Abstract #3492

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

Chao-Yu Shen^1,2,3, Zhen-Hui Li¹, Vincent Chin-Hung Chen⁴, Ming-Chou Ho⁵, Yeu-Sheng Tyan^1,2, and Jun-Cheng Weng^1,2

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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