and all other methods discussed here are implemented and readily available in the open source GIFT software.

Memory efficient PCA methods for large group ICA

Directory of Open Access Journals (Sweden)

Srinivas eRachakonda

2016-02-01

ideal for big data analysis. Implications to other methods such as expectation maximization PCA (EM PCA are also presented. Based on our results, general recommendations for efficient application of PCA methods are given according to problem size and available computational resources. MPOWIT and all other methods discussed here are implemented and readily available in the open source GIFT software.

Motion Interplay as a Function of Patient Parameters and Spot Size in Spot Scanning Proton Therapy for Lung Cancer

Science.gov (United States)

Grassberger, Clemens; Dowdell, Stephen; Lomax, Antony; Sharp, Greg; Shackleford, James; Choi, Noah; Willers, Henning; Paganetti, Harald

2013-01-01

Purpose Quantify the impact of respiratory motion on the treatment of lung tumors with spot scanning proton therapy. Methods and Materials 4D Monte Carlo simulations were used to assess the interplay effect, which results from relative motion of the tumor and the proton beam, on the dose distribution in the patient. Ten patients with varying tumor sizes (2.6-82.3cc) and motion amplitudes (3-30mm) were included in the study. We investigated the impact of the spot size, which varies between proton facilities, and studied single fractions and conventionally fractionated treatments. The following metrics were used in the analysis: minimum/maximum/mean dose, target dose homogeneity and 2-year local control rate (2y-LC). Results Respiratory motion reduces the target dose homogeneity, with the largest effects observed for the highest motion amplitudes. Smaller spot sizes (σ≈3mm) are inherently more sensitive to motion, decreasing target dose homogeneity on average by a factor ~2.8 compared to a larger spot size (σ≈13mm). Using a smaller spot size to treat a tumor with 30mm motion amplitude reduces the minimum dose to 44.7% of the prescribed dose, decreasing modeled 2y-LC from 87.0% to 2.7%, assuming a single fraction. Conventional fractionation partly mitigates this reduction, yielding a 2y-LC of 71.6%. For the large spot size, conventional fractionation increases target dose homogeneity and prevents a deterioration of 2y-LC for all patients. No correlation with tumor volume is observed. The effect on the normal lung dose distribution is minimal: observed changes in mean lung dose and lung V20 are interplay using a large spot size and conventional fractionation. For treatments employing smaller spot sizes and/or in the delivery of single fractions, interplay effects can lead to significant deterioration of the dose distribution and lower 2y-LC. PMID:23462423

Motion Interplay as a Function of Patient Parameters and Spot Size in Spot Scanning Proton Therapy for Lung Cancer

International Nuclear Information System (INIS)

Grassberger, Clemens; Dowdell, Stephen; Lomax, Antony; Sharp, Greg; Shackleford, James; Choi, Noah; Willers, Henning; Paganetti, Harald

2013-01-01

Purpose: To quantify the impact of respiratory motion on the treatment of lung tumors with spot scanning proton therapy. Methods and Materials: Four-dimensional Monte Carlo simulations were used to assess the interplay effect, which results from relative motion of the tumor and the proton beam, on the dose distribution in the patient. Ten patients with varying tumor sizes (2.6-82.3 cc) and motion amplitudes (3-30 mm) were included in the study. We investigated the impact of the spot size, which varies between proton facilities, and studied single fractions and conventionally fractionated treatments. The following metrics were used in the analysis: minimum/maximum/mean dose, target dose homogeneity, and 2-year local control rate (2y-LC). Results: Respiratory motion reduces the target dose homogeneity, with the largest effects observed for the highest motion amplitudes. Smaller spot sizes (σ ≈ 3 mm) are inherently more sensitive to motion, decreasing target dose homogeneity on average by a factor 2.8 compared with a larger spot size (σ ≈ 13 mm). Using a smaller spot size to treat a tumor with 30-mm motion amplitude reduces the minimum dose to 44.7% of the prescribed dose, decreasing modeled 2y-LC from 87.0% to 2.7%, assuming a single fraction. Conventional fractionation partly mitigates this reduction, yielding a 2y-LC of 71.6%. For the large spot size, conventional fractionation increases target dose homogeneity and prevents a deterioration of 2y-LC for all patients. No correlation with tumor volume is observed. The effect on the normal lung dose distribution is minimal: observed changes in mean lung dose and lung V 20 are <0.6 Gy(RBE) and <1.7%, respectively. Conclusions: For the patients in this study, 2y-LC could be preserved in the presence of interplay using a large spot size and conventional fractionation. For treatments using smaller spot sizes and/or in the delivery of single fractions, interplay effects can lead to significant deterioration of the

Short-term PV/T module temperature prediction based on PCA-RBF neural network

Science.gov (United States)

Li, Jiyong; Zhao, Zhendong; Li, Yisheng; Xiao, Jing; Tang, Yunfeng

2018-02-01

Aiming at the non-linearity and large inertia of temperature control in PV/T system, short-term temperature prediction of PV/T module is proposed, to make the PV/T system controller run forward according to the short-term forecasting situation to optimize control effect. Based on the analysis of the correlation between PV/T module temperature and meteorological factors, and the temperature of adjacent time series, the principal component analysis (PCA) method is used to pre-process the original input sample data. Combined with the RBF neural network theory, the simulation results show that the PCA method makes the prediction accuracy of the network model higher and the generalization performance stronger than that of the RBF neural network without the main component extraction.

PET Motion Compensation for Radiation Therapy Using a CT-Based Mid-Position Motion Model: Methodology and Clinical Evaluation

International Nuclear Information System (INIS)

Kruis, Matthijs F.; Kamer, Jeroen B. van de; Houweling, Antonetta C.; Sonke, Jan-Jakob; Belderbos, José S.A.; Herk, Marcel van

2013-01-01

Purpose: Four-dimensional positron emission tomography (4D PET) imaging of the thorax produces sharper images with reduced motion artifacts. Current radiation therapy planning systems, however, do not facilitate 4D plan optimization. When images are acquired in a 2-minute time slot, the signal-to-noise ratio of each 4D frame is low, compromising image quality. The purpose of this study was to implement and evaluate the construction of mid-position 3D PET scans, with motion compensated using a 4D computed tomography (CT)-derived motion model. Methods and Materials: All voxels of 4D PET were registered to the time-averaged position by using a motion model derived from the 4D CT frames. After the registration the scans were summed, resulting in a motion-compensated 3D mid-position PET scan. The method was tested with a phantom dataset as well as data from 27 lung cancer patients. Results: PET motion compensation using a CT-based motion model improved image quality of both phantoms and patients in terms of increased maximum SUV (SUV max ) values and decreased apparent volumes. In homogenous phantom data, a strong relationship was found between the amplitude-to-diameter ratio and the effects of the method. In heterogeneous patient data, the effect correlated better with the motion amplitude. In case of large amplitudes, motion compensation may increase SUV max up to 25% and reduce the diameter of the 50% SUV max volume by 10%. Conclusions: 4D CT-based motion-compensated mid-position PET scans provide improved quantitative data in terms of uptake values and volumes at the time-averaged position, thereby facilitating more accurate radiation therapy treatment planning of pulmonary lesions

Shallow-Land Buriable PCA-type austenitic stainless steel for fusion application

International Nuclear Information System (INIS)

Zucchetti, M.

1991-01-01

Neutron-induced activity in the PCA (Primary Candidate Alloy) austenitic stainless steel is examined, when used for first-wall components in a DEMO fusion reactor. Some low-activity definitions, based on different waste management and disposal concepts, are introduced. Activity in the PCA is so high that any recycling of the irradiated material can be excluded. Disposal of PCA radioactive wastes in Shallow-Land Buriable (SLB) is prevented as well. Mo, Nb and some impurity elements have to be removed or limited, in order to reduce the radioactivity of the PCA. Possible low-activity versions of the PCA are introduced (PCA-la); they meet the requirements for SLB and may also be recycled under certain conditions. (author)

PCA-based algorithm for calibration of spectrophotometric analysers of food

International Nuclear Information System (INIS)

Morawski, Roman Z; Miekina, Andrzej

2013-01-01

Spectrophotometric analysers of food, being instruments for determination of the composition of food products and ingredients, are today of growing importance for food industry, as well as for food distributors and consumers. Their metrological performance significantly depends of the numerical performance of available means for spectrophotometric data processing; in particular – the means for calibration of analysers. In this paper, a new algorithm for this purpose is proposed, viz. the algorithm using principal components analysis (PCA). It is almost as efficient as PLS-based algorithms of calibration, but much simpler

TH-AB-202-01: Daily Lung Tumor Motion Characterization On EPIDs Using a Markerless Tiling Model

Energy Technology Data Exchange (ETDEWEB)

Rozario, T [University of Texas Southwestern Medical Center, Dallas, TX (United States); University of Texas at Dallas, Richardson, TX (United States); Chiu, T; Lu, W; Chen, M; Yan, Y [University of Texas Southwestern Medical Center, Dallas, TX (United States); Bereg, S [University of Texas at Dallas, Richardson, TX (United States); Mao, W [University of Texas Southwestern Medical Center, Dallas, TX (United States); Henry Ford Hospital, Detroit, MI (United States)

2016-06-15

Purpose: Tracking lung tumor motion in real time allows for target dose escalation while simultaneously reducing dose to sensitive structures, thus increasing local control without increasing toxicity. We present a novel intra-fractional markerless lung tumor tracking algorithm using MV treatment beam images acquired during treatment delivery. Strong signals superimposed on the tumor significantly reduced the soft tissue resolution; while different imaging modalities involved introduce global imaging discrepancies. This reduced the comparison accuracies. A simple yet elegant Tiling algorithm is reported to overcome the aforementioned issues. Methods: MV treatment beam images were acquired continuously in beam’s eye view (BEV) by an electronic portal imaging device (EPID) during treatment and analyzed to obtain tumor positions on every frame. Every frame of the MV image was simulated by a composite of two components with separate digitally reconstructed radiographs (DRRs): all non-moving structures and the tumor. This Titling algorithm divides the global composite DRR and the corresponding MV projection into sub-images called tiles. Rigid registration is performed independently on tile-pairs in order to improve local soft tissue resolution. This enables the composite DRR to be transformed accurately to match the MV projection and attain a high correlation value through a pixel-based linear transformation. The highest cumulative correlation for all tile-pairs achieved over a user-defined search range indicates the 2-D coordinates of the tumor location on the MV projection. Results: This algorithm was successfully applied to cine-mode BEV images acquired during two SBRT plans delivered five times with different motion patterns to each of two phantoms. Approximately 15000 beam’s eye view images were analyzed and tumor locations were successfully identified on every projection with a maximum/average error of 1.8 mm / 1.0 mm. Conclusion: Despite the presence of

A Study of Wind Turbine Comprehensive Operational Assessment Model Based on EM-PCA Algorithm

Science.gov (United States)

Zhou, Minqiang; Xu, Bin; Zhan, Yangyan; Ren, Danyuan; Liu, Dexing

2018-01-01

To assess wind turbine performance accurately and provide theoretical basis for wind farm management, a hybrid assessment model based on Entropy Method and Principle Component Analysis (EM-PCA) was established, which took most factors of operational performance into consideration and reach to a comprehensive result. To verify the model, six wind turbines were chosen as the research objects, the ranking obtained by the method proposed in the paper were 4#>6#>1#>5#>2#>3#, which are completely in conformity with the theoretical ranking, which indicates that the reliability and effectiveness of the EM-PCA method are high. The method could give guidance for processing unit state comparison among different units and launching wind farm operational assessment.

On the Link Between L1-PCA and ICA.

Science.gov (United States)

Martin-Clemente, Ruben; Zarzoso, Vicente

2017-03-01

Principal component analysis (PCA) based on L1-norm maximization is an emerging technique that has drawn growing interest in the signal processing and machine learning research communities, especially due to its robustness to outliers. The present work proves that L1-norm PCA can perform independent component analysis (ICA) under the whitening assumption. However, when the source probability distributions fulfil certain conditions, the L1-norm criterion needs to be minimized rather than maximized, which can be accomplished by simple modifications on existing optimal algorithms for L1-PCA. If the sources have symmetric distributions, we show in addition that L1-PCA is linked to kurtosis optimization. A number of numerical experiments illustrate the theoretical results and analyze the comparative performance of different algorithms for ICA via L1-PCA. Although our analysis is asymptotic in the sample size, this equivalence opens interesting new perspectives for performing ICA using optimal algorithms for L1-PCA with guaranteed global convergence while inheriting the increased robustness to outliers of the L1-norm criterion.

WE-G-207-06: 3D Fluoroscopic Image Generation From Patient-Specific 4DCBCT-Based Motion Models Derived From Physical Phantom and Clinical Patient Images

International Nuclear Information System (INIS)

Dhou, S; Cai, W; Hurwitz, M; Rottmann, J; Myronakis, M; Cifter, F; Berbeco, R; Lewis, J; Williams, C; Mishra, P; Ionascu, D

2015-01-01

Purpose: Respiratory-correlated cone-beam CT (4DCBCT) images acquired immediately prior to treatment have the potential to represent patient motion patterns and anatomy during treatment, including both intra- and inter-fractional changes. We develop a method to generate patient-specific motion models based on 4DCBCT images acquired with existing clinical equipment and used to generate time varying volumetric images (3D fluoroscopic images) representing motion during treatment delivery. Methods: Motion models are derived by deformably registering each 4DCBCT phase to a reference phase, and performing principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated by optimizing the resulting PCA coefficients iteratively through comparison of the cone-beam projections simulating kV treatment imaging and digitally reconstructed radiographs generated from the motion model. Patient and physical phantom datasets are used to evaluate the method in terms of tumor localization error compared to manually defined ground truth positions. Results: 4DCBCT-based motion models were derived and used to generate 3D fluoroscopic images at treatment time. For the patient datasets, the average tumor localization error and the 95th percentile were 1.57 and 3.13 respectively in subsets of four patient datasets. For the physical phantom datasets, the average tumor localization error and the 95th percentile were 1.14 and 2.78 respectively in two datasets. 4DCBCT motion models are shown to perform well in the context of generating 3D fluoroscopic images due to their ability to reproduce anatomical changes at treatment time. Conclusion: This study showed the feasibility of deriving 4DCBCT-based motion models and using them to generate 3D fluoroscopic images at treatment time in real clinical settings. 4DCBCT-based motion models were found to account for the 3D non-rigid motion of the patient anatomy during treatment and have the potential

4D cone beam CT-based dose assessment for SBRT lung cancer treatment

International Nuclear Information System (INIS)

Cai, Weixing; Dhou, Salam; Cifter, Fulya; Myronakis, Marios; Hurwitz, Martina H; Williams, Christopher L; Berbeco, Ross I; Seco, Joao; Lewis, John H

2016-01-01

The purpose of this research is to develop a 4DCBCT-based dose assessment method for calculating actual delivered dose for patients with significant respiratory motion or anatomical changes during the course of SBRT. To address the limitation of 4DCT-based dose assessment, we propose to calculate the delivered dose using time-varying (‘fluoroscopic’) 3D patient images generated from a 4DCBCT-based motion model. The method includes four steps: (1) before each treatment, 4DCBCT data is acquired with the patient in treatment position, based on which a patient-specific motion model is created using a principal components analysis algorithm. (2) During treatment, 2D time-varying kV projection images are continuously acquired, from which time-varying ‘fluoroscopic’ 3D images of the patient are reconstructed using the motion model. (3) Lateral truncation artifacts are corrected using planning 4DCT images. (4) The 3D dose distribution is computed for each timepoint in the set of 3D fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach is validated using six modified XCAT phantoms with lung tumors and different respiratory motions derived from patient data. The estimated doses are compared to that calculated using ground-truth XCAT phantoms. For each XCAT phantom, the calculated delivered tumor dose values generally follow the same trend as that of the ground truth and at most timepoints the difference is less than 5%. For the overall delivered dose, the normalized error of calculated 3D dose distribution is generally less than 3% and the tumor D95 error is less than 1.5%. XCAT phantom studies indicate the potential of the proposed method to accurately estimate 3D tumor dose distributions for SBRT lung treatment based on 4DCBCT imaging and motion modeling. Further research is necessary to investigate its performance for clinical patient data. (paper)

Quantification of heterogeneity in lung disease with image-based pulmonary function testing.

Science.gov (United States)

Stahr, Charlene S; Samarage, Chaminda R; Donnelley, Martin; Farrow, Nigel; Morgan, Kaye S; Zosky, Graeme; Boucher, Richard C; Siu, Karen K W; Mall, Marcus A; Parsons, David W; Dubsky, Stephen; Fouras, Andreas

2016-07-27

Computed tomography (CT) and spirometry are the mainstays of clinical pulmonary assessment. Spirometry is effort dependent and only provides a single global measure that is insensitive for regional disease, and as such, poor for capturing the early onset of lung disease, especially patchy disease such as cystic fibrosis lung disease. CT sensitively measures change in structure associated with advanced lung disease. However, obstructions in the peripheral airways and early onset of lung stiffening are often difficult to detect. Furthermore, CT imaging poses a radiation risk, particularly for young children, and dose reduction tends to result in reduced resolution. Here, we apply a series of lung tissue motion analyses, to achieve regional pulmonary function assessment in β-ENaC-overexpressing mice, a well-established model of lung disease. The expiratory time constants of regional airflows in the segmented airway tree were quantified as a measure of regional lung function. Our results showed marked heterogeneous lung function in β-ENaC-Tg mice compared to wild-type littermate controls; identified locations of airway obstruction, and quantified regions of bimodal airway resistance demonstrating lung compensation. These results demonstrate the applicability of regional lung function derived from lung motion as an effective alternative respiratory diagnostic tool.

Continuous Positive Airway Pressure for Motion Management in Stereotactic Body Radiation Therapy to the Lung: A Controlled Pilot Study

Energy Technology Data Exchange (ETDEWEB)

Goldstein, Jeffrey D. [Department of Radiation Oncology, Chaim Sheba Medical Center, Tel Hashomer, Tel Aviv (Israel); Lawrence, Yaacov R. [Department of Radiation Oncology, Chaim Sheba Medical Center, Tel Hashomer, Tel Aviv (Israel); Sackler School of Medicine, Tel Aviv University, Tel Aviv (Israel); Appel, Sarit; Landau, Efrat; Ben-David, Merav A.; Rabin, Tatiana; Benayun, Maoz; Dubinski, Sergey; Weizman, Noam; Alezra, Dror; Gnessin, Hila; Goldstein, Adam M.; Baidun, Khader [Department of Radiation Oncology, Chaim Sheba Medical Center, Tel Hashomer, Tel Aviv (Israel); Segel, Michael J.; Peled, Nir [Department of Pulmonary Medicine, Chaim Sheba Medical Center, Tel Hashomer, Tel Aviv (Israel); Sackler School of Medicine, Tel Aviv University, Tel Aviv (Israel); Symon, Zvi, E-mail: symonz@sheba.health.gov.il [Department of Radiation Oncology, Chaim Sheba Medical Center, Tel Hashomer, Tel Aviv (Israel); Sackler School of Medicine, Tel Aviv University, Tel Aviv (Israel)

2015-10-01

Objective: To determine the effect of continuous positive airway pressure (CPAP) on tumor motion, lung volume, and dose to critical organs in patients receiving stereotactic body radiation therapy (SBRT) for lung tumors. Methods and Materials: After institutional review board approval in December 2013, patients with primary or secondary lung tumors referred for SBRT underwent 4-dimensional computed tomographic simulation twice: with free breathing and with CPAP. Tumor excursion was calculated by subtracting the vector of the greatest dimension of the gross tumor volume (GTV) from the internal target volume (ITV). Volumetric and dosimetric determinations were compared with the Wilcoxon signed-rank test. CPAP was used during treatment if judged beneficial. Results: CPAP was tolerated well in 10 of the 11 patients enrolled. Ten patients with 18 lesions were evaluated. The use of CPAP decreased tumor excursion by 0.5 ± 0.8 cm, 0.4 ± 0.7 cm, and 0.6 ± 0.8 cm in the superior–inferior, right–left, and anterior–posterior planes, respectively (P≤.02). Relative to free breathing, the mean ITV reduction was 27% (95% confidence interval [CI] 16%-39%, P<.001). CPAP significantly augmented lung volume, with a mean absolute increase of 915 ± 432 cm{sup 3} and a relative increase of 32% (95% CI 21%-42%, P=.003), contributing to a 22% relative reduction (95% CI 13%-32%, P=.001) in mean lung dose. The use of CPAP was also associated with a relative reduction in mean heart dose by 29% (95% CI 23%-36%, P=.001). Conclusion: In this pilot study, CPAP significantly reduced lung tumor motion compared with free breathing. The smaller ITV, the planning target volume (PTV), and the increase in total lung volume associated with CPAP contributed to a reduction in lung and heart dose. CPAP was well tolerated, reproducible, and simple to implement in the treatment room and should be evaluated further as a novel strategy for motion management in radiation therapy.

Continuous Positive Airway Pressure for Motion Management in Stereotactic Body Radiation Therapy to the Lung: A Controlled Pilot Study

International Nuclear Information System (INIS)

Goldstein, Jeffrey D.; Lawrence, Yaacov R.; Appel, Sarit; Landau, Efrat; Ben-David, Merav A.; Rabin, Tatiana; Benayun, Maoz; Dubinski, Sergey; Weizman, Noam; Alezra, Dror; Gnessin, Hila; Goldstein, Adam M.; Baidun, Khader; Segel, Michael J.; Peled, Nir; Symon, Zvi

2015-01-01

Objective: To determine the effect of continuous positive airway pressure (CPAP) on tumor motion, lung volume, and dose to critical organs in patients receiving stereotactic body radiation therapy (SBRT) for lung tumors. Methods and Materials: After institutional review board approval in December 2013, patients with primary or secondary lung tumors referred for SBRT underwent 4-dimensional computed tomographic simulation twice: with free breathing and with CPAP. Tumor excursion was calculated by subtracting the vector of the greatest dimension of the gross tumor volume (GTV) from the internal target volume (ITV). Volumetric and dosimetric determinations were compared with the Wilcoxon signed-rank test. CPAP was used during treatment if judged beneficial. Results: CPAP was tolerated well in 10 of the 11 patients enrolled. Ten patients with 18 lesions were evaluated. The use of CPAP decreased tumor excursion by 0.5 ± 0.8 cm, 0.4 ± 0.7 cm, and 0.6 ± 0.8 cm in the superior–inferior, right–left, and anterior–posterior planes, respectively (P≤.02). Relative to free breathing, the mean ITV reduction was 27% (95% confidence interval [CI] 16%-39%, P<.001). CPAP significantly augmented lung volume, with a mean absolute increase of 915 ± 432 cm 3 and a relative increase of 32% (95% CI 21%-42%, P=.003), contributing to a 22% relative reduction (95% CI 13%-32%, P=.001) in mean lung dose. The use of CPAP was also associated with a relative reduction in mean heart dose by 29% (95% CI 23%-36%, P=.001). Conclusion: In this pilot study, CPAP significantly reduced lung tumor motion compared with free breathing. The smaller ITV, the planning target volume (PTV), and the increase in total lung volume associated with CPAP contributed to a reduction in lung and heart dose. CPAP was well tolerated, reproducible, and simple to implement in the treatment room and should be evaluated further as a novel strategy for motion management in radiation therapy

Craniocaudal Safety Margin Calculation Based on Interfractional Changes in Tumor Motion in Lung SBRT Assessed With an EPID in Cine Mode

International Nuclear Information System (INIS)

Ueda, Yoshihiro; Miyazaki, Masayoshi; Nishiyama, Kinji; Suzuki, Osamu; Tsujii, Katsutomo; Miyagi, Ken

2012-01-01

Purpose: To evaluate setup error and interfractional changes in tumor motion magnitude using an electric portal imaging device in cine mode (EPID cine) during the course of stereotactic body radiation therapy (SBRT) for non–small-cell lung cancer (NSCLC) and to calculate margins to compensate for these variations. Materials and Methods: Subjects were 28 patients with Stage I NSCLC who underwent SBRT. Respiratory-correlated four-dimensional computed tomography (4D-CT) at simulation was binned into 10 respiratory phases, which provided average intensity projection CT data sets (AIP). On 4D-CT, peak-to-peak motion of the tumor (M-4DCT) in the craniocaudal direction was assessed and the tumor center (mean tumor position [MTP]) of the AIP (MTP-4DCT) was determined. At treatment, the tumor on cone beam CT was registered to that on AIP for patient setup. During three sessions of irradiation, peak-to-peak motion of the tumor (M-cine) and the mean tumor position (MTP-cine) were obtained using EPID cine and in-house software. Based on changes in tumor motion magnitude (∆M) and patient setup error (∆MTP), defined as differences between M-4DCT and M-cine and between MTP-4DCT and MTP-cine, a margin to compensate for these variations was calculated with Stroom’s formula. Results: The means (±standard deviation: SD) of M-4DCT and M-cine were 3.1 (±3.4) and 4.0 (±3.6) mm, respectively. The means (±SD) of ∆M and ∆MTP were 0.9 (±1.3) and 0.2 (±2.4) mm, respectively. Internal target volume-planning target volume (ITV-PTV) margins to compensate for ∆M, ∆MTP, and both combined were 3.7, 5.2, and 6.4 mm, respectively. Conclusion: EPID cine is a useful modality for assessing interfractional variations of tumor motion. The ITV-PTV margins to compensate for these variations can be calculated.

Testing a Modified PCA-Based Sharpening Approach for Image Fusion

Directory of Open Access Journals (Sweden)

Jan Jelének

2016-09-01

Full Text Available Image data sharpening is a challenging field of remote sensing science, which has become more relevant as high spatial-resolution satellites and superspectral sensors have emerged. Although the spectral property is crucial for mineral mapping, spatial resolution is also important as it allows targeted minerals/rocks to be identified/interpreted in a spatial context. Therefore, improving the spatial context, while keeping the spectral property provided by the superspectral sensor, would bring great benefits for geological/mineralogical mapping especially in arid environments. In this paper, a new concept was tested using superspectral data (ASTER and high spatial-resolution panchromatic data (WorldView-2 for image fusion. A modified Principal Component Analysis (PCA-based sharpening method, which implements a histogram matching workflow that takes into account the real distribution of values, was employed to test whether the substitution of Principal Components (PC1–PC4 can bring a fused image which is spectrally more accurate. The new approach was compared to those most widely used—PCA sharpening and Gram–Schmidt sharpening (GS, both available in ENVI software (Version 5.2 and lower as well as to the standard approach—sharpening Landsat 8 multispectral bands (MUL using its own panchromatic (PAN band. The visual assessment and the spectral quality indicators proved that the spectral performance of the proposed sharpening approach employing PC1 and PC2 improve the performance of the PCA algorithm, moreover, comparable or better results are achieved compared to the GS method. It was shown that, when using the PC1, the visible-near infrared (VNIR part of the spectrum was preserved better, however, if the PC2 was used, the short-wave infrared (SWIR part was preserved better. Furthermore, this approach improved the output spectral quality when fusing image data from different sensors (e.g., ASTER and WorldView-2 while keeping the proper albedo

[Identification of varieties of cashmere by Vis/NIR spectroscopy technology based on PCA-SVM].

Science.gov (United States)

Wu, Gui-Fang; He, Yong

2009-06-01

One mixed algorithm was presented to discriminate cashmere varieties with principal component analysis (PCA) and support vector machine (SVM). Cashmere fiber has such characteristics as threadlike, softness, glossiness and high tensile strength. The quality characters and economic value of each breed of cashmere are very different. In order to safeguard the consumer's rights and guarantee the quality of cashmere product, quickly, efficiently and correctly identifying cashmere has significant meaning to the production and transaction of cashmere material. The present research adopts Vis/NIRS spectroscopy diffuse techniques to collect the spectral data of cashmere. The near infrared fingerprint of cashmere was acquired by principal component analysis (PCA), and support vector machine (SVM) methods were used to further identify the cashmere material. The result of PCA indicated that the score map made by the scores of PC1, PC2 and PC3 was used, and 10 principal components (PCs) were selected as the input of support vector machine (SVM) based on the reliabilities of PCs of 99.99%. One hundred cashmere samples were used for calibration and the remaining 75 cashmere samples were used for validation. A one-against-all multi-class SVM model was built, the capabilities of SVM with different kernel function were comparatively analyzed, and the result showed that SVM possessing with the Gaussian kernel function has the best identification capabilities with the accuracy of 100%. This research indicated that the data mining method of PCA-SVM has a good identification effect, and can work as a new method for rapid identification of cashmere material varieties.

