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Abstract #3492

Assessment of brain structural network alterations in major depressive disorder using generalized q-sampling imaging and connectome analysis

Chao-Yu Shen1,2,3, Zhen-Hui Li1, Vincent Chin-Hung Chen4, Ming-Chou Ho5, Yeu-Sheng Tyan1,2, and Jun-Cheng Weng1,2

1Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan, 2Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan, 3Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan, 4Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan, 5Department of Psychology, Chung Shan Medical University, Taichung, Taiwan

Major depressive disorder (MDD) is the most common mood disorder in the world and the most important precursor of suicide. Despite decades of research, the pathophysiology of MDD remains not well understood. Recently, several MRI studies have focused on structural and functional connectivity evaluation and suggested that alterations of some specific regions of the brain, in both gray and white matter structures and some specific cortical–subcortical neuronal circuits, may play important roles of MDD. Generalized q-sampling imaging (GQI) is a more accurate and sophisticated diffusion MR approach compared to diffusion tensor imaging (DTI), which can extract additional information about the altered diffusion environments to resolve the complicated neural structure changes of neural disease. In this study, we used GQI and graph theoretical analysis to evaluate brain structure and connectivity change of MDD compared to healthy controls and correlation with symptom severity. Our results indicated GQI indices can help to detect structural and connective abnormalities of MDD patients and these alterations are correlated with depressive severity.

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