Artificial Intelligence on Molecular Imaging to Predict the Risks of Parkinson's Disease for Patients With Rapid Eye Movement Sleep Behavior Disorder
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 20
- 试验地点
- 2
- 主要终点
- Assessment of Deep Learning Model Accuracy in Predicting Neurodegenerative Conversion in isolated REM sleep behavior disorder (iRBD) through Early Biomarker Detection
研究概览
简要总结
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Confirmed clinical iRBD diagnosis by movement disorder specialists according to the International Classification of Sleep Disorders
- •Written informed consent
排除标准
- •Known diagnosis of PD or other neurodegenerative disorder
- •Unequivocal signs of parkinsonism on examination
- •Narcolepsy or other known causes of RBD
- •Moderate to severe obstructive sleep apnea
- •Abnormal neurological or MRI examination
结局指标
主要结局
Assessment of Deep Learning Model Accuracy in Predicting Neurodegenerative Conversion in isolated REM sleep behavior disorder (iRBD) through Early Biomarker Detection
时间窗: From enrollment to end of follow-up period, expected to be 48 months
The investigators aim to evaluate the predictive accuracy of a deep learning model in identifying patients with iRBD who will progress to a neurodegenerative disorder. The primary outcome will assess the model's sensitivity in detecting early imaging biomarkers linked to disease progression, with the goal of enabling earlier intervention and improving long-term outcomes.
次要结局
- Comparison of the Estimated versus Observed Annual Conversion Risk of Isolated Rapid Eye Movement Behavior Disorder (iRBD) to Neurodegenerative Disorders(From enrollment to end of follow-up period, expected to be 48 months)
- Evaluation of Deep Learning Model Accuracy in Predicting Conversion of Isolated REM Sleep Behavior Disorder (iRBD) to Parkinson's Disease(From enrollment to end of follow-up period, expected to be 48 months)