MD-11 PCA - Research flight team photo

Science.gov (United States)

1995-01-01

On Aug. 30, 1995, a the McDonnell Douglas MD-11 transport aircraft landed equipped with a computer-assisted engine control system that has the potential to increase flight safety. In landings at NASA Dryden Flight Research Center, Edwards, California, on August 29 and 30, the aircraft demonstrated software used in the aircraft's flight control computer that essentially landed the MD-11 without a need for the pilot to manipulate the flight controls significantly. In partnership with McDonnell Douglas Aerospace (MDA), with Pratt & Whitney and Honeywell helping to design the software, NASA developed this propulsion-controlled aircraft (PCA) system following a series of incidents in which hydraulic failures resulted in the loss of flight controls. This new system enables a pilot to operate and land the aircraft safely when its normal, hydraulically-activated control surfaces are disabled. This August 29, 1995, photo shows the MD-11 team. Back row, left to right: Tim Dingen, MDA pilot; John Miller, MD-11 Chief pilot (MDA); Wayne Anselmo, MD-11 Flight Test Engineer (MDA); Gordon Fullerton, PCA Project pilot; Bill Burcham, PCA Chief Engineer; Rudey Duran, PCA Controls Engineer (MDA); John Feather, PCA Controls Engineer (MDA); Daryl Townsend, Crew Chief; Henry Hernandez, aircraft mechanic; Bob Baron, PCA Project Manager; Don Hermann, aircraft mechanic; Jerry Cousins, aircraft mechanic; Eric Petersen, PCA Manager (Honeywell); Trindel Maine, PCA Data Engineer; Jeff Kahler, PCA Software Engineer (Honeywell); Steve Goldthorpe, PCA Controls Engineer (MDA). Front row, left to right: Teresa Hass, Senior Project Management Analyst; Hollie Allingham (Aguilera), Senior Project Management Analyst; Taher Zeglum, PCA Data Engineer (MDA); Drew Pappas, PCA Project Manager (MDA); John Burken, PCA Control Engineer.

TH-CD-207A-07: Prediction of High Dimensional State Subject to Respiratory Motion: A Manifold Learning Approach

International Nuclear Information System (INIS)

Liu, W; Sawant, A; Ruan, D

2016-01-01

Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit more descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction

SBRT of lung tumours: Monte Carlo simulation with PENELOPE of dose distributions including respiratory motion and comparison with different treatment planning systems

Science.gov (United States)

Panettieri, Vanessa; Wennberg, Berit; Gagliardi, Giovanna; Amor Duch, Maria; Ginjaume, Mercè; Lax, Ingmar

2007-07-01

The purpose of this work was to simulate with the Monte Carlo (MC) code PENELOPE the dose distribution in lung tumours including breathing motion in stereotactic body radiation therapy (SBRT). Two phantoms were modelled to simulate a pentagonal cross section with chestwall (unit density), lung (density 0.3 g cm-3) and two spherical tumours (unit density) of diameters respectively of 2 cm and 5 cm. The phase-space files (PSF) of four different SBRT field sizes of 6 MV from a Varian accelerator were calculated and used as beam sources to obtain both dose profiles and dose-volume histograms (DVHs) in different volumes of interest. Dose distributions were simulated for five beams impinging on the phantom. The simulations were conducted both for the static case and including the influence of respiratory motion. To reproduce the effect of breathing motion different simulations were performed keeping the beam fixed and displacing the phantom geometry in chosen positions in the cranial and caudal and left-right directions. The final result was obtained by combining the different position with two motion patterns. The MC results were compared with those obtained with three commercial treatment planning systems (TPSs), two based on the pencil beam (PB) algorithm, the TMS-HELAX (Nucletron, Sweden) and Eclipse (Varian Medical System, Palo Alto, CA), and one based on the collapsed cone algorithm (CC), Pinnacle3 (Philips). Some calculations were also carried out with the analytical anisotropic algorithm (AAA) in the Eclipse system. All calculations with the TPSs were performed without simulated breathing motion, according to clinical practice. In order to compare all the TPSs and MC an absolute dose calibration in Gy/MU was performed. The analysis shows that the dose (Gy/MU) in the central part of the gross tumour volume (GTV) is calculated for both tumour sizes with an accuracy of 2-3% with PB and CC algorithms, compared to MC. At the periphery of the GTV the TPSs overestimate

TH-E-17A-10: Markerless Lung Tumor Tracking Based On Beams Eye View EPID Images

Energy Technology Data Exchange (ETDEWEB)

Chiu, T; Kearney, V; Liu, H; Jiang, L; Foster, R; Mao, W [UT Southwestern Medical Center, Dallas, Texas (United States); Rozario, T; Bereg, S [University of Texas at Dallas, Richardson, Texas (United States); Klash, S [Premier Cancer Centers, Dallas, TX (United States)

2014-06-15

Purpose: Dynamic tumor tracking or motion compensation techniques have proposed to modify beam delivery following lung tumor motion on the flight. Conventional treatment plan QA could be performed in advance since every delivery may be different. Markerless lung tumor tracking using beams eye view EPID images provides a best treatment evaluation mechanism. The purpose of this study is to improve the accuracy of the online markerless lung tumor motion tracking method. Methods: The lung tumor could be located on every frame of MV images during radiation therapy treatment by comparing with corresponding digitally reconstructed radiograph (DRR). A kV-MV CT corresponding curve is applied on planning kV CT to generate MV CT images for patients in order to enhance the similarity between DRRs and MV treatment images. This kV-MV CT corresponding curve was obtained by scanning a same CT electron density phantom by a kV CT scanner and MV scanner (Tomotherapy) or MV CBCT. Two sets of MV DRRs were then generated for tumor and anatomy without tumor as the references to tracking the tumor on beams eye view EPID images. Results: Phantom studies were performed on a Varian TrueBeam linac. MV treatment images were acquired continuously during each treatment beam delivery at 12 gantry angles by iTools. Markerless tumor tracking was applied with DRRs generated from simulated MVCT. Tumors were tracked on every frame of images and compared with expected positions based on programed phantom motion. It was found that the average tracking error were 2.3 mm. Conclusion: This algorithm is capable of detecting lung tumors at complicated environment without implanting markers. It should be noted that the CT data has a slice thickness of 3 mm. This shows the statistical accuracy is better than the spatial accuracy. This project has been supported by a Varian Research Grant.

2D-3D Face Recognition Method Basedon a Modified CCA-PCA Algorithm

Directory of Open Access Journals (Sweden)

Patrik Kamencay

2014-03-01

Full Text Available This paper presents a proposed methodology for face recognition based on an information theory approach to coding and decoding face images. In this paper, we propose a 2D-3D face-matching method based on a principal component analysis (PCA algorithm using canonical correlation analysis (CCA to learn the mapping between a 2D face image and 3D face data. This method makes it possible to match a 2D face image with enrolled 3D face data. Our proposed fusion algorithm is based on the PCA method, which is applied to extract base features. PCA feature-level fusion requires the extraction of different features from the source data before features are merged together. Experimental results on the TEXAS face image database have shown that the classification and recognition results based on the modified CCA-PCA method are superior to those based on the CCA method. Testing the 2D-3D face match results gave a recognition rate for the CCA method of a quite poor 55% while the modified CCA method based on PCA-level fusion achieved a very good recognition score of 85%.

Sparse PCA with Oracle Property.

Science.gov (United States)

Gu, Quanquan; Wang, Zhaoran; Liu, Han

In this paper, we study the estimation of the k -dimensional sparse principal subspace of covariance matrix Σ in the high-dimensional setting. We aim to recover the oracle principal subspace solution, i.e., the principal subspace estimator obtained assuming the true support is known a priori. To this end, we propose a family of estimators based on the semidefinite relaxation of sparse PCA with novel regularizations. In particular, under a weak assumption on the magnitude of the population projection matrix, one estimator within this family exactly recovers the true support with high probability, has exact rank- k , and attains a [Formula: see text] statistical rate of convergence with s being the subspace sparsity level and n the sample size. Compared to existing support recovery results for sparse PCA, our approach does not hinge on the spiked covariance model or the limited correlation condition. As a complement to the first estimator that enjoys the oracle property, we prove that, another estimator within the family achieves a sharper statistical rate of convergence than the standard semidefinite relaxation of sparse PCA, even when the previous assumption on the magnitude of the projection matrix is violated. We validate the theoretical results by numerical experiments on synthetic datasets.

Respiration-Correlated Image Guidance Is the Most Important Radiotherapy Motion Management Strategy for Most Lung Cancer Patients

International Nuclear Information System (INIS)

Korreman, Stine; Persson, Gitte; Nygaard, Ditte; Brink, Carsten; Juhler-Nøttrup, Trine

2012-01-01

Purpose: The purpose of this study was to quantify the effects of four-dimensional computed tomography (4DCT), 4D image guidance (4D-IG), and beam gating on calculated treatment field margins in a lung cancer patient population. Materials and Methods: Images were acquired from 46 lung cancer patients participating in four separate protocols at three institutions in Europe and the United States. Seven patients were imaged using fluoroscopy, and 39 patients were imaged using 4DCT. The magnitude of respiratory tumor motion was measured. The required treatment field margins were calculated using a statistical recipe (van Herk M, et al. Int J Radiat Oncol Biol Phys 2000;474:1121–1135), with magnitudes of all uncertainties, except respiratory peak-to-peak displacement, the same for all patients, taken from literature. Required margins for respiratory motion management were calculated using the residual respiratory tumor motion for each patient for various motion management strategies. Margin reductions for respiration management were calculated using 4DCT, 4D-IG, and gated beam delivery. Results: The median tumor motion magnitude was 4.4 mm for the 46 patients (range 0–29.3 mm). This value corresponded to required treatment field margins of 13.7 to 36.3 mm (median 14.4 mm). The use of 4DCT, 4D-IG, and beam gating required margins that were reduced by 0 to 13.9 mm (median 0.5 mm), 3 to 5.2 mm (median 5.1 mm), and 0 to 7 mm (median 0.2 mm), respectively, to a total of 8.5 to 12.4 mm (median 8.6 mm). Conclusion: A respiratory management strategy for lung cancer radiotherapy including planning on 4DCT scans and daily image guidance provides a potential reduction of 37% to 47% in treatment field margins. The 4D image guidance strategy was the most effective strategy for >85% of the patients.

Improved k-t PCA Algorithm Using Artificial Sparsity in Dynamic MRI.

Science.gov (United States)

Wang, Yiran; Chen, Zhifeng; Wang, Jing; Yuan, Lixia; Xia, Ling; Liu, Feng

2017-01-01

The k - t principal component analysis ( k - t PCA) is an effective approach for high spatiotemporal resolution dynamic magnetic resonance (MR) imaging. However, it suffers from larger residual aliasing artifacts and noise amplification when the reduction factor goes higher. To further enhance the performance of this technique, we propose a new method called sparse k - t PCA that combines the k - t PCA algorithm with an artificial sparsity constraint. It is a self-calibrated procedure that is based on the traditional k - t PCA method by further eliminating the reconstruction error derived from complex subtraction of the sampled k - t space from the original reconstructed k - t space. The proposed method is tested through both simulations and in vivo datasets with different reduction factors. Compared to the standard k - t PCA algorithm, the sparse k - t PCA can improve the normalized root-mean-square error performance and the accuracy of temporal resolution. It is thus useful for rapid dynamic MR imaging.

Lung tumor tracking in fluoroscopic video based on optical flow

International Nuclear Information System (INIS)

Xu Qianyi; Hamilton, Russell J.; Schowengerdt, Robert A.; Alexander, Brian; Jiang, Steve B.

2008-01-01

Respiratory gating and tumor tracking for dynamic multileaf collimator delivery require accurate and real-time localization of the lung tumor position during treatment. Deriving tumor position from external surrogates such as abdominal surface motion may have large uncertainties due to the intra- and interfraction variations of the correlation between the external surrogates and internal tumor motion. Implanted fiducial markers can be used to track tumors fluoroscopically in real time with sufficient accuracy. However, it may not be a practical procedure when implanting fiducials bronchoscopically. In this work, a method is presented to track the lung tumor mass or relevant anatomic features projected in fluoroscopic images without implanted fiducial markers based on an optical flow algorithm. The algorithm generates the centroid position of the tracked target and ignores shape changes of the tumor mass shadow. The tracking starts with a segmented tumor projection in an initial image frame. Then, the optical flow between this and all incoming frames acquired during treatment delivery is computed as initial estimations of tumor centroid displacements. The tumor contour in the initial frame is transferred to the incoming frames based on the average of the motion vectors, and its positions in the incoming frames are determined by fine-tuning the contour positions using a template matching algorithm with a small search range. The tracking results were validated by comparing with clinician determined contours on each frame. The position difference in 95% of the frames was found to be less than 1.4 pixels (∼0.7 mm) in the best case and 2.8 pixels (∼1.4 mm) in the worst case for the five patients studied.

ECG-derived respiration methods: adapted ICA and PCA.

Science.gov (United States)

Tiinanen, Suvi; Noponen, Kai; Tulppo, Mikko; Kiviniemi, Antti; Seppänen, Tapio

2015-05-01

Respiration is an important signal in early diagnostics, prediction, and treatment of several diseases. Moreover, a growing trend toward ambulatory measurements outside laboratory environments encourages developing indirect measurement methods such as ECG derived respiration (EDR). Recently, decomposition techniques like principal component analysis (PCA), and its nonlinear version, kernel PCA (KPCA), have been used to derive a surrogate respiration signal from single-channel ECG. In this paper, we propose an adapted independent component analysis (AICA) algorithm to obtain EDR signal, and extend the normal linear PCA technique based on the best principal component (PC) selection (APCA, adapted PCA) to improve its performance further. We also demonstrate that the usage of smoothing spline resampling and bandpass-filtering improve the performance of all EDR methods. Compared with other recent EDR methods using correlation coefficient and magnitude squared coherence, the proposed AICA and APCA yield a statistically significant improvement with correlations 0.84, 0.82, 0.76 and coherences 0.90, 0.91, 0.85 between reference respiration and AICA, APCA and KPCA, respectively. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Prostate cancer (PCa) risk variants and risk of fatal PCa in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium.

Science.gov (United States)

Shui, Irene M; Lindström, Sara; Kibel, Adam S; Berndt, Sonja I; Campa, Daniele; Gerke, Travis; Penney, Kathryn L; Albanes, Demetrius; Berg, Christine; Bueno-de-Mesquita, H Bas; Chanock, Stephen; Crawford, E David; Diver, W Ryan; Gapstur, Susan M; Gaziano, J Michael; Giles, Graham G; Henderson, Brian; Hoover, Robert; Johansson, Mattias; Le Marchand, Loic; Ma, Jing; Navarro, Carmen; Overvad, Kim; Schumacher, Fredrick R; Severi, Gianluca; Siddiq, Afshan; Stampfer, Meir; Stevens, Victoria L; Travis, Ruth C; Trichopoulos, Dimitrios; Vineis, Paolo; Mucci, Lorelei A; Yeager, Meredith; Giovannucci, Edward; Kraft, Peter

2014-06-01

Screening and diagnosis of prostate cancer (PCa) is hampered by an inability to predict who has the potential to develop fatal disease and who has indolent cancer. Studies have identified multiple genetic risk loci for PCa incidence, but it is unknown whether they could be used as biomarkers for PCa-specific mortality (PCSM). To examine the association of 47 established PCa risk single-nucleotide polymorphisms (SNPs) with PCSM. We included 10 487 men who had PCa and 11 024 controls, with a median follow-up of 8.3 yr, during which 1053 PCa deaths occurred. The main outcome was PCSM. The risk allele was defined as the allele associated with an increased risk for PCa in the literature. We used Cox proportional hazards regression to calculate the hazard ratios of each SNP with time to progression to PCSM after diagnosis. We also used logistic regression to calculate odds ratios for each risk SNP, comparing fatal PCa cases to controls. Among the cases, we found that 8 of the 47 SNPs were significantly associated (pPCa, but most did not differentiate between fatal and nonfatal PCa. Rs11672691 and rs10993994 were associated with both fatal and nonfatal PCa, while rs6465657, rs7127900, rs2735839, and rs13385191 were associated with nonfatal PCa only. Eight established risk loci were associated with progression to PCSM after diagnosis. Twenty-two SNPs were associated with fatal PCa incidence, but most did not differentiate between fatal and nonfatal PCa. The relatively small magnitudes of the associations do not translate well into risk prediction, but these findings merit further follow-up, because they may yield important clues about the complex biology of fatal PCa. In this report, we assessed whether established PCa risk variants could predict PCSM. We found eight risk variants associated with PCSM: One predicted an increased risk of PCSM, while seven were associated with decreased risk. Larger studies that focus on fatal PCa are needed to identify more markers that

Prostate-Specific Antigen (PSA) Screening and New Biomarkers for Prostate Cancer (PCa).

Science.gov (United States)

Stephan, Carsten; Rittenhouse, Harry; Hu, Xinhai; Cammann, Henning; Jung, Klaus

2014-04-01

PSA screening reduces PCa-mortality but the disadvantages overdiagnosis and overtreatment require multivariable risk-prediction tools to select appropriate treatment or active surveillance. This review explains the differences between the two largest screening trials and discusses the drawbacks of screening and its meta-analysisxs. The current American and European screening strategies are described. Nonetheless, PSA is one of the most widely used tumor markers and strongly correlates with the risk of harboring PCa. However, while PSA has limitations for PCa detection with its low specificity there are several potential biomarkers presented in this review with utility for PCa currently being studied. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved prostate health index (phi) shows improved specificity over percent free and total PSA. Another kallikrein panel, 4K, which includes KLK2 has recently shown promise in clinical research studies but has not yet undergone formal validation studies. In urine, prostate cancer gene 3 (PCA3) has also been validated and approved by the FDA for its utility to detect PCa. The potential correlation of PCA3 with cancer aggressiveness requires more clinical studies. The detection of the fusion of androgen-regulated genes with genes of the regulatory transcription factors in tissue of (~)50% of all PCa-patients is a milestone in PCa research. A combination of the urinary assays for TMPRSS2:ERG gene fusion and PCA3 shows an improved accuracy for PCa detection. Overall, the field of PCa biomarker discovery is very exciting and prospective.

SU-D-207A-07: The Effects of Inter-Cycle Respiratory Motion Variation On Dose Accumulation in Single Fraction MR-Guided SBRT Treatment of Renal Cell Carcinoma

Energy Technology Data Exchange (ETDEWEB)

Stemkens, B; Glitzner, M; Kontaxis, C; Prins, F; Crijns, SPM; Kerkmeijer, L; Lagendijk, J; Berg, CAT van den; Tijssen, RHN [Department of Radiotherapy, University Medical Center Utrecht, Utrecht (Netherlands); Denis de Senneville, B [Imaging Division, University Medical Center Utrecht, Utrecht (Netherlands); IMB, UMR 5251 CNRS/University of Bordeaux (France)

2016-06-15

Purpose: To assess the dose deposition in simulated single-fraction MR-Linac treatments of renal cell carcinoma, when inter-cycle respiratory motion variation is taken into account using online MRI. Methods: Three motion characterization methods, with increasing complexity, were compared to evaluate the effect of inter-cycle motion variation and drifts on the accumulated dose for an SBRT kidney MR-Linac treatment: 1) STATIC, in which static anatomy was assumed, 2) AVG-RESP, in which 4D-MRI phase-volumes were time-weighted, based on the respiratory phase and 3) PCA, in which 3D volumes were generated using a PCA-model, enabling the detection of inter-cycle variations and drifts. An experimental ITV-based kidney treatment was simulated in a 1.5T magnetic field on three volunteer datasets. For each volunteer a retrospectively sorted 4D-MRI (ten respiratory phases) and fast 2D cine-MR images (temporal resolution = 476ms) were acquired to simulate MR-imaging during radiation. For each method, the high spatio-temporal resolution 3D volumes were non-rigidly registered to obtain deformation vector fields (DVFs). Using the DVFs, pseudo-CTs (generated from the 4D-MRI) were deformed and the dose was accumulated for the entire treatment. The accuracies of all methods were independently determined using an additional, orthogonal 2D-MRI slice. Results: Motion was most accurately estimated using the PCA method, which correctly estimated drifts and inter-cycle variations (RMSE=3.2, 2.2, 1.1mm on average for STATIC, AVG-RESP and PCA, compared to the 2DMRI slice). Dose-volume parameters on the ITV showed moderate changes (D99=35.2, 32.5, 33.8Gy for STATIC, AVG-RESP and PCA). AVG-RESP showed distinct hot/cold spots outside the ITV margin, which were more distributed for the PCA scenario, since inter-cycle variations were not modeled by the AVG-RESP method. Conclusion: Dose differences were observed when inter-cycle variations were taken into account. The increased inter

Comparison of PCA and ICA based clutter reduction in GPR systems for anti-personal landmine detection

DEFF Research Database (Denmark)

Karlsen, Brian; Larsen, Jan; Sørensen, Helge Bjarup Dissing

2001-01-01

This paper presents statistical signal processing approaches for clutter reduction in stepped-frequency ground penetrating radar (SF-GPR) data. In particular, we suggest clutter/signal separation techniques based on principal and independent component analysis (PCA/ICA). The approaches...

Comparison of lung cancer cell lines representing four histopathological subtypes with gene expression profiling using quantitative real-time PCR

Directory of Open Access Journals (Sweden)

Kawaguchi Makoto

2010-01-01

Full Text Available Abstract Background Lung cancers are the most common type of human malignancy and are intractable. Lung cancers are generally classified into four histopathological subtypes: adenocarcinoma (AD, squamous cell carcinoma (SQ, large cell carcinoma (LC, and small cell carcinoma (SC. Molecular biological characterization of these subtypes has been performed mainly using DNA microarrays. In this study, we compared the gene expression profiles of these four subtypes using twelve human lung cancer cell lines and the more reliable quantitative real-time PCR (qPCR. Results We selected 100 genes from public DNA microarray data and examined them by DNA microarray analysis in eight test cell lines (A549, ABC-1, EBC-1, LK-2, LU65, LU99, STC 1, RERF-LC-MA and a normal control lung cell line (MRC-9. From this, we extracted 19 candidate genes. We quantified the expression of the 19 genes and a housekeeping gene, GAPDH, with qPCR, using the same eight cell lines plus four additional validation lung cancer cell lines (RERF-LC-MS, LC-1/sq, 86-2, and MS-1-L. Finally, we characterized the four subtypes of lung cancer cell lines using principal component analysis (PCA of gene expression profiling for 12 of the 19 genes (AMY2A, CDH1, FOXG1, IGSF3, ISL1, MALL, PLAU, RAB25, S100P, SLCO4A1, STMN1, and TGM2. The combined PCA and gene pathway analyses suggested that these genes were related to cell adhesion, growth, and invasion. S100P in AD cells and CDH1 in AD and SQ cells were identified as candidate markers of these lung cancer subtypes based on their upregulation and the results of PCA analysis. Immunohistochemistry for S100P and RAB25 was closely correlated to gene expression. Conclusions These results show that the four subtypes, represented by 12 lung cancer cell lines, were well characterized using qPCR and PCA for the 12 genes examined. Certain genes, in particular S100P and CDH1, may be especially important for distinguishing the different subtypes. Our results

A g-factor metric for k-t SENSE and k-t PCA based parallel imaging.

Science.gov (United States)

Binter, Christian; Ramb, Rebecca; Jung, Bernd; Kozerke, Sebastian

2016-02-01

To propose and validate a g-factor formalism for k-t SENSE, k-t PCA and related k-t methods for assessing SNR and temporal fidelity. An analytical gxf -factor formulation in the spatiotemporal frequency domain is derived, enabling assessment of noise and depiction fidelity in both the spatial and frequency domain. Using pseudoreplica analysis of cardiac cine data the gxf -factor description is validated and example data are used to analyze the performance of k-t methods for various parameter settings. Analytical gxf -factor maps were found to agree well with pseudoreplica analysis for 3x, 5x, and 7x k-t SENSE and k-t PCA. While k-t SENSE resulted in lower average gxf values (gx (avg) ) in static regions when compared with k-t PCA, k-t PCA yielded lower gx (avg) values in dynamic regions. Temporal transfer was better preserved with k-t PCA for increasing undersampling factors. The proposed gxf -factor and temporal transfer formalism allows assessing noise performance and temporal depiction fidelity of k-t methods including k-t SENSE and k-t PCA. The framework enables quantitative comparison of different k-t methods relative to frame-by-frame parallel imaging reconstruction. © 2015 Wiley Periodicals, Inc.

Reference geometry-based detection of (4D-)CT motion artifacts: a feasibility study

Science.gov (United States)

Werner, René; Gauer, Tobias

2015-03-01

Respiration-correlated computed tomography (4D or 3D+t CT) can be considered as standard of care in radiation therapy treatment planning for lung and liver lesions. The decision about an application of motion management devices and the estimation of patient-specific motion effects on the dose distribution relies on precise motion assessment in the planning 4D CT data { which is impeded in case of CT motion artifacts. The development of image-based/post-processing approaches to reduce motion artifacts would benefit from precise detection and localization of the artifacts. Simple slice-by-slice comparison of intensity values and threshold-based analysis of related metrics suffer from- depending on the threshold- high false-positive or -negative rates. In this work, we propose exploiting prior knowledge about `ideal' (= artifact free) reference geometries to stabilize metric-based artifact detection by transferring (multi-)atlas-based concepts to this specific task. Two variants are introduced and evaluated: (S1) analysis and comparison of warped atlas data obtained by repeated non-linear atlas-to-patient registration with different levels of regularization; (S2) direct analysis of vector field properties (divergence, curl magnitude) of the atlas-to-patient transformation. Feasibility of approaches (S1) and (S2) is evaluated by motion-phantom data and intra-subject experiments (four patients) as well as - adopting a multi-atlas strategy- inter-subject investigations (twelve patients involved). It is demonstrated that especially sorting/double structure artifacts can be precisely detected and localized by (S1). In contrast, (S2) suffers from high false positive rates.

Prostate-Specific Antigen (PSA) Screening and New Biomarkers for Prostate Cancer (PCa)

Science.gov (United States)

Rittenhouse, Harry; Hu, Xinhai; Cammann, Henning; Jung, Klaus

2014-01-01

Abstract PSA screening reduces PCa-mortality but the disadvantages overdiagnosis and overtreatment require multivariable risk-prediction tools to select appropriate treatment or active surveillance. This review explains the differences between the two largest screening trials and discusses the drawbacks of screening and its meta-analysisxs. The current American and European screening strategies are described. Nonetheless, PSA is one of the most widely used tumor markers and strongly correlates with the risk of harboring PCa. However, while PSA has limitations for PCa detection with its low specificity there are several potential biomarkers presented in this review with utility for PCa currently being studied. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved prostate health index (phi) shows improved specificity over percent free and total PSA. Another kallikrein panel, 4K, which includes KLK2 has recently shown promise in clinical research studies but has not yet undergone formal validation studies. In urine, prostate cancer gene 3 (PCA3) has also been validated and approved by the FDA for its utility to detect PCa. The potential correlation of PCA3 with cancer aggressiveness requires more clinical studies. The detection of the fusion of androgen-regulated genes with genes of the regulatory transcription factors in tissue of ~50% of all PCa-patients is a milestone in PCa research. A combination of the urinary assays for TMPRSS2:ERG gene fusion and PCA3 shows an improved accuracy for PCa detection. Overall, the field of PCa biomarker discovery is very exciting and prospective. PMID:27683457

Effect of intra-fraction motion on the accumulated dose for free-breathing MR-guided stereotactic body radiation therapy of renal-cell carcinoma

Science.gov (United States)

Stemkens, Bjorn; Glitzner, Markus; Kontaxis, Charis; de Senneville, Baudouin Denis; Prins, Fieke M.; Crijns, Sjoerd P. M.; Kerkmeijer, Linda G. W.; Lagendijk, Jan J. W.; van den Berg, Cornelis A. T.; Tijssen, Rob H. N.

