Robustly uncovering the heterogeneity of neurodegenerative disease by using data-driven subtyping in neuroimaging: A review

doi:10.1016/j.brainres.2023.148675

	Robustly uncovering the heterogeneity of neurodegenerative disease by using data-driven subtyping in neuroimaging: A review
	Chen, Pindong 1,2,3; Zhang, Shirui 4; Zhao, Kun 4; Kang, Xiaopeng 1,2; Rittman, Timothy 3; Liu, Yong 1,2,4,5
刊名	BRAIN RESEARCH
	2024-01-15
卷号	1823 页码:13
关键词	Neurodegenerative diseases Alzheimer's disease Heterogeneity Subtype Data-driven
ISSN号	0006-8993
DOI	10.1016/j.brainres.2023.148675
通讯作者	Liu, Yong(yongliu@bupt.edu.cn)
英文摘要	Neurodegenerative diseases are associated with heterogeneity in genetics, pathology, and clinical manifestation. Understanding this heterogeneity is particularly relevant for clinical prognosis and stratifying patients for disease modifying treatments. Recently, data-driven methods based on neuroimaging have been applied to investigate the subtyping of neurodegenerative disease, helping to disentangle this heterogeneity. We reviewed brain-based subtyping studies in aging and representative neurodegenerative diseases, including Alzheimer's disease, mild cognitive impairment, frontotemporal dementia, and Lewy body dementia, from January 2000 to November 2022. We summarized clustering methods, validation, robustness, reproducibility, and clinical relevance of 71 eligible studies in the present study. We found vast variations in approaches between studies, including ten neuroimaging modalities, 24 cluster algorithms, and 41 methods of cluster number determination. The clinical relevance of subtyping studies was evaluated by summarizing the analysis method of clinical measurements, showing a relatively low clinical utility in the current studies. Finally, we conclude that future studies of heterogeneity in neurodegenerative disease should focus on validation, comparison between subtyping approaches, and prioritise clinical utility.
资助项目	Fundamental Research Funds for the Central Universities[2021XD-A03] ; Beijing Nat- ural Science Funds for Distinguished Young Scholars[JQ20036] ; National Natural Science Foundation of China[62333002] ; National Natural Science Foundation of China[82172018]
WOS关键词	ALZHEIMERS-DISEASE ; CLINICAL CHARACTERISTICS ; FRONTOTEMPORAL DEMENTIA ; CORTICAL THICKNESS ; DEFINED SUBTYPES ; COMPOSITE SCORE ; BRAIN ATROPHY ; PATTERNS ; CLUSTERS ; MEMORY
WOS研究方向	Neurosciences & Neurology
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:001125335800001
资助机构	Fundamental Research Funds for the Central Universities ; Beijing Nat- ural Science Funds for Distinguished Young Scholars ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/54931]
专题	自动化研究所_脑网络组研究中心
通讯作者	Liu, Yong
作者单位	1.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 3.Univ Cambridge, Dept Clin Neurosci, Cambridge, England 4.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing, Peoples R China 5.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100876, Peoples R China
推荐引用方式 GB/T 7714	Chen, Pindong,Zhang, Shirui,Zhao, Kun,et al. Robustly uncovering the heterogeneity of neurodegenerative disease by using data-driven subtyping in neuroimaging: A review[J]. BRAIN RESEARCH,2024,1823:13.
APA	Chen, Pindong,Zhang, Shirui,Zhao, Kun,Kang, Xiaopeng,Rittman, Timothy,&Liu, Yong.(2024).Robustly uncovering the heterogeneity of neurodegenerative disease by using data-driven subtyping in neuroimaging: A review.BRAIN RESEARCH,1823,13.
MLA	Chen, Pindong,et al."Robustly uncovering the heterogeneity of neurodegenerative disease by using data-driven subtyping in neuroimaging: A review".BRAIN RESEARCH 1823(2024):13.