CASIA OpenIR  > 脑网络组研究
Generalizable, Reproducible, and Neuroscientifically Interpretable Imaging Biomarkers for Alzheimer's Disease
Jin, Dan1,2,3; Zhou, Bo4; Han, Ying5; Ren, Jiaji1,2,3; Han, Tong6; Liu, Bing1,2,3,7; Lu, Jie8; Song, Chengyuan9; Wang, Pan10; Wang, Dawei11; Xu, Jian12; Yang, Zhengyi1,2,3; Yao, Hongxiang13; Yu, Chunshui14; Zhao, Kun15; Wintermark, Max16; Zuo, Nianming1,2,3; Zhang, Xinqing5; Zhou, Yuying10; Zhang, Xi4; Jiang, Tianzi1,2,3,7; Wang, Qing11; Liu, Yong1,2,3,7,17
Source PublicationADVANCED SCIENCE
2020-06-09
Pages12
Corresponding AuthorWang, Qing(wangqing663@163.com) ; Liu, Yong(yliu@nlpr.ia.ac.cn)
AbstractPrecision medicine for Alzheimer's disease (AD) necessitates the development of personalized, reproducible, and neuroscientifically interpretable biomarkers, yet despite remarkable advances, few such biomarkers are available. Also, a comprehensive evaluation of the neurobiological basis and generalizability of the end-to-end machine learning system should be given the highest priority. For this reason, a deep learning model (3D attention network, 3DAN) that can simultaneously capture candidate imaging biomarkers with an attention mechanism module and advance the diagnosis of AD based on structural magnetic resonance imaging is proposed. The generalizability and reproducibility are evaluated using cross-validation on in-house, multicenter (n = 716), and public (n = 1116) databases with an accuracy up to 92%. Significant associations between the classification output and clinical characteristics of AD and mild cognitive impairment (MCI, a middle stage of dementia) groups provide solid neurobiological support for the 3DAN model. The effectiveness of the 3DAN model is further validated by its good performance in predicting the MCI subjects who progress to AD with an accuracy of 72%. Collectively, the findings highlight the potential for structural brain imaging to provide a generalizable, and neuroscientifically interpretable imaging biomarker that can support clinicians in the early diagnosis of AD.
KeywordAlzheimer's disease computer-aided diagnosis neurobiological basis neuroscientifically interpretable biomarkers structural magnetic resonance imaging
DOI10.1002/advs.202000675
WOS KeywordMILD COGNITIVE IMPAIRMENT ; RESTING-STATE FMRI ; CLASSIFICATION ; ATROPHY ; RISK ; MRI ; HIPPOCAMPAL ; PERFORMANCE ; PREDICTION ; NETWORK
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program of China[2016YFC1305904] ; National Key Research and Development Program of China[2018YFC2001700] ; Strategic Priority Research Program (B) of the Chinese Academy of Sciences[XDB32020200] ; National Natural Science Foundation of China[81871438] ; National Natural Science Foundation of China[81901101] ; National Natural Science Foundation of China[61633018] ; National Natural Science Foundation of China[81571062] ; National Natural Science Foundation of China[81400890] ; National Natural Science Foundation of China[81471120] ; National Natural Science Foundation of China[81701781] ; Medical Big Data R&D Project of the PLA General Hospital[2018MBD028] ; Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health)[U01 AG024904] ; DOD ADNI (Department of Defense)[W81XWH-12-2-0012] ; National Institute on Aging ; National Institute of Biomedical Imaging and Bioengineering ; AbbVie ; Alzheimer's Association ; Alzheimer's Drug Discovery Foundation ; Araclon Biotech ; BioClinica, Inc. ; Biogen ; Bristol-Myers Squibb Company ; CereSpir, Inc. ; Cogstate ; Eisai Inc. ; Elan Pharmaceuticals, Inc. ; Eli Lilly and Company ; EuroImmun ; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc. ; Fujirebio ; GE Healthcare ; IXICO Ltd. ; Janssen Alzheimer Immunotherapy Research & Development, LLC. ; Johnson & Johnson Pharmaceutical Research & Development LLC. ; Lumosity ; Lundbeck ; Merck Co., Inc. ; Meso Scale Diagnostics, LLC. ; NeuroRx Research ; Neurotrack Technologies ; Novartis Pharmaceuticals Corporation ; Pfizer Inc. ; Piramal Imaging ; Servier ; Takeda Pharmaceutical Company ; Transition Therapeutics ; Canadian Institutes of Health Research