2017-09-01

Stereotactic body radiation therapy (SBRT) has shown great promise in increasing local control rates for renal-cell carcinoma (RCC). Characterized by steep dose gradients and high fraction doses, these hypo-fractionated treatments are, however, prone to dosimetric errors as a result of variations in intra-fraction respiratory-induced motion, such as drifts and amplitude alterations. This may lead to significant variations in the deposited dose. This study aims to develop a method for calculating the accumulated dose for MRI-guided SBRT of RCC in the presence of intra-fraction respiratory variations and determine the effect of such variations on the deposited dose. For this, RCC SBRT treatments were simulated while the underlying anatomy was moving, based on motion information from three motion models with increasing complexity: (1) STATIC, in which static anatomy was assumed, (2) AVG-RESP, in which 4D-MRI phase-volumes were time-weighted, and (3) PCA, a method that generates 3D volumes with sufficient spatio-temporal resolution to capture respiration and intra-fraction variations. Five RCC patients and two volunteers were included and treatments delivery was simulated, using motion derived from subject-specific MR imaging. Motion was most accurately estimated using the PCA method with root-mean-squared errors of 2.7, 2.4, 1.0 mm for STATIC, AVG-RESP and PCA, respectively. The heterogeneous patient group demonstrated relatively large dosimetric differences between the STATIC and AVG-RESP, and the PCA reconstructed dose maps, with hotspots up to 40% of the D99 and an underdosed GTV in three out of the five patients. This shows the potential importance of including intra-fraction motion variations in dose calculations.

Real-time prediction of respiratory motion based on local regression methods

International Nuclear Information System (INIS)

Ruan, D; Fessler, J A; Balter, J M

2007-01-01

Recent developments in modulation techniques enable conformal delivery of radiation doses to small, localized target volumes. One of the challenges in using these techniques is real-time tracking and predicting target motion, which is necessary to accommodate system latencies. For image-guided-radiotherapy systems, it is also desirable to minimize sampling rates to reduce imaging dose. This study focuses on predicting respiratory motion, which can significantly affect lung tumours. Predicting respiratory motion in real-time is challenging, due to the complexity of breathing patterns and the many sources of variability. We propose a prediction method based on local regression. There are three major ingredients of this approach: (1) forming an augmented state space to capture system dynamics, (2) local regression in the augmented space to train the predictor from previous observation data using semi-periodicity of respiratory motion, (3) local weighting adjustment to incorporate fading temporal correlations. To evaluate prediction accuracy, we computed the root mean square error between predicted tumor motion and its observed location for ten patients. For comparison, we also investigated commonly used predictive methods, namely linear prediction, neural networks and Kalman filtering to the same data. The proposed method reduced the prediction error for all imaging rates and latency lengths, particularly for long prediction lengths

4D-MRI analysis of lung tumor motion in patients with hemidiaphragmatic paralysis

International Nuclear Information System (INIS)

Dinkel, Julien; Hintze, Christian; Tetzlaff, Ralf; Huber, Peter E.; Herfarth, Klaus; Debus, Juergen; Kauczor, Hans U.; Thieke, Christian

2009-01-01

Purpose: To investigate the complex breathing patterns in patients with hemidiaphragmatic paralysis due to malignant infiltration using four-dimensional magnetic resonance imaging (4D-MRI). Patients and methods: Seven patients with bronchial carcinoma infiltrating the phrenic nerve were examined using 1.5 T MRI. The motion of the tumor and of both hemi-diaphragms were measured on dynamic 2D TrueFISP and 4D FLASH MRI sequences. Results: For each patient, 3-6 breathing cycles were recorded. The respiratory-induced mean cranio-caudal displacement of the tumor was 6.6 mm (±2.8 SD). The mean displacement anterior-posterior was 7.4 mm (±2.6), while right-left movement was about 7.4 mm (±4.5). The mediastinum moved sidewards during inspiration, realizing a 'mediastinal shift'. The paralyzed hemidiaphragm and the tumor showed a paradox motion during respiration in five patients. In two patients, the affected hemidiaphragm had a regular, however minimal and asynchronous motion during respiration. Respiratory variability of both tumor and diaphragm motions was about 20% although patients were instructed to breath normally. The findings showed significant differences compared to breathing patterns of patients without diaphragm dysfunction. Conclusion: 4D-MRI is a promising tool to analyze complex breathing patterns in patients with lung tumors. It should be considered for use in planning of radiotherapy to account for individual tumor motion.

Tensile properties of unirradiated path A PCA

International Nuclear Information System (INIS)

Braski, D.N.; Maziasz, P.J.

1983-01-01

The tensile properties of PCA in the Al (solution annealed), A3 (25%-cold worked), and B2 (aged, cold worked, and reaged) conditions were determined from room temperature to 600 0 C. The tensile behavior of PCA-A1 and -A3 was generally similar to that of titanium-modified type 316 stainless steel with similar microstructures. The PCA-B2 was weaker than PCA-A3, especially above 500 0 C, but demonstrated slightly better ducility

Motion monitoring during a course of lung radiotherapy with anchored electromagnetic transponders. Quantification of inter- and intrafraction motion and variability of relative transponder positions

Energy Technology Data Exchange (ETDEWEB)

Schmitt, Daniela [German Cancer Research Center (DKFZ), Division of Medical Physics in Radiation Oncology, Heidelberg (Germany); National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg (Germany); Heidelberg University Hospital, Department of Radiation Oncology, Heidelberg (Germany); Nill, Simeon; Oelfke, Uwe [German Cancer Research Center (DKFZ), Division of Medical Physics in Radiation Oncology, Heidelberg (Germany); National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg (Germany); The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Joint Department of Physics, London (United Kingdom); Roeder, Falk [German Cancer Research Center (DKFZ), Clinical Cooperation Unit Molecular Radiooncology, Heidelberg (Germany); University of Munich (LMU), Department of Radiation Oncology, Munich (Germany); Gompelmann, Daniela; Herth, Felix [University of Heidelberg, Pneumology and Critical Care Medicine, Thoraxklinik, Heidelberg (Germany); German Center for Lung Research, Translational Lung Research Center Heidelberg (TLRC), Heidelberg (Germany)

2017-10-15

Anchored electromagnetic transponders for tumor motion monitoring during lung radiotherapy were clinically evaluated. First, intrafractional motion patterns were analyzed as well as their interfractional variations. Second, intra- and interfractional changes of the geometric transponder positions were investigated. Intrafractional motion data from 7 patients with an upper or middle lobe tumor and three implanted transponders each was used to calculate breathing amplitudes, overall motion amount and motion midlines in three mutual perpendicular directions and three-dimensionally (3D) for 162 fractions. For 6 patients intra- and interfractional variations in transponder distances and in the size of the triangle defined by the transponder locations over the treatment course were determined. Mean 3D values of all fractions were up to 4.0, 4.6 and 3.4 mm per patient for amplitude, overall motion amount and midline deviation, respectively. Intrafractional transponder distances varied with standard deviations up to 3.2 mm, while a maximal triangle shrinkage of 36.5% over 39 days was observed. Electromagnetic real-time motion monitoring was feasible for all patients. Detected respiratory motion was on average modest in this small cohort without lower lobe tumors, but changes in motion midline were of the same size as the amplitudes and greater midline motion can be observed in some fractions. Intra- and interfractional variations of the geometric transponder positions can be large, so for reliable motion management correlation between transponder and tumor motion needs to be evaluated per patient. (orig.) [German] Verankerte, elektromagnetische Transponder fuer die Bewegungserkennung des Tumors waehrend der Strahlentherapie der Lunge wurden klinisch evaluiert. Dafuer wurden intrafraktionelle Bewegungsmuster und ihre interfraktionellen Variationen analysiert und intra- und interfraktionelle Veraenderungen der geometrischen Transponderpositionen untersucht. Intrafraktionelle

A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

Directory of Open Access Journals (Sweden)

Fernando Sánchez Lasheras

2015-03-01

Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

PCA safety data review after clinical decision support and smart pump technology implementation.

Science.gov (United States)

Prewitt, Judy; Schneider, Susan; Horvath, Monica; Hammond, Julia; Jackson, Jason; Ginsberg, Brian

2013-06-01

Medication errors account for 20% of medical errors in the United States with the largest risk at prescribing and administration. Analgesics or opioids are frequently used medications that can be associated with patient harm when prescribed or administered improperly. In an effort to decrease medication errors, Duke University Hospital implemented clinical decision support via computer provider order entry (CPOE) and "smart pump" technology, 2/2008, with the goal to decrease patient-controlled analgesia (PCA) adverse events. This project evaluated PCA safety events, reviewing voluntary report system and adverse drug events via surveillance (ADE-S), on intermediate and step-down units preimplementation and postimplementation of clinical decision support via CPOE and PCA smart pumps for the prescribing and administration of opioids therapy in the adult patient requiring analgesia for acute pain. Voluntary report system and ADE-S PCA events decreased based upon 1000 PCA days; ADE-S PCA events per 1000 PCA days decreased 22%, from 5.3 (pre) to 4.2 (post) (P = 0.09). Voluntary report system events decreased 72%, from 2.4/1000 PCA days (pre) to 0.66/1000 PCA days (post) and was statistically significant (P PCA events between time periods in both the ADE-S and voluntary report system data, thus supporting the recommendation of clinical decision support via CPOE and PCA smart pump technology.

Synthesis and bioactivities of Phenazine-1-carboxylic acid derivatives based on the modification of PCA carboxyl group.

Science.gov (United States)

Xiong, Zhipeng; Niu, Junfan; Liu, Hao; Xu, Zhihong; Li, Junkai; Wu, Qinglai

2017-05-01

Phenazine-1-carboxylic acid (PCA) as a natural product widely exists in microbial metabolites of Pseudomonads and Streptomycetes and has been registered for the fungicide against rice sheath blight in China. To find higher fungicidal activities compounds and study the effects on fungicidal activities after changing the carboxyl group of PCA, we synthesized a series of PCA derivatives by modifying the carboxyl group of PCA and their structures were confirmed by 1 H NMR and HRMS. Most compounds exhibited significant fungicidal activities in vitro. In particular, compound 6 exhibited inhibition effect against Rhizoctonia solani with EC 50 values of 4.35mg/L and compound 3b exhibited effect against Fusarium graminearum with EC 50 values of 8.30mg/L, compared to the positive control PCA with its EC 50 values of 7.88mg/L (Rhizoctonia solani) and 127.28mg/L (Fusarium graminearum), respectively. The results indicated that the carboxyl group of PCA could be modified to be amide group, acylhydrazine group, ester group, methyl, hydroxymethyl, chloromethyl and ether group etc. And appropriate modifications on carboxyl group of PCA were useful to extend the fungicidal scope. Copyright © 2017 Elsevier Ltd. All rights reserved.

PCaPAC 2006 Proceedings

Energy Technology Data Exchange (ETDEWEB)

Pavel Chevtsov; Matthew Bickley (Eds.)

2007-03-30

The 6-th international PCaPAC (Personal Computers and Particle Accelerator Controls) workshop was held at Jefferson Lab, Newport News, Virginia, from October 24-27, 2006. The main objectives of the conference were to discuss the most important issues of the use of PCs and modern IT technologies for controls of accelerators and to give scientists, engineers, and technicians a forum to exchange the ideas on control problems and their solutions. The workshop consisted of plenary sessions and poster sessions. No parallel sessions were held.Totally, more than seventy oral and poster presentations as well as tutorials were made during the conference, on the basis of which about fifty papers were submitted by the authors and included in this publication. This printed version of the PCaPAC 2006 Proceedings is published at Jefferson Lab according to the decision of the PCaPAC International Program Committee of October 26, 2006.

Research on distributed heterogeneous data PCA algorithm based on cloud platform

Science.gov (United States)

Zhang, Jin; Huang, Gang

2018-05-01

Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

Elevated YKL40 is associated with advanced prostate cancer (PCa) and positively regulates invasion and migration of PCa cells.

Science.gov (United States)

Jeet, Varinder; Tevz, Gregor; Lehman, Melanie; Hollier, Brett; Nelson, Colleen

2014-10-01

Chitinase 3-like 1 (CHI3L1 or YKL40) is a secreted glycoprotein highly expressed in tumours from patients with advanced stage cancers, including prostate cancer (PCa). The exact function of YKL40 is poorly understood, but it has been shown to play an important role in promoting tumour angiogenesis and metastasis. The therapeutic value and biological function of YKL40 are unknown in PCa. The objective of this study was to examine the expression and function of YKL40 in PCa. Gene expression analysis demonstrated that YKL40 was highly expressed in metastatic PCa cells when compared with less invasive and normal prostate epithelial cell lines. In addition, the expression was primarily limited to androgen receptor-positive cell lines. Evaluation of YKL40 tissue expression in PCa patients showed a progressive increase in patients with aggressive disease when compared with those with less aggressive cancers and normal controls. Treatment of LNCaP and C4-2B cells with androgens increased YKL40 expression, whereas treatment with an anti-androgen agent decreased the gene expression of YKL40 in androgen-sensitive LNCaP cells. Furthermore, knockdown of YKL40 significantly decreased invasion and migration of PCa cells, whereas overexpression rendered them more invasive and migratory, which was commensurate with an enhancement in the anchorage-independent growth of cells. To our knowledge, this study characterises the role of YKL40 for the first time in PCa. Together, these results suggest that YKL40 plays an important role in PCa progression and thus inhibition of YKL40 may be a potential therapeutic strategy for the treatment of PCa. © 2014 The authors.

Low-Resolution Tactile Image Recognition for Automated Robotic Assembly Using Kernel PCA-Based Feature Fusion and Multiple Kernel Learning-Based Support Vector Machine

Directory of Open Access Journals (Sweden)

Yi-Hung Liu

2014-01-01

Full Text Available In this paper, we propose a robust tactile sensing image recognition scheme for automatic robotic assembly. First, an image reprocessing procedure is designed to enhance the contrast of the tactile image. In the second layer, geometric features and Fourier descriptors are extracted from the image. Then, kernel principal component analysis (kernel PCA is applied to transform the features into ones with better discriminating ability, which is the kernel PCA-based feature fusion. The transformed features are fed into the third layer for classification. In this paper, we design a classifier by combining the multiple kernel learning (MKL algorithm and support vector machine (SVM. We also design and implement a tactile sensing array consisting of 10-by-10 sensing elements. Experimental results, carried out on real tactile images acquired by the designed tactile sensing array, show that the kernel PCA-based feature fusion can significantly improve the discriminating performance of the geometric features and Fourier descriptors. Also, the designed MKL-SVM outperforms the regular SVM in terms of recognition accuracy. The proposed recognition scheme is able to achieve a high recognition rate of over 85% for the classification of 12 commonly used metal parts in industrial applications.

EEG frequency PCA in EEG-ERP dynamics.

Science.gov (United States)

Barry, Robert J; De Blasio, Frances M

2018-05-01

Principal components analysis (PCA) has long been used to decompose the ERP into components, and these mathematical entities are increasingly accepted as meaningful and useful representatives of the electrophysiological components constituting the ERP. A similar expansion appears to be beginning in regard to decomposition of the EEG amplitude spectrum into frequency components via frequency PCA. However, to date, there has been no exploration of the brain's dynamic EEG-ERP linkages using PCA decomposition to assess components in each measure. Here, we recorded intrinsic EEG in both eyes-closed and eyes-open resting conditions, followed by an equiprobable go/no-go task. Frequency PCA of the EEG, including the nontask resting and within-task prestimulus periods, found seven frequency components within the delta to beta range. These differentially predicted PCA-derived go and no-go N1 and P3 ERP components. This demonstration suggests that it may be beneficial in future brain dynamics studies to implement PCA for the derivation of data-driven components from both the ERP and EEG. © 2017 Society for Psychophysiological Research.

SU-G-BRA-04: Simulation of Errors in Maximal Intensity Projection (MIP)-Based Lung Tumor Internal Target Volumes (ITV) Using Real-Time 2D MRI and Deformable Image Registration Based Lung Tumor Tracking

Energy Technology Data Exchange (ETDEWEB)

Thomas, D; Kishan, A; Santhanam, A; Min, Y; O’Connell, D; Lamb, J; Cao, M; Agazaryan, N; Yang, Y; Lee, P; Low, D [University of California, Los Angeles, Ca (United States)

2016-06-15

Purpose: To evaluate the effect of inter- and intra-fractional tumor motion on the error in four-dimensional computed tomography (4DCT) maximal intensity projection (MIP)–based lung tumor internal target volumes (ITV), using deformable image registration of real-time 2D-sagital cine-mode MRI acquired during lung SBRT treatments. Methods: Five lung tumor patients underwent free breathing SBRT treatment on the ViewRay, with dose prescribed to PTV (4DCT MIP-based ITV+3–6mm margin). Sagittal slice cine-MR images (3.5×3.5mm pixels) were acquired through the center of the tumor at 4 frames per second throughout the treatments (3–4 fractions of 21–32 minutes duration). Tumor GTVs were contoured on the first frame of the cine and tracked throughout the treatment using off-line optical-flow based deformable registration implemented on a GPU cluster. Pseudo-4DCT MIP-based ITVs were generated from MIPs of the deformed GTV contours limited to short segments of image data. All possible pseudo-4DCT MIP-based ITV volumes were generated with 1s resolution and compared to the ITV volume of the entire treatment course. Varying pseudo-4DCT durations from 10-50s were analyzed. Results: Tumors were covered in their entirety by PTV in the patients analysed here. However, pseudo-4DCT based ITV volumes were observed that were as small as 29% of the entire treatment-ITV, depending on breathing irregularity and the duration of pseudo-4DCT. With an increase in duration of pseudo-4DCT from 10–50s the minimum volume acquired from 95% of all pseudo-4DCTs increased from 62%–81% of the treatment ITV. Conclusion: A 4DCT MIP-based ITV offers a ‘snap-shot’ of breathing motion for the brief period of time the tumor is imaged on a specific day. Real time MRI over prolonged periods of time and over multiple treatment fractions shows that the accuracy of this snap-shot varies according to inter- and intra-fractional tumor motion. Further work is required to investigate the dosimetric

SU-G-BRA-04: Simulation of Errors in Maximal Intensity Projection (MIP)-Based Lung Tumor Internal Target Volumes (ITV) Using Real-Time 2D MRI and Deformable Image Registration Based Lung Tumor Tracking

International Nuclear Information System (INIS)

Thomas, D; Kishan, A; Santhanam, A; Min, Y; O’Connell, D; Lamb, J; Cao, M; Agazaryan, N; Yang, Y; Lee, P; Low, D

2016-01-01

Purpose: To evaluate the effect of inter- and intra-fractional tumor motion on the error in four-dimensional computed tomography (4DCT) maximal intensity projection (MIP)–based lung tumor internal target volumes (ITV), using deformable image registration of real-time 2D-sagital cine-mode MRI acquired during lung SBRT treatments. Methods: Five lung tumor patients underwent free breathing SBRT treatment on the ViewRay, with dose prescribed to PTV (4DCT MIP-based ITV+3–6mm margin). Sagittal slice cine-MR images (3.5×3.5mm pixels) were acquired through the center of the tumor at 4 frames per second throughout the treatments (3–4 fractions of 21–32 minutes duration). Tumor GTVs were contoured on the first frame of the cine and tracked throughout the treatment using off-line optical-flow based deformable registration implemented on a GPU cluster. Pseudo-4DCT MIP-based ITVs were generated from MIPs of the deformed GTV contours limited to short segments of image data. All possible pseudo-4DCT MIP-based ITV volumes were generated with 1s resolution and compared to the ITV volume of the entire treatment course. Varying pseudo-4DCT durations from 10-50s were analyzed. Results: Tumors were covered in their entirety by PTV in the patients analysed here. However, pseudo-4DCT based ITV volumes were observed that were as small as 29% of the entire treatment-ITV, depending on breathing irregularity and the duration of pseudo-4DCT. With an increase in duration of pseudo-4DCT from 10–50s the minimum volume acquired from 95% of all pseudo-4DCTs increased from 62%–81% of the treatment ITV. Conclusion: A 4DCT MIP-based ITV offers a ‘snap-shot’ of breathing motion for the brief period of time the tumor is imaged on a specific day. Real time MRI over prolonged periods of time and over multiple treatment fractions shows that the accuracy of this snap-shot varies according to inter- and intra-fractional tumor motion. Further work is required to investigate the dosimetric

PCA as a practical indicator of OPLS-DA model reliability.

Science.gov (United States)

Worley, Bradley; Powers, Robert

Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that provide insights into separations between experimental groups based on high-dimensional spectral measurements from NMR, MS or other analytical instrumentation. However, when used without validation, these tools may lead investigators to statistically unreliable conclusions. This danger is especially real for Partial Least Squares (PLS) and OPLS, which aggressively force separations between experimental groups. As a result, OPLS-DA is often used as an alternative method when PCA fails to expose group separation, but this practice is highly dangerous. Without rigorous validation, OPLS-DA can easily yield statistically unreliable group separation. A Monte Carlo analysis of PCA group separations and OPLS-DA cross-validation metrics was performed on NMR datasets with statistically significant separations in scores-space. A linearly increasing amount of Gaussian noise was added to each data matrix followed by the construction and validation of PCA and OPLS-DA models. With increasing added noise, the PCA scores-space distance between groups rapidly decreased and the OPLS-DA cross-validation statistics simultaneously deteriorated. A decrease in correlation between the estimated loadings (added noise) and the true (original) loadings was also observed. While the validity of the OPLS-DA model diminished with increasing added noise, the group separation in scores-space remained basically unaffected. Supported by the results of Monte Carlo analyses of PCA group separations and OPLS-DA cross-validation metrics, we provide practical guidelines and cross-validatory recommendations for reliable inference from PCA and OPLS-DA models.

Global Clustering Quality Coefficient Assessing the Efficiency of PCA Class Assignment

Directory of Open Access Journals (Sweden)

Mirela Praisler

2014-01-01

Full Text Available An essential factor influencing the efficiency of the predictive models built with principal component analysis (PCA is the quality of the data clustering revealed by the score plots. The sensitivity and selectivity of the class assignment are strongly influenced by the relative position of the clusters and by their dispersion. We are proposing a set of indicators inspired from analytical geometry that may be used for an objective quantitative assessment of the data clustering quality as well as a global clustering quality coefficient (GCQC that is a measure of the overall predictive power of the PCA models. The use of these indicators for evaluating the efficiency of the PCA class assignment is illustrated by a comparative study performed for the identification of the preprocessing function that is generating the most efficient PCA system screening for amphetamines based on their GC-FTIR spectra. The GCQC ranking of the tested feature weights is explained based on estimated density distributions and validated by using quadratic discriminant analysis (QDA.

Radical stereotactic radiosurgery with real-time tumor motion tracking in the treatment of small peripheral lung tumors

Directory of Open Access Journals (Sweden)

Chang Thomas

2007-10-01

Full Text Available Abstract Background Recent developments in radiotherapeutic technology have resulted in a new approach to treating patients with localized lung cancer. We report preliminary clinical outcomes using stereotactic radiosurgery with real-time tumor motion tracking to treat small peripheral lung tumors. Methods Eligible patients were treated over a 24-month period and followed for a minimum of 6 months. Fiducials (3–5 were placed in or near tumors under CT-guidance. Non-isocentric treatment plans with 5-mm margins were generated. Patients received 45–60 Gy in 3 equal fractions delivered in less than 2 weeks. CT imaging and routine pulmonary function tests were completed at 3, 6, 12, 18, 24 and 30 months. Results Twenty-four consecutive patients were treated, 15 with stage I lung cancer and 9 with single lung metastases. Pneumothorax was a complication of fiducial placement in 7 patients, requiring tube thoracostomy in 4. All patients completed radiation treatment with minimal discomfort, few acute side effects and no procedure-related mortalities. Following treatment transient chest wall discomfort, typically lasting several weeks, developed in 7 of 11 patients with lesions within 5 mm of the pleura. Grade III pneumonitis was seen in 2 patients, one with prior conventional thoracic irradiation and the other treated with concurrent Gefitinib. A small statistically significant decline in the mean % predicted DLCO was observed at 6 and 12 months. All tumors responded to treatment at 3 months and local failure was seen in only 2 single metastases. There have been no regional lymph node recurrences. At a median follow-up of 12 months, the crude survival rate is 83%, with 3 deaths due to co-morbidities and 1 secondary to metastatic disease. Conclusion Radical stereotactic radiosurgery with real-time tumor motion tracking is a promising well-tolerated treatment option for small peripheral lung tumors.

Dynamic simulation of motion effects in IMAT lung SBRT.

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Zou, Wei; Yin, Lingshu; Shen, Jiajian; Corradetti, Michael N; Kirk, Maura; Munbodh, Reshma; Fang, Penny; Jabbour, Salma K; Simone, Charles B; Yue, Ning J; Rengan, Ramesh; Teo, Boon-Keng Kevin

2014-11-01

Intensity modulated arc therapy (IMAT) has been widely adopted for Stereotactic Body Radiotherapy (SBRT) for lung cancer. While treatment dose is optimized and calculated on a static Computed Tomography (CT) image, the effect of the interplay between the target and linac multi-leaf collimator (MLC) motion is not well described and may result in deviations between delivered and planned dose. In this study, we investigated the dosimetric consequences of the inter-play effect on target and organs at risk (OAR) by simulating dynamic dose delivery using dynamic CT datasets. Fifteen stage I non-small cell lung cancer (NSCLC) patients with greater than 10 mm tumor motion treated with SBRT in 4 fractions to a dose of 50 Gy were retrospectively analyzed for this study. Each IMAT plan was initially optimized using two arcs. Simulated dynamic delivery was performed by associating the MLC leaf position, gantry angle and delivered beam monitor units (MUs) for each control point with different respiratory phases of the 4D-CT using machine delivery log files containing time stamps of the control points. Dose maps associated with each phase of the 4D-CT dose were calculated in the treatment planning system and accumulated using deformable image registration onto the exhale phase of the 4D-CT. The original IMAT plans were recalculated on the exhale phase of the CT for comparison with the dynamic simulation. The dose coverage of the PTV showed negligible variation between the static and dynamic simulation. There was less than 1.5% difference in PTV V95% and V90%. The average inter-fraction and cumulative dosimetric effects among all the patients were less than 0.5% for PTV V95% and V90% coverage and 0.8 Gy for the OARs. However, in patients where target is close to the organs, large variations were observed on great vessels and bronchus for as much as 4.9 Gy and 7.8 Gy. Limited variation in target dose coverage and OAR constraints were seen for each SBRT fraction as well as over all

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.

Identification of an IL-1-induced gene expression pattern in AR+ PCa cells that mimics the molecular phenotype of AR- PCa cells.

Science.gov (United States)

Thomas-Jardin, Shayna E; Kanchwala, Mohammed S; Jacob, Joan; Merchant, Sana; Meade, Rachel K; Gahnim, Nagham M; Nawas, Afshan F; Xing, Chao; Delk, Nikki A

2018-06-01

In immunosurveillance, bone-derived immune cells infiltrate the tumor and secrete inflammatory cytokines to destroy cancer cells. However, cancer cells have evolved mechanisms to usurp inflammatory cytokines to promote tumor progression. In particular, the inflammatory cytokine, interleukin-1 (IL-1), is elevated in prostate cancer (PCa) patient tissue and serum, and promotes PCa bone metastasis. IL-1 also represses androgen receptor (AR) accumulation and activity in PCa cells, yet the cells remain viable and tumorigenic; suggesting that IL-1 may also contribute to AR-targeted therapy resistance. Furthermore, IL-1 and AR protein levels negatively correlate in PCa tumor cells. Taken together, we hypothesize that IL-1 reprograms AR positive (AR + ) PCa cells into AR negative (AR - ) PCa cells that co-opt IL-1 signaling to ensure AR-independent survival and tumor progression in the inflammatory tumor microenvironment. LNCaP and PC3 PCa cells were treated with IL-1β or HS-5 bone marrow stromal cell (BMSC) conditioned medium and analyzed by RNA sequencing and RT-QPCR. To verify genes identified by RNA sequencing, LNCaP, MDA-PCa-2b, PC3, and DU145 PCa cell lines were treated with the IL-1 family members, IL-1α or IL-1β, or exposed to HS-5 BMSC in the presence or absence of Interleukin-1 Receptor Antagonist (IL-1RA). Treated cells were analyzed by western blot and/or RT-QPCR. Comparative analysis of sequencing data from the AR + LNCaP PCa cell line versus the AR - PC3 PCa cell line reveals an IL-1-conferred gene suite in LNCaP cells that is constitutive in PC3 cells. Bioinformatics analysis of the IL-1 regulated gene suite revealed that inflammatory and immune response pathways are primarily elicited; likely facilitating PCa cell survival and tumorigenicity in an inflammatory tumor microenvironment. Our data supports that IL-1 reprograms AR + PCa cells to mimic AR - PCa gene expression patterns that favor AR-targeted treatment resistance and cell survival. © 2018 Wiley

Can we use PCA to detect small signals in noisy data?

