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Quantitative Radiomic Features as New Biomarkers for Alzheimer's Disease: An Amyloid PET Study

文献类型：期刊论文

作者Ding, Yanhui1; Zhao, Kun2,3,4; Che, Tongtong2; Du, Kai3,4,5,6; Sun, Hongzan7; Liu, Shu3,4,6; Zheng, Yuanjie1; Li, Shuyu2; Liu, Bing3,4,5,6; Liu, Yong3,4,5,6,8,9
刊名CEREBRAL CORTEX
出版日期2021-08-01
卷号31期号:8页码:3950-3961
ISSN号1047-3211
关键词Alzheimer's disease biomarker machine learning prediction quantitative radiomic features
DOI10.1093/cercor/bhab061
通讯作者Liu, Yong(yongliu@bupt.edu.cn)
英文摘要Growing evidence indicates that amyloid-beta (A beta) accumulation is one of the most common neurobiological biomarkers in Alzheimer's disease (AD). The primary aim of this study was to explore whether the radiomic features of A beta positron emission tomography (PET) images are used as predictors and provide a neurobiological foundation for AD. The radiomics features of A beta PET imaging of each brain region of the Brainnetome Atlas were computed for classification and prediction using a support vector machine model. The results showed that the area under the receiver operating characteristic curve (AUC) was 0.93 for distinguishing AD (N=291) from normal control (NC; N= 334). Additionally, the AUC was 0.83 for the prediction of mild cognitive impairment (MCI) converting (N=88) (vs. no conversion, N=100) to AD. In the MCI and AD groups, the systemic analysis demonstrated that the classification outputs were significantly associated with clinical measures (apolipoprotein E genotype, polygenic risk scores, polygenic hazard scores, cerebrospinal fluid A beta, and Tau, cognitive ability score, the conversion time for progressive MCI subjects and cognitive changes). These findings provide evidence that the radiomic features of A beta PET images can serve as new biomarkers for clinical applications in AD/MCI, further providing evidence for predicting whether MCI subjects will convert to AD.
WOS关键词MILD COGNITIVE IMPAIRMENT ; POLYGENIC HAZARD SCORE ; CLASSIFICATION ; RISK ; METAANALYSIS ; IMAGES ; ATLAS
资助项目Beijing Natural Science Funds for Distinguished Young Scholars[JQ200036] ; National Natural Science Foundation of China[81871438] ; National Natural Science Foundation of China[81901101] ; Primary Research & Development Plan of Shandong Province[2017GGX10112] ; Natural Science Foundation of Shandong Province[ZR2020MF051]
WOS研究方向Neurosciences & Neurology
语种英语
出版者OXFORD UNIV PRESS INC
WOS记录号WOS:000674446400027
资助机构Beijing Natural Science Funds for Distinguished Young Scholars ; National Natural Science Foundation of China ; Primary Research & Development Plan of Shandong Province ; Natural Science Foundation of Shandong Province
源URL[http://ir.ia.ac.cn/handle/173211/45514]  
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.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250014, Peoples R China
2.Beihang Univ, Sch Biol Sci & Med Engn, Beijing 100191, Peoples R China
3.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
5.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Inst Automat, Beijing 100190, Peoples R China
6.Chinese Acad Sci, Univ Chinese Acad Sci, Beijing 100049, Peoples R China
7.China Med Univ, Dept Radiol, Shengjing Hosp, Shenyang 110004, Peoples R China
8.Pazhou Lab, Guangzhou 510330, Peoples R China
9.Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing 100876, Peoples R China
推荐引用方式
GB/T 7714		 Ding, Yanhui,Zhao, Kun,Che, Tongtong,et al. Quantitative Radiomic Features as New Biomarkers for Alzheimer's Disease: An Amyloid PET Study[J]. CEREBRAL CORTEX,2021,31(8):3950-3961.
APA Ding, Yanhui.,Zhao, Kun.,Che, Tongtong.,Du, Kai.,Sun, Hongzan.,...&Liu, Yong.(2021).Quantitative Radiomic Features as New Biomarkers for Alzheimer's Disease: An Amyloid PET Study.CEREBRAL CORTEX,31(8),3950-3961.
MLA Ding, Yanhui,et al."Quantitative Radiomic Features as New Biomarkers for Alzheimer's Disease: An Amyloid PET Study".CEREBRAL CORTEX 31.8(2021):3950-3961.

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来源：自动化研究所

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