Application of machine learning to structural connectome to predict symptom reduction in depressed adolescents with cognitive behavioral therapy (CBT).

Journal: NeuroImage. Clinical
Published Date: Jan 1, 2019

Abstract

PURPOSE: Adolescent major depressive disorder (MDD) is a highly prevalent, incapacitating and costly illness. Many depressed teens do not improve with cognitive behavioral therapy (CBT), a first-line treatment for adolescent MDD, and face devastating consequences of increased risk of suicide and many negative health outcomes. "Who will improve with CBT?" is a crucial question that remains unanswered, and treatment planning for adolescent depression remains biologically unguided. The purpose of this study was to utilize machine learning applied to patients' brain imaging data in order to help predict depressive symptom reduction with CBT.

Authors

  • Olga Tymofiyeva
    Department of Radiology & Biomedical Imaging, University of California, San Francisco, 1700 4th Street, BH102, San Francisco, CA 94143, USA. Electronic address: Olga.Tymofiyeva@ucsf.edu.
  • Justin P Yuan
    Department of Radiology & Biomedical Imaging, University of California, San Francisco, 1700 4th Street, BH102, San Francisco, CA 94143, USA.
  • Chiung-Yu Huang
    Department of Epidemiology and Biostatistics, University of California, San Francisco, 550 16th Street, San Francisco, CA 94143, USA.
  • Colm G Connolly
    Department of Psychiatry and the Langley Porter Psychiatric Institute, Division of Child and Adolescent Psychiatry, Weill Institute for Neurosciences, University of California, San Francisco, 401 Parnassus Avenue, San Francisco, CA 94143, USA; Department of Biomedical Sciences, Florida State University College of Medicine, 1115 West Call Street, Tallahassee, FL 32306, USA.
  • Eva Henje Blom
    Department of Psychiatry and the Langley Porter Psychiatric Institute, Division of Child and Adolescent Psychiatry, Weill Institute for Neurosciences, University of California, San Francisco, 401 Parnassus Avenue, San Francisco, CA 94143, USA; Department of Clinical Science/Child- and Adolescent Psychiatry, Umeå University, SE-901 87 Umeå, Sweden.
  • Duan Xu
    Department of Radiology, Seoul National University Hospital, Republic of Korea. Electronic address: duan.xu@ucsf.edu.
  • Tony T Yang
    Department of Psychiatry and the Langley Porter Psychiatric Institute, Division of Child and Adolescent Psychiatry, Weill Institute for Neurosciences, University of California, San Francisco, 401 Parnassus Avenue, San Francisco, CA 94143, USA.

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