| Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease | |
Pan, Dan1; Zeng, An2; Yang, Baoyao2; Lai, Gangyong2; Hu, Bing3; Song, Xiaowei4; Jiang, Tianzi5,6
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| Source Publication | ADVANCED SCIENCE
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| 2022-12-27 | |
| Pages | 19 |
| Corresponding Author | Zeng, An(zengan@gdut.edu.cn) ; Yang, Baoyao(ybaoyao@gdut.edu.cn) |
| Abstract | Deep learning (DL) on brain magnetic resonance imaging (MRI) data has shown excellent performance in differentiating individuals with Alzheimer's disease (AD). However, the value of DL in detecting progressive structural MRI (sMRI) abnormalities linked to AD pathology has yet to be established. In this study, an interpretable DL algorithm named the Ensemble of 3-dimensional convolutional neural network (Ensemble 3DCNN) with enhanced parsing techniques is proposed to investigate the longitudinal trajectories of whole-brain sMRI changes denoting AD onset and progression. A set of 2369 T1-weighted images from the multi-centre Alzheimer's Disease Neuroimaging Initiative and Open Access Series of Imaging Studies cohorts are applied to model derivation, validation, testing, and pattern analysis. An Ensemble-3DCNN-based P-score is generated, based on which multiple brain regions, including amygdala, insular, parahippocampal, and temporal gyrus, exhibit early and connected progressive neurodegeneration. Complex individual variability in the sMRI is also observed. This study combining non-invasive sMRI and interpretable DL in detecting patterned sMRI changes confirmed AD pathological progression, shedding new light on predicting AD progression using whole-brain sMRI. |
| Keyword | Alzheimer's disease deep learning longitudinal trajectories of neurodegeneration structural magnetic resonance imaging |
| DOI | 10.1002/advs.202204717 |
| WOS Keyword | NEUROIMAGING BIOMARKERS ; ATROPHY ; HETEROGENEITY ; DECLINE ; INSULA ; CORTEX ; SCALE ; AGE |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[61976058] ; National Natural Science Foundation of China[61772143] ; National Natural Science Foundation of China[62102098] ; Science and Technology Planning Project of Guangdong[2021A1515012300] ; Science and Technology Planning Project of Guangdong[2019A050510041] ; Science and Technology Planning Project of Guangdong[2021B0101220006] ; Science and Technology Planning Project of Guangzhou[202103000034] ; Science and Technology Planning Project of Guangzhou[202206010007] ; Science and Technology Planning Project of Guangzhou[202002020090] ; Science and Technology Planning Project of Guangzhou[202201010266] ; Science and Technology Planning Project of Guangzhou[FHG2017-001] ; Surrey Hospital and Outpatient Centre Foundation[FHG2017-001] ; Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health)[U01 AG024904] ; DOD ADNI (Department of Defense Award[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 ; companyGenentech, Inc. ; Fujirebio ; GEHealthcare ; 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 Organization | National Natural Science Foundation of China ; Science and Technology Planning Project of Guangdong ; Science and Technology Planning Project of Guangzhou ; Surrey Hospital and Outpatient Centre Foundation ; Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) ; DOD ADNI (Department of Defense Award ; 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 ; companyGenentech, Inc. ; Fujirebio ; GEHealthcare ; 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 Area | Chemistry ; Science & Technology - Other Topics ; Materials Science |
| WOS Subject | Chemistry, Multidisciplinary ; Nanoscience & Nanotechnology ; Materials Science, Multidisciplinary |
| WOS ID | WOS:000904760100001 |
| Publisher | WILEY |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/51151 |
| Collection | 脑网络组研究 |
| Corresponding Author | Zeng, An; Yang, Baoyao |
| Affiliation | 1.Guangdong Polytech Normal Univ, Sch Elect & Informat, Guangzhou 510665, Peoples R China 2.Guangdong Univ Technol, Fac Comp, Guangzhou 510006, Peoples R China 3.Sun Yat Sen Univ, Dept Radiol, Affiliated Hosp 3, Guangzhou 510630, Peoples R China 4.Fraser Hlth, Clin Res Ctr, Surrey Mem Hosp, Surrey, BC V3V 1Z2, Canada 5.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China 6.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China |
| Recommended Citation GB/T 7714 | Pan, Dan,Zeng, An,Yang, Baoyao,et al. Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease[J]. ADVANCED SCIENCE,2022:19. |
| APA | Pan, Dan.,Zeng, An.,Yang, Baoyao.,Lai, Gangyong.,Hu, Bing.,...&Jiang, Tianzi.(2022).Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease.ADVANCED SCIENCE,19. |
| MLA | Pan, Dan,et al."Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease".ADVANCED SCIENCE (2022):19. |
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