Prediction of Individual Response to Electroconvulsive Therapy via Machine Learning on Structural Magnetic Resonance Imaging Data.

Journal: JAMA psychiatry
Published Date:

Abstract

IMPORTANCE: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depression. However, biomarkers that accurately predict a response to ECT remain unidentified.

Authors

  • Ronny Redlich
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Nils Opel
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Dominik Grotegerd
    Department of Psychiatry and Psychotherapy, University of Münster, Germany.
  • Katharina Dohm
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Dario Zaremba
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Christian Bürger
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Sandra Münker
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Lisa Mühlmann
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Patricia Wahl
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Walter Heindel
    Department of Clinical Radiology, University of Muenster, Muenster, Germany.
  • Volker Arolt
    Department of Psychiatry, University of Muenster, Muenster, Germany.
  • Judith Alferink
    Department of Psychiatry, University of Muenster, Muenster, Germany3Cells-in-Motion Cluster of Excellence, University of Muenster, Muenster, Germany.
  • Peter Zwanzger
    Department of Psychiatry, University of Muenster, Muenster, Germany4Department of Psychiatry, Inn-Salzach Hospital, Wasserburg am Inn, Germany.
  • Maxim Zavorotnyy
    Department of Psychiatry, University of Marburg, Marburg, Germany.
  • Harald Kugel
    Department of Clinical Radiology, University of Muenster, Muenster, Germany.
  • Udo Dannlowski
    Department of Psychiatry and Psychotherapy, University of Münster, Germany.