Evaluation of non-motor symptoms in Parkinson’s disease using multiparametric MRI with the multiplex sequence

BackgroundNon-motor symptoms (NMS) in Parkinson’s disease (PD) often precede motor manifestations and are challenging to detect with conventional MRI. This study investigates the use of the Multi-Flip-Angle and Multi-Echo Gradient Echo Sequence (MULTIPLEX) in MRI to detect previously undetectable mi...

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Main Authors: He Sui, Zhanhao Mo, Feng Shi, Qing Zhou, Dan Yu, Jiaqi Wang, Lin Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Aging Neuroscience
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Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2025.1602245/full
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author He Sui
Zhanhao Mo
Feng Shi
Qing Zhou
Dan Yu
Jiaqi Wang
Lin Liu
author_facet He Sui
Zhanhao Mo
Feng Shi
Qing Zhou
Dan Yu
Jiaqi Wang
Lin Liu
author_sort He Sui
collection DOAJ
description BackgroundNon-motor symptoms (NMS) in Parkinson’s disease (PD) often precede motor manifestations and are challenging to detect with conventional MRI. This study investigates the use of the Multi-Flip-Angle and Multi-Echo Gradient Echo Sequence (MULTIPLEX) in MRI to detect previously undetectable microstructural changes in brain tissue associated with NMS in PD.MethodsA prospective study was conducted on 37 patients diagnosed with PD. Anxiety and depression levels were assessed using the Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD), respectively. MRI techniques, including 3D T1-weighted imaging (3D T1WI) and MULTIPLEX - which encompasses T2*-mapping, T1-mapping, proton density-mapping, and quantitative susceptibility mapping (QSM)—were performed. Brain subregions were automatically segmented using deep learning, and their volume and quantitative parameters were correlated with NMS-related assessment scales using Spearman’s rank correlation coefficient.ResultsCorrelations were observed between QSM and T2* values of certain subregions within the left frontal and bilateral temporal lobes and both anxiety and depression (absolute r-values ranging from 0.358 to 0.480, p < 0.05). Additionally, volume measurements of regions within the bilateral frontal, temporal, and insular lobes exhibited negative correlations with anxiety and depression (absolute r-values ranging from 0.354 to 0.658, p < 0.05). In T1-mapping and proton density-mapping, no specific brain regions were found to be significantly associated with the NMS of PD under investigation.ConclusionQuantitative parameters derived from MULTIPLEX MRI show significant associations with clinical evaluations of NMS in PD. Multiparametric MR neuroimaging may serve as a potential early diagnostic tool for PD.
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spelling doaj-art-9a3b2d69fa5a43299834476989c6ffb72025-08-20T03:27:43ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652025-07-011710.3389/fnagi.2025.16022451602245Evaluation of non-motor symptoms in Parkinson’s disease using multiparametric MRI with the multiplex sequenceHe Sui0Zhanhao Mo1Feng Shi2Qing Zhou3Dan Yu4Jiaqi Wang5Lin Liu6China-Japan Union Hospital of Jilin University, Changchun, ChinaChina-Japan Union Hospital of Jilin University, Changchun, ChinaShanghai United Imaging Intelligence Co., Ltd., Shanghai, ChinaShanghai United Imaging Intelligence Co., Ltd., Shanghai, ChinaUnited Imaging Research Institute of Intelligent Imaging, Beijing, ChinaUnited Imaging Research, Shanghai, ChinaChina-Japan Union Hospital of Jilin University, Changchun, ChinaBackgroundNon-motor symptoms (NMS) in Parkinson’s disease (PD) often precede motor manifestations and are challenging to detect with conventional MRI. This study investigates the use of the Multi-Flip-Angle and Multi-Echo Gradient Echo Sequence (MULTIPLEX) in MRI to detect previously undetectable microstructural changes in brain tissue associated with NMS in PD.MethodsA prospective study was conducted on 37 patients diagnosed with PD. Anxiety and depression levels were assessed using the Hamilton Anxiety Scale (HAMA) and Hamilton Depression Scale (HAMD), respectively. MRI techniques, including 3D T1-weighted imaging (3D T1WI) and MULTIPLEX - which encompasses T2*-mapping, T1-mapping, proton density-mapping, and quantitative susceptibility mapping (QSM)—were performed. Brain subregions were automatically segmented using deep learning, and their volume and quantitative parameters were correlated with NMS-related assessment scales using Spearman’s rank correlation coefficient.ResultsCorrelations were observed between QSM and T2* values of certain subregions within the left frontal and bilateral temporal lobes and both anxiety and depression (absolute r-values ranging from 0.358 to 0.480, p < 0.05). Additionally, volume measurements of regions within the bilateral frontal, temporal, and insular lobes exhibited negative correlations with anxiety and depression (absolute r-values ranging from 0.354 to 0.658, p < 0.05). In T1-mapping and proton density-mapping, no specific brain regions were found to be significantly associated with the NMS of PD under investigation.ConclusionQuantitative parameters derived from MULTIPLEX MRI show significant associations with clinical evaluations of NMS in PD. Multiparametric MR neuroimaging may serve as a potential early diagnostic tool for PD.https://www.frontiersin.org/articles/10.3389/fnagi.2025.1602245/fullParkinson’s diseasenon-motor symptomsquantitative MRI analysisbrain segmentationearly diagnosis
spellingShingle He Sui
Zhanhao Mo
Feng Shi
Qing Zhou
Dan Yu
Jiaqi Wang
Lin Liu
Evaluation of non-motor symptoms in Parkinson’s disease using multiparametric MRI with the multiplex sequence
Frontiers in Aging Neuroscience
Parkinson’s disease
non-motor symptoms
quantitative MRI analysis
brain segmentation
early diagnosis
title Evaluation of non-motor symptoms in Parkinson’s disease using multiparametric MRI with the multiplex sequence
title_full Evaluation of non-motor symptoms in Parkinson’s disease using multiparametric MRI with the multiplex sequence
title_fullStr Evaluation of non-motor symptoms in Parkinson’s disease using multiparametric MRI with the multiplex sequence
title_full_unstemmed Evaluation of non-motor symptoms in Parkinson’s disease using multiparametric MRI with the multiplex sequence
title_short Evaluation of non-motor symptoms in Parkinson’s disease using multiparametric MRI with the multiplex sequence
title_sort evaluation of non motor symptoms in parkinson s disease using multiparametric mri with the multiplex sequence
topic Parkinson’s disease
non-motor symptoms
quantitative MRI analysis
brain segmentation
early diagnosis
url https://www.frontiersin.org/articles/10.3389/fnagi.2025.1602245/full
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