Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.
Journal
Annals of neurology
ISSN: 1531-8249
Titre abrégé: Ann Neurol
Pays: United States
ID NLM: 7707449
Informations de publication
Date de publication:
11 Mar 2024
11 Mar 2024
Historique:
revised:
09
02
2024
received:
09
01
2023
accepted:
19
02
2024
medline:
11
3
2024
pubmed:
11
3
2024
entrez:
11
3
2024
Statut:
aheadofprint
Résumé
To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : National Institute for Health and Care Research
Organisme : Foundation for the National Institutes of Health
ID : AG016574
Organisme : Foundation for the National Institutes of Health
ID : AG62677
Organisme : Foundation for the National Institutes of Health
ID : NS100620
Organisme : Foundation for the National Institutes of Health
ID : AG056639
Organisme : Foundation for the National Institutes of Health
ID : AG071754
Organisme : Slovak Scientific Grant Agency
ID : VEGA 1/0712/22
Organisme : Czech Ministry of Health
ID : NU21-04-00535
Organisme : Agentúra na Podporu Výskumu a Vývoja
ID : APVV-18-0547
Organisme : Agentúra na Podporu Výskumu a Vývoja
ID : APVV-22-0279
Organisme : Ted Turner and Family Foundation
Organisme : National Institute for Neurological Research
ID : LX22NPO5107
Organisme : Monument Trust Discovery Award from Parkinson's UK
Organisme : Ministero della Salute
Organisme : Mayo Clinic Dorothy and Harry T. Mangurian Jr. Lewy Body Dementia Program
Organisme : Little Family Foundation
Organisme : Ministero dell'Università e della Ricerca
Organisme : GE Healthcare
Informations de copyright
© 2024 The Authors. Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.
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