PT - JOURNAL ARTICLE AU - Paul Zhutovsky AU - Rajat M. Thomas AU - Miranda Olff AU - Sanne J.H. van Rooij AU - Mitzy Kennis AU - Guido A. van Wingen AU - Elbert Geuze TI - Individual Prediction of Psychotherapy Outcome in Posttraumatic Stress Disorder using Neuroimaging Data AID - 10.1101/647925 DP - 2019 Jan 01 TA - bioRxiv PG - 647925 4099 - http://biorxiv.org/content/early/2019/05/23/647925.short 4100 - http://biorxiv.org/content/early/2019/05/23/647925.full AB - Objective 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.Methods 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.Results 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.Conclusions 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.