scholarly journals Individual Prediction of Psychotherapy Outcome in Posttraumatic Stress Disorder using Neuroimaging Data

2019 ◽  
Author(s):  
Paul Zhutovsky ◽  
Rajat M. Thomas ◽  
Miranda Olff ◽  
Sanne J.H. van Rooij ◽  
Mitzy Kennis ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Gray Matter ◽  
Resting State ◽  
Stress Disorder ◽  
Gray Matter Volume ◽  
Fmri Data ◽  
Single Subject ◽  
Permutation Testing ◽  
Individual Level

AbstractObjectiveTrauma-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.MethodsForty-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.ResultsA 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.ConclusionsThis 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.

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

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Paul Zhutovsky ◽  
Rajat M. Thomas ◽  
Miranda Olff ◽  
Sanne J. H. van Rooij ◽  
Mitzy Kennis ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Gray Matter ◽  
Resting State ◽  
Stress Disorder ◽  
Gray Matter Volume ◽  
Fmri Data ◽  
Single Subject ◽  
Permutation Testing ◽  
Individual Level

AbstractTrauma-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.

scholarly journals Combining Deep Learning and Graph-Theoretic Brain Features to Detect Posttraumatic Stress Disorder at the Individual Level

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1416
Author(s):  
Ziyu Zhu ◽  
Du Lei ◽  
Kun Qin ◽  
Xueling Suo ◽  
Wenbin Li ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Deep Learning ◽  
Posttraumatic Stress ◽  
Stress Disorder ◽  
Support Vector ◽  
Single Subject ◽  
Theoretic Approach ◽  
Individual Level ◽  
Graph Theoretic ◽  
The Individual

Previous studies using resting-state functional MRI (rs-fMRI) have revealed alterations in graphical metrics in groups of individuals with posttraumatic stress disorder (PTSD). To explore the ability of graph measures to diagnose PTSD and capture its essential features in individual patients, we used a deep learning (DL) model based on a graph-theoretic approach to discriminate PTSD from trauma-exposed non-PTSD at the individual level and to identify its most discriminant features. Our study was performed on rs-fMRI data from 91 individuals with PTSD and 126 trauma-exposed non-PTSD patients. To evaluate our DL method, we used the traditional support vector machine (SVM) classifier as a reference. Our results showed that the proposed DL model allowed single-subject discrimination of PTSD and trauma-exposed non-PTSD individuals with higher accuracy (average: 80%) than the traditional SVM (average: 57.7%). The top 10 DL features were identified within the default mode, central executive, and salience networks; the first two of these networks were also identified in the SVM classification. We also found that nodal efficiency in the left fusiform gyrus was negatively correlated with the Clinician Administered PTSD Scale score. These findings demonstrate that DL based on graphical features is a promising method for assisting in the diagnosis of PTSD.

scholarly journals Individual prediction of trauma-focused psychotherapy response in youth with posttraumatic stress disorder using resting-state functional connectivity

2021 ◽  
Author(s):  
Paul Zhutovsky ◽  
Jasper B. Zantvoord ◽  
Judith B.M. Ensink ◽  
Rosanne Op den Kelder ◽  
Ramon J.L. Lindauer ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Functional Connectivity ◽  
Posttraumatic Stress ◽  
Resting State ◽  
Prediction Models ◽  
Stress Disorder ◽  
Network Connectivity ◽  
Support Vector ◽  
Permutation Testing ◽  
Resting State Functional Connectivity