Science.gov (United States)

Spiegelberg, Jakob; Rusz, Ján

2017-01-01

Principal component analysis (PCA) is among the most commonly applied dimension reduction techniques suitable to denoise data. Focusing on its limitations to detect low variance signals in noisy data, we discuss how statistical and systematical errors occur in PCA reconstructed data as a function of the size of the data set, which extends the work of Lichtert and Verbeeck, (2013) [16]. Particular attention is directed towards the estimation of bias introduced by PCA and its influence on experiment design. Aiming at the denoising of large matrices, nullspace based denoising (NBD) is introduced. Copyright © 2016 Elsevier B.V. All rights reserved.

Radiotherapy of tumors under respiratory motion. Estimation of the motional velocity field and dose accumulation based on 4D image data; Strahlentherapie atmungsbewegter Tumoren. Bewegungsfeldschaetzung und Dosisakkumulation anhand von 4D-Bilddaten

Energy Technology Data Exchange (ETDEWEB)

Werner, Rene

2013-07-01

developed methods belong to the most precise methods currently available. In clinical practice, however, there exists the problem that many medical facilities are not equipped with 4D imaging devices. Further, 4D images still offer only a snapshot of the patient-specific motion range and potential motion variability may limit the conclusions that can be drawn from them. To address these aspects, in the next part of the thesis - based on the optimized methods for motion field estimation in 4D CT image data and further including statistical motion information and models, respectively - model-based approaches for motion field estimation and prediction are developed. First, a novel approach for statistical modeling of lung motion in a patient collective is presented, and methods for adapting the model for prediction of patient-specific motion patterns are provided. The latter allow, for instance, the estimation of respiratory lung and lung tumor motion for radiation therapy treatment planning, if no temporally resolved image sequences are available for the patient; this use case is demonstrated. Further, techniques of multivariate statistics are applied to account for variations of motion patterns by integrating additional information provided by motion indicators used in 4D radiation therapy (e.g. abdominal belts or spirometer measurements) for a patient-specific, situation-related adaption of the motion fields computed using 4D images and the methods for motion field estimation described before. In the last part of the thesis, the developed methods are finally applied for assessing and analyzing the dosimetric impact of respiratory motion during radiation therapy of lung tumors. Both 3D conformal radiotherapy and intensity modulated radiotherapy are modeled as treatment modalities. In the case of intensity modulated radiotherapy, short delivery times for single radiation fields lead to the risk that the corresponding dose contributions are not only subject to a motion

Coarse-to-fine markerless gait analysis based on PCA and Gauss-Laguerre decomposition

Science.gov (United States)

Goffredo, Michela; Schmid, Maurizio; Conforto, Silvia; Carli, Marco; Neri, Alessandro; D'Alessio, Tommaso

2005-04-01

Human movement analysis is generally performed through the utilization of marker-based systems, which allow reconstructing, with high levels of accuracy, the trajectories of markers allocated on specific points of the human body. Marker based systems, however, show some drawbacks that can be overcome by the use of video systems applying markerless techniques. In this paper, a specifically designed computer vision technique for the detection and tracking of relevant body points is presented. It is based on the Gauss-Laguerre Decomposition, and a Principal Component Analysis Technique (PCA) is used to circumscribe the region of interest. Results obtained on both synthetic and experimental tests provide significant reduction of the computational costs, with no significant reduction of the tracking accuracy.

Amorphization of Fe-based alloy via wet mechanical alloying assisted by PCA decomposition

Energy Technology Data Exchange (ETDEWEB)

Neamţu, B.V., E-mail: Bogdan.Neamtu@stm.utcluj.ro [Materials Science and Engineering Department, Technical University of Cluj-Napoca, 103-105, Muncii Avenue, 400641, Cluj-Napoca (Romania); Chicinaş, H.F.; Marinca, T.F. [Materials Science and Engineering Department, Technical University of Cluj-Napoca, 103-105, Muncii Avenue, 400641, Cluj-Napoca (Romania); Isnard, O. [Université Grenoble Alpes, Institut NEEL, F-38042, Grenoble (France); CNRS, Institut NEEL, 25 rue des martyrs, BP166, F-38042, Grenoble (France); Pană, O. [National Institute for Research and Development of Isotopic and Molecular Technologies, 65-103 Donath Street, 400293, Cluj-Napoca (Romania); Chicinaş, I. [Materials Science and Engineering Department, Technical University of Cluj-Napoca, 103-105, Muncii Avenue, 400641, Cluj-Napoca (Romania)

2016-11-01

Amorphization of Fe{sub 75}Si{sub 20}B{sub 5} (at.%) alloy has been attempted both by wet and dry mechanical alloying starting from a mixture of elemental powders. Powder amorphization was not achieved even after 140 hours of dry mechanical alloying. Using the same milling parameters, when wet mechanical alloying was used, the powder amorphization was achieved after 40 h of milling. Our assumption regarding the powder amorphization capability enhancement by contamination with carbon was proved by X-ray Photoelectron Spectroscopy (XPS) measurements which revealed the presence of carbon in the chemical composition of the wet mechanically alloyed sample. Using shorter milling times and several process control agents (PCA) (ethanol, oleic acid and benzene) with different carbon content it was proved that the milling duration required for powder amorphization is linked to the carbon content of the PCA. Differential Scanning Calorimetry (DSC), thermomagnetic (TG) and X-ray Diffraction (XRD) measurements performed to the heated samples revealed the fact that, the crystallisation occurs at 488 °C, thus leading to the formation of Fe{sub 3}Si and Fe{sub 2}B. Thermogravimetry measurements performed under H{sub 2} atmosphere, showed the same amount of contamination with C, which is about 2.3 wt%, for the amorphous samples regardless of the type of PCA. Saturation magnetisation of the wet milled samples decreases upon increasing milling time. In the case of the amorphous samples wet milled with benzene up to 20 h and with oleic acid up to 30 h, the saturation magnetisation has roughly the same value, indicating the same degree of contamination. The XRD performed on the samples milled using the same parameters, revealed that powder amorphization can be achieved even via dry milling, just by adding the equivalent amount of elemental C calculated from the TG plots. This proves that in this system by considering the atomic species which can contaminate the powder, they can be

Utilize target motion to cover clinical target volume (ctv) - a novel and practical treatment planning approach to manage respiratory motion

International Nuclear Information System (INIS)

Jin Jianyue; Ajlouni, Munther; Kong Fengming; Ryu, Samuel; Chetty, Indrin J.; Movsas, Benjamin

2008-01-01

Purpose: To use probability density function (PDF) to model motion effects and incorporate this information into treatment planning for lung cancers. Material and methods: PDFs were calculated from the respiratory motion traces of 10 patients. Motion effects were evaluated by convolving static dose distributions with various PDFs. Based on a differential dose prescription with relatively lower dose to the clinical target volume (CTV) than to the gross tumor volume (GTV), two approaches were proposed to incorporate PDFs into treatment planning. The first approach uses the GTV-based internal target volume (ITV) as the planning target volume (PTV) to ensure full dose to the GTV, and utilizes the motion-induced dose gradient to cover the CTV. The second approach employs an inhomogeneous static dose distribution within a minimized PTV to best match the prescription dose gradient. Results: Motion effects on dose distributions were minimal in the anterior-posterior (AP) and lateral directions: a 10-mm motion only induced about 3% of dose reduction in the peripheral target region. The motion effect was remarkable in the cranial-caudal direction. It varied with the motion amplitude, but tended to be similar for various respiratory patterns. For the first approach, a 10-15 mm motion would adequately cover the CTV (presumed to be 60-70% of the GTV dose) without employing the CTV in planning. For motions 15-mm. An example of inhomogeneous static dose distribution in a reduced PTV was given, and it showed significant dose reduction in the normal tissue without compromising target coverage. Conclusions: Respiratory motion-induced dose gradient can be utilized to cover the CTV and minimize the lung dose without the need for more sophisticated technologies

Deep inspiration breath-hold technique for lung tumors: the potential value of target immobilization and reduced lung density in dose escalation

International Nuclear Information System (INIS)

Hanley, J.; Debois, M.M.; Raben, A.; Mageras, G.S.; Lutz, W.R.; Mychalczak, B.; Schwartz, L.H.; Gloeggler, P.J.; Leibel, S.A.; Fuks, Z.; Kutcher, G.J.

1996-01-01

Purpose/Objective: Lung tumors are subject to movement due to respiratory motion. Conventionally, a margin is applied to the clinical target volume (CTV) to account for this and other treatment uncertainties. The purpose of this study is to evaluate the dosimetric benefits of a deep inspiration breath-hold (DIBH) technique which has two distinct features - deep inspiration which reduces lung density and breath-hold which immobilizes lung tumors. Both properties can potentially reduce the mass of normal lung tissue in the high dose region, thus improving the possibility of dose escalation. Methods and Materials: To study the efficacy of the DIBH technique, CT scans are acquired for each patient under 4 respiration conditions: free-breathing; DIBH; shallow inspiration breath-hold; shallow expiration breath-hold. The free-breathing and DIBH scans are used to generate treatment plans for comparison of standard and DIBH techniques, while the shallow inspiration and expiration scans provide information on the maximum extent of tumor motion under free-breathing conditions. To acquire the breath-hold scans, the patients are brought to reproducible respiration levels using spirometry and slow vital capacity maneuvers. For the treatment plan comparison free-breathing and DIBH planning target volumes (PTVs) are constructed consisting of the CTV plus a margin for setup error and lung tumor motion. For both plans the margin for setup error is the same while the margin for lung tumor motion differs. The margin for organ motion in free-breathing is determined by the maximum tumor excursions in the shallow inspiration and expiration CT scans. For the DIBH, tumor motion is reduced to the extent to which DIBH can be maintained and the margin for any residual tumor motion is determined from repeat fluoroscopic movies, acquired with the patient monitored using spirometry. Three-dimensional treatment plans, generated using apertures based on the free-breathing and DIBH PTVs, are

Discrimination of liver cancer in cellular level based on backscatter micro-spectrum with PCA algorithm and BP neural network

Science.gov (United States)

Yang, Jing; Wang, Cheng; Cai, Gan; Dong, Xiaona

2016-10-01

The incidence and mortality rate of the primary liver cancer are very high and its postoperative metastasis and recurrence have become important factors to the prognosis of patients. Circulating tumor cells (CTC), as a new tumor marker, play important roles in the early diagnosis and individualized treatment. This paper presents an effective method to distinguish liver cancer based on the cellular scattering spectrum, which is a non-fluorescence technique based on the fiber confocal microscopic spectrometer. Combining the principal component analysis (PCA) with back propagation (BP) neural network were utilized to establish an automatic recognition model for backscatter spectrum of the liver cancer cells from blood cell. PCA was applied to reduce the dimension of the scattering spectral data which obtained by the fiber confocal microscopic spectrometer. After dimensionality reduction by PCA, a neural network pattern recognition model with 2 input layer nodes, 11 hidden layer nodes, 3 output nodes was established. We trained the network with 66 samples and also tested it. Results showed that the recognition rate of the three types of cells is more than 90%, the relative standard deviation is only 2.36%. The experimental results showed that the fiber confocal microscopic spectrometer combining with the algorithm of PCA and BP neural network can automatically identify the liver cancer cell from the blood cells. This will provide a better tool for investigating the metastasis of liver cancers in vivo, the biology metabolic characteristics of liver cancers and drug transportation. Additionally, it is obviously referential in practical application.

An efficient algorithm for weighted PCA

NARCIS (Netherlands)

Krijnen, W.P.; Kiers, H.A.L.

1995-01-01

The method for analyzing three-way data where one of the three components matrices in TUCKALS3 is chosen to have one column is called Replicated PCA. The corresponding algorithm is relatively inefficient. This is shown by offering an alternative algorithm called Weighted PCA. Specifically it is

MO-C-17A-06: Online Adaptive Re-Planning to Account for Independent Motions Between Multiple Targets During Radiotherapy of Lung Cancer

International Nuclear Information System (INIS)

Liu, F; Tai, A; Ahunbay, E; Gore, E; Johnstone, C; Li, X

2014-01-01

Purpose: To quantify interfractional independent motions between multiple targets in radiotherapy (RT) of lung cancer, and to study the dosimetric benefits of an online adaptive replanning method to account for these variations. Methods: Ninety five diagnostic-quality daily CTs acquired for 9 lung cancer patients treated with IGRT using an in-room CT (CTVision, Siemens) were analyzed. On each daily CT set, contours of the targets (GTV, CTV, or involved nodes) and organs at risk were generated by populating the planning contours using an auto-segmentation tool (ABAS, Elekta) with manual editing. For each patient, an IMRT plan was generated based on the planning CT with a prescription dose of 60 Gy in 2Gy fractions. Three plans were generated and compared for each daily CT set: an IGRT (repositioning) plan by copying the original plan with the required shifts, an online adaptive plan by rapidly modifying the aperture shapes and segment weights of the original plan to conform to the daily anatomy, and a new fully re-optimized plan based on the daily CT using a planning system (Panther, Prowess). Results: The daily deviations of the distance between centers of masses of the targets from the plans varied daily from -10 to 8 mm with an average −0.9±4.1 mm (one standard deviation). The average CTV V100 are 99.0±0.7%, 97.9±2.8%, 99.0±0.6%, and 99.1±0.6%, and the lung V20 Gy 928±332 cc, 944±315 cc, 917±300 cc, and 891±295 cc for the original, repositioning, adaptive, and re-optimized plans, respectively. Wilcoxon signed-rank tests show that the adaptive plans are statistically significantly better than the repositioning plans and comparable with the reoptimized plans. Conclusion: There exist unpredictable, interfractional, relative volume changes and independent motions between multiple targets during lung cancer RT which cannot be accounted for by the current IGRT repositioning but can be corrected by the online adaptive replanning method

MO-C-17A-06: Online Adaptive Re-Planning to Account for Independent Motions Between Multiple Targets During Radiotherapy of Lung Cancer

Energy Technology Data Exchange (ETDEWEB)

Liu, F; Tai, A; Ahunbay, E; Gore, E; Johnstone, C; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

2014-06-15

Purpose: To quantify interfractional independent motions between multiple targets in radiotherapy (RT) of lung cancer, and to study the dosimetric benefits of an online adaptive replanning method to account for these variations. Methods: Ninety five diagnostic-quality daily CTs acquired for 9 lung cancer patients treated with IGRT using an in-room CT (CTVision, Siemens) were analyzed. On each daily CT set, contours of the targets (GTV, CTV, or involved nodes) and organs at risk were generated by populating the planning contours using an auto-segmentation tool (ABAS, Elekta) with manual editing. For each patient, an IMRT plan was generated based on the planning CT with a prescription dose of 60 Gy in 2Gy fractions. Three plans were generated and compared for each daily CT set: an IGRT (repositioning) plan by copying the original plan with the required shifts, an online adaptive plan by rapidly modifying the aperture shapes and segment weights of the original plan to conform to the daily anatomy, and a new fully re-optimized plan based on the daily CT using a planning system (Panther, Prowess). Results: The daily deviations of the distance between centers of masses of the targets from the plans varied daily from -10 to 8 mm with an average −0.9±4.1 mm (one standard deviation). The average CTV V100 are 99.0±0.7%, 97.9±2.8%, 99.0±0.6%, and 99.1±0.6%, and the lung V20 Gy 928±332 cc, 944±315 cc, 917±300 cc, and 891±295 cc for the original, repositioning, adaptive, and re-optimized plans, respectively. Wilcoxon signed-rank tests show that the adaptive plans are statistically significantly better than the repositioning plans and comparable with the reoptimized plans. Conclusion: There exist unpredictable, interfractional, relative volume changes and independent motions between multiple targets during lung cancer RT which cannot be accounted for by the current IGRT repositioning but can be corrected by the online adaptive replanning method.

Characterizing spatiotemporal information loss in sparse-sampling-based dynamic MRI for monitoring respiration-induced tumor motion in radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Arai, Tatsuya J. [Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Nofiele, Joris; Yuan, Qing [Department of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Madhuranthakam, Ananth J.; Pedrosa, Ivan; Chopra, Rajiv [Department of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Sawant, Amit, E-mail: amit.sawant@utsouthwestern.edu [Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Department of Radiology, UT Southwestern Medical Center, Dallas, Texas 75390 (United States); Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, 21201 (United States)

2016-06-15

Purpose: Sparse-sampling and reconstruction techniques represent an attractive strategy to achieve faster image acquisition speeds, while maintaining adequate spatial resolution and signal-to-noise ratio in rapid magnetic resonance imaging (MRI). The authors investigate the use of one such sequence, broad-use linear acquisition speed-up technique (k-t BLAST) in monitoring tumor motion for thoracic and abdominal radiotherapy and examine the potential trade-off between increased sparsification (to increase imaging speed) and the potential loss of “true” information due to greater reliance on a priori information. Methods: Lung tumor motion trajectories in the superior–inferior direction, previously recorded from ten lung cancer patients, were replayed using a motion phantom module driven by an MRI-compatible motion platform. Eppendorf test tubes filled with water which serve as fiducial markers were placed in the phantom. The modeled rigid and deformable motions were collected in a coronal image slice using balanced fast field echo in conjunction with k-t BLAST. Root mean square (RMS) error was used as a metric of spatial accuracy as measured trajectories were compared to input data. The loss of spatial information was characterized for progressively increasing acceleration factor from 1 to 16; the resultant sampling frequency was increased approximately from 2.5 to 19 Hz when the principal direction of the motion was set along frequency encoding direction. In addition to the phantom study, respiration-induced tumor motions were captured from two patients (kidney tumor and lung tumor) at 13 Hz over 49 s to demonstrate the impact of high speed motion monitoring over multiple breathing cycles. For each subject, the authors compared the tumor centroid trajectory as well as the deformable motion during free breathing. Results: In the rigid and deformable phantom studies, the RMS error of target tracking at the acquisition speed of 19 Hz was approximately 0.3–0

Beyond textbook neuroanatomy: The syndrome of malignant PCA infarction.

Science.gov (United States)

Gogela, Steven L; Gozal, Yair M; Rahme, Ralph; Zuccarello, Mario; Ringer, Andrew J

2015-01-01

Given its limited vascular territory, occlusion of the posterior cerebral artery (PCA) usually does not result in malignant infarction. Challenging this concept, we present 3 cases of unilateral PCA infarction with secondary malignant progression, resulting from extension into what would classically be considered the posterior middle cerebral artery (MCA) territory. Interestingly, these were true PCA infarctions, not "MCA plus" strokes, since the underlying occlusive lesion was in the PCA. We hypothesize that congenital and/or acquired variability in the distribution and extent of territory supplied by the PCA may underlie this rare clinical entity. Patients with a PCA infarction should thus be followed closely and offered early surgical decompression in the event of malignant progression.

MO-FG-BRA-08: Swarm Intelligence-Based Personalized Respiratory Gating in Lung SAbR

Energy Technology Data Exchange (ETDEWEB)

Modiri, A; Sabouri, P; Sawant, A [University of Maryland in Baltimore, Baltimore, MD (United States); Gu, X; Timmerman, R [University of Texas Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: Respiratory gating is widely deployed as a clinical motion-management strategy in lung radiotherapy. In conventional gating, the beam is turned on during a pre-determined phase window; typically, around end-exhalation. In this work, we challenge the notion that end-exhalation is always the optimal gating phase. Specifically, we use a swarm-intelligence-based, inverse planning approach to determine the optimal respiratory phase and MU for each beam with respect to (i) the state of the anatomy at each phase and (ii) the time spent in that state, estimated from long-term monitoring of the patient’s breathing motion. Methods: In a retrospective study of five lung cancer patients, we compared the dosimetric performance of our proposed personalized gating (PG) with that of conventional end-of-exhale gating (CEG) and a previously-developed, fully 4D-optimized plan (combined with MLC tracking delivery). For each patient, respiratory phase probabilities (indicative of the time duration of the phase) were estimated over 2 minutes from lung tumor motion traces recorded previously using the Synchrony system (Accuray Inc.). Based on this information, inverse planning optimization was performed to calculate the optimal respiratory gating phase and MU for each beam. To ensure practical deliverability, each PG beam was constrained to deliver the assigned MU over a time duration comparable to that of CEG delivery. Results: Maximum OAR sparing for the five patients achieved by the PG and the 4D plans compared to CEG plans was: Esophagus Dmax [PG:57%, 4D:37%], Heart Dmax [PG:71%, 4D:87%], Spinal cord Dmax [PG:18%, 4D:68%] and Lung V13 [PG:16%, 4D:31%]. While patients spent the most time in exhalation, the PG-optimization chose end-exhale only for 28% of beams. Conclusion: Our novel gating strategy achieved significant dosimetric improvements over conventional gating, and approached the upper limit represented by fully 4D optimized planning while being significantly simpler

MO-FG-BRA-08: Swarm Intelligence-Based Personalized Respiratory Gating in Lung SAbR

International Nuclear Information System (INIS)

Modiri, A; Sabouri, P; Sawant, A; Gu, X; Timmerman, R

2016-01-01

Purpose: Respiratory gating is widely deployed as a clinical motion-management strategy in lung radiotherapy. In conventional gating, the beam is turned on during a pre-determined phase window; typically, around end-exhalation. In this work, we challenge the notion that end-exhalation is always the optimal gating phase. Specifically, we use a swarm-intelligence-based, inverse planning approach to determine the optimal respiratory phase and MU for each beam with respect to (i) the state of the anatomy at each phase and (ii) the time spent in that state, estimated from long-term monitoring of the patient’s breathing motion. Methods: In a retrospective study of five lung cancer patients, we compared the dosimetric performance of our proposed personalized gating (PG) with that of conventional end-of-exhale gating (CEG) and a previously-developed, fully 4D-optimized plan (combined with MLC tracking delivery). For each patient, respiratory phase probabilities (indicative of the time duration of the phase) were estimated over 2 minutes from lung tumor motion traces recorded previously using the Synchrony system (Accuray Inc.). Based on this information, inverse planning optimization was performed to calculate the optimal respiratory gating phase and MU for each beam. To ensure practical deliverability, each PG beam was constrained to deliver the assigned MU over a time duration comparable to that of CEG delivery. Results: Maximum OAR sparing for the five patients achieved by the PG and the 4D plans compared to CEG plans was: Esophagus Dmax [PG:57%, 4D:37%], Heart Dmax [PG:71%, 4D:87%], Spinal cord Dmax [PG:18%, 4D:68%] and Lung V13 [PG:16%, 4D:31%]. While patients spent the most time in exhalation, the PG-optimization chose end-exhale only for 28% of beams. Conclusion: Our novel gating strategy achieved significant dosimetric improvements over conventional gating, and approached the upper limit represented by fully 4D optimized planning while being significantly simpler

PCA-derived factors that may be predictive of postoperative pain in pediatric patients: a possible role for the PCA ratio.

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McDonnell, Conor; Pehora, Carolyne; Crawford, Mark W

2012-01-01

No method exists to reliably predict which patients will develop severe postoperative pain. The authors hypothesized that data derived from patient-controlled analgesia (PCA) pumps (specifically the ratio of patient demands to pump deliveries) may predict which patients would develop severe pain after scoliosis repair. Quaternary, university-affiliated, pediatric hospital. Forty American Society of Anesthesiologists I-Il pediatric patients who had undergone elective scoliosis repair and had consented to recruitment to a randomized clinical trial investigating the effects of early morphine administration on remifentanil-induced hyperalgesia. To test the hypothesis of the current study, the authors calculated the PCA ratio of demand to delivery at every 4 hours throughout the first 24 hours after surgery for all the patients recruited to the original study. The authors compared calculated PCA ratios, numeric rating scale pain scores, and cumulative morphine consumption for those patients who developed severe postoperative pain and met the criteria for opioid rotation versus those patients who did not. Seven patients required opioid rotation from PCA morphine to PCA hydromorphone. Eight hours after surgery, the median PCA ratio for those seven patients (2.5[range, 1.8-4.3]) was significantly greater than that for all other recruited patients (1.3 [range, 0-2.7]; p PCA ratios of demand to delivery as early as 8 hours after surgery.

An analytical approach based on ESI-MS, LC-MS and PCA for the quali-quantitative analysis of cycloartane derivatives in Astragalus spp.

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Napolitano, Assunta; Akay, Seref; Mari, Angela; Bedir, Erdal; Pizza, Cosimo; Piacente, Sonia

2013-11-01

Astragalus species are widely used as health foods and dietary supplements, as well as drugs in traditional medicine. To rapidly evaluate metabolite similarities and differences among the EtOH extracts of the roots of eight commercial Astragalus spp., an approach based on direct analyses by ESI-MS followed by PCA of ESI-MS data, was carried out. Successively, quali-quantitative analyses of cycloartane derivatives in the eight Astragalus spp. by LC-ESI-MS(n) and PCA of LC-ESI-MS data were performed. This approach allowed to promptly highlighting metabolite similarities and differences among the various Astragalus spp. PCA results from LC-ESI-MS data of Astragalus samples were in reasonable agreement with both PCA results of ESI-MS data and quantitative results. This study affords an analytical method for the quali-quantitative determination of cycloartane derivatives in herbal preparations used as health and food supplements. Copyright © 2013 Elsevier B.V. All rights reserved.

Cumulative Lung Dose for Several Motion Management Strategies as a Function of Pretreatment Patient Parameters

International Nuclear Information System (INIS)

Hugo, Geoffrey D.; Campbell, Jonathon; Zhang Tiezhi; Yan Di

2009-01-01

Purpose: To evaluate patient parameters that may predict for relative differences in cumulative four-dimensional (4D) lung dose among several motion management strategies. Methods and Materials: Deformable image registration and dose accumulation were used to generate 4D treatment plans for 18 patients with 4D computed tomography scans. Three plans were generated to simulate breath hold at normal inspiration, target tracking with the beam aperture, and mid-ventilation aperture (control of the target at the mean daily position and application of an iteratively computed margin to compensate for respiration). The relative reduction in mean lung dose (MLD) between breath hold and mid-ventilation aperture (ΔMLD BH ) and between target tracking and mid-ventilation aperture (ΔMLD TT ) was calculated. Associations between these two variables and parameters of the lesion (excursion, size, location, and deformation) and dose distribution (local dose gradient near the target) were also calculated. Results: The largest absolute and percentage differences in MLD were 1.0 Gy and 21.5% between breath hold and mid-ventilation aperture. ΔMLD BH was significantly associated (p TT was significantly associated with excursion, deformation, and local dose gradient. A linear model was constructed to represent ΔMLD vs. excursion. For each 5 mm of excursion, target tracking reduced the MLD by 4% compared with the results of a mid-ventilation aperture plan. For breath hold, the reduction was 5% per 5 mm of excursion. Conclusions: The relative difference in MLD among different motion management strategies varied with patient and tumor characteristics for a given dosimetric target coverage. Tumor excursion is useful to aid in stratifying patients according to appropriate motion management strategies.

Model-Based Motion Tracking of Infants

DEFF Research Database (Denmark)

Olsen, Mikkel Damgaard; Herskind, Anna; Nielsen, Jens Bo

2014-01-01

Even though motion tracking is a widely used technique to analyze and measure human movements, only a few studies focus on motion tracking of infants. In recent years, a number of studies have emerged focusing on analyzing the motion pattern of infants, using computer vision. Most of these studies...... are based on 2D images, but few are based on 3D information. In this paper, we present a model-based approach for tracking infants in 3D. The study extends a novel study on graph-based motion tracking of infants and we show that the extension improves the tracking results. A 3D model is constructed...

Example-based human motion denoising.

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Lou, Hui; Chai, Jinxiang

2010-01-01

With the proliferation of motion capture data, interest in removing noise and outliers from motion capture data has increased. In this paper, we introduce an efficient human motion denoising technique for the simultaneous removal of noise and outliers from input human motion data. The key idea of our approach is to learn a series of filter bases from precaptured motion data and use them along with robust statistics techniques to filter noisy motion data. Mathematically, we formulate the motion denoising process in a nonlinear optimization framework. The objective function measures the distance between the noisy input and the filtered motion in addition to how well the filtered motion preserves spatial-temporal patterns embedded in captured human motion data. Optimizing the objective function produces an optimal filtered motion that keeps spatial-temporal patterns in captured motion data. We also extend the algorithm to fill in the missing values in input motion data. We demonstrate the effectiveness of our system by experimenting with both real and simulated motion data. We also show the superior performance of our algorithm by comparing it with three baseline algorithms and to those in state-of-art motion capture data processing software such as Vicon Blade.

