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Abstract #0126

Magnetic Resonance Imaging-Assisted Diagnosis of Major Depressive Disorder Using a Multiparameter Classification Approach Based on Gray Matter Abnormality

Lihua Qiu1, Xiaoqi Huang1, Qizhu Wu1, Shiguang Li1, Su Lui1, Peiyu Huang2, Qiyong Gong1

1Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China; 2Institute of Neuroscience, Chongqing Medical University, Chongqing, China

Past studies applied Support Vector Machine (SVM) using structural MRI data had yielded some promising results in distinguish psychiatric disorders. However, only volumetric information had been consideration in those past studies. In the present study, we use multiparameter(seven morphometric parameters including volumetric and geometric features on grey matter) classification approach to distinguish first-episode, drug-nave MDD patients from normal controls. Among all parameters, we found cortical thickness measurement showed the highest accuracy in revealing group differences between control and MDD. Current study provided new approach which might be useful for translational application of MRI in future.