Knowledge Commons of Institute of Automation,CAS
Robustly uncovering the heterogeneity of neurodegenerative disease by using data-driven subtyping in neuroimaging: A review | |
Chen, Pindong1,2,3; Zhang, Shirui4; Zhao, Kun4; Kang, Xiaopeng1,2; Rittman, Timothy3; Liu, Yong1,2,4 | |
发表期刊 | Brain research |
ISSN | 0006-8993 |
2024-01-15 | |
卷号 | 1823页码:13 |
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. |
关键词 | Neurodegenerative diseases Alzheimer's disease Heterogeneity Subtype Data-driven |
DOI | 10.1016/j.brainres.2023.148675 |
关键词[WOS] | ALZHEIMERS-DISEASE ; CLINICAL CHARACTERISTICS ; FRONTOTEMPORAL DEMENTIA ; CORTICAL THICKNESS ; DEFINED SUBTYPES ; COMPOSITE SCORE ; BRAIN ATROPHY ; PATTERNS ; CLUSTERS ; MEMORY |
收录类别 | SCI |
语种 | 英语 |
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] |
项目资助者 | Fundamental Research Funds for the Central Universities ; Beijing Nat- ural Science Funds for Distinguished Young Scholars ; National Natural Science Foundation of China |
WOS研究方向 | Neurosciences & Neurology |
WOS类目 | Neurosciences |
WOS记录号 | WOS:001125335800001 |
出版者 | ELSEVIER |
七大方向——子方向分类 | 脑网络分析 |
国重实验室规划方向分类 | 其他 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/54932 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
通讯作者 | Liu, Yong |
作者单位 | 1.Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China 3.Department of Clinical Neurosciences, University of Cambridge, Cambridge, Cambridgeshire, UK 4.School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
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. |
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