Toward efficient biomechanical-based deformable image registration of lungs for image-guided radiotherapy

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Al-Mayah, Adil; Moseley, Joanne; Velec, Mike; Brock, Kristy

2011-08-01

Both accuracy and efficiency are critical for the implementation of biomechanical model-based deformable registration in clinical practice. The focus of this investigation is to evaluate the potential of improving the efficiency of the deformable image registration of the human lungs without loss of accuracy. Three-dimensional finite element models have been developed using image data of 14 lung cancer patients. Each model consists of two lungs, tumor and external body. Sliding of the lungs inside the chest cavity is modeled using a frictionless surface-based contact model. The effect of the type of element, finite deformation and elasticity on the accuracy and computing time is investigated. Linear and quadrilateral tetrahedral elements are used with linear and nonlinear geometric analysis. Two types of material properties are applied namely: elastic and hyperelastic. The accuracy of each of the four models is examined using a number of anatomical landmarks representing the vessels bifurcation points distributed across the lungs. The registration error is not significantly affected by the element type or linearity of analysis, with an average vector error of around 2.8 mm. The displacement differences between linear and nonlinear analysis methods are calculated for all lungs nodes and a maximum value of 3.6 mm is found in one of the nodes near the entrance of the bronchial tree into the lungs. The 95 percentile of displacement difference ranges between 0.4 and 0.8 mm. However, the time required for the analysis is reduced from 95 min in the quadratic elements nonlinear geometry model to 3.4 min in the linear element linear geometry model. Therefore using linear tetrahedral elements with linear elastic materials and linear geometry is preferable for modeling the breathing motion of lungs for image-guided radiotherapy applications.

The Feasibility Study for Multigeometries Identification of Uranium Components Using PCA-LSSVM Based on Correlation Measurements

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Mi Zhou

2018-01-01

Full Text Available The geometry of uranium components is one of the key characteristics and strictly confidential. The geometry identification of metal uranium components was studied using 252Cf source-driven correlation measurement method. For the 3 uranium samples with the same mass and enrichment, there are subtle differences in neutron signals. Even worse, the correlation functions were disturbed by scatter neutrons and include “accidental” coincidence, which is not conductive to the geometry identification. In this paper, we proposed an identification method combining principal component analysis and least-square support vector machine (PCA-LSSVM. The results based on PCA-LSSVM showed that the training precision was 100% and the test precision was 95.83% of the identification model. The total precision of the identification model was 98.41%, which indicated that the identification model was an effective way to identify the geometry properties with the correlation functions.

MotionExplorer: exploratory search in human motion capture data based on hierarchical aggregation.

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Bernard, Jürgen; Wilhelm, Nils; Krüger, Björn; May, Thorsten; Schreck, Tobias; Kohlhammer, Jörn

2013-12-01

We present MotionExplorer, an exploratory search and analysis system for sequences of human motion in large motion capture data collections. This special type of multivariate time series data is relevant in many research fields including medicine, sports and animation. Key tasks in working with motion data include analysis of motion states and transitions, and synthesis of motion vectors by interpolation and combination. In the practice of research and application of human motion data, challenges exist in providing visual summaries and drill-down functionality for handling large motion data collections. We find that this domain can benefit from appropriate visual retrieval and analysis support to handle these tasks in presence of large motion data. To address this need, we developed MotionExplorer together with domain experts as an exploratory search system based on interactive aggregation and visualization of motion states as a basis for data navigation, exploration, and search. Based on an overview-first type visualization, users are able to search for interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results by details on demand. We developed MotionExplorer in close collaboration with the targeted users who are researchers working on human motion synthesis and analysis, including a summative field study. Additionally, we conducted a laboratory design study to substantially improve MotionExplorer towards an intuitive, usable and robust design. MotionExplorer enables the search in human motion capture data with only a few mouse clicks. The researchers unanimously confirm that the system can efficiently support their work.

Metoclopramide improves the quality of tramadol PCA indistinguishable to morphine PCA: a prospective, randomized, double blind clinical comparison.

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Pang, Weiwu; Liu, Yu-Cheng; Maboudou, Edgard; Chen, Tom Xianxiu; Chois, John M; Liao, Cheng-Chun; Wu, Rick Sai-Chuen

2013-09-01

Multimodal analgesia has been effectively used in postoperative pain control. Tramadol can be considered "multimodal" because it has two main mechanisms of action, an opioid agonist and a reuptake inhibitor of norepinephrine and serotonin. Tramadol is not as commonly used as morphine due to the increased incidence of postoperative nausea and vomiting (PONV). As metoclopramide is an antiemetic and an analgesic, it was hypothesized that when added to reduce PONV, metoclopromide may enhance the multimodal feature of tramadol by the analgesic property of metoclopramide. Therefore, the effectiveness of postoperative patient-controlled analgesia (PCA) with morphine was compared against PCA with combination of tramadol and metoclopramide. A prospective, randomized, double blind clinical trial. Academic pain service of a university hospital. Sixty patients undergoing elective total knee arthroplasty with general anesthesia. Sixty patients were randomly divided into Group M and Group T. In a double-blinded fashion, Group M received intraoperative 0.2 mg/kg morphine and postoperative PCA with 1 mg morphine per bolus, whereas Group T received intraoperative tramadol 2.5 mg/kg and postoperative PCA with 20 mg tramadol plus 1 mg metoclopramide per bolus. Lockout interval was 5 minutes in both groups. Pain scale, satisfaction rate, analgesic consumption, PCA demand, and side effects were recorded by a blind investigator. These two groups displayed no statistically significant difference between the items and variables evaluated. This combination provides analgesia equivalent to that of morphine and can be used as an alternative to morphine PCA. Wiley Periodicals, Inc.

PCA-based ANN approach to leak classification in the main pipes of VVER-1000

International Nuclear Information System (INIS)

Hadad, Kamal; Jabbari, Masoud; Tabadar, Z.; Hashemi-Tilehnoee, Mehdi

2012-01-01

This paper presents a neural network based fault diagnosing approach which allows dynamic crack and leaks fault identification. The method utilizes the Principal Component Analysis (PCA) technique to reduce the problem dimension. Such a dimension reduction approach leads to faster diagnosing and allows a better graphic presentation of the results. To show the effectiveness of the proposed approach, two methodologies are used to train the neural network (NN). At first, a training matrix composed of 14 variables is used to train a Multilayer Perceptron neural network (MLP) with Resilient Backpropagation (RBP) algorithm. Employing the proposed method, a more accurate and simpler network is designed where the input size is reduced from 14 to 6 variables for training the NN. In short, the application of PCA highly reduces the network topology and allows employing more efficient training algorithms. The accuracy, generalization ability, and reliability of the designed networks are verified using 10 simulated events data from a VVER-1000 simulation using DINAMIKA-97 code. Noise is added to the data to evaluate the robustness of the method and the method again shows to be effective and powerful. (orig.)

Surrogate-driven deformable motion model for organ motion tracking in particle radiation therapy

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Fassi, Aurora; Seregni, Matteo; Riboldi, Marco; Cerveri, Pietro; Sarrut, David; Battista Ivaldi, Giovanni; Tabarelli de Fatis, Paola; Liotta, Marco; Baroni, Guido

2015-02-01

The aim of this study is the development and experimental testing of a tumor tracking method for particle radiation therapy, providing the daily respiratory dynamics of the patient’s thoraco-abdominal anatomy as a function of an external surface surrogate combined with an a priori motion model. The proposed tracking approach is based on a patient-specific breathing motion model, estimated from the four-dimensional (4D) planning computed tomography (CT) through deformable image registration. The model is adapted to the interfraction baseline variations in the patient’s anatomical configuration. The driving amplitude and phase parameters are obtained intrafractionally from a respiratory surrogate signal derived from the external surface displacement. The developed technique was assessed on a dataset of seven lung cancer patients, who underwent two repeated 4D CT scans. The first 4D CT was used to build the respiratory motion model, which was tested on the second scan. The geometric accuracy in localizing lung lesions, mediated over all breathing phases, ranged between 0.6 and 1.7 mm across all patients. Errors in tracking the surrounding organs at risk, such as lungs, trachea and esophagus, were lower than 1.3 mm on average. The median absolute variation in water equivalent path length (WEL) within the target volume did not exceed 1.9 mm-WEL for simulated particle beams. A significant improvement was achieved compared with error compensation based on standard rigid alignment. The present work can be regarded as a feasibility study for the potential extension of tumor tracking techniques in particle treatments. Differently from current tracking methods applied in conventional radiotherapy, the proposed approach allows for the dynamic localization of all anatomical structures scanned in the planning CT, thus providing complete information on density and WEL variations required for particle beam range adaptation.

Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

Science.gov (United States)

Huang, Ai-Mei; Nguyen, Truong

2009-04-01

In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

Condition Monitoring of Sensors in a NPP Using Optimized PCA

Directory of Open Access Journals (Sweden)

Wei Li

2018-01-01

Full Text Available An optimized principal component analysis (PCA framework is proposed to implement condition monitoring for sensors in a nuclear power plant (NPP in this paper. Compared with the common PCA method in previous research, the PCA method in this paper is optimized at different modeling procedures, including data preprocessing stage, modeling parameter selection stage, and fault detection and isolation stage. Then, the model’s performance is greatly improved through these optimizations. Finally, sensor measurements from a real NPP are used to train the optimized PCA model in order to guarantee the credibility and reliability of the simulation results. Meanwhile, artificial faults are sequentially imposed to sensor measurements to estimate the fault detection and isolation ability of the proposed PCA model. Simulation results show that the optimized PCA model is capable of detecting and isolating the sensors regardless of whether they exhibit major or small failures. Meanwhile, the quantitative evaluation results also indicate that better performance can be obtained in the optimized PCA method compared with the common PCA method.

Denoising by semi-supervised kernel PCA preimaging

DEFF Research Database (Denmark)

Hansen, Toke Jansen; Abrahamsen, Trine Julie; Hansen, Lars Kai

2014-01-01

Kernel Principal Component Analysis (PCA) has proven a powerful tool for nonlinear feature extraction, and is often applied as a pre-processing step for classification algorithms. In denoising applications Kernel PCA provides the basis for dimensionality reduction, prior to the so-called pre-imag...

Parent-controlled PCA for pain management in pediatric oncology: is it safe?

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Anghelescu, Doralina L; Faughnan, Lane G; Oakes, Linda L; Windsor, Kelley B; Pei, Deqing; Burgoyne, Laura L

2012-08-01

Patient-controlled analgesia offers safe and effective pain control for children who can self-administer medication. Some children may not be candidates for patient-controlled analgesia (PCA) unless a proxy can administer doses. The safety of proxy-administered PCA has been studied, but the safety of parent-administered PCA in children with cancer has not been reported. In this study, we compare the rate of complications in PCA by parent proxy versus PCA by clinician (nurse) proxy and self-administered PCA. Our pediatric institution's quality improvement database was reviewed for adverse events associated with PCA from 2004 through 2010. Each PCA day was categorized according to patient or proxy authorization. Data from 6151 PCA observation days were included; 61.3% of these days were standard PCA, 23.5% were parent-proxy PCA, and 15.2% were clinician-proxy PCA days. The mean duration of PCA use was 12.1 days, and the mean patient age was 12.3 years. The mean patient age was lower in the clinician-proxy (9.4 y) and parent-proxy (5.1 y) groups, respectively. The complication rate was lowest in the parent-proxy group (0.62%). We found that proxy administration of PCA by authorized parents is as safe as clinician administered and standard PCA at our pediatric institution.

Effect of respiratory motion on internal radiation dosimetry

Energy Technology Data Exchange (ETDEWEB)

Xie, Tianwu [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva 4 CH-1211 (Switzerland); Zaidi, Habib, E-mail: habib.zaidi@hcuge.ch [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva 4 CH-1211 (Switzerland); Geneva Neuroscience Center, Geneva University, Geneva CH-1205 (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen 9700 RB (Netherlands)

2014-11-01

anatomical model provides more accurate internal radiation dosimetry estimates for the lungs and abdominal organs based on realistic modeling of respiratory motion. This work also contributes to a better understanding of model-induced uncertainties in internal radiation dosimetry.

Four-dimensional Monte Carlo simulations demonstrating how the extent of intensity-modulation impacts motion effects in proton therapy lung treatments

International Nuclear Information System (INIS)

Dowdell, Stephen; Paganetti, Harald; Grassberger, Clemens

2013-01-01

Purpose: To compare motion effects in intensity modulated proton therapy (IMPT) lung treatments with different levels of intensity modulation.Methods: Spot scanning IMPT treatment plans were generated for ten lung cancer patients for 2.5Gy(RBE) and 12Gy(RBE) fractions and two distinct energy-dependent spot sizes (σ∼8–17 mm and ∼2–4 mm). IMPT plans were generated with the target homogeneity of each individual field restricted to 20% ). These plans were compared to full IMPT (IMPT full ), which had no restriction on the single field homogeneity. 4D Monte Carlo simulations were performed upon the patient 4DCT geometry, including deformable image registration and incorporating the detailed timing structure of the proton delivery system. Motion effects were quantified via comparison of the results of the 4D simulations (4D-IMPT 20% , 4D-IMPT full ) with those of a 3D Monte Carlo simulation (3D-IMPT 20% , 3D-IMPT full ) upon the planning CT using the equivalent uniform dose (EUD), V 95 and D 1 -D 99 . The effects in normal lung were quantified using mean lung dose (MLD) and V 90% .Results: For 2.5Gy(RBE), the mean EUD for the large spot size is 99.9%± 2.8% for 4D-IMPT 20% compared to 100.1%± 2.9% for 4D-IMPT full . The corresponding values are 88.6%± 8.7% (4D-IMPT 20% ) and 91.0%± 9.3% (4D-IMPT full ) for the smaller spot size. The EUD value is higher in 69.7% of the considered deliveries for 4D-IMPT full . The V 95 is also higher in 74.7% of the plans for 4D-IMPT full , implying that IMPT full plans experience less underdose compared to IMPT 20% . However, the target dose homogeneity is improved in the majority (67.8%) of plans for 4D-IMPT 20% . The higher EUD and V 95 suggests that the degraded homogeneity in IMPT full is actually due to the introduction of hot spots in the target volume, perhaps resulting from the sharper in-target dose gradients. The greatest variations between the IMPT 20% and IMPT full deliveries are observed for patients with the

The microbiome of the lung and its extracellular vesicles in nonsmokers, healthy smokers and COPD patients

Science.gov (United States)

Kim, Hyun Jung; Kim, You-Sun; Kim, Kang-Hyun; Choi, Jun-Pyo; Kim, Yoon-Keun; Yun, Sunmi; Sharma, Lokesh; Dela Cruz, Charles S; Lee, Jae Seung; Oh, Yeon-Mok; Lee, Sang-Do; Lee, Sei Won

2017-01-01

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease, and bacterial infection plays a role in its pathogenesis. Bacteria secrete nanometer-sized extracellular vesicles (EVs), which may induce more immune dysfunction and inflammation than the bacteria themselves. We hypothesized that the microbiome of lung EVs might have distinct characteristics depending on the presence of COPD and smoking status. We analyzed and compared the microbiomes of 13 nonsmokers with normal spirometry, 13 smokers with normal spirometry (healthy smokers) and 13 patients with COPD by using 16S ribosomal RNA gene sequencing of surgical lung tissue and lung EVs. Subjects were matched for age and sex in all groups and for smoking levels in the COPD and healthy smoker groups. Each group included 12 men and 1 woman with the same mean age of 65.5 years. In all groups, EVs consistently showed more operational taxonomic units (OTUs) than lung tissue. In the healthy smoker and COPD groups, EVs had a higher Shannon index and a lower Simpson index than lung tissue and this trend was more prominent in the COPD group. Principal component analysis (PCA) showed clusters based on sample type rather than participants' clinical characteristics. Stenotrophomonas, Propionibacterium and Alicyclobacillus were the most commonly found genera. Firmicutes were highly present in the EVs of the COPD group compared with other samples or groups. Our analysis of the lung microbiome revealed that the bacterial communities present in the EVs and in the COPD group possessed distinct characteristics with differences in the OTUs, diversity indexes and PCA clustering. PMID:28408748

Correlated motion of protein subdomains and large-scale conformational flexibility of RecA protein filament

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Yu, Garmay; A, Shvetsov; D, Karelov; D, Lebedev; A, Radulescu; M, Petukhov; V, Isaev-Ivanov

2012-02-01

Based on X-ray crystallographic data available at Protein Data Bank, we have built molecular dynamics (MD) models of homologous recombinases RecA from E. coli and D. radiodurans. Functional form of RecA enzyme, which is known to be a long helical filament, was approximated by a trimer, simulated in periodic water box. The MD trajectories were analyzed in terms of large-scale conformational motions that could be detectable by neutron and X-ray scattering techniques. The analysis revealed that large-scale RecA monomer dynamics can be described in terms of relative motions of 7 subdomains. Motion of C-terminal domain was the major contributor to the overall dynamics of protein. Principal component analysis (PCA) of the MD trajectories in the atom coordinate space showed that rotation of C-domain is correlated with the conformational changes in the central domain and N-terminal domain, that forms the monomer-monomer interface. Thus, even though C-terminal domain is relatively far from the interface, its orientation is correlated with large-scale filament conformation. PCA of the trajectories in the main chain dihedral angle coordinate space implicates a co-existence of a several different large-scale conformations of the modeled trimer. In order to clarify the relationship of independent domain orientation with large-scale filament conformation, we have performed analysis of independent domain motion and its implications on the filament geometry.

24 CFR 401.451 - PAE Physical Condition Analysis (PCA).

Science.gov (United States)

2010-04-01

... (PCA). 401.451 Section 401.451 Housing and Urban Development Regulations Relating to Housing and Urban... PROGRAM (MARK-TO-MARKET) Restructuring Plan § 401.451 PAE Physical Condition Analysis (PCA). (a) Review... of the project by means of a PCA. If the PAE finds any immediate threats to health and safety, the...

Joint Group Sparse PCA for Compressed Hyperspectral Imaging.

Science.gov (United States)

Khan, Zohaib; Shafait, Faisal; Mian, Ajmal

2015-12-01

A sparse principal component analysis (PCA) seeks a sparse linear combination of input features (variables), so that the derived features still explain most of the variations in the data. A group sparse PCA introduces structural constraints on the features in seeking such a linear combination. Collectively, the derived principal components may still require measuring all the input features. We present a joint group sparse PCA (JGSPCA) algorithm, which forces the basic coefficients corresponding to a group of features to be jointly sparse. Joint sparsity ensures that the complete basis involves only a sparse set of input features, whereas the group sparsity ensures that the structural integrity of the features is maximally preserved. We evaluate the JGSPCA algorithm on the problems of compressed hyperspectral imaging and face recognition. Compressed sensing results show that the proposed method consistently outperforms sparse PCA and group sparse PCA in reconstructing the hyperspectral scenes of natural and man-made objects. The efficacy of the proposed compressed sensing method is further demonstrated in band selection for face recognition.

PCA and Postoperative Pain Management After Orthopedic Surgeries

Directory of Open Access Journals (Sweden)

S.M. Hashemi

2016-08-01

Full Text Available Background: Patients often suffer from inadequate treatment of postoperative pain. The aim of this study was to investigate effect of PCA on postoperative pain management and patients’ satisfaction from use of PCA. Materials and Methods: In this prospective study, between 2010 to 2011, patients presented by orthopedic specialists to acute and chronic pain service of Akhtar Hospital. A satisfaction questionnaire was given on discharge to this patients, were asked to fill out it . Then collected by ward nurse. Results: patients’ satisfaction from pain relief with use of PCA was high ( 94.9% . In this patient pain relief at third day after surgery and require analgesic was low, significantly (p=0.0001. Significant patients’ satisfaction from effect of PCA in pain control and products support was high (p=0.0001.     Conclusion: Patient controlled analgesia is a safe, effective and noninvasive method for post operative pain management and in this study patients’ satisfaction for pain management was high for use of PCA and pain service. 

Dosimetric study of the different techniques to deal with respiratory motion for lung stereotactic radiotherapy

International Nuclear Information System (INIS)

Paumier, A.; Krhili, S.; Georgin-Mege, M.; Tuchais, C.; Cellier, P.; Crespeau, A.; Mesgouez, J.; Autret, D.; Lisbona, A.; Denis, F.

2012-01-01

Purpose. - To evaluate the different respiratory movement management techniques during irradiation of lung tumours. Patients and methods. - Seven patients with one or more primary or secondary lung lesions less than 5 cm (11 tumours in total) had three computed tomographies (CT): free-breathing, deep-inspiration breath hold using a spirometer, and 4-dimensional (4D). From these three acquisitions, five treatment plans were performed: free-breathing (reference method), deep-inspiration breath-hold, and three from the 4D CT: two breathing synchronized treatments (inspiration and expiration) and one treatment taking into account all the tumour motions (definition of the internal target volume [ITV]). Planning target volume (PTV) size and dose delivered to the lungs were compared. Results. - Mean PTV with the free-breathing modality was 83±28 cm 3 , which was significantly greater than any of the other techniques (P 3 ), and PTV with the deep-inspiration breath-hold, breathing synchronized inspiration and breathing synchronized expiration techniques were reduced by one third (50 to 54±24 to 26 cm 3 ). Deep-inspiration led to significantly increase the healthy lung volume compared to other methods (mean volume of 5500±1500 cm 3 versus 3540 to 3920 cm 3 , respectively, P < 0.0001). The volume of healthy lungs receiving at least 5 and 20 Gy (V5 and V5) were significantly higher with the free-breathing method than any of the other methods (P < 0.0001). The deep-inspiration breath-hold modality led to the lowest lung V5 and V20. Conclusion. - Deep-inspiration breath-hold technique provides the most significant dosimetric advantages: small PTV and large lung volume. However, patients must be able to hold 20 seconds of apnea. Respiratory gating also reduces the PTV, but its application often requires the implantation of fiducial, which limit its use. A 4-dimensional CT allows for a personalized and reduced PTV compared to free-breathing CT. (authors)

Lung tumor motion change during stereotactic body radiotherapy (SBRT): an evaluation using MRI

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Olivier, Kenneth R.; Li, Jonathan G.; Liu, Chihray; Newlin, Heather E.; Schmalfuss, Ilona; Kyogoku, Shinsuke; Dempsey, James F.

2014-01-01

The purpose of this study is to investigate changes in lung tumor internal target volume during stereotactic body radiotherapy treatment (SBRT) using magnetic resonance imaging (MRI). Ten lung cancer patients (13 tumors) undergoing SBRT (48 Gy over four consecutive days) were evaluated. Each patient underwent three lung MRI evaluations: before SBRT (MRI‐1), after fraction 3 of SBRT (MRI‐3), and three months after completion of SBRT (MRI‐3m). Each MRI consisted of T1‐weighted images in axial plane through the entire lung. A cone‐beam CT (CBCT) was taken before each fraction. On MRI and CBCT taken before fractions 1 and 3, gross tumor volume (GTV) was contoured and differences between the two volumes were compared. Median tumor size on CBCT before fractions 1 (CBCT‐1) and 3 (CBCT‐3) was 8.68 and 11.10 cm3, respectively. In 12 tumors, the GTV was larger on CBCT‐3 compared to CBCT‐1 (median enlargement, 1.56 cm3). Median tumor size on MRI‐1, MRI‐3, and MRI‐3m was 7.91, 11.60, and 3.33 cm3, respectively. In all patients, the GTV was larger on MRI‐3 compared to MRI‐1 (median enlargement, 1.54 cm3). In all patients, GTV was smaller on MRI‐3m compared to MRI‐1 (median shrinkage, 5.44 cm3). On CBCT and MRI, all patients showed enlargement of the GTV during the treatment week of SBRT, except for one patient who showed minimal shrinkage (0.86 cm3). Changes in tumor volume are unpredictable; therefore, motion and breathing must be taken into account during treatment planning, and image‐guided methods should be used, when treating with large fraction sizes. PACS number: 87.53.Ly PMID:24892328

Investigating the impact of audio instruction and audio-visual biofeedback for lung cancer radiation therapy

Science.gov (United States)

George, Rohini

Lung cancer accounts for 13% of all cancers in the Unites States and is the leading cause of deaths among both men and women. The five-year survival for lung cancer patients is approximately 15%.(ACS facts & figures) Respiratory motion decreases accuracy of thoracic radiotherapy during imaging and delivery. To account for respiration, generally margins are added during radiation treatment planning, which may cause a substantial dose delivery to normal tissues and increase the normal tissue toxicity. To alleviate the above-mentioned effects of respiratory motion, several motion management techniques are available which can reduce the doses to normal tissues, thereby reducing treatment toxicity and allowing dose escalation to the tumor. This may increase the survival probability of patients who have lung cancer and are receiving radiation therapy. However the accuracy of these motion management techniques are inhibited by respiration irregularity. The rationale of this thesis was to study the improvement in regularity of respiratory motion by breathing coaching for lung cancer patients using audio instructions and audio-visual biofeedback. A total of 331 patient respiratory motion traces, each four minutes in length, were collected from 24 lung cancer patients enrolled in an IRB-approved breathing-training protocol. It was determined that audio-visual biofeedback significantly improved the regularity of respiratory motion compared to free breathing and audio instruction, thus improving the accuracy of respiratory gated radiotherapy. It was also observed that duty cycles below 30% showed insignificant reduction in residual motion while above 50% there was a sharp increase in residual motion. The reproducibility of exhale based gating was higher than that of inhale base gating. Modeling the respiratory cycles it was found that cosine and cosine 4 models had the best correlation with individual respiratory cycles. The overall respiratory motion probability distribution

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

Energy Technology Data Exchange (ETDEWEB)

Mishra, Pankaj, E-mail: pankaj.mishra@varian.com; Mak, Raymond H.; Rottmann, Joerg; Bryant, Jonathan H.; Williams, Christopher L.; Berbeco, Ross I.; Lewis, John H. [Brigham and Women' s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States); Li, Ruijiang [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94305 (United States)

2014-08-15

Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model

Optimization of CNC end milling process parameters using PCA ...

African Journals Online (AJOL)

Optimization of CNC end milling process parameters using PCA-based Taguchi method. ... International Journal of Engineering, Science and Technology ... To meet the basic assumption of Taguchi method; in the present work, individual response correlations have been eliminated first by means of Principal Component ...

On the use of A PCA as a multichannel time analyzer

International Nuclear Information System (INIS)

Adib, M.; Abdelkawy, A.; Abuelela, M.; Habib, N.; Wahba, M.; Salama, F.

1992-01-01

PCA and PCA-11 software programmes have been used to utilize the operation of the nucleus personal computer analyzer PCA-8000 in its multichannel scaler (MCS) mode. The operating condition of PCA-8000 were selected to match the time-of-flight (TOF) spectrometer which is in operation at the ET-RR-1 reactor. The results of measuring the main parameters of PCA-8000 operating in its MCS mode showed that it can be successfully used as a multichannel time analyzer.5 fig

New genomic structure for prostate cancer specific gene PCA3 within BMCC1: implications for prostate cancer detection and progression.

Directory of Open Access Journals (Sweden)

Raymond A Clarke

Full Text Available The prostate cancer antigen 3 (PCA3/DD3 gene is a highly specific biomarker upregulated in prostate cancer (PCa. In order to understand the importance of PCA3 in PCa we investigated the organization and evolution of the PCA3 gene locus.We have employed cDNA synthesis, RTPCR and DNA sequencing to identify 4 new transcription start sites, 4 polyadenylation sites and 2 new differentially spliced exons in an extended form of PCA3. Primers designed from these novel PCA3 exons greatly improve RT-PCR based discrimination between PCa, PCa metastases and BPH specimens. Comparative genomic analyses demonstrated that PCA3 has only recently evolved in an anti-sense orientation within a second gene, BMCC1/PRUNE2. BMCC1 has been shown previously to interact with RhoA and RhoC, determinants of cellular transformation and metastasis, respectively. Using RT-PCR we demonstrated that the longer BMCC1-1 isoform - like PCA3 - is upregulated in PCa tissues and metastases and in PCa cell lines. Furthermore PCA3 and BMCC1-1 levels are responsive to dihydrotestosterone treatment.Upregulation of two new PCA3 isoforms in PCa tissues improves discrimination between PCa and BPH. The functional relevance of this specificity is now of particular interest given PCA3's overlapping association with a second gene BMCC1, a regulator of Rho signalling. Upregulation of PCA3 and BMCC1 in PCa has potential for improved diagnosis.

Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers.

