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Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages

Differentiating the parkinsonian variant of multiple system atrophy (MSA‐P) from idiopathic Parkinson's disease (IPD) is challenging, especially in the early stages. This study aimed to investigate differences and similarities in the brain functional connectomes of IPD and MSA‐P patients and us...

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Autores principales: Chen, Boyu, Cui, Wenzhuo, Wang, Shanshan, Sun, Anlan, Yu, Hongmei, Liu, Yu, He, Jiachuan, Fan, Guoguang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028675/
https://www.ncbi.nlm.nih.gov/pubmed/36661217
http://dx.doi.org/10.1002/hbm.26201
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author Chen, Boyu
Cui, Wenzhuo
Wang, Shanshan
Sun, Anlan
Yu, Hongmei
Liu, Yu
He, Jiachuan
Fan, Guoguang
author_facet Chen, Boyu
Cui, Wenzhuo
Wang, Shanshan
Sun, Anlan
Yu, Hongmei
Liu, Yu
He, Jiachuan
Fan, Guoguang
author_sort Chen, Boyu
collection PubMed
description Differentiating the parkinsonian variant of multiple system atrophy (MSA‐P) from idiopathic Parkinson's disease (IPD) is challenging, especially in the early stages. This study aimed to investigate differences and similarities in the brain functional connectomes of IPD and MSA‐P patients and use machine learning methods to explore the diagnostic utility of these features. Resting‐state fMRI data were acquired from 88 healthy controls, 76 MSA‐P patients, and 53 IPD patients using a 3.0 T scanner. The whole‐brain functional connectome was constructed by thresholding the Pearson correlation matrices of 116 regions, and topological properties were evaluated through graph theory approaches. Connectome measurements were used as features in machine learning models (random forest [RF]/logistic regression [LR]/support vector machine) to distinguish IPD and MSA‐P patients. Regarding graph metrics, early IPD and MSA‐P patients shared network topological properties. Both patient groups showed functional connectivity disruptions within the cerebellum‐basal ganglia‐cortical network, but these disconnections were mainly in the cortico‐thalamo‐cerebellar circuits in MSA‐P patients and the basal ganglia‐thalamo‐cortical circuits in IPD patients. Among the connectome parameters, t tests combined with the RF method identified 15 features, from which the LR classifier achieved the best diagnostic performance on the validation set (accuracy = 92.31%, sensitivity = 90.91%, specificity = 93.33%, area under the receiver operating characteristic curve = 0.89). MSA‐P and IPD patients show similar whole‐brain network topological alterations. MSA‐P primarily affects cerebellar nodes, and IPD primarily affects basal ganglia nodes; both conditions disrupt the cerebellum‐basal ganglia‐cortical network. Moreover, functional connectome parameters showed outstanding value in the differential diagnosis of early MSA‐P and IPD.
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spelling pubmed-100286752023-03-22 Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages Chen, Boyu Cui, Wenzhuo Wang, Shanshan Sun, Anlan Yu, Hongmei Liu, Yu He, Jiachuan Fan, Guoguang Hum Brain Mapp Research Articles Differentiating the parkinsonian variant of multiple system atrophy (MSA‐P) from idiopathic Parkinson's disease (IPD) is challenging, especially in the early stages. This study aimed to investigate differences and similarities in the brain functional connectomes of IPD and MSA‐P patients and use machine learning methods to explore the diagnostic utility of these features. Resting‐state fMRI data were acquired from 88 healthy controls, 76 MSA‐P patients, and 53 IPD patients using a 3.0 T scanner. The whole‐brain functional connectome was constructed by thresholding the Pearson correlation matrices of 116 regions, and topological properties were evaluated through graph theory approaches. Connectome measurements were used as features in machine learning models (random forest [RF]/logistic regression [LR]/support vector machine) to distinguish IPD and MSA‐P patients. Regarding graph metrics, early IPD and MSA‐P patients shared network topological properties. Both patient groups showed functional connectivity disruptions within the cerebellum‐basal ganglia‐cortical network, but these disconnections were mainly in the cortico‐thalamo‐cerebellar circuits in MSA‐P patients and the basal ganglia‐thalamo‐cortical circuits in IPD patients. Among the connectome parameters, t tests combined with the RF method identified 15 features, from which the LR classifier achieved the best diagnostic performance on the validation set (accuracy = 92.31%, sensitivity = 90.91%, specificity = 93.33%, area under the receiver operating characteristic curve = 0.89). MSA‐P and IPD patients show similar whole‐brain network topological alterations. MSA‐P primarily affects cerebellar nodes, and IPD primarily affects basal ganglia nodes; both conditions disrupt the cerebellum‐basal ganglia‐cortical network. Moreover, functional connectome parameters showed outstanding value in the differential diagnosis of early MSA‐P and IPD. John Wiley & Sons, Inc. 2023-01-20 /pmc/articles/PMC10028675/ /pubmed/36661217 http://dx.doi.org/10.1002/hbm.26201 Text en © 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Chen, Boyu
Cui, Wenzhuo
Wang, Shanshan
Sun, Anlan
Yu, Hongmei
Liu, Yu
He, Jiachuan
Fan, Guoguang
Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages
title Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages
title_full Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages
title_fullStr Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages
title_full_unstemmed Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages
title_short Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages
title_sort functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic parkinson's disease at early stages
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028675/
https://www.ncbi.nlm.nih.gov/pubmed/36661217
http://dx.doi.org/10.1002/hbm.26201
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