Multiscale brain age prediction reveals region-specific accelerated brain aging in Parkinson's disease

被引:1
|
作者
Chen, Yueh-Sheng [1 ,2 ]
Kuo, Chen-Yuan [3 ]
Lu, Cheng-Hsien [2 ,4 ]
Wang, Yuan-Wei [5 ]
Chou, Kun-Hsien [3 ,6 ]
Lin, Wei-Che [1 ,2 ]
机构
[1] Kaohsiung Chang Gung Mem Hosp, Dept Diagnost Radiol, Kaohsiung, Taiwan
[2] Chang Gung Univ, Coll Med, Kaohsiung, Taiwan
[3] Natl Yang Ming Chiao Tung Univ, Inst Neurosci, Taipei, Taiwan
[4] Kaohsiung Chang Gung Mem Hosp, Dept Neurol, Kaohsiung, Taiwan
[5] Natl Appl Res Labs NARLabs, Sci & Technol Policy Res & Informat Ctr, Taipei, Taiwan
[6] Natl Yang Ming Chiao Tung Univ, Brain Res Ctr, Taipei, Taiwan
关键词
Brain aging; Machine learning; Parkinson disease; Magnetic resonance imaging; CEREBELLUM; SELECTION; NETWORK; ATLAS;
D O I
10.1016/j.neurobiolaging.2024.05.003
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Brain biological age, which measures the aging process in the brain using neuroimaging data, has been used to assess advanced brain aging in neurodegenerative diseases, including Parkinson disease (PD). However, assuming that whole brain degeneration is uniform may not be sufficient for assessing the complex neurodegenerative processes in PD. In this study we constructed a multiscale brain age prediction models based on structural MRI of 1240 healthy participants. To assess the brain aging patterns using the brain age prediction model, 93 PD patients and 91 healthy controls matching for sex and age were included. We found increased global and regional brain age in PD patients. The advanced aging regions were predominantly noted in the frontal and temporal cortices, limbic system, basal ganglia, thalamus, and cerebellum. Furthermore, region-level rather than global brain age in PD patients was associated with disease severity. Our multiscale brain age prediction model could aid in the development of objective image-based biomarkers to detect advanced brain aging in neurodegenerative diseases.
引用
收藏
页码:122 / 129
页数:8
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