Science.gov (United States)

Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Marino, Ada; Sorrentino, Alessandra; Di Carlo, Angelina; Autorino, Riccardo; Di Lorenzo, Giuseppe; Buonerba, Carlo; Altieri, Vincenzo; Mariano, Angela; Macchia, Vincenzo; Terracciano, Daniela

2012-08-16

Indication for prostate biopsy is presently mainly based on prostate-specific antigen (PSA) serum levels and digital-rectal examination (DRE). In view of the unsatisfactory accuracy of these two diagnostic exams, research has focused on novel markers to improve pre-biopsy prostate cancer detection, such as phi and PCA3. The purpose of this prospective study was to assess the diagnostic accuracy of phi and PCA3 for prostate cancer using biopsy as gold standard. Phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay) and other established biomarkers (tPSA, fPSA and %fPSA) were assessed before a 18-core prostate biopsy in a group of 251 subjects at their first biopsy. Values of %p2PSA and phi were significantly higher in patients with PCa compared with PCa-negative group (pphi and PCA3 are predictive of malignancy. In conclusion, %p2PSA, phi and PCA3 may predict a diagnosis of PCa in men undergoing their first prostate biopsy. PCA3 score is more useful in discriminating between HGPIN and non-cancer. Copyright © 2012 Elsevier B.V. All rights reserved.

Performance assessment of a programmable five degrees-of-freedom motion platform for quality assurance of motion management techniques in radiotherapy.

Science.gov (United States)

Huang, Chen-Yu; Keall, Paul; Rice, Adam; Colvill, Emma; Ng, Jin Aun; Booth, Jeremy T

2017-09-01

Inter-fraction and intra-fraction motion management methods are increasingly applied clinically and require the development of advanced motion platforms to facilitate testing and quality assurance program development. The aim of this study was to assess the performance of a 5 degrees-of-freedom (DoF) programmable motion platform HexaMotion (ScandiDos, Uppsala, Sweden) towards clinically observed tumor motion range, velocity, acceleration and the accuracy requirements of SABR prescribed in AAPM Task Group 142. Performance specifications for the motion platform were derived from literature regarding the motion characteristics of prostate and lung tumor targets required for real time motion management. The performance of the programmable motion platform was evaluated against (1) maximum range, velocity and acceleration (5 DoF), (2) static position accuracy (5 DoF) and (3) dynamic position accuracy using patient-derived prostate and lung tumor motion traces (3 DoF). Translational motion accuracy was compared against electromagnetic transponder measurements. Rotation was benchmarked with a digital inclinometer. The static accuracy and reproducibility for translation and rotation was quality assurance and commissioning of motion management systems in radiation oncology.

Permeability Estimation of Rock Reservoir Based on PCA and Elman Neural Networks

Science.gov (United States)

Shi, Ying; Jian, Shaoyong

2018-03-01

an intelligent method which based on fuzzy neural networks with PCA algorithm, is proposed to estimate the permeability of rock reservoir. First, the dimensionality reduction process is utilized for these parameters by principal component analysis method. Further, the mapping relationship between rock slice characteristic parameters and permeability had been found through fuzzy neural networks. The estimation validity and reliability for this method were tested with practical data from Yan’an region in Ordos Basin. The result showed that the average relative errors of permeability estimation for this method is 6.25%, and this method had the better convergence speed and more accuracy than other. Therefore, by using the cheap rock slice related information, the permeability of rock reservoir can be estimated efficiently and accurately, and it is of high reliability, practicability and application prospect.

Dosimetric Comparison of Real-Time MRI-Guided Tri-Cobalt-60 Versus Linear Accelerator-Based Stereotactic Body Radiation Therapy Lung Cancer Plans.

Science.gov (United States)

Wojcieszynski, Andrzej P; Hill, Patrick M; Rosenberg, Stephen A; Hullett, Craig R; Labby, Zacariah E; Paliwal, Bhudatt; Geurts, Mark W; Bayliss, R Adam; Bayouth, John E; Harari, Paul M; Bassetti, Michael F; Baschnagel, Andrew M

2017-06-01

Magnetic resonance imaging-guided radiation therapy has entered clinical practice at several major treatment centers. Treatment of early-stage non-small cell lung cancer with stereotactic body radiation therapy is one potential application of this modality, as some form of respiratory motion management is important to address. We hypothesize that magnetic resonance imaging-guided tri-cobalt-60 radiation therapy can be used to generate clinically acceptable stereotactic body radiation therapy treatment plans. Here, we report on a dosimetric comparison between magnetic resonance imaging-guided radiation therapy plans and internal target volume-based plans utilizing volumetric-modulated arc therapy. Ten patients with early-stage non-small cell lung cancer who underwent radiation therapy planning and treatment were studied. Following 4-dimensional computed tomography, patient images were used to generate clinically deliverable plans. For volumetric-modulated arc therapy plans, the planning tumor volume was defined as an internal target volume + 0.5 cm. For magnetic resonance imaging-guided plans, a single mid-inspiratory cycle was used to define a gross tumor volume, then expanded 0.3 cm to the planning tumor volume. Treatment plan parameters were compared. Planning tumor volumes trended larger for volumetric-modulated arc therapy-based plans, with a mean planning tumor volume of 47.4 mL versus 24.8 mL for magnetic resonance imaging-guided plans ( P = .08). Clinically acceptable plans were achievable via both methods, with bilateral lung V20, 3.9% versus 4.8% ( P = .62). The volume of chest wall receiving greater than 30 Gy was also similar, 22.1 versus 19.8 mL ( P = .78), as were all other parameters commonly used for lung stereotactic body radiation therapy. The ratio of the 50% isodose volume to planning tumor volume was lower in volumetric-modulated arc therapy plans, 4.19 versus 10.0 ( P guided tri-cobalt-60 radiation therapy is capable of delivering lung high

Theoretical analysis of the PCA experiment

International Nuclear Information System (INIS)

Minsart, G.

1980-01-01

A very brief description of the PCA-PVF facility is given, and the studied configurations are mentioned. The analysis of the experiment has been divided into two parts: study of the fission density distribution across the PCA core and neutronic analysis of the flux spectra and spatial distributions in the whole facility. For both parts, the procedure of calculation is explained: cross section sets, one- and two-dimensional models, group collapsing, choice of bucklings, ... . The obtained results are shortly compared with the measured values, and illustrated by a figure and several tables. The computations of the fission map in the PCA core yield results in good agreement with the experimental ones (within a few percents for nearly all points). The discrepancies observed for relative reaction rates and spectral indices of a series of threshold detectors at the selected locations in and between steel and iron layers in the water reflector are briefly discussed

Parent-Controlled PCA for Pain Management in Pediatric Oncology: Is it Safe?

OpenAIRE

Anghelescu, Doralina L.; Faughnan, Lane G.; Oakes, Linda L.; Windsor, Kelley B.; Pei, Deqing; Burgoyne, Laura L.

2012-01-01

Patient-controlled analgesia offers safe and effective pain control for children who can self-administer medication. Some children may not be candidates for PCA unless a proxy can administer doses. The safety of proxy-administered PCA has been studied, but the safety of parent-administered PCA in children with cancer has not been reported. In this study we compare the rate of complications in PCA by parent proxy versus PCA by clinician (nurse) proxy and self-administered PCA. Our pediatric in...

The potential role of respiratory motion management and image guidance in the reduction of severe toxicities following stereotactic ablative radiation therapy for patients with centrally located early stage non-small cell lung cancer or lung metastases

Directory of Open Access Journals (Sweden)

Alexander eChi

2014-06-01

Full Text Available Image guidance allows delivery of very high doses of radiation over a few fractions, known as stereotactic ablative radiotherapy (SABR. This treatment is associated with excellent outcome for early stage non-small cell lung cancer and metastases to the lungs. In the delivery of SABR, central location constantly poses a challenge due to the difficulty of adequately sparing critical thoracic structures that are immediately adjacent to the tumor if an ablative dose of radiation is to be delivered to the tumor target. As of current, various respiratory motion management and image guidance strategies can be used to ensure accurate tumor target localization prior and/ or during daily treatment, which allows for maximal and safe reduction of set up margins. The incorporation of both may lead to the most optimal normal tissue sparing and the most accurate SABR delivery. Here, the clinical outcome, treatment related toxicities, and the pertinent respiratory motion management/image guidance strategies reported in the current literature on SABR for central lung tumors are reviewed.

TH-CD-207A-05: Lung Surface Deformation Vector Fields Prediction by Monitoring Respiratory Surrogate Signals

International Nuclear Information System (INIS)

Nasehi Tehrani, J; Wang, J; McEwan, A

2016-01-01

Purpose: In this study, we developed and evaluated a method for predicting lung surface deformation vector fields (SDVFs) based on surrogate signals such as chest and abdomen motion at selected locations and spirometry measurements. Methods: A Patient-specific 3D triangular surface mesh of the lung region at end-expiration (EE) phase was obtained by threshold-based segmentation method. For each patient, a spirometer recorded the flow volume changes of the lungs; and 192 selected points at a regular spacing of 2cm X 2cm matrix points over a total area of 34cm X 24cm on the surface of chest and abdomen was used to detect chest wall motions. Preprocessing techniques such as QR factorization with column pivoting (QRCP) were employed to remove redundant observations of the chest and abdominal area. To create a statistical model between the lung surface and the corresponding surrogate signals, we developed a predictive model based on canonical ridge regression (CRR). Two unique weighting vectors were selected for each vertex on the surface of the lung, and they were optimized during the training process using the all other phases of 4D-CT except the end-inspiration (EI) phase. These parameters were employed to predict the vertices locations of a testing data set, which was the EI phase of 4D-CT. Results: For ten lung cancer patients, the deformation vector field of each vertex of lung surface mesh was estimated from the external motion at selected positions on the chest wall surface plus spirometry measurements. The average estimation of 98th percentile of error was less than 1 mm (AP= 0.85, RL= 0.61, and SI= 0.82). Conclusion: The developed predictive model provides a non-invasive approach to derive lung boundary condition. Together with personalized biomechanical respiration modelling, the proposed model can be used to derive the lung tumor motion during radiation therapy accurately from non-invasive measurements.

TH-CD-207A-05: Lung Surface Deformation Vector Fields Prediction by Monitoring Respiratory Surrogate Signals

Energy Technology Data Exchange (ETDEWEB)

Nasehi Tehrani, J; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States); McEwan, A [The University of Sydney, Sydney, New South Wales (Australia)

2016-06-15

Purpose: In this study, we developed and evaluated a method for predicting lung surface deformation vector fields (SDVFs) based on surrogate signals such as chest and abdomen motion at selected locations and spirometry measurements. Methods: A Patient-specific 3D triangular surface mesh of the lung region at end-expiration (EE) phase was obtained by threshold-based segmentation method. For each patient, a spirometer recorded the flow volume changes of the lungs; and 192 selected points at a regular spacing of 2cm X 2cm matrix points over a total area of 34cm X 24cm on the surface of chest and abdomen was used to detect chest wall motions. Preprocessing techniques such as QR factorization with column pivoting (QRCP) were employed to remove redundant observations of the chest and abdominal area. To create a statistical model between the lung surface and the corresponding surrogate signals, we developed a predictive model based on canonical ridge regression (CRR). Two unique weighting vectors were selected for each vertex on the surface of the lung, and they were optimized during the training process using the all other phases of 4D-CT except the end-inspiration (EI) phase. These parameters were employed to predict the vertices locations of a testing data set, which was the EI phase of 4D-CT. Results: For ten lung cancer patients, the deformation vector field of each vertex of lung surface mesh was estimated from the external motion at selected positions on the chest wall surface plus spirometry measurements. The average estimation of 98th percentile of error was less than 1 mm (AP= 0.85, RL= 0.61, and SI= 0.82). Conclusion: The developed predictive model provides a non-invasive approach to derive lung boundary condition. Together with personalized biomechanical respiration modelling, the proposed model can be used to derive the lung tumor motion during radiation therapy accurately from non-invasive measurements.

Motion Analysis Based on Invertible Rapid Transform

Directory of Open Access Journals (Sweden)

J. Turan

1999-06-01

Full Text Available This paper presents the results of a study on the use of invertible rapid transform (IRT for the motion estimation in a sequence of images. Motion estimation algorithms based on the analysis of the matrix of states (produced in the IRT calculation are described. The new method was used experimentally to estimate crowd and traffic motion from the image data sequences captured at railway stations and at high ways in large cities. The motion vectors may be used to devise a polar plot (showing velocity magnitude and direction for moving objects where the dominant motion tendency can be seen. The experimental results of comparison of the new motion estimation methods with other well known block matching methods (full search, 2D-log, method based on conventional (cross correlation (CC function or phase correlation (PC function for application of crowd motion estimation are also presented.

Using a cross-model loadings plot to identify protein spots causing 2-DE gels to become outliers in PCA

DEFF Research Database (Denmark)

Kristiansen, Luise Cederkvist; Jacobsen, Susanne; Jessen, Flemming

2010-01-01

The multivariate method PCA is an exploratory tool often used to get an overview of multivariate data, such as the quantified spot volumes of digitized 2-DE gels. PCA can reveal hidden structures present in the data, and thus enables identification of potential outliers and clustering. Based on PCA...

Stability and chaos of LMSER PCA learning algorithm

International Nuclear Information System (INIS)

Lv Jiancheng; Y, Zhang

2007-01-01

LMSER PCA algorithm is a principal components analysis algorithm. It is used to extract principal components on-line from input data. The algorithm has both stability and chaotic dynamic behavior under some conditions. This paper studies the local stability of the LMSER PCA algorithm via a corresponding deterministic discrete time system. Conditions for local stability are derived. The paper also explores the chaotic behavior of this algorithm. It shows that the LMSER PCA algorithm can produce chaos. Waveform plots, Lyapunov exponents and bifurcation diagrams are presented to illustrate the existence of chaotic behavior of this algorithm

Nonlinear PCA: characterizing interactions between modes of brain activity.

OpenAIRE

Friston, K; Phillips, J; Chawla, D; Büchel, C

2000-01-01

This paper presents a nonlinear principal component analysis (PCA) that identifies underlying sources causing the expression of spatial modes or patterns of activity in neuroimaging time-series. The critical aspect of this technique is that, in relation to conventional PCA, the sources can interact to produce (second-order) spatial modes that represent the modulation of one (first-order) spatial mode by another. This nonlinear PCA uses a simple neural network architecture that embodies a spec...

Tumor motion in lung cancers: An overview of four-dimensional radiotherapy treatment of lung cancers

Directory of Open Access Journals (Sweden)

Anusheel Munshi

2017-01-01

Full Text Available Most modern radiotherapy centers have adopted contouring based treatment. Sparing of the normal structures has been made more achievable than ever before by use of technologies such as Intensity Modulated Radiotherapy (IMRT and Image guided radiotherapy (IGRT. However, unlike, sites such as brain or head neck, thorax is a site in active motion, mostly contributed by patient's respiratory movement. 4 D radiotherapy, that addresses the issues of motion in thoracic tumours answers this critical question. The present article outlines the scope of need for 4 D radiotherapy and discusses the options available for 4 D treatments of cancer patients.

A state-based probabilistic model for tumor respiratory motion prediction

International Nuclear Information System (INIS)

Kalet, Alan; Sandison, George; Schmitz, Ruth; Wu Huanmei

2010-01-01

This work proposes a new probabilistic mathematical model for predicting tumor motion and position based on a finite state representation using the natural breathing states of exhale, inhale and end of exhale. Tumor motion was broken down into linear breathing states and sequences of states. Breathing state sequences and the observables representing those sequences were analyzed using a hidden Markov model (HMM) to predict the future sequences and new observables. Velocities and other parameters were clustered using a k-means clustering algorithm to associate each state with a set of observables such that a prediction of state also enables a prediction of tumor velocity. A time average model with predictions based on average past state lengths was also computed. State sequences which are known a priori to fit the data were fed into the HMM algorithm to set a theoretical limit of the predictive power of the model. The effectiveness of the presented probabilistic model has been evaluated for gated radiation therapy based on previously tracked tumor motion in four lung cancer patients. Positional prediction accuracy is compared with actual position in terms of the overall RMS errors. Various system delays, ranging from 33 to 1000 ms, were tested. Previous studies have shown duty cycles for latencies of 33 and 200 ms at around 90% and 80%, respectively, for linear, no prediction, Kalman filter and ANN methods as averaged over multiple patients. At 1000 ms, the previously reported duty cycles range from approximately 62% (ANN) down to 34% (no prediction). Average duty cycle for the HMM method was found to be 100% and 91 ± 3% for 33 and 200 ms latency and around 40% for 1000 ms latency in three out of four breathing motion traces. RMS errors were found to be lower than linear and no prediction methods at latencies of 1000 ms. The results show that for system latencies longer than 400 ms, the time average HMM prediction outperforms linear, no prediction, and the more

3D delivered dose assessment using a 4DCT-based motion model

Energy Technology Data Exchange (ETDEWEB)

Cai, Weixing; Hurwitz, Martina H.; Williams, Christopher L.; Dhou, Salam; Berbeco, Ross I.; Mishra, Pankaj, E-mail: wcai@lroc.harvard.edu, E-mail: jhlewis@lroc.harvard.edu; Lewis, John H., E-mail: wcai@lroc.harvard.edu, E-mail: jhlewis@lroc.harvard.edu [Brigham and Women’s Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115 (United States); Seco, Joao [Francis H. Burr Proton Therapy Center, Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02115 (United States)

2015-06-15

Purpose: The purpose of this work is to develop a clinically feasible method of calculating actual delivered dose distributions for patients who have significant respiratory motion during the course of stereotactic body radiation therapy (SBRT). Methods: A novel approach was proposed to calculate the actual delivered dose distribution for SBRT lung treatment. This approach can be specified in three steps. (1) At the treatment planning stage, a patient-specific motion model is created from planning 4DCT data. This model assumes that the displacement vector field (DVF) of any respiratory motion deformation can be described as a linear combination of some basis DVFs. (2) During the treatment procedure, 2D time-varying projection images (either kV or MV projections) are acquired, from which time-varying “fluoroscopic” 3D images of the patient are reconstructed using the motion model. The DVF of each timepoint in the time-varying reconstruction is an optimized linear combination of basis DVFs such that the 2D projection of the 3D volume at this timepoint matches the projection image. (3) 3D dose distribution is computed for each timepoint in the set of 3D reconstructed fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach was first validated using two modified digital extended cardio-torso (XCAT) phantoms with lung tumors and different respiratory motions. The estimated doses were compared to the dose that would be calculated for routine 4DCT-based planning and to the actual delivered dose that was calculated using “ground truth” XCAT phantoms at all timepoints. The approach was also tested using one set of patient data, which demonstrated the application of our method in a clinical scenario. Results: For the first XCAT phantom that has a mostly regular breathing pattern, the errors in 95% volume dose (D95) are 0.11% and 0.83%, respectively for 3D fluoroscopic images

3D delivered dose assessment using a 4DCT-based motion model

International Nuclear Information System (INIS)

Cai, Weixing; Hurwitz, Martina H.; Williams, Christopher L.; Dhou, Salam; Berbeco, Ross I.; Mishra, Pankaj; Lewis, John H.; Seco, Joao

2015-01-01

Purpose: The purpose of this work is to develop a clinically feasible method of calculating actual delivered dose distributions for patients who have significant respiratory motion during the course of stereotactic body radiation therapy (SBRT). Methods: A novel approach was proposed to calculate the actual delivered dose distribution for SBRT lung treatment. This approach can be specified in three steps. (1) At the treatment planning stage, a patient-specific motion model is created from planning 4DCT data. This model assumes that the displacement vector field (DVF) of any respiratory motion deformation can be described as a linear combination of some basis DVFs. (2) During the treatment procedure, 2D time-varying projection images (either kV or MV projections) are acquired, from which time-varying “fluoroscopic” 3D images of the patient are reconstructed using the motion model. The DVF of each timepoint in the time-varying reconstruction is an optimized linear combination of basis DVFs such that the 2D projection of the 3D volume at this timepoint matches the projection image. (3) 3D dose distribution is computed for each timepoint in the set of 3D reconstructed fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach was first validated using two modified digital extended cardio-torso (XCAT) phantoms with lung tumors and different respiratory motions. The estimated doses were compared to the dose that would be calculated for routine 4DCT-based planning and to the actual delivered dose that was calculated using “ground truth” XCAT phantoms at all timepoints. The approach was also tested using one set of patient data, which demonstrated the application of our method in a clinical scenario. Results: For the first XCAT phantom that has a mostly regular breathing pattern, the errors in 95% volume dose (D95) are 0.11% and 0.83%, respectively for 3D fluoroscopic images

PCA3 Silencing Sensitizes Prostate Cancer Cells to Enzalutamide-mediated Androgen Receptor Blockade.

Science.gov (United States)

Özgür, Emre; Celik, Ayca Iribas; Darendeliler, Emin; Gezer, Ugur

2017-07-01

Prostate cancer (PCa) is an androgen-dependent disease. Novel anti-androgens (i.e. enzalutamide) have recently been developed for the treatment of patients with metastatic castration-resistant prostate cancer (CRPC). Evidence is accumulating that prostate cancer antigen 3 (PCA3) is involved in androgen receptor (AR) signaling. Here, in combination with enzalutamide-mediated AR blockade, we investigated the effect of PCA3 targeting on the viability of PCa cells. In hormone-sensitive LNCaP cells, AR-overexpressing LNCaP-AR + cells and VCaP cells (representing CRPC), PCA3 was silenced using siRNA oligonucleotides. Gene expression and cell viability was assessed in PCA3-silenced and/or AR-blocked cells. PCA3 targeting reduced the expression of AR-related genes (i.e. prostate-specific antigen (PSA) and prostate-specific transcript 1 (non-protein coding) (PCGEM1)) and potentiated the effect of enzalutamide. Proliferation of PCa cells was suppressed upon PCA3 silencing with a greater effect in LNCaP-AR + cells. Furthermore, PCA3 silencing sensitized PCa cells to enzalutamide-induced loss of cell growth. PCA3, as a therapeutic target in PCa, might be used to potentiate AR antagonists. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

The in-reactor deformation of the PCA alloy

International Nuclear Information System (INIS)

Puigh, R.J.

1986-04-01

The swelling and in-reactor creep behaviors of the PCA alloy have been determined from the irradiation of pressurized tube specimens in the FFTF reactor. These data have been obtained to a peak neutron fluence corresponding to approximately 80 dpa in the FFTF reactor for irradiation temperatures between 400 and 750 0 C. Diametral measurements performed on the unstressed specimens indicate the possible onset of swelling in the PCA alloy for irradiation temperatures between 400 and 550 0 C and at a neutron fluence corresponding to ∼50 dpa. The creep data suggest a non-linear fluence dependence and linear stress dependence (for hoop stresses less than 100 MPa) which is consistent with the in-reactor creep behavior of many cold worked austenitic stainless steels. These PCA creep data are compared to available 316 SS in-reactor creep data. The in-reactor creep strains for PCA are significantly less than observed in 20% cold worked 316 SS over the temperature ranges and fluences investigated

[An improved low spectral distortion PCA fusion method].

Science.gov (United States)

Peng, Shi; Zhang, Ai-Wu; Li, Han-Lun; Hu, Shao-Xing; Meng, Xian-Gang; Sun, Wei-Dong

2013-10-01

Aiming at the spectral distortion produced in PCA fusion process, the present paper proposes an improved low spectral distortion PCA fusion method. This method uses NCUT (normalized cut) image segmentation algorithm to make a complex hyperspectral remote sensing image into multiple sub-images for increasing the separability of samples, which can weaken the spectral distortions of traditional PCA fusion; Pixels similarity weighting matrix and masks were produced by using graph theory and clustering theory. These masks are used to cut the hyperspectral image and high-resolution image into some sub-region objects. All corresponding sub-region objects between the hyperspectral image and high-resolution image are fused by using PCA method, and all sub-regional integration results are spliced together to produce a new image. In the experiment, Hyperion hyperspectral data and Rapid Eye data were used. And the experiment result shows that the proposed method has the same ability to enhance spatial resolution and greater ability to improve spectral fidelity performance.

Analyzing locomotion synthesis with feature-based motion graphs.

Science.gov (United States)

Mahmudi, Mentar; Kallmann, Marcelo

2013-05-01

We propose feature-based motion graphs for realistic locomotion synthesis among obstacles. Among several advantages, feature-based motion graphs achieve improved results in search queries, eliminate the need of postprocessing for foot skating removal, and reduce the computational requirements in comparison to traditional motion graphs. Our contributions are threefold. First, we show that choosing transitions based on relevant features significantly reduces graph construction time and leads to improved search performances. Second, we employ a fast channel search method that confines the motion graph search to a free channel with guaranteed clearance among obstacles, achieving faster and improved results that avoid expensive collision checking. Lastly, we present a motion deformation model based on Inverse Kinematics applied over the transitions of a solution branch. Each transition is assigned a continuous deformation range that does not exceed the original transition cost threshold specified by the user for the graph construction. The obtained deformation improves the reachability of the feature-based motion graph and in turn also reduces the time spent during search. The results obtained by the proposed methods are evaluated and quantified, and they demonstrate significant improvements in comparison to traditional motion graph techniques.

Region of interest-based versus whole-lung segmentation-based approach for MR lung perfusion quantification in 2-year-old children after congenital diaphragmatic hernia repair

International Nuclear Information System (INIS)

Weis, M.; Sommer, V.; Hagelstein, C.; Schoenberg, S.O.; Neff, K.W.; Zoellner, F.G.; Zahn, K.; Schaible, T.

2016-01-01

With a region of interest (ROI)-based approach 2-year-old children after congenital diaphragmatic hernia (CDH) show reduced MR lung perfusion values on the ipsilateral side compared to the contralateral. This study evaluates whether results can be reproduced by segmentation of whole-lung and whether there are differences between the ROI-based and whole-lung measurements. Using dynamic contrast-enhanced (DCE) MRI, pulmonary blood flow (PBF), pulmonary blood volume (PBV) and mean transit time (MTT) were quantified in 30 children after CDH repair. Quantification results of an ROI-based (six cylindrical ROIs generated of five adjacent slices per lung-side) and a whole-lung segmentation approach were compared. In both approaches PBF and PBV were significantly reduced on the ipsilateral side (p always <0.0001). In ipsilateral lungs, PBF of the ROI-based and the whole-lung segmentation-based approach was equal (p=0.50). In contralateral lungs, the ROI-based approach significantly overestimated PBF in comparison to the whole-lung segmentation approach by approximately 9.5 % (p=0.0013). MR lung perfusion in 2-year-old children after CDH is significantly reduced ipsilaterally. In the contralateral lung, the ROI-based approach significantly overestimates perfusion, which can be explained by exclusion of the most ventral parts of the lung. Therefore whole-lung segmentation should be preferred. (orig.)

Region of interest-based versus whole-lung segmentation-based approach for MR lung perfusion quantification in 2-year-old children after congenital diaphragmatic hernia repair

Energy Technology Data Exchange (ETDEWEB)

Weis, M.; Sommer, V.; Hagelstein, C.; Schoenberg, S.O.; Neff, K.W. [Heidelberg University, Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany); Zoellner, F.G. [Heidelberg University, Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Mannheim (Germany); Zahn, K. [University of Heidelberg, Department of Paediatric Surgery, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany); Schaible, T. [Heidelberg University, Department of Paediatrics, University Medical Center Mannheim, Medical Faculty Mannheim, Mannheim (Germany)

2016-12-15

With a region of interest (ROI)-based approach 2-year-old children after congenital diaphragmatic hernia (CDH) show reduced MR lung perfusion values on the ipsilateral side compared to the contralateral. This study evaluates whether results can be reproduced by segmentation of whole-lung and whether there are differences between the ROI-based and whole-lung measurements. Using dynamic contrast-enhanced (DCE) MRI, pulmonary blood flow (PBF), pulmonary blood volume (PBV) and mean transit time (MTT) were quantified in 30 children after CDH repair. Quantification results of an ROI-based (six cylindrical ROIs generated of five adjacent slices per lung-side) and a whole-lung segmentation approach were compared. In both approaches PBF and PBV were significantly reduced on the ipsilateral side (p always <0.0001). In ipsilateral lungs, PBF of the ROI-based and the whole-lung segmentation-based approach was equal (p=0.50). In contralateral lungs, the ROI-based approach significantly overestimated PBF in comparison to the whole-lung segmentation approach by approximately 9.5 % (p=0.0013). MR lung perfusion in 2-year-old children after CDH is significantly reduced ipsilaterally. In the contralateral lung, the ROI-based approach significantly overestimates perfusion, which can be explained by exclusion of the most ventral parts of the lung. Therefore whole-lung segmentation should be preferred. (orig.)

