Artificial Intelligence in Molecular Imaging: Predicting Parkinson's Risk in REM Sleep Behavior Disorder
Artificial Intelligence on Molecular Imaging to Predict the Risks of Parkinson's Disease for Patients With Rapid Eye Movement Sleep Behavior Disorder
About This Trial
The study aims to systematically document the course of REM sleep behavior disorder (RBD) and investigate possible clinical and imaging biomarkers for disease progression and conversion risk to Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). The study will use artificial intelligence to analyze imaging and develop a reliable method to predict and stratify patients approaching conversion to overt a-synucleinopathy. Participants will be clinically evaluated and 2 imaging procedures will be done.
Who May Be Eligible (Plain English)
Original Eligibility Criteria
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Treatments Being Tested
PET/CT with 18-FDG
FDG-PET scans will be acquired in a Siemens Biograph Vision Quadra PET/CT (Siemens, Germany) at 30-minute post-injection of approximately 80 MBq 18F-FDG. The duration of the acquisition is 20 minutes. The PET images will be reconstructed with the vendor's time of flight (TOF) point-spread-function (PSF) algorithm, following corrections for randoms, scatter, and decay. Attenuation correction will be performed first using low-dose CT.
SPECT : 123 I-FP-CIT (DATSCAN)
DaT-Scans will be acquired in a GE Discovery NM/CT 670 Pro™. After injection of approximately 110 MBq 123I-FP-CIT, images will be acquired within 4 h post-injection. The duration of the acquisition is 35 minutes.
MRI
MRI examination to exclude structural brain anomalies.