Comparison of compressed sensing diffusion spectrum imaging and diffusion tensor imaging in patients with intracranial masses |
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| Institution: | 1. Department of Radiology, Memorial Sloan Kettering Cancer Center;2. Department of Medical Physics, Memorial Sloan Kettering Cancer Center;3. Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center;4. Brain Tumor Center, Memorial Sloan Kettering Cancer Center;5. Department of Diagnostics, Imaging and Biomedical Technologies, GE Global Research;1. Shanghai Clinical Research Center/Xuhui Central Hospital, Chinese Academy of Sciences, Shanghai, China;2. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China;3. Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA;4. Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA;1. ParIMéd/LRPE, FEI, USTHB, BP 32 El Alia, Bab Ezzouar, 16111, Algiers, Algeria;2. PRISME Laboratory, University of Orléans, 12 Rue de Blois, 45067 Orléans, France;1. Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China;2. Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China;3. GE Healthcare MR Research China, Beijing, China;4. McGovern Institute for Brain Research, Peking University, Beijing, China;1. Computer Imaging and Medical Applications Laboratory – CIM@LAB, Universidad Nacional de Colombia, Bogotá, Colombia;2. Universidad Militar Nueva Granada, Bogotá, Colombia;3. Departamento de Ingeniería de Sistemas, Pontificia Universidad Javeriana, Bogotá, Colombia;4. Departamento de Física Matemática y de Fluidos, Universidad Nacional de Educación a Distancia, Madrid, Spain;1. Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan;2. Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong;3. Brain Imaging and Analysis Center, Duke University Medical Center, Durham, North Carolina, USA;4. Graduate Institute of Medical Informatics, National Cheng-Kung University, Tainan, Taiwan;5. Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;1. Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, P.R. China;2. Department of Radiology, Affiliated Hospital of Xuzhou Medical College, Xuzhou, P.R. China;3. Department of Radiology, The Third Hospital of Xuzhou City, Xuzhou, P.R. China |
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| Abstract: | PurposeTo compare compressed diffusion spectrum imaging (CS-DSI) with diffusion tensor imaging (DTI) in patients with intracranial masses. We hypothesized that CS-DSI would provide superior visualization of the motor and language tracts.Materials and methodsWe retrospectively analyzed 25 consecutive patients with intracranial masses who underwent DTI and CS-DSI for preoperative planning. Directionally-encoded anisotropy maps, and streamline hand corticospinal motor tracts and arcuate fasciculus language tracts were graded according to a 3-point scale. Tract counts, anisotropy, and lengths were also calculated. Comparisons were made using exact marginal homogeneity, McNemar's and Wilcoxon signed-rank tests.ResultsReaders preferred the CS-DSI over DTI anisotropy maps in 92% of the cases, and the CS-DSI over DTI tracts in 84%. The motor tracts were graded as excellent in 80% of cases for CS-DSI versus 52% for DTI; 58% of the motor tracts graded as acceptable in DTI were graded as excellent in CS-DSI (p = 0.02). The language tracts were graded as excellent in 68% for CS-DSI versus none for DTI; 78% of the language tracts graded as acceptable by DTI were graded as excellent by CS-DSI (p < 0.001). CS-DSI demonstrated smaller normalized mean differences than DTI for motor tract counts, anisotropy and language tract counts (p ≤ 0.01).ConclusionCS-DSI was preferred over DTI for the evaluation of motor and language white matter tracts in patients with intracranial masses. Results suggest that CS-DSI may be more useful than DTI for preoperative planning purposes. |
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