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Abstract
An objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder (iRBD) is crucial for the management. This study aimed to investigate cognitive signature of brain [18F]FDG PET based on deep learning (DL) for evaluating patients with iRBD. Fifty iRBD patients, 19 with mild cognitive impairment (MCI) (RBD-MCI) and 31 without MCI (RBD-nonMCI), were prospectively enrolled. A DL model for the cognitive signature was trained by using Alzheimer's Disease Neuroimaging Initiative database and transferred to baseline [18F]FDG PET from the iRBD cohort. The results showed that the DL-based cognitive dysfunction score was significantly higher in RBD-MCI than in RBD-nonMCI. The AUC of ROC curve for differentiating RBD-MCI from RBD-nonMCI was 0.70 (95% CI 0.56-0.82). The baseline DL-based cognitive dysfunction score was significantly higher in iRBD patients who showed a decrease in CERAD scores during 2 years than in those who did not. Brain metabolic features related to cognitive dysfunction-related regions of individual iRBD patients mainly included posterior cortical regions. This work demonstrates that the cognitive signature based on DL could be used to objectively evaluate cognitive function in iRBD. We suggest that this approach could be extended to an objective biomarker predicting cognitive decline and neurodegeneration in iRBD.

Affiliations

Hyun Gee Ryoo # 1 2, Jung-Ick Byun # 3, Hongyoon Choi 4 5, Ki-Young Jung 6 7
1Department of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.
2Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
3Department of Neurology, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, Seoul, Republic of Korea.
4Department of Nuclear Medicine, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea. chy1000@snu.ac.kr.
5Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea. chy1000@snu.ac.kr.
6Department of Neurology, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea. jungky@snu.ac.kr.
7Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Korea. jungky@snu.ac.kr.
#Contributed equally.