Individual prediction of psychotherapy outcome in posttraumatic stress disorder using neuroimaging data. Academic Article uri icon

Overview

abstract

  • Trauma-focused psychotherapy is the first-line treatment for posttraumatic stress disorder (PTSD) but 30-50% of patients do not benefit sufficiently. We investigated whether structural and resting-state functional magnetic resonance imaging (MRI/rs-fMRI) data could distinguish between treatment responders and non-responders on the group and individual level. Forty-four male veterans with PTSD underwent baseline scanning followed by trauma-focused psychotherapy. Voxel-wise gray matter volumes were extracted from the structural MRI data and resting-state networks (RSNs) were calculated from rs-fMRI data using independent component analysis. Data were used to detect differences between responders and non-responders on the group level using permutation testing, and the single-subject level using Gaussian process classification with cross-validation. A RSN centered on the bilateral superior frontal gyrus differed between responders and non-responder groups (PFWE < 0.05) while a RSN centered on the pre-supplementary motor area distinguished between responders and non-responders on an individual-level with 81.4% accuracy (P < 0.001, 84.8% sensitivity, 78% specificity and AUC of 0.93). No significant single-subject classification or group differences were observed for gray matter volume. This proof-of-concept study demonstrates the feasibility of using rs-fMRI to develop neuroimaging biomarkers for treatment response, which could enable personalized treatment of patients with PTSD.

publication date

  • December 2, 2019

Research

keywords

  • Cognitive Behavioral Therapy
  • Connectome
  • Outcome Assessment, Health Care
  • Psychological Trauma
  • Stress Disorders, Post-Traumatic
  • Veterans

Identity

PubMed Central ID

  • PMC6889413

Scopus Document Identifier

  • 85075949069

Digital Object Identifier (DOI)

  • 10.1038/s41398-019-0663-7

PubMed ID

  • 31792202

Additional Document Info

volume

  • 9

issue

  • 1