Motion Learning Based on Bayesian Program Learning

Directory of Open Access Journals (Sweden)

Cheng Meng-Zhen

2017-01-01

Full Text Available The concept of virtual human has been highly anticipated since the 1980s. By using computer technology, Human motion simulation could generate authentic visual effect, which could cheat human eyes visually. Bayesian Program Learning train one or few motion data, generate new motion data by decomposing and combining. And the generated motion will be more realistic and natural than the traditional one.In this paper, Motion learning based on Bayesian program learning allows us to quickly generate new motion data, reduce workload, improve work efficiency, reduce the cost of motion capture, and improve the reusability of data.

SU-G-BRA-13: An Advanced Deformable Lung Phantom for Analyzing the Dosimetric Impact of Respiratory Motion

International Nuclear Information System (INIS)

Shin, D; Kang, S; Kim, D; Kim, T; Kim, K; Cho, M; Suh, T

2016-01-01

Purpose: The difference between three-dimensional (3D) and four-dimensional (4D) dose is affected by factors such as tumor size and motion. To quantitatively analyze the effects of these factors, a phantom that can independently control for each factor is required. The purpose of this study is to develop a deformable lung phantom with the above attributes and evaluate characteristics. Methods: A phantom was designed to simulate diaphragm motion with amplitude in the range 1 to 7 cm and various periods of regular breathing. To simulate different size tumors, tumors were produced by pouring liquid silicone into custom molds created by a 3D printer. The accuracy of phantom diaphragm motion was assessed using calipers and protractor. To control tumor motion, tumor trajectories were evaluated using 4D computed tomography (CT), and diaphragm-tumor correlation curve was calculated by curve fitting method. Three-dimensional dose and 4D dose were calculated and compared according to tumor motion. Results: The accuracy of phantom diaphragm motion was less than 1 mm. Maximum tumor motion amplitudes in the left-right and anterior-posterior directions were 0.08 and 0.12 cm, respectively, in a 10 cm"3 tumor, and 0.06 and 0.27 cm, respectively, in a 90 cm"3 tumor. The diaphragm-tumor correlation curve showed that tumor motion in the superior-inferior direction was increased with increasing diaphragm motion. In the 10 cm"3 tumor, the tumor motion was larger than the 90 cm"3 tumor. According to tumor motion, variation of dose difference between 3D and 4D was identified. Conclusion: The developed phantom can independently control factors such as tumor size and motion. In potentially, this phantom can be used to quantitatively analyze the dosimetric impact of respiratory motion according to the factors that influence the difference between 3D and 4D dose. This research was supported by the Mid-career Researcher Program through NRF funded by the Ministry of Science, ICT & Future

Innovative Comparison of Transient Ignition Temperature at the Booster Interface, New Stainless Steel Pyrovalve Primer Chamber Assembly "V" (PCA) Design Versus the Current Aluminum "Y" PCA Design

Science.gov (United States)

Saulsberry, Regor L.; McDougle, Stephen H.; Garcia,Roberto; Johnson, Kenneth L.; Sipes, William; Rickman, Steven; Hosangadi, Ashvin

2011-01-01

An assessment of four spacecraft pyrovalve anomalies that occurred during ground testing was conducted by the NASA Engineering & Safety Center (NESC) in 2008. In all four cases, a common aluminum (Al) primer chamber assembly (PCA) was used with dual NASA Standard Initiators (NSIs) and the nearly simultaneous (separated by less than 80 microseconds) firing of both initiators failed to ignite the booster charge. The results of the assessment and associated test program were reported in AIAA Paper AIAA-2008-4798, NESC Independent Assessment of Pyrovalve Ground Test Anomalies. As a result of the four Al PCA anomalies, and the test results and findings of the NESC assessment, the Mars Science Laboratory (MSL) project team decided to make changes to the PCA. The material for the PCA body was changed from aluminum (Al) to stainless steel (SS) to avoid melting, distortion, and potential leakage of the NSI flow passages when the device functioned. The flow passages, which were interconnected in a Y-shaped configuration (Y-PCA) in the original design, were changed to a V-shaped configuration (V-PCA). The V-shape was used to more efficiently transfer energy from the NSIs to the booster. Development and qualification testing of the new design clearly demonstrated faster booster ignition times compared to the legacy AL Y-PCA design. However, the final NESC assessment report recommended that the SS V-PCA be experimentally characterized and quantitatively compared to the Al Y-PCA design. This data was deemed important for properly evaluating the design options for future NASA projects. This test program has successfully quantified the improvement of the SS V-PCA over the Al Y-PCA. A phase B of the project was also conducted and evaluated the effect of firing command skew and enlargement of flame channels to further assist spacecraft applications.

WE-AB-303-11: Verification of a Deformable 4DCT Motion Model for Lung Tumor Tracking Using Different Driving Surrogates

Energy Technology Data Exchange (ETDEWEB)

Woelfelschneider, J [University Hospital Erlangen, Erlangen, DE (Germany); Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, DE (Germany); Seregni, M; Fassi, A; Baroni, G; Riboldi, M [Politecnico di Milano, Milano (Italy); Bert, C [University Hospital Erlangen, Erlangen, DE (Germany); Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, DE (Germany); GSI - Helmholtz Centre for Heavy Ion Research, Darmstadt, DE (Germany)

2015-06-15

Purpose: Tumor tracking is an advanced technique to treat intra-fractionally moving tumors. The aim of this study is to validate a surrogate-driven model based on four-dimensional computed tomography (4DCT) that is able to predict CT volumes corresponding to arbitrary respiratory states. Further, the comparison of three different driving surrogates is evaluated. Methods: This study is based on multiple 4DCTs of two patients treated for bronchial carcinoma and metastasis. Analyses for 18 additional patients are currently ongoing. The motion model was estimated from the planning 4DCT through deformable image registration. To predict a certain phase of a follow-up 4DCT, the model considers for inter-fractional variations (baseline correction) and intra-fractional respiratory parameters (amplitude and phase) derived from surrogates. In this evaluation, three different approaches were used to extract the motion surrogate: for each 4DCT phase, the 3D thoraco-abdominal surface motion, the body volume and the anterior-posterior motion of a virtual single external marker defined on the sternum were investigated. The estimated volumes resulting from the model were compared to the ground-truth clinical 4DCTs using absolute HU differences in the lung volume and landmarks localized using the Scale Invariant Feature Transform (SIFT). Results: The results show absolute HU differences between estimated and ground-truth images with median values limited to 55 HU and inter-quartile ranges (IQR) lower than 100 HU. Median 3D distances between about 1500 matching landmarks are below 2 mm for 3D surface motion and body volume methods. The single marker surrogates Result in increased median distances up to 0.6 mm. Analyses for the extended database incl. 20 patients are currently in progress. Conclusion: The results depend mainly on the image quality of the initial 4DCTs and the deformable image registration. All investigated surrogates can be used to estimate follow-up 4DCT phases

A Hold-out method to correct PCA variance inflation

DEFF Research Database (Denmark)

Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Hansen, Lars Kai

2012-01-01

In this paper we analyze the problem of variance inflation experienced by the PCA algorithm when working in an ill-posed scenario where the dimensionality of the training set is larger than its sample size. In an earlier article a correction method based on a Leave-One-Out (LOO) procedure...

PRINCIPAL COMPONENT ANALYSIS (PCA DAN APLIKASINYA DENGAN SPSS

Directory of Open Access Journals (Sweden)

Hermita Bus Umar

2009-03-01

Full Text Available PCA (Principal Component Analysis are statistical techniques applied to a single set of variables when the researcher is interested in discovering which variables in the setform coherent subset that are relativity independent of one another.Variables that are correlated with one another but largely independent of other subset of variables are combined into factors. The Coals of PCA to which each variables is explained by each dimension. Step in PCA include selecting and mean measuring a set of variables, preparing the correlation matrix, extracting a set offactors from the correlation matrixs. Rotating the factor to increase interpretabilitv and interpreting the result.

SVD vs PCA: Comparison of Performance in an Imaging Spectrometer

Directory of Open Access Journals (Sweden)

Wilma Oblefias

2004-12-01

Full Text Available The calculation of basis spectra from a spectral library is an important prerequisite of any compact imaging spectrometer. In this paper, we compare the basis spectra computed by singular-value decomposition (SVD and principal component analysis (PCA in terms of estimation performance with respect to resolution, presence of noise, intensity variation, and quantization error. Results show that SVD is robust in intensity variation while PCA is not. However, PCA performs better with signals of low signal-to-noise ratio. No significant difference is seen between SVD and PCA in terms of resolution and quantization error.

Lip motion recognition of speaker based on SIFT%基于SIFT的说话人唇动识别

Institute of Scientific and Technical Information of China (English)

马新军; 吴晨晨; 仲乾元; 李园园

2017-01-01

Aiming at the problem that the lip feature dimension is too high and sensitive to the scale space,a technique based on the Scale-Invariant Feature Transform (SIFT) algorithm was proposed to carry out the speaker authentication.Firstly,a simple video frame image neat algorithm was proposed to adjust the length of the lip video to the same length,and the representative lip motion pictures were extracted.Then,a new algorithm based on key points of SIFT was proposed to extract the texture and motion features.After the integration of Principal Component Analysis (PCA) algorithm,the typical lip motion features were obtained for authentication.Finally,a simple classification algorithm was presented according to the obtained features.The experimental results show that compared to the common Local Binary Pattern (LBP) feature and the Histogram of Oriental Gradient (HOG) feature,the False Acceptance Rate (FAR) and False Rejection Rate (FRR) of the proposed feature extraction algorithm are better,which proves that the whole speaker lip motion recognition algorithm is effective and can get the ideal results.%针对唇部特征提取维度过高以及对尺度空间敏感的问题,提出了一种基于尺度不变特征变换(SIFT)算法作特征提取来进行说话人身份认证的技术.首先,提出了一种简单的视频帧图片规整算法,将不同长度的唇动视频规整到同一的长度,提取出具有代表性的唇动图片;然后,提出一种在SIFT关键点的基础上,进行纹理和运动特征的提取算法,并经过主成分分析(PCA)算法的整合,最终得到具有代表性的唇动特征进行认证;最后,根据所得到的特征,提出了一种简单的分类算法.实验结果显示,和常见的局部二元模式(LBP)特征和方向梯度直方图(HOG)特征相比较,该特征提取算法的错误接受率(FAR)和错误拒绝率(FRR)表现更佳.说明整个说话人唇动特征识别算法是有效的,能够得到较为理想的结果.

Application of PCA-LDA method to determine the geographical origin of tea based on determination of stable isotopes and multi-elements

International Nuclear Information System (INIS)

Yuan Yuwei; Zhang Yongzhi; Yang Guiling; Zhang Zhiheng; Fu Haiyan; Han Wenyan; Li Shufang

2013-01-01

The ratio of stable isotope and concentration of multi-element in tea was determinated with isotope ratio mass spectrometry (IRMS) and inductively coupled plasma mass spectrometry (ICP-MS). Pattern recognition techniques with principal component analysis (PCA) and linear discriminant analysis (LDA) were used to classify the geographical origins of tea from Fujian, Shandong and Zhejiang province, and Yuyao, Jinhua and Xihu region of Zhejiang. The results showed the values of δ"1"5N, δ"1"3C, δD, δ"1"8O and the ratios of "2"0"6Pb/"2"0"7Pb, "2"0"8Pb/"2"0"6Pb and "8"7Sr/"8"6Sr in tea samples were different from different origins. There was also large variable for the concentrations of 27 mineral elements, such as Li, Be, Na and so on, with a specific character of origin. The method of PCA could be used to classify the geographical origin of tea from different origins but with a cross in the scatter plot. However, PCA combining with LDA could gave correct assignation percentages of 99% for the tea samples among Fujian, Shandong and Zhejiang provinces, and 87% for the tea samples among Yuyao, Jinhua and Xihu region of Zhejiang. These results revealed that it was possible and feasible to classify the geographical origin of tea by the method of PCA-LDA based on the determination of isotopes and multi-elements. (authors)

Learning Motion Features for Example-Based Finger Motion Estimation for Virtual Characters

Science.gov (United States)

Mousas, Christos; Anagnostopoulos, Christos-Nikolaos

2017-09-01

This paper presents a methodology for estimating the motion of a character's fingers based on the use of motion features provided by a virtual character's hand. In the presented methodology, firstly, the motion data is segmented into discrete phases. Then, a number of motion features are computed for each motion segment of a character's hand. The motion features are pre-processed using restricted Boltzmann machines, and by using the different variations of semantically similar finger gestures in a support vector machine learning mechanism, the optimal weights for each feature assigned to a metric are computed. The advantages of the presented methodology in comparison to previous solutions are the following: First, we automate the computation of optimal weights that are assigned to each motion feature counted in our metric. Second, the presented methodology achieves an increase (about 17%) in correctly estimated finger gestures in comparison to a previous method.

Imaging network level language recovery after left PCA stroke.

Science.gov (United States)

Sebastian, Rajani; Long, Charltien; Purcell, Jeremy J; Faria, Andreia V; Lindquist, Martin; Jarso, Samson; Race, David; Davis, Cameron; Posner, Joseph; Wright, Amy; Hillis, Argye E

2016-05-11

The neural mechanisms that support aphasia recovery are not yet fully understood. Our goal was to evaluate longitudinal changes in naming recovery in participants with posterior cerebral artery (PCA) stroke using a case-by-case analysis. Using task based and resting state functional magnetic resonance imaging (fMRI) and detailed language testing, we longitudinally studied the recovery of the naming network in four participants with PCA stroke with naming deficits at the acute (0 week), sub acute (3-5 weeks), and chronic time point (5-7 months) post stroke. Behavioral and imaging analyses (task related and resting state functional connectivity) were carried out to elucidate longitudinal changes in naming recovery. Behavioral and imaging analysis revealed that an improvement in naming accuracy from the acute to the chronic stage was reflected by increased connectivity within and between left and right hemisphere "language" regions. One participant who had persistent moderate naming deficit showed weak and decreasing connectivity longitudinally within and between left and right hemisphere language regions. These findings emphasize a network view of aphasia recovery, and show that the degree of inter- and intra- hemispheric balance between the language-specific regions is necessary for optimal recovery of naming, at least in participants with PCA stroke.

A method for selection of beam angles robust to intra-fractional motion in proton therapy of lung cancer

DEFF Research Database (Denmark)

Casares-Magaz, Oscar; Toftegaard, Jakob; Muren, Ludvig P.

2014-01-01

that are robust to patient-specific patterns of intra-fractional motion. Material and methods. Using four-dimensional computed tomography (4DCT) images of three lung cancer patients we evaluated the impact of the WEPL changes on target dose coverage for a series of coplanar single-beam plans. The plans were...... reduction was associated with the mean difference between the WEPL and the phase-averaged WEPL computed for all beam rays across all possible gantry-couch angle combinations. Results. The gantry-couch angle maps showed areas of both high and low WEPL variation, with overall quite similar patterns yet...... presented a 4DCT-based method to quantify WEPL changes during the breathing cycle. The method identified proton field gantry-couch angle combinations that were either sensitive or robust to WEPL changes. WEPL variations along the beam path were associated with target under-dosage....

A method for volumetric imaging in radiotherapy using single x-ray projection

International Nuclear Information System (INIS)

Xu, Yuan; Yan, Hao; Ouyang, Luo; Wang, Jing; Jiang, Steve B.; Jia, Xun; Zhou, Linghong; Cervino, Laura

2015-01-01

Purpose: It is an intriguing problem to generate an instantaneous volumetric image based on the corresponding x-ray projection. The purpose of this study is to develop a new method to achieve this goal via a sparse learning approach. Methods: To extract motion information hidden in projection images, the authors partitioned a projection image into small rectangular patches. The authors utilized a sparse learning method to automatically select patches that have a high correlation with principal component analysis (PCA) coefficients of a lung motion model. A model that maps the patch intensity to the PCA coefficients was built along with the patch selection process. Based on this model, a measured projection can be used to predict the PCA coefficients, which are then further used to generate a motion vector field and hence a volumetric image. The authors have also proposed an intensity baseline correction method based on the partitioned projection, in which the first and the second moments of pixel intensities at a patch in a simulated projection image are matched with those in a measured one via a linear transformation. The proposed method has been validated in both simulated data and real phantom data. Results: The algorithm is able to identify patches that contain relevant motion information such as the diaphragm region. It is found that an intensity baseline correction step is important to remove the systematic error in the motion prediction. For the simulation case, the sparse learning model reduced the prediction error for the first PCA coefficient to 5%, compared to the 10% error when sparse learning was not used, and the 95th percentile error for the predicted motion vector was reduced from 2.40 to 0.92 mm. In the phantom case with a regular tumor motion, the predicted tumor trajectory was successfully reconstructed with a 0.82 mm error for tumor center localization compared to a 1.66 mm error without using the sparse learning method. When the tumor motion

Two-dimensional PCA-based human gait identification

Science.gov (United States)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

Tissue Feature-Based and Segmented Deformable Image Registration for Improved Modeling of Shear Movement of Lungs

International Nuclear Information System (INIS)

Xie Yaoqin; Chao Ming; Xing Lei

2009-01-01

Purpose: To report a tissue feature-based image registration strategy with explicit inclusion of the differential motions of thoracic structures. Methods and Materials: The proposed technique started with auto-identification of a number of corresponding points with distinct tissue features. The tissue feature points were found by using the scale-invariant feature transform method. The control point pairs were then sorted into different 'colors' according to the organs in which they resided and used to model the involved organs individually. A thin-plate spline method was used to register a structure characterized by the control points with a given 'color.' The proposed technique was applied to study a digital phantom case and 3 lung and 3 liver cancer patients. Results: For the phantom case, a comparison with the conventional thin-plate spline method showed that the registration accuracy was markedly improved when the differential motions of the lung and chest wall were taken into account. On average, the registration error and standard deviation of the 15 points against the known ground truth were reduced from 3.0 to 0.5 mm and from 1.5 to 0.2 mm, respectively, when the new method was used. A similar level of improvement was achieved for the clinical cases. Conclusion: The results of our study have shown that the segmented deformable approach provides a natural and logical solution to model the discontinuous organ motions and greatly improves the accuracy and robustness of deformable registration.

4D-CT-based target volume definition in stereotactic radiotherapy of lung tumours: Comparison with a conventional technique using individual margins

International Nuclear Information System (INIS)

Hof, Holger; Rhein, Bernhard; Haering, Peter; Kopp-Schneider, Annette; Debus, Juergen; Herfarth, Klaus

2009-01-01

Purpose: To investigate the dosimetric benefit of integration of 4D-CT in the planning target volume (PTV) definition process compared to conventional PTV definition using individual margins in stereotactic body radiotherapy (SBRT) of lung tumours. Material and methods: Two different PTVs were defined: PTV conv consisting of the helical-CT-based clinical target volume (CTV) enlarged isotropically for each spatial direction by the individually measured amount of motion in the 4D-CT, and PTV 4D encompassing the CTVs defined in the 4D-CT phases displaying the extremes of the tumour position. Tumour motion as well as volumetric and dosimetric differences and relations of both PTVs were evaluated. Results: Volumetric examinations revealed a significant reduction of the mean PTV by 4D-CT from 57.7 to 40.7 cm 3 (31%) (p 4D in PTV conv (r = -0.69, 90% confidence limits: -0.87 and -0.34, p = 0.007). Mean lung dose (MLD) was decreased significantly by 17% (p < 0.001). Conclusions: In SBRT of lung tumours the mere use of individual margins for target volume definition cannot compensate for the additional effects that the implementation of 4D-CT phases can offer.

Motion-compensated cone beam computed tomography using a conjugate gradient least-squares algorithm and electrical impedance tomography imaging motion data.

Science.gov (United States)

Pengpen, T; Soleimani, M

2015-06-13

Cone beam computed tomography (CBCT) is an imaging modality that has been used in image-guided radiation therapy (IGRT). For applications such as lung radiation therapy, CBCT images are greatly affected by the motion artefacts. This is mainly due to low temporal resolution of CBCT. Recently, a dual modality of electrical impedance tomography (EIT) and CBCT has been proposed, in which the high temporal resolution EIT imaging system provides motion data to a motion-compensated algebraic reconstruction technique (ART)-based CBCT reconstruction software. High computational time associated with ART and indeed other variations of ART make it less practical for real applications. This paper develops a motion-compensated conjugate gradient least-squares (CGLS) algorithm for CBCT. A motion-compensated CGLS offers several advantages over ART-based methods, including possibilities for explicit regularization, rapid convergence and parallel computations. This paper for the first time demonstrates motion-compensated CBCT reconstruction using CGLS and reconstruction results are shown in limited data CBCT considering only a quarter of the full dataset. The proposed algorithm is tested using simulated motion data in generic motion-compensated CBCT as well as measured EIT data in dual EIT-CBCT imaging. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Quality of Life and Sexual Health in the Aging of PCa Survivors.

Science.gov (United States)

Gacci, Mauro; Baldi, Elisabetta; Tamburrino, Lara; Detti, Beatrice; Livi, Lorenzo; De Nunzio, Cosimo; Tubaro, Andrea; Gravas, Stavros; Carini, Marco; Serni, Sergio

2014-01-01

Prostate cancer (PCa) is the most common malignancy in elderly men. The progressive ageing of the world male population will further increase the need for tailored assessment and treatment of PCa patients. The determinant role of androgens and sexual hormones for PCa growth and progression has been established. However, several trials on androgens and PCa are recently focused on urinary continence, quality of life, and sexual function, suggesting a new point of view on the whole endocrinological aspect of PCa. During aging, metabolic syndrome, including diabetes, hypertension, dyslipidemia, and central obesity, can be associated with a chronic, low-grade inflammation of the prostate and with changes in the sex steroid pathways. These factors may affect both the carcinogenesis processes and treatment outcomes of PCa. Any treatment for PCa can have a long-lasting negative impact on quality of life and sexual health, which should be assessed by validated self-reported questionnaires. In particular, sexual health, urinary continence, and bowel function can be worsened after prostatectomy, radiotherapy, or hormone treatment, mostly in the elderly population. In the present review we summarized the current knowledge on the role of hormones, metabolic features, and primary treatments for PCa on the quality of life and sexual health of elderly Pca survivors.

PCA-based approach for subtracting thermal background emission in high-contrast imaging data

Science.gov (United States)

Hunziker, S.; Quanz, S. P.; Amara, A.; Meyer, M. R.

2018-03-01

Aims.Ground-based observations at thermal infrared wavelengths suffer from large background radiation due to the sky, telescope and warm surfaces in the instrument. This significantly limits the sensitivity of ground-based observations at wavelengths longer than 3 μm. The main purpose of this work is to analyse this background emission in infrared high-contrast imaging data as illustrative of the problem, show how it can be modelled and subtracted and demonstrate that it can improve the detection of faint sources, such as exoplanets. Methods: We used principal component analysis (PCA) to model and subtract the thermal background emission in three archival high-contrast angular differential imaging datasets in the M' and L' filter. We used an M' dataset of β Pic to describe in detail how the algorithm works and explain how it can be applied. The results of the background subtraction are compared to the results from a conventional mean background subtraction scheme applied to the same dataset. Finally, both methods for background subtraction are compared by performing complete data reductions. We analysed the results from the M' dataset of HD 100546 only qualitatively. For the M' band dataset of β Pic and the L' band dataset of HD 169142, which was obtained with an angular groove phase mask vortex vector coronagraph, we also calculated and analysed the achieved signal-to-noise ratio (S/N). Results: We show that applying PCA is an effective way to remove spatially and temporarily varying thermal background emission down to close to the background limit. The procedure also proves to be very successful at reconstructing the background that is hidden behind the point spread function. In the complete data reductions, we find at least qualitative improvements for HD 100546 and HD 169142, however, we fail to find a significant increase in S/N of β Pic b. We discuss these findings and argue that in particular datasets with strongly varying observing conditions or

Inter-fraction variations in respiratory motion models

Energy Technology Data Exchange (ETDEWEB)

McClelland, J R; Modat, M; Ourselin, S; Hawkes, D J [Centre for Medical Image Computing, University College London (United Kingdom); Hughes, S; Qureshi, A; Ahmad, S; Landau, D B, E-mail: j.mcclelland@cs.ucl.ac.uk [Department of Oncology, Guy' s and St Thomas' s Hospitals NHS Trust, London (United Kingdom)

2011-01-07

Respiratory motion can vary dramatically between the planning stage and the different fractions of radiotherapy treatment. Motion predictions used when constructing the radiotherapy plan may be unsuitable for later fractions of treatment. This paper presents a methodology for constructing patient-specific respiratory motion models and uses these models to evaluate and analyse the inter-fraction variations in the respiratory motion. The internal respiratory motion is determined from the deformable registration of Cine CT data and related to a respiratory surrogate signal derived from 3D skin surface data. Three different models for relating the internal motion to the surrogate signal have been investigated in this work. Data were acquired from six lung cancer patients. Two full datasets were acquired for each patient, one before the course of radiotherapy treatment and one at the end (approximately 6 weeks later). Separate models were built for each dataset. All models could accurately predict the respiratory motion in the same dataset, but had large errors when predicting the motion in the other dataset. Analysis of the inter-fraction variations revealed that most variations were spatially varying base-line shifts, but changes to the anatomy and the motion trajectories were also observed.

PCA Based Stress Monitoring of Cylindrical Specimens Using PZTs and Guided Waves

Directory of Open Access Journals (Sweden)

Jabid Quiroga

2017-12-01

Full Text Available Since mechanical stress in structures affects issues such as strength, expected operational life and dimensional stability, a continuous stress monitoring scheme is necessary for a complete integrity assessment. Consequently, this paper proposes a stress monitoring scheme for cylindrical specimens, which are widely used in structures such as pipelines, wind turbines or bridges. The approach consists of tracking guided wave variations due to load changes, by comparing wave statistical patterns via Principal Component Analysis (PCA. Each load scenario is projected to the PCA space by means of a baseline model and represented using the Q-statistical indices. Experimental validation of the proposed methodology is conducted on two specimens: (i a 12.7 mm ( 1 / 2 ″ diameter, 0.4 m length, AISI 1020 steel rod, and (ii a 25.4 mm ( 1 ″ diameter, 6m length, schedule 40, A-106, hollow cylinder. Specimen 1 was subjected to axial loads, meanwhile specimen 2 to flexion. In both cases, simultaneous longitudinal and flexural guided waves were generated via piezoelectric devices (PZTs in a pitch-catch configuration. Experimental results show the feasibility of the approach and its potential use as in-situ continuous stress monitoring application.

Tensile properties of unirradiated PCA from room temperature to 7000C

International Nuclear Information System (INIS)

Braski, D.N.; Maziasz, P.J.

1983-01-01

The tensile properties of Prime Candidate Alloy (PCA) austenitic stainless steel after three different thermomechanical treatments were determined from room temperature to 700 0 C. The solution-annealed PCA had the lowest strength and highest ductility, while the reverse was true for the 25%-cold-worked material. The PCA containing titanium-rich MC particles fell between the other two heats. The cold-worked PCA had nearly the same tensile properties as cold-worked type 316 stainless steel. Both alloys showed ductility minima at 300 0 C

The biological knowledge discovery by PCCF measure and PCA-F projection.

Science.gov (United States)

Jia, Xingang; Zhu, Guanqun; Han, Qiuhong; Lu, Zuhong

2017-01-01

In the process of biological knowledge discovery, PCA is commonly used to complement the clustering analysis, but PCA typically gives the poor visualizations for most gene expression data sets. Here, we propose a PCCF measure, and use PCA-F to display clusters of PCCF, where PCCF and PCA-F are modeled from the modified cumulative probabilities of genes. From the analysis of simulated and experimental data sets, we demonstrate that PCCF is more appropriate and reliable for analyzing gene expression data compared to other commonly used distances or similarity measures, and PCA-F is a good visualization technique for identifying clusters of PCCF, where we aim at such data sets that the expression values of genes are collected at different time points.

