Predicting treatment response in individuals with major depressive disorder using structural MRI-based similarity features.

Journal: BMC psychiatry
Published Date: May 26, 2025

Abstract

BACKGROUND: Major Depressive Disorder (MDD) is a prevalent mental health condition with significant societal impact. Structural magnetic resonance imaging (sMRI) and machine learning have shown promise in psychiatry, offering insights into brain abnormalities in MDD. However, predicting treatment response remains challenging. This study leverages inter-brain similarity from sMRI as a novel feature to enhance prediction accuracy and explore disease mechanisms. The method's generalizability across adult and adolescent cohorts is also evaluated.

Authors

  • Sutao Song
    School of Education and Psychology, University of Jinan, Jinan, China. Electronic address: sep_songst@ujn.edu.cn.
  • Songling Wang
    School of Information Science and Engineering, Shandong Normal University, Jinan, China.
  • Jingjing Gao
    School of Electronic Engineering, University of Electronic Science and Technology of China, Xiyuan Ave. 2006, West Hi-Tech Zone, Chengdu, Sichuan, 611731, China.
  • Lingkai Zhu
    School of Information Science and Engineering, Shandong Normal University, Jinan, China.
  • Wenxin Zhang
    Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, Institute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
  • Yan Wang
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.
  • Donglin Wang
  • Danning Zhang
    Shandong Mental Health Center, Shandong University, Jinan, Shandong, China. haohaizi21c@sina.com.
  • Kangcheng Wang
    Department of Psychology, Southwest University, Chongqing, China.

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