ArticleHuman brain mapping2024
Brain structure ages-A new biomarker for multi-disease classification.
Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Methodological limitations of the BrainStructureAges pipeline from the volBrain platform: a brief report of the normative pediatric group.Pediatric radiology · 2026Article
- Expanded Access use of Intravenous Gene Transfer with AAV9-GLB1 in a Juvenile GM1 Gangliosidosis Participant.medRxiv : the preprint server for health sciences · 2026Article
- Aging beyond diagnosis: the MRI brain age gap across disorders.GeroScience · 2026Review
- [Research progress on intelligent brain age prediction methods in diagnosis of Parkinson's disease].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Review
- Infratentorial cerebral microbleeds and brain age gap in stroke patients: a cross-sectional neuroimaging study.GeroScience · 2026Article
- Brain age gradients as intermediate phenotypes linking plasma p-tau217 to cognition in community-dwelling older adults.NPJ dementia · 2026Article
- Subcortical Brain-Age Gaps Reveal Asymmetric Aging Patterns in Parkinson's Disease With Cognitive Impairment.Brain and behavior · 2026Article
- Brain age gap as predictor of disease progression in Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Biological Age Prediction of the Cerebellar Vermis in the Human Lifespan.Cerebellum (London, England) · 2025Article
- Regional brain aging patterns reveal disease-specific pathways of neurodegeneration.medRxiv : the preprint server for health sciences · 2025Article
- Epigenetic age is associated with regional brain aging along the sensorimotor-to-association axis of cortical organization.Neurobiology of aging · 2025Article
- Brain-age models with lower age prediction accuracy have higher sensitivity for disease detection.PLoS biology · 2025Article
- Lifespan Tree of Brain Anatomy: Diagnostic Values for Motor and Cognitive Neurodegenerative Diseases.Human brain mapping · 2025Article
- Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study.Translational psychiatry · 2025Article
- Validation of dementia-free status in the iranian brain imaging database using ADNI data: a transition point from middle age to older adulthood.BMC neurology · 2025Article
- Deep ensemble learning with transformer models for enhanced Alzheimer's disease detection.Scientific reports · 2025Article
- Mapping Divergent Subfield-Specific Hippocampal Degeneration in Mild Cognitive Impairment Continuum: Volumetric, Cognitive, and Genetic Predictors of Accelerated Hippocampal Biological Aging.CNS neuroscience & therapeutics · 2025Article
- Association of Psychological Resilience With Decelerated Brain Aging in Cognitively Healthy World Trade Center Responders.Biological psychiatry global open science · 2025Article
- Regional Brain Aging Disparity Index: Region-Specific Brain Aging State Index for Neurodegenerative Diseases and Chronic Disease Specificity.Bioengineering (Basel, Switzerland) · 2025Article
- Distinct brain age gradients across the adult lifespan reflect diverse neurobiological hierarchies.Communications biology · 2025Article
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4 authors.
Funding
Abstract
Age is an important variable to describe the expected brain's anatomy status across the normal aging trajectory. The deviation from that normative aging trajectory may provide some insights into neurological diseases. In neuroimaging, predicted brain age is widely used to analyze different diseases. However, using only the brain age gap information (i.e., the difference between the chronological age and the estimated age) can be not enough informative for disease classification problems. In this paper, we propose to extend the notion of global brain age by estimating brain structure ages using structural magnetic resonance imaging. To this end, an ensemble of deep learning models is first used to estimate a 3D aging map (i.e., voxel-wise age estimation). Then, a 3D segmentation mask is used to obtain the final brain structure ages. This biomarker can be used in several situations. First, it enables to accurately estimate the brain age for the purpose of anomaly detection at the population level. In this situation, our approach outperforms several state-of-the-art methods. Second, brain structure ages can be used to compute the deviation from the normal aging process of each brain structure. This feature can be used in a multi-disease classification task for an accurate differential diagnosis at the subject level. Finally, the brain structure age deviations of individuals can be visualized, providing some insights about brain abnormality and helping clinicians in real medical contexts.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.