Individual prediction of psychotherapy outcome in posttraumatic stress disorder using neuroimaging data

Paul Zhutovsky*, Rajat M. Thomas, Miranda Olff, Sanne J.H. van Rooij, Mitzy Kennis, Guido A. van Wingen, Elbert Geuze

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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.

Original languageEnglish
Article number326
Number of pages10
JournalTranslational Psychiatry
Volume9
Issue number1
DOIs
Publication statusPublished - 1 Dec 2019

Keywords

  • Neuroscience
  • Psychology

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