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Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder

Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute the...

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Autores principales: Yuan, Minlan, Qiu, Changjian, Meng, Yajing, Ren, Zhengjia, Yuan, Cui, Li, Yuchen, Gao, Meng, Lui, Su, Zhu, Hongru, Gong, Qiyong, Zhang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6218594/
https://www.ncbi.nlm.nih.gov/pubmed/30425661
http://dx.doi.org/10.3389/fpsyt.2018.00532
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author Yuan, Minlan
Qiu, Changjian
Meng, Yajing
Ren, Zhengjia
Yuan, Cui
Li, Yuchen
Gao, Meng
Lui, Su
Zhu, Hongru
Gong, Qiyong
Zhang, Wei
author_facet Yuan, Minlan
Qiu, Changjian
Meng, Yajing
Ren, Zhengjia
Yuan, Cui
Li, Yuchen
Gao, Meng
Lui, Su
Zhu, Hongru
Gong, Qiyong
Zhang, Wei
author_sort Yuan, Minlan
collection PubMed
description Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited. Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier. Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%. Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis.
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spelling pubmed-62185942018-11-13 Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder Yuan, Minlan Qiu, Changjian Meng, Yajing Ren, Zhengjia Yuan, Cui Li, Yuchen Gao, Meng Lui, Su Zhu, Hongru Gong, Qiyong Zhang, Wei Front Psychiatry Psychiatry Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited. Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier. Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%. Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis. Frontiers Media S.A. 2018-10-30 /pmc/articles/PMC6218594/ /pubmed/30425661 http://dx.doi.org/10.3389/fpsyt.2018.00532 Text en Copyright © 2018 Yuan, Qiu, Meng, Ren, Yuan, Li, Gao, Lui, Zhu, Gong and Zhang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Yuan, Minlan
Qiu, Changjian
Meng, Yajing
Ren, Zhengjia
Yuan, Cui
Li, Yuchen
Gao, Meng
Lui, Su
Zhu, Hongru
Gong, Qiyong
Zhang, Wei
Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder
title Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder
title_full Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder
title_fullStr Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder
title_full_unstemmed Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder
title_short Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder
title_sort pre-treatment resting-state functional mr imaging predicts the long-term clinical outcome after short-term paroxtine treatment in post-traumatic stress disorder
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6218594/
https://www.ncbi.nlm.nih.gov/pubmed/30425661
http://dx.doi.org/10.3389/fpsyt.2018.00532
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