Search for: voxel-based-morphometry
Article Neurology ; Volume 86, Issue 5 , 2016 , Pages 410-417 ; 00283878 (ISSN) ; Sadaghiani, S ; Park, M. T. M ; Mashhadi, R ; Nazeri, A ; Noshad, S ; Salehi, M. J ; Naghibzadeh, M ; Moghadasi, A. N ; Owji, M ; Doosti, R ; Hashemi Taheri, A. P ; Rad, A. S ; Azimi, A ; Chakravarty, M. M ; Voineskos, A. N ; Nazeri, A ; Sahraian, M. A ; Sharif University of Technology
Lippincott Williams and Wilkins
Objective: To determine the motor-behavioral and neural correlates of putative functional common variants in the sodium-channel NaV1.8 encoding gene (SCN10A) in vivo in patients with multiple sclerosis (MS). Methods: We recruited 161 patients with relapsing-onset MS and 94 demographically comparable healthy participants. All patients with MS underwent structural MRI and clinical examinations (Expanded Disability Status Scale [EDSS] and Multiple Sclerosis Functional Composite [MSFC]). Whole-brain voxel-wise and cerebellar volumetry were performed to assess differences in regional brain volumes between genotype groups. Resting-state fMRI was acquired from 62 patients with MS to evaluate...
Article Brain Sciences ; Volume 7, Issue 8 , 2017 ; 20763425 (ISSN) ; Habibollahi Saatlou, F ; Mohammadzade, H ; Sharif University of Technology
Alzheimer’s disease (AD) is currently ranked as the sixth leading cause of death in the United States and recent estimates indicate that the disorder may rank third, just behind heart disease and cancer, as a cause of death for older people. Clearly, predicting this disease in the early stages and preventing it from progressing is of great importance. The diagnosis of Alzheimer’s disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. It can be difficult and exhausting to manually compare, visualize, and analyze this data due to the heterogeneous nature of medical tests, therefore, an efficient approach for accurate prediction of the...