Funding OrganizationNational Key Research and Development Program of China ; Strategic Priority Research Program (B) of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; Medical Big Data R&D Project of the PLA General Hospital ; Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) ; DOD ADNI (Department of Defense) ; National Institute on Aging ; National Institute of Biomedical Imaging and Bioengineering ; AbbVie ; Alzheimer's Association ; Alzheimer's Drug Discovery Foundation ; Araclon Biotech ; BioClinica, Inc. ; Biogen ; Bristol-Myers Squibb Company ; CereSpir, Inc. ; Cogstate ; Eisai Inc. ; Elan Pharmaceuticals, Inc. ; Eli Lilly and Company ; EuroImmun ; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc. ; Fujirebio ; GE Healthcare ; IXICO Ltd. ; Janssen Alzheimer Immunotherapy Research & Development, LLC. ; Johnson & Johnson Pharmaceutical Research & Development LLC. ; Lumosity ; Lundbeck ; Merck Co., Inc. ; Meso Scale Diagnostics, LLC. ; NeuroRx Research ; Neurotrack Technologies ; Novartis Pharmaceuticals Corporation ; Pfizer Inc. ; Piramal Imaging ; Servier ; Takeda Pharmaceutical Company ; Transition Therapeutics ; Canadian Institutes of Health Research
WOS Research AreaChemistry ; Science & Technology - Other Topics ; Materials Science
WOS SubjectChemistry, Multidisciplinary ; Nanoscience & Nanotechnology ; Materials Science, Multidisciplinary
WOS IDWOS:000538998400001
PublisherWILEY
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/39823
Collection脑网络组研究
Corresponding AuthorWang, Qing; Liu, Yong
Affiliation1.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
4.Chinese Peoples Liberat Army Gen Hosp, Natl Clin Res Ctr Geriatr Dis, Med Ctr 2, Dept Neurol, Beijing 100853, Peoples R China
5.Capital Med Univ, Xuanwu Hosp, Dept Neurol, Beijing 100053, Peoples R China
6.Tianjin Huanhu Hosp, Dept Radiol, Tianjin 300350, Peoples R China
7.Chinese Acad Sci, Inst Automat, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China
8.Capital Med Univ, Xuanwu Hosp, Dept Radiol, Beijing 100053, Peoples R China
9.Shandong Univ, Qilu Hosp, Dept Neurol, Jinan 250012, Peoples R China
10.Tianjin Univ, Tianjin Huanhu Hosp, Dept Neurol, Tianjin 300350, Peoples R China
11.Shandong Univ, Qilu Hosp, Dept Radiol, Jinan 250012, Peoples R China
12.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
13.Chinese Peoples Liberat Army Gen Hosp, Natl Clin Res Ctr Geriatr Dis, Med Ctr 2, Dept Radiol, Beijing 100853, Peoples R China
14.Tianjin Med Univ, Gen Hosp, Dept Radiol, Tianjin 300052, Peoples R China
15.Beihang Univ, Beijing 100191, Peoples R China
16.Stanford Univ, Dept Radiol, Stanford, CA 94305 USA
17.Pazhou Lab, Guangzhou 510330, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences;  Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences;  Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Jin, Dan,Zhou, Bo,Han, Ying,et al. Generalizable, Reproducible, and Neuroscientifically Interpretable Imaging Biomarkers for Alzheimer's Disease[J]. ADVANCED SCIENCE,2020:12.
APA Jin, Dan.,Zhou, Bo.,Han, Ying.,Ren, Jiaji.,Han, Tong.,...&Liu, Yong.(2020).Generalizable, Reproducible, and Neuroscientifically Interpretable Imaging Biomarkers for Alzheimer's Disease.ADVANCED SCIENCE,12.
MLA Jin, Dan,et al."Generalizable, Reproducible, and Neuroscientifically Interpretable Imaging Biomarkers for Alzheimer's Disease".ADVANCED SCIENCE (2020):12.
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