4D Lung Reconstruction with Phase Optimization

DEFF Research Database (Denmark)

Lyksborg, Mark; Paulsen, Rasmus; Brink, Carsten

2009-01-01

This paper investigates and demonstrates a 4D lung CT reconstruction/registration method which results in a complete volumetric model of the lung that deforms according to a respiratory motion field. The motion field is estimated iteratively between all available slice samples and a reference...... volume which is updated on the fly. The method is two part and the second part of the method aims to correct wrong phase information by employing another iterative optimizer. This two part iterative optimization allows for complete reconstruction at any phase and it will be demonstrated that it is better...... than using an optimization which does not correct for phase errors. Knowing how the lung and any tumors located within the lung deforms is relevant in planning the treatment of lung cancer....

SU-G-BRA-13: An Advanced Deformable Lung Phantom for Analyzing the Dosimetric Impact of Respiratory Motion

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Shin, D; Kang, S; Kim, D; Kim, T; Kim, K; Cho, M; Suh, T [Department of Biomedical Engineering and Research Institute of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul (Korea, Republic of)

2016-06-15

Purpose: The difference between three-dimensional (3D) and four-dimensional (4D) dose is affected by factors such as tumor size and motion. To quantitatively analyze the effects of these factors, a phantom that can independently control for each factor is required. The purpose of this study is to develop a deformable lung phantom with the above attributes and evaluate characteristics. Methods: A phantom was designed to simulate diaphragm motion with amplitude in the range 1 to 7 cm and various periods of regular breathing. To simulate different size tumors, tumors were produced by pouring liquid silicone into custom molds created by a 3D printer. The accuracy of phantom diaphragm motion was assessed using calipers and protractor. To control tumor motion, tumor trajectories were evaluated using 4D computed tomography (CT), and diaphragm-tumor correlation curve was calculated by curve fitting method. Three-dimensional dose and 4D dose were calculated and compared according to tumor motion. Results: The accuracy of phantom diaphragm motion was less than 1 mm. Maximum tumor motion amplitudes in the left-right and anterior-posterior directions were 0.08 and 0.12 cm, respectively, in a 10 cm{sup 3} tumor, and 0.06 and 0.27 cm, respectively, in a 90 cm{sup 3} tumor. The diaphragm-tumor correlation curve showed that tumor motion in the superior-inferior direction was increased with increasing diaphragm motion. In the 10 cm{sup 3} tumor, the tumor motion was larger than the 90 cm{sup 3} tumor. According to tumor motion, variation of dose difference between 3D and 4D was identified. Conclusion: The developed phantom can independently control factors such as tumor size and motion. In potentially, this phantom can be used to quantitatively analyze the dosimetric impact of respiratory motion according to the factors that influence the difference between 3D and 4D dose. This research was supported by the Mid-career Researcher Program through NRF funded by the Ministry of Science

Gas-Chromatographic Determination Of Water In Freon PCA

Science.gov (United States)

Melton, Donald M.

1994-01-01

Gas-chromatographic apparatus measures small concentrations of water in specimens of Freon PCA. Testing by use of apparatus faster and provides greater protection against accidental contamination of specimens by water in testing environment. Automated for unattended operation. Also used to measure water contents of materials, other than Freon PCA. Innovation extended to development of purgeable sampling accessory for gas chromatographs.

Synthesis and antifungal evaluation of PCA amide analogues.

Science.gov (United States)

Qin, Chuan; Yu, Di-Ya; Zhou, Xu-Dong; Zhang, Min; Wu, Qing-Lai; Li, Jun-Kai

2018-04-18

To improve the physical and chemical properties of phenazine-1-carboxylic acid (PCA) and find higher antifungal compounds, a series of PCA amide analogues were designed and synthesized and their structures were confirmed by 1 H NMR, HRMS, and X-ray. Most compounds showed some antifungal activities in vitro. Particularly, compound 3d exhibited inhibition effect against Pyriculariaoryzac Cavgra with EC 50 value of 28.7 μM and compound 3q exhibited effect against Rhizoctonia solani with EC 50 value of 24.5 μM, more potently active than that of the positive control PCA with its EC 50 values of 37.3 μM (Pyriculariaoryzac Cavgra) and 33.2 μM (Rhizoctonia solani), respectively.

TU-AB-BRA-06: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An MRI Compatible Externally and Internally Deformable Lung Motion Phantom for Multi-Modality IGRT

Energy Technology Data Exchange (ETDEWEB)

Sabouri, P; Sawant, A [University of Texas Southwestern Medical Center, Dallas, TX (United States); Arai, T [University of Maryland School of Medicine, Baltimore, MD (United States)

2016-06-15

Purpose: MRI has become an attractive tool for tumor motion management. Current MR-compatible phantoms are only capable of reproducing translational motion. This study describes the construction and validation of a more realistic, MRI-compatible lung phantom that is deformable internally as well as externally. We demonstrate a radiotherapy application of this phantom by validating the geometric accuracy of the open-source deformable image registration software NiftyReg (UCL, UK). Methods: The outer shell of a commercially-available dynamic breathing torso phantom was filled with natural latex foam with eleven water tubes. A rigid foam cut-out served as the diaphragm. A high-precision programmable, in-house, MRI-compatible motion platform was used to drive the diaphragm. The phantom was imaged on a 3T scanner (Philips, Ingenia). Twenty seven tumor traces previously recorded from lung cancer patients were programmed into the phantom and 2D+t image sequences were acquired using a sparse-sampling sequence k-t BLAST (accn=3, resolution=0.66×0.66×5mm3; acquisition-time=110ms/slice). The geometric fidelity of the MRI-derived trajectories was validated against those obtained via fluoroscopy using the on board kV imager on a Truebeam linac. NiftyReg was used to perform frame by frame deformable image registration. The location of each marker predicted by using NiftyReg was compared with the values calculated by intensity-based segmentation on each frame. Results: In all cases, MR trajectories were within 1 mm of corresponding fluoroscopy trajectories. RMSE between centroid positions obtained from segmentation with those obtained by NiftyReg varies from 0.1 to 0.21 mm in the SI direction and 0.08 to 0.13 mm in the LR direction showing the high accuracy of deformable registration. Conclusion: We have successfully designed and demonstrated a phantom that can accurately reproduce deformable motion under a variety of imaging modalities including MRI, CT and x-ray fluodoscopy

MO-E-BRB-00: PANEL DISCUSSION: SBRT/SRS Case Studies - Lung

Energy Technology Data Exchange (ETDEWEB)

NONE

2016-06-15

In this interactive session, lung SBRT patient cases will be presented to highlight real-world considerations for ensuring safe and accurate treatment delivery. An expert panel of speakers will discuss challenges specific to lung SBRT including patient selection, patient immobilization techniques, 4D CT simulation and respiratory motion management, target delineation for treatment planning, online treatment alignment, and established prescription regimens and OAR dose limits. Practical examples of cases, including the patient flow thought the clinical process are presented and audience participation will be encouraged. This panel session is designed to provide case demonstration and review for lung SBRT in terms of (1) clinical appropriateness in patient selection, (2) strategies for simulation, including 4D and respiratory motion management, and (3) applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent, and (4) image guidance in treatment delivery. Learning Objectives: Understand the established requirements for patient selection in lung SBRT Become familiar with the various immobilization strategies for lung SBRT, including technology for respiratory motion management Understand the benefits and pitfalls of applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent determination for lung SBRT Understand established prescription regimes and OAR dose limits.

Predictive local receptive fields based respiratory motion tracking for motion-adaptive radiotherapy.

Science.gov (United States)

Yubo Wang; Tatinati, Sivanagaraja; Liyu Huang; Kim Jeong Hong; Shafiq, Ghufran; Veluvolu, Kalyana C; Khong, Andy W H

2017-07-01

Extracranial robotic radiotherapy employs external markers and a correlation model to trace the tumor motion caused by the respiration. The real-time tracking of tumor motion however requires a prediction model to compensate the latencies induced by the software (image data acquisition and processing) and hardware (mechanical and kinematic) limitations of the treatment system. A new prediction algorithm based on local receptive fields extreme learning machines (pLRF-ELM) is proposed for respiratory motion prediction. All the existing respiratory motion prediction methods model the non-stationary respiratory motion traces directly to predict the future values. Unlike these existing methods, the pLRF-ELM performs prediction by modeling the higher-level features obtained by mapping the raw respiratory motion into the random feature space of ELM instead of directly modeling the raw respiratory motion. The developed method is evaluated using the dataset acquired from 31 patients for two horizons in-line with the latencies of treatment systems like CyberKnife. Results showed that pLRF-ELM is superior to that of existing prediction methods. Results further highlight that the abstracted higher-level features are suitable to approximate the nonlinear and non-stationary characteristics of respiratory motion for accurate prediction.

Example-Based Automatic Music-Driven Conventional Dance Motion Synthesis

Energy Technology Data Exchange (ETDEWEB)

Xu, Songhua [ORNL; Fan, Rukun [University of North Carolina, Chapel Hill; Geng, Weidong [Zhejiang University

2011-04-21

We introduce a novel method for synthesizing dance motions that follow the emotions and contents of a piece of music. Our method employs a learning-based approach to model the music to motion mapping relationship embodied in example dance motions along with those motions' accompanying background music. A key step in our method is to train a music to motion matching quality rating function through learning the music to motion mapping relationship exhibited in synchronized music and dance motion data, which were captured from professional human dance performance. To generate an optimal sequence of dance motion segments to match with a piece of music, we introduce a constraint-based dynamic programming procedure. This procedure considers both music to motion matching quality and visual smoothness of a resultant dance motion sequence. We also introduce a two-way evaluation strategy, coupled with a GPU-based implementation, through which we can execute the dynamic programming process in parallel, resulting in significant speedup. To evaluate the effectiveness of our method, we quantitatively compare the dance motions synthesized by our method with motion synthesis results by several peer methods using the motions captured from professional human dancers' performance as the gold standard. We also conducted several medium-scale user studies to explore how perceptually our dance motion synthesis method can outperform existing methods in synthesizing dance motions to match with a piece of music. These user studies produced very positive results on our music-driven dance motion synthesis experiments for several Asian dance genres, confirming the advantages of our method.

Example-based automatic music-driven conventional dance motion synthesis.

Science.gov (United States)

Fan, Rukun; Xu, Songhua; Geng, Weidong

2012-03-01

We introduce a novel method for synthesizing dance motions that follow the emotions and contents of a piece of music. Our method employs a learning-based approach to model the music to motion mapping relationship embodied in example dance motions along with those motions' accompanying background music. A key step in our method is to train a music to motion matching quality rating function through learning the music to motion mapping relationship exhibited in synchronized music and dance motion data, which were captured from professional human dance performance. To generate an optimal sequence of dance motion segments to match with a piece of music, we introduce a constraint-based dynamic programming procedure. This procedure considers both music to motion matching quality and visual smoothness of a resultant dance motion sequence. We also introduce a two-way evaluation strategy, coupled with a GPU-based implementation, through which we can execute the dynamic programming process in parallel, resulting in significant speedup. To evaluate the effectiveness of our method, we quantitatively compare the dance motions synthesized by our method with motion synthesis results by several peer methods using the motions captured from professional human dancers' performance as the gold standard. We also conducted several medium-scale user studies to explore how perceptually our dance motion synthesis method can outperform existing methods in synthesizing dance motions to match with a piece of music. These user studies produced very positive results on our music-driven dance motion synthesis experiments for several Asian dance genres, confirming the advantages of our method.

Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy

International Nuclear Information System (INIS)

Seppenwoolde, Yvette; Shirato, Hiroki; Kitamura, Kei; Shimizu, Shinichi; Herk, Marcel van; Lebesque, Joos V.; Miyasaka, Kazuo

2002-01-01

Purpose: In this work, three-dimensional (3D) motion of lung tumors during radiotherapy in real time was investigated. Understanding the behavior of tumor motion in lung tissue to model tumor movement is necessary for accurate (gated or breath-hold) radiotherapy or CT scanning. Methods: Twenty patients were included in this study. Before treatment, a 2-mm gold marker was implanted in or near the tumor. A real-time tumor tracking system using two fluoroscopy image processor units was installed in the treatment room. The 3D position of the implanted gold marker was determined by using real-time pattern recognition and a calibrated projection geometry. The linear accelerator was triggered to irradiate the tumor only when the gold marker was located within a certain volume. The system provided the coordinates of the gold marker during beam-on and beam-off time in all directions simultaneously, at a sample rate of 30 images per second. The recorded tumor motion was analyzed in terms of the amplitude and curvature of the tumor motion in three directions, the differences in breathing level during treatment, hysteresis (the difference between the inhalation and exhalation trajectory of the tumor), and the amplitude of tumor motion induced by cardiac motion. Results: The average amplitude of the tumor motion was greatest (12±2 mm [SD]) in the cranial-caudal direction for tumors situated in the lower lobes and not attached to rigid structures such as the chest wall or vertebrae. For the lateral and anterior-posterior directions, tumor motion was small both for upper- and lower-lobe tumors (2±1 mm). The time-averaged tumor position was closer to the exhale position, because the tumor spent more time in the exhalation than in the inhalation phase. The tumor motion was modeled as a sinusoidal movement with varying asymmetry. The tumor position in the exhale phase was more stable than the tumor position in the inhale phase during individual treatment fields. However, in many

2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.

Science.gov (United States)

Du, Qi-Shi; Wang, Shu-Qing; Xie, Neng-Zhong; Wang, Qing-Yan; Huang, Ri-Bo; Chou, Kuo-Chen

2017-09-19

A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.

Quantitation of passive cutaneous anaphylaxis (PCA) by using radiolabelled antigen

International Nuclear Information System (INIS)

Ring, J.; Seifert, J.; Brendel, W.

1978-01-01

The major problem of detecting reaginic antibody by passive cutaneous anaphylaxis (PCA) is the quantitation of the dye reaction. Radiolabelled antigen was used in an attempt to quantitate the PCA reaction (Radio-PCA). Antisera containing reaginic antibody against human serum albumin (HSA) were produced in rabbits. These antisera were injected into normal rabbit skin in different dilutions. Twentyfour hours later HSA was injected intravenously either with Evans Blue or as 125-I-HSA. Radioactivity found in antibody-containing skin was significantly higher than in control specimens containing saline or normal rabbit serum, as low as antiserum dilutions of 1:1,000. Compared with Evans Blue technique Radio-PCA was able to distinguish quantitatively between different antiserum dilutions at a higher level of statistical significance. (author)

Fault detection of feed water treatment process using PCA-WD with parameter optimization.

Science.gov (United States)

Zhang, Shirong; Tang, Qian; Lin, Yu; Tang, Yuling

2017-05-01

Feed water treatment process (FWTP) is an essential part of utility boilers; and fault detection is expected for its reliability improvement. Classical principal component analysis (PCA) has been applied to FWTPs in our previous work; however, the noises of T 2 and SPE statistics result in false detections and missed detections. In this paper, Wavelet denoise (WD) is combined with PCA to form a new algorithm, (PCA-WD), where WD is intentionally employed to deal with the noises. The parameter selection of PCA-WD is further formulated as an optimization problem; and PSO is employed for optimization solution. A FWTP, sustaining two 1000MW generation units in a coal-fired power plant, is taken as a study case. Its operation data is collected for following verification study. The results show that the optimized WD is effective to restrain the noises of T 2 and SPE statistics, so as to improve the performance of PCA-WD algorithm. And, the parameter optimization enables PCA-WD to get its optimal parameters in an automatic way rather than on individual experience. The optimized PCA-WD is further compared with classical PCA and sliding window PCA (SWPCA), in terms of four cases as bias fault, drift fault, broken line fault and normal condition, respectively. The advantages of the optimized PCA-WD, against classical PCA and SWPCA, is finally convinced with the results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Biometric identification based on feature fusion with PCA and SVM

Science.gov (United States)

Lefkovits, László; Lefkovits, Szidónia; Emerich, Simina

2018-04-01

Biometric identification is gaining ground compared to traditional identification methods. Many biometric measurements may be used for secure human identification. The most reliable among them is the iris pattern because of its uniqueness, stability, unforgeability and inalterability over time. The approach presented in this paper is a fusion of different feature descriptor methods such as HOG, LIOP, LBP, used for extracting iris texture information. The classifiers obtained through the SVM and PCA methods demonstrate the effectiveness of our system applied to one and both irises. The performances measured are highly accurate and foreshadow a fusion system with a rate of identification approaching 100% on the UPOL database.

[A Quantitative Verification for Operability of Three PCA Devices Attached to the Disposable Infusion Pumps].

Science.gov (United States)

Tadokoro, Takahiro; Fuchibe, Makoto; Odo, Yuichiro; Kakinohana, Manabu

2015-11-01

In this study using 3 different PCA devices (Baxter infuser LVBB +PCM 2 ml: Pump B, Coopdech Balloonjector +PCA 3 ml: Pump C, Rakuraku fuser +PCA 3 ml: Pump S), we investigated how easily PCA devices could be handled. In this study with 42 volunteers (14 elders and 28 nurses), we compared 3 PCA ejection volume and ejection rate among three PCA devices. PCA ejection rate was defined as the ratio of actual ejection volume to the maximum ejection volume (MEV) of each PCA device. Although not only elders but also nurses failed to produce accurate PCA ejection volume in the Pump B, Pump S could provide the MEV even by elders. In the Pump C, approximately 80% of MEV could be achieved by nurses, but 60% of MEV by elders (P PCA ejection volume might be dependent on PCA device.

Evaluation of an automated deformable image matching method for quantifying lung motion in respiration-correlated CT images

International Nuclear Information System (INIS)

Pevsner, A.; Davis, B.; Joshi, S.; Hertanto, A.; Mechalakos, J.; Yorke, E.; Rosenzweig, K.; Nehmeh, S.; Erdi, Y.E.; Humm, J.L.; Larson, S.; Ling, C.C.; Mageras, G.S.

2006-01-01

We have evaluated an automated registration procedure for predicting tumor and lung deformation based on CT images of the thorax obtained at different respiration phases. The method uses a viscous fluid model of tissue deformation to map voxels from one CT dataset to another. To validate the deformable matching algorithm we used a respiration-correlated CT protocol to acquire images at different phases of the respiratory cycle for six patients with nonsmall cell lung carcinoma. The position and shape of the deformable gross tumor volumes (GTV) at the end-inhale (EI) phase predicted by the algorithm was compared to those drawn by four observers. To minimize interobserver differences, all observers used the contours drawn by a single observer at end-exhale (EE) phase as a guideline to outline GTV contours at EI. The differences between model-predicted and observer-drawn GTV surfaces at EI, as well as differences between structures delineated by observers at EI (interobserver variations) were evaluated using a contour comparison algorithm written for this purpose, which determined the distance between the two surfaces along different directions. The mean and 90% confidence interval for model-predicted versus observer-drawn GTV surface differences over all patients and all directions were 2.6 and 5.1 mm, respectively, whereas the mean and 90% confidence interval for interobserver differences were 2.1 and 3.7 mm. We have also evaluated the algorithm's ability to predict normal tissue deformations by examining the three-dimensional (3-D) vector displacement of 41 landmarks placed by each observer at bronchial and vascular branch points in the lung between the EE and EI image sets (mean and 90% confidence interval displacements of 11.7 and 25.1 mm, respectively). The mean and 90% confidence interval discrepancy between model-predicted and observer-determined landmark displacements over all patients were 2.9 and 7.3 mm, whereas interobserver discrepancies were 2.8 and 6

An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.

Science.gov (United States)

Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

2017-12-07

Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the necessity of real world diagnostic situations. In this paper, an efficient PBDS based on MR images is proposed that markedly improves the recent results. The proposed system makes use of contrast limited adaptive histogram equalization (CLAHE) to enhance the quality of the input MR images. Thereafter, two-dimensional PCA (2DPCA) strategy is employed to extract the features and subsequently, a PCA+LDA approach is used to generate a compact and discriminative feature set. Finally, a new learning algorithm called MDE-ELM is suggested that combines modified differential evolution (MDE) and extreme learning machine (ELM) for segregation of MR images as pathological or healthy. The MDE is utilized to optimize the input weights and hidden biases of single-hidden-layer feed-forward neural networks (SLFN), whereas an analytical method is used for determining the output weights. The proposed algorithm performs optimization based on both the root mean squared error (RMSE) and norm of the output weights of SLFNs. The suggested scheme is benchmarked on three standard datasets and the results are compared against other competent schemes. The experimental outcomes show that the proposed scheme offers superior results compared to its counterparts. Further, it has been noticed that the proposed MDE-ELM classifier obtains better accuracy with compact network architecture than conventional algorithms.

Does Motion Assessment With 4-Dimensional Computed Tomographic Imaging for Non–Small Cell Lung Cancer Radiotherapy Improve Target Volume Coverage?

Directory of Open Access Journals (Sweden)

Naseer Ahmed

2017-03-01

Full Text Available Introduction: Modern radiotherapy with 4-dimensional computed tomographic (4D-CT image acquisition for non–small cell lung cancer (NSCLC captures respiratory-mediated tumor motion to provide more accurate target delineation. This study compares conventional 3-dimensional (3D conformal radiotherapy (3DCRT plans generated with standard helical free-breathing CT (FBCT with plans generated on 4D-CT contoured volumes to determine whether target volume coverage is affected. Materials and methods: Fifteen patients with stage I to IV NSCLC were enrolled in the study. Free-breathing CT and 4D-CT data sets were acquired at the same simulation session and with the same immobilization. Gross tumor volume (GTV for primary and/or nodal disease was contoured on FBCT (GTV_3D. The 3DCRT plans were obtained, and the patients were treated according to our institution’s standard protocol using FBCT imaging. Gross tumor volume was contoured on 4D-CT for primary and/or nodal disease on all 10 respiratory phases and merged to create internal gross tumor volume (IGTV_4D. Clinical target volume margin was 5 mm in both plans, whereas planning tumor volume (PTV expansion was 1 cm axially and 1.5 cm superior/inferior for FBCT-based plans to incorporate setup errors and an estimate of respiratory-mediated tumor motion vs 8 mm isotropic margin for setup error only in all 4D-CT plans. The 3DCRT plans generated from the FBCT scan were copied on the 4D-CT data set with the same beam parameters. GTV_3D, IGTV_4D, PTV, and dose volume histogram from both data sets were analyzed and compared. Dice coefficient evaluated PTV similarity between FBCT and 4D-CT data sets. Results: In total, 14 of the 15 patients were analyzed. One patient was excluded as there was no measurable GTV. Mean GTV_3D was 115.3 cm 3 and mean IGTV_4D was 152.5 cm 3 ( P = .001. Mean PTV_3D was 530.0 cm 3 and PTV_4D was 499.8 cm 3 ( P = .40. Both gross primary and nodal disease analyzed separately were larger

Synchronized moving aperture radiation therapy (SMART): average tumour trajectory for lung patients

International Nuclear Information System (INIS)

Neicu, Toni; Shirato, Hiroki; Seppenwoolde, Yvette; Jiang, Steve B

2003-01-01

Synchronized moving aperture radiation therapy (SMART) is a new technique for treating mobile tumours under development at Massachusetts General Hospital (MGH). The basic idea of SMART is to synchronize the moving radiation beam aperture formed by a dynamic multileaf collimator (DMLC) with the tumour motion induced by respiration. SMART is based on the concept of the average tumour trajectory (ATT) exhibited by a tumour during respiration. During the treatment simulation stage, tumour motion is measured and the ATT is derived. Then, the original IMRT MLC leaf sequence is modified using the ATT to compensate for tumour motion. During treatment, the tumour motion is monitored. The treatment starts when leaf motion and tumour motion are synchronized at a specific breathing phase. The treatment will halt when the tumour drifts away from the ATT and will resume when the synchronization between tumour motion and radiation beam is re-established. In this paper, we present a method to derive the ATT from measured tumour trajectory data. We also investigate the validity of the ATT concept for lung tumours during normal breathing. The lung tumour trajectory data were acquired during actual radiotherapy sessions using a real-time tumour-tracking system. SMART treatment is simulated by assuming that the radiation beam follows the derived ATT and the tumour follows the measured trajectory. In simulation, the treatment starts at exhale phase. The duty cycle of SMART delivery was calculated for various treatment times and gating thresholds, as well as for various exhale phases where the treatment begins. The simulation results show that in the case of free breathing, for 4 out of 11 lung datasets with tumour motion greater than 1 cm from peak to peak, the error in tumour tracking can be controlled to within a couple of millimetres while maintaining a reasonable delivery efficiency. That is to say, without any breath coaching/control, the ATT is a valid concept for some lung

Effect of immobilization and performance status on intrafraction motion for stereotactic lung radiotherapy: analysis of 133 patients.

Science.gov (United States)

Li, Winnie; Purdie, Thomas G; Taremi, Mojgan; Fung, Sharon; Brade, Anthony; Cho, B C John; Hope, Andrew; Sun, Alexander; Jaffray, David A; Bezjak, Andrea; Bissonnette, Jean-Pierre

2011-12-01

To assess intrafractional geometric accuracy of lung stereotactic body radiation therapy (SBRT) patients treated with volumetric image guidance. Treatment setup accuracy was analyzed in 133 SBRT patients treated via research ethics board-approved protocols. For each fraction, a localization cone-beam computed tomography (CBCT) scan was acquired for soft-tissue registration to the internal target volume, followed by a couch adjustment for positional discrepancies greater than 3 mm, verified with a second CBCT scan. CBCT scans were also performed at intrafraction and end fraction. Patient positioning data from 2047 CBCT scans were recorded to determine systematic (Σ) and random (σ) uncertainties, as well as planning target volume margins. Data were further stratified and analyzed by immobilization method (evacuated cushion [n=75], evacuated cushion plus abdominal compression [n=33], or chest board [n=25]) and by patients' Eastern Cooperative Oncology Group performance status (PS): 0 (n=31), 1 (n=70), or 2 (n=32). Using CBCT internal target volume was matched within ±3 mm in 16% of all fractions at localization, 89% at verification, 72% during treatment, and 69% after treatment. Planning target volume margins required to encompass residual setup errors after couch corrections (verification CBCT scans) were 4 mm, and they increased to 5 mm with target intrafraction motion (post-treatment CBCT scans). Small differences (position were observed between the immobilization cohorts in the localization, verification, intrafraction, and post-treatment CBCT scans (pPositional drift varied according to patient PS, with the PS 1 and 2 cohorts drifting out of position by mid treatment more than the PS 0 cohort in the cranial-caudal direction (p=0.04). Image guidance ensures high geometric accuracy for lung SBRT irrespective of immobilization method or PS. A 5-mm setup margin suffices to address intrafraction motion. This setup margin may be further reduced by strategies such as

Effect of Immobilization and Performance Status on Intrafraction Motion for Stereotactic Lung Radiotherapy: Analysis of 133 Patients

International Nuclear Information System (INIS)

Li, Winnie; Purdie, Thomas G.; Taremi, Mojgan; Fung, Sharon; Brade, Anthony; Cho, B.C. John; Hope, Andrew; Sun, Alexander; Jaffray, David A.; Bezjak, Andrea; Bissonnette, Jean-Pierre

2011-01-01

Purpose: To assess intrafractional geometric accuracy of lung stereotactic body radiation therapy (SBRT) patients treated with volumetric image guidance. Methods and Materials: Treatment setup accuracy was analyzed in 133 SBRT patients treated via research ethics board–approved protocols. For each fraction, a localization cone-beam computed tomography (CBCT) scan was acquired for soft-tissue registration to the internal target volume, followed by a couch adjustment for positional discrepancies greater than 3 mm, verified with a second CBCT scan. CBCT scans were also performed at intrafraction and end fraction. Patient positioning data from 2047 CBCT scans were recorded to determine systematic (Σ) and random (σ) uncertainties, as well as planning target volume margins. Data were further stratified and analyzed by immobilization method (evacuated cushion [n = 75], evacuated cushion plus abdominal compression [n = 33], or chest board [n = 25]) and by patients’ Eastern Cooperative Oncology Group performance status (PS): 0 (n = 31), 1 (n = 70), or 2 (n = 32). Results: Using CBCT internal target volume was matched within ±3 mm in 16% of all fractions at localization, 89% at verification, 72% during treatment, and 69% after treatment. Planning target volume margins required to encompass residual setup errors after couch corrections (verification CBCT scans) were 4 mm, and they increased to 5 mm with target intrafraction motion (post-treatment CBCT scans). Small differences (<1 mm) in the cranial–caudal direction of target position were observed between the immobilization cohorts in the localization, verification, intrafraction, and post-treatment CBCT scans (p < 0.01). Positional drift varied according to patient PS, with the PS 1 and 2 cohorts drifting out of position by mid treatment more than the PS 0 cohort in the cranial-caudal direction (p = 0.04). Conclusions: Image guidance ensures high geometric accuracy for lung SBRT irrespective of immobilization