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Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies
INTRODUCTION: Identifying the optimal treatment for individuals with major depressive disorder (MDD) is often a long and complicated process. Functional magnetic resonance imaging (fMRI) studies have been used to help predict and explain differences in treatment response among individuals with MDD....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9567359/ http://dx.doi.org/10.1192/j.eurpsy.2022.758 |
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author | Torres, M. Manghera, P. Miller, C. |
author_facet | Torres, M. Manghera, P. Miller, C. |
author_sort | Torres, M. |
collection | PubMed |
description | INTRODUCTION: Identifying the optimal treatment for individuals with major depressive disorder (MDD) is often a long and complicated process. Functional magnetic resonance imaging (fMRI) studies have been used to help predict and explain differences in treatment response among individuals with MDD. OBJECTIVES: We conducted a comprehensive meta-analysis of treatment prediction studies utilizing fMRI in patients with MDD to provide evidence that neural activity can be used to predict response to antidepressant treatment. METHODS: A multi-level kernel density analysis was applied to these primary fMRI studies, in which we analyzed brain activation patterns of depressed patients (N= 364) before receiving antidepressant treatment. RESULTS: The results of this analysis demonstrated that hyperactivity in six brain regions significantly predicted treatment response in patients with MDD: the right anterior cingulate, right cuneus, left fusiform gyrus, left middle frontal gyrus, right cingulate gyrus, and left superior frontal gyrus. CONCLUSIONS: This study provides evidence that neural activity, as measured by standard fMRI paradigms, can be used to successfully predict response to antidepressant treatment. This may be used in the future clinically to improve decision-making processes and treatment outcomes for patients. DISCLOSURE: No significant relationships. |
format | Online Article Text |
id | pubmed-9567359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-95673592022-10-17 Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies Torres, M. Manghera, P. Miller, C. Eur Psychiatry Abstract INTRODUCTION: Identifying the optimal treatment for individuals with major depressive disorder (MDD) is often a long and complicated process. Functional magnetic resonance imaging (fMRI) studies have been used to help predict and explain differences in treatment response among individuals with MDD. OBJECTIVES: We conducted a comprehensive meta-analysis of treatment prediction studies utilizing fMRI in patients with MDD to provide evidence that neural activity can be used to predict response to antidepressant treatment. METHODS: A multi-level kernel density analysis was applied to these primary fMRI studies, in which we analyzed brain activation patterns of depressed patients (N= 364) before receiving antidepressant treatment. RESULTS: The results of this analysis demonstrated that hyperactivity in six brain regions significantly predicted treatment response in patients with MDD: the right anterior cingulate, right cuneus, left fusiform gyrus, left middle frontal gyrus, right cingulate gyrus, and left superior frontal gyrus. CONCLUSIONS: This study provides evidence that neural activity, as measured by standard fMRI paradigms, can be used to successfully predict response to antidepressant treatment. This may be used in the future clinically to improve decision-making processes and treatment outcomes for patients. DISCLOSURE: No significant relationships. Cambridge University Press 2022-09-01 /pmc/articles/PMC9567359/ http://dx.doi.org/10.1192/j.eurpsy.2022.758 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstract Torres, M. Manghera, P. Miller, C. Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies |
title | Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies |
title_full | Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies |
title_fullStr | Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies |
title_full_unstemmed | Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies |
title_short | Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies |
title_sort | prediction of treatment response in patients with major depressive disorder: a meta-analysis of functional magnetic resonance imaging studies |
topic | Abstract |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9567359/ http://dx.doi.org/10.1192/j.eurpsy.2022.758 |
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