AbstractRandomized controlled trials have shown efficacy of trauma-focused psychotherapies in youth with posttraumatic stress disorder (PTSD). However, response varies considerably among individuals. Currently, no biomarkers are available to assist clinicians in identifying youth who are most likely to benefit from treatment. In this study, we investigated whether resting-state functional magnetic resonance imaging (rs-fMRI) could distinguish between responders and non-responders on the group- and individual patient level.Pre-treatment rs-fMRI was recorded in 40 youth (ages 8-17 years) with (partial) PTSD before trauma-focused psychotherapy. Change in symptom severity from pre- to post-treatment was assessed using the Clinician-Administered PTSD scale for Children and Adolescents to divide participants into responders (≥30% symptom reduction) and non-responders. Functional networks were identified using meta-independent component analysis. Group-differences within- and between-network connectivity between responders and non-responders were tested using permutation testing. Individual predictions were made using multivariate, cross-validated support vector machine classification.A network centered on the bilateral superior temporal gyrus predicted treatment response for individual patients with 76.17% accuracy (pFWE = 0.018, 87.14% sensitivity, 65.20% specificity, area-under-receiver-operator-curve of 0.82). Functional connectivity between the frontoparietal and sensorimotor network was significantly stronger in non-responders (pFWE = 0.012) on the group-level. Within-network connectivity was not significantly different between groups.This study provides proof-of-concept evidence for the feasibility to predict trauma-focused psychotherapy response in youth with PTSD at an individual-level. Future studies are required to test if larger cohorts could increase accuracy and to test further generalizability of the prediction models.

scholarly journals Evidence for Acquired Pregenual Anterior Cingulate Gray Matter Loss from a Twin Study of Combat-Related Posttraumatic Stress Disorder

2008 ◽  
Vol 63 (6) ◽  
pp. 550-556 ◽  
Author(s):  
Kiyoto Kasai ◽  
Hidenori Yamasue ◽  
Mark W. Gilbertson ◽  
Martha E. Shenton ◽  
Scott L. Rauch ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Gray Matter ◽  
Twin Study ◽  
Stress Disorder ◽  
Anterior Cingulate ◽  
Gray Matter Loss

scholarly journals Voxel-based morphometric gray matter correlates of posttraumatic stress disorder

2013 ◽  
Vol 27 (4) ◽  
pp. 413-419 ◽  
Author(s):  
Mareen Weber ◽  
William D.S. Killgore ◽  
Isabelle M. Rosso ◽  
Jennifer C. Britton ◽  
Zachary J. Schwab ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Gray Matter ◽  
Stress Disorder

scholarly journals Culturally informed research design issues in a study for MDMA-assisted psychotherapy for posttraumatic stress disorder

2019 ◽  
Vol 4 (1) ◽  
pp. 40-50 ◽  
Author(s):  
Monnica T. Williams ◽  
Sara Reed ◽  
Ritika Aggarwal
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Stress Disorder ◽  
Late Phase ◽  
Community Outreach ◽  
People Of Color ◽  
Treatment Team ◽  
Open Label ◽  
Individual Level ◽  
Culturally Informed

Recent research suggests that psychedelic drugs can be powerful agents of change when utilized in conjunction with psychotherapy. Methylenedioxymethamphetamine (MDMA)-assisted psychotherapy has been studied as a means of helping people overcome posttraumatic stress disorder, believed to work by reducing fear of traumatic memories and increasing feelings of trust and compassion toward others, without inhibiting access to difficult emotions. However, research studies for psychedelic psychotherapies have largely excluded people of color, leaving important questions unaddressed for these populations. At the University of Connecticut, we participated as a study site in a MAPS-sponsored, FDA-reviewed Phase 2 open-label multisite study, with a focus on providing culturally informed care to people of color. We discuss the development of a study site focused on the ethnic minority trauma experience, including assessment of racial trauma, design of informed consent documents to improve understanding and acceptability to people of color, diversification of the treatment team, ongoing training for team members, validation of participant experiences of racial oppression at a cultural and individual level, examination of the setting and music used during sessions for cultural congruence, training for the independent rater pool, community outreach, and institutional resistance. We also discuss next steps in ensuring that access to culturally informed care is prioritized as MDMA and other psychedelics move into late phase trials, including the importance of diverse sites and training focused on therapy providers of color.

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