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Abstract #1723

Predicting Early Antidepressant Response in Patients with Major Depressive Disorder: Insight from Many Dimensions of Hippocampal Organization

Mengyue Tang1, Liangqing Zhang1, Xinyue Hu1, Zilin Zhou1, Yingying Wang1, Weijie Bao1, Qiyong Gong1,2, and Xiaoqi Huang1,2
1Huaxi MR Research Center (HMRRC)ï¼›West China Hospital, Sichuan University, Chengdu, China, 2Institute of psychoradiology, West China Xiamen Hospital of Sichuan University, Xiamen, China

Synopsis

Keywords: Psychiatric Disorders, Psychiatric Disorders

Motivation: It is currently unknown which hippocampal substructure or composite based on the different is the most effective in evaluating treatment outcomes.

Goal(s): To explore which hippocampal organization might predict an early antidepressant response to in patients with major depressive disorder.

Approach: We used Freesurfer software to segment the hippocampus automatically, and created the hippocampal composites by summing component substructures early antidepressants response were evaluated from many dimensions of hippocampal organization.

Results: We found hippocampal substructures segmented along its transverse axis exhibit best classification performance, and the most relevant region for treatments efficacy maybe located in the CA1 and ML.

Impact: We found hippocampal substructures segmented along its transverse axis exhibit best classification performance, and the most relevant region for treatments efficacy maybe located in the CA1 and ML.

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