Deep Learning‐Based Neuromelanin MRI Changes of Isolated REM Sleep Behavior Disorder

ABSTRACT Background Isolated REM sleep behavior disorder (iRBD) is considered a prodromal stage of parkinsonism. Neurodegenerative changes in the substantia nigra pars compacta (SNc) in parkinsonism can be detected using neuromelanin‐sensitive MRI. Objective To investigate SNc neuromelanin changes in iRBD patients using fully automatic segmentation. Methods We included 47 iRBD patients, 134 early Parkinson's disease (PD) patients and 55 healthy volunteers (HVs) scanned at 3 Tesla. SNc regions‐of‐interest were delineated automatically using convolutional neural network. SNc volumes, volumes corrected by total intracranial volume, signal‐to‐noise ratio (SNR) and contrast‐to‐noise ratio were computed. One‐way general linear models (GLM) analysis of covariance (ANCOVA) was conducted while adjusting for age and sex. Results All SNc measurements differed significantly between the three groups (except SNR in iRBD). Changes in iRBD were intermediate between those in PD and HVs. Conclusions Using fully automated SNc segmentation method and neuromelanin‐sensitive imaging, iRBD patients showed neurodegenerative changes in the SNc at a lower level than in PD patients. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society