Longitudinal prognosis of Parkinson's outcomes using causal connectivity.
Connectivity
Effective connectivity
Functional connectivity
Parkinson’s
Prognosis
fMRI
Journal
NeuroImage. Clinical
ISSN: 2213-1582
Titre abrégé: Neuroimage Clin
Pays: Netherlands
ID NLM: 101597070
Informations de publication
Date de publication:
06 Feb 2024
06 Feb 2024
Historique:
received:
25
08
2023
revised:
24
01
2024
accepted:
26
01
2024
medline:
13
3
2024
pubmed:
13
3
2024
entrez:
12
3
2024
Statut:
aheadofprint
Résumé
Despite the prevalence of Parkinson's disease (PD), there are no clinically-accepted neuroimaging biomarkers to predict the trajectory of motor or cognitive decline or differentiate Parkinson's disease from atypical progressive parkinsonian diseases. Since abnormal connectivity in the motor circuit and basal ganglia have been previously shown as early markers of neurodegeneration, we hypothesize that patterns of interregional connectivity could be useful to form patient-specific predictive models of disease state and of PD progression. We use fMRI data from subjects with Multiple System Atrophy (MSA), Progressive Supranuclear Palsy (PSP), idiopathic PD, and healthy controls to construct predictive models for motor and cognitive decline and differentiate between the four subgroups. Further, we identify the specific connections most informative for progression and diagnosis. When predicting the one-year progression in the MDS-UPDRS-III
Identifiants
pubmed: 38471435
pii: S2213-1582(24)00010-X
doi: 10.1016/j.nicl.2024.103571
pmc: PMC10944096
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
103571Informations de copyright
Copyright © 2024. Published by Elsevier Inc.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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