Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study

Spatial covariance mapping of brain activity has been used increasingly with metabolic imaging to detect and quantify abnormal disease patterns in patient populations. Metabolic topographies such as the Parkinson's disease-related pattern (PDRP), while extensively validated, require access to p...

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Main Authors: Andrea Rommal, An Vo, Katharina A. Schindlbeck, Andrea Greuel, Marina C. Ruppert, Carsten Eggers, David Eidelberg
Format: Article
Language:English
Published: Elsevier 2021-09-01
Series:NeuroImage: Reports
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666956021000246
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author Andrea Rommal
An Vo
Katharina A. Schindlbeck
Andrea Greuel
Marina C. Ruppert
Carsten Eggers
David Eidelberg
author_facet Andrea Rommal
An Vo
Katharina A. Schindlbeck
Andrea Greuel
Marina C. Ruppert
Carsten Eggers
David Eidelberg
author_sort Andrea Rommal
collection DOAJ
description Spatial covariance mapping of brain activity has been used increasingly with metabolic imaging to detect and quantify abnormal disease patterns in patient populations. Metabolic topographies such as the Parkinson's disease-related pattern (PDRP), while extensively validated, require access to positron emission tomography (PET) and radiation exposure. Recently, we developed a fully non-invasive approach to identify analogous disease networks with resting-state functional MRI (rs-fMRI) using independent component analysis (ICA) and bootstrap resampling. We designated the original rs-fMRI PD topography as fPDRPNS after its site of identification at North Shore University Hospital (Manhasset, New York).In this study, we validated fPDRPNS in rs-fMRI scans of PD patients (n = 51; 25 training and 26 testing) and age-matched healthy control subjects (n = 25) acquired in Cologne, Germany. These scans were also used to identify an independent rs-fMRI PD pattern termed fPDRPCOL. The resulting topography and expression levels (subject scores) were then compared to corresponding fPDRPNS values computed in the two populations.We found that fPDRPNS and fPDRPCOL were topographically similar. Prominent contributions arose from the putamen, globus pallidus, pons, cerebellum, and thalamus, which have been linked to the core zone of the PDRP in prior studies. Indeed, a significant correlation was noted between core region weights on the two fPDRP topographies (r = 0.62, p < 0.005). Expression levels for fPDRPCOL and fPDRPNS were significantly correlated in the patients scanned at each site (Cologne: r = 0.39, p < 0.01; North Shore: r = 0.65, p < 0.005). Abnormal elevations in fPDRPCOL core expression were observed for both patient groups (Cologne: p = 0.01; North Shore: p = 0.05) compared to healthy controls. Correlations of fPDRP subject scores with clinical motor disability ratings were significant in each of the derivation samples (fPDRPCOL p < 0.005 for Cologne patients; fPDRPNS p < 0.05 for North Shore patients); clinical correlations were less robust on out-of-sample testing. Of note, significant clinical correlations were observed (p < 0.05) when expression values were computed for the fPDRP core in isolation as opposed to the whole network.The findings demonstrate the reproducibility of fPDRP networks across patient populations, sites, and scanning platforms. Rs-fMRI may provide a non-invasive alternative to metabolic PET for the quantitative assessment of disease networks in the clinical setting.
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spelling doaj-art-a089a2c1662445f5a80962bc458618c52025-08-20T02:00:39ZengElsevierNeuroImage: Reports2666-95602021-09-011310002610.1016/j.ynirp.2021.100026Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation studyAndrea Rommal0An Vo1Katharina A. Schindlbeck2Andrea Greuel3Marina C. Ruppert4Carsten Eggers5David Eidelberg6Center for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USACenter for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USACenter for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USADepartment of Neurology, University Hospital Giessen and Marburg, Marburg, GermanyDepartment of Neurology, University Hospital Giessen and Marburg, Marburg, Germany; Center for Mind, Brain and Behavior, Universities of Marburg and Giessen, GermanyDepartment of Neurology, University Hospital Giessen and Marburg, Marburg, Germany; Center for Mind, Brain and Behavior, Universities of Marburg and Giessen, GermanyCenter for Neurosciences, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA; Corresponding author. Center for Neurosciences, The Feinstein Institutes for Medical Research, 350 Community Drive, Manhasset, NY, 11030, USA.Spatial covariance mapping of brain activity has been used increasingly with metabolic imaging to detect and quantify abnormal disease patterns in patient populations. Metabolic topographies such as the Parkinson's disease-related pattern (PDRP), while extensively validated, require access to positron emission tomography (PET) and radiation exposure. Recently, we developed a fully non-invasive approach to identify analogous disease networks with resting-state functional MRI (rs-fMRI) using independent component analysis (ICA) and bootstrap resampling. We designated the original rs-fMRI PD topography as fPDRPNS after its site of identification at North Shore University Hospital (Manhasset, New York).In this study, we validated fPDRPNS in rs-fMRI scans of PD patients (n = 51; 25 training and 26 testing) and age-matched healthy control subjects (n = 25) acquired in Cologne, Germany. These scans were also used to identify an independent rs-fMRI PD pattern termed fPDRPCOL. The resulting topography and expression levels (subject scores) were then compared to corresponding fPDRPNS values computed in the two populations.We found that fPDRPNS and fPDRPCOL were topographically similar. Prominent contributions arose from the putamen, globus pallidus, pons, cerebellum, and thalamus, which have been linked to the core zone of the PDRP in prior studies. Indeed, a significant correlation was noted between core region weights on the two fPDRP topographies (r = 0.62, p < 0.005). Expression levels for fPDRPCOL and fPDRPNS were significantly correlated in the patients scanned at each site (Cologne: r = 0.39, p < 0.01; North Shore: r = 0.65, p < 0.005). Abnormal elevations in fPDRPCOL core expression were observed for both patient groups (Cologne: p = 0.01; North Shore: p = 0.05) compared to healthy controls. Correlations of fPDRP subject scores with clinical motor disability ratings were significant in each of the derivation samples (fPDRPCOL p < 0.005 for Cologne patients; fPDRPNS p < 0.05 for North Shore patients); clinical correlations were less robust on out-of-sample testing. Of note, significant clinical correlations were observed (p < 0.05) when expression values were computed for the fPDRP core in isolation as opposed to the whole network.The findings demonstrate the reproducibility of fPDRP networks across patient populations, sites, and scanning platforms. Rs-fMRI may provide a non-invasive alternative to metabolic PET for the quantitative assessment of disease networks in the clinical setting.http://www.sciencedirect.com/science/article/pii/S2666956021000246Parkinson's diseaseBrain networkResting-state functional MRIIndependent component analysis
spellingShingle Andrea Rommal
An Vo
Katharina A. Schindlbeck
Andrea Greuel
Marina C. Ruppert
Carsten Eggers
David Eidelberg
Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study
NeuroImage: Reports
Parkinson's disease
Brain network
Resting-state functional MRI
Independent component analysis
title Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study
title_full Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study
title_fullStr Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study
title_full_unstemmed Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study
title_short Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study
title_sort parkinson s disease related pattern pdrp identified using resting state functional mri validation study
topic Parkinson's disease
Brain network
Resting-state functional MRI
Independent component analysis
url http://www.sciencedirect.com/science/article/pii/S2666956021000246
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