Deep learning-based brain age prediction in normal aging and dementia.
Journal
Nature aging
ISSN: 2662-8465
Titre abrégé: Nat Aging
Pays: United States
ID NLM: 101773306
Informations de publication
Date de publication:
05 2022
05 2022
Historique:
received:
11
08
2021
accepted:
29
03
2022
medline:
1
5
2023
pubmed:
29
4
2023
entrez:
28
4
2023
Statut:
ppublish
Résumé
Brain aging is accompanied by patterns of functional and structural change. Alzheimer's disease (AD), a representative neurodegenerative disease, has been linked to accelerated brain aging. Here, we developed a deep learning-based brain age prediction model using a large collection of fluorodeoxyglucose positron emission tomography and structural magnetic resonance imaging and tested how the brain age gap relates to degenerative syndromes including mild cognitive impairment, AD, frontotemporal dementia and Lewy body dementia. Occlusion analysis, performed to facilitate the interpretation of the model, revealed that the model learns an age- and modality-specific pattern of brain aging. The elevated brain age gap was highly correlated with cognitive impairment and the AD biomarker. The higher gap also showed a longitudinal predictive nature across clinical categories, including cognitively unimpaired individuals who converted to a clinical stage. However, regions generating brain age gaps were different for each diagnostic group of which the AD continuum showed similar patterns to normal aging.
Identifiants
pubmed: 37118071
doi: 10.1038/s43587-022-00219-7
pii: 10.1038/s43587-022-00219-7
pmc: PMC10154042
mid: NIHMS1883781
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
412-424Subventions
Organisme : NIA NIH HHS
ID : R01 AG073282
Pays : United States
Organisme : NIA NIH HHS
ID : P50 AG016574
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG041851
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG011378
Pays : United States
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.
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