TY - JOUR
T1 - Individual prediction of psychotherapy outcome in posttraumatic stress disorder using neuroimaging data
AU - Zhutovsky, Paul
AU - Thomas, Rajat M.
AU - Olff, Miranda
AU - van Rooij, Sanne J. H.
AU - Kennis, Mitzy
AU - van Wingen, Guido A.
AU - Geuze, Elbert
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85075949069&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/31792202
U2 - https://doi.org/10.1038/s41398-019-0663-7
DO - https://doi.org/10.1038/s41398-019-0663-7
M3 - Article
C2 - 31792202
SN - 2158-3188
VL - 9
JO - Translational Psychiatry
JF - Translational Psychiatry
IS - 1
M1 - 326
ER -