ArticleScientific reports2024
Exploring the relationship among Alzheimer's disease, aging and cognitive scores through neuroimaging-based approach.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Brain age as an accurate biomarker of preclinical cognitive decline: evidence from a 12-year longitudinal study.Journal of neurology · 2025Article
- Neuron-Astrocyte Interactions in Aging and Alzheimer's Disease: Dysregulation of Amyloid Precursor Protein.Ageing & longevity · 2025Article
- An explainable AI approach for mapping multivariate regional brain age and clinical severity patterns in Alzheimer's disease.Biology methods & protocols · 2025Article
- Real-world diagnosis and management of mild cognitive impairment and Alzheimer's disease dementia in the United Kingdom.Journal of Alzheimer's disease reportsArticle
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3 authors.
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Abstract
Alzheimer's disease (AD) is a fatal neurodegenerative disorder, with the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) serving significant roles in monitoring its progression. We hypothesize that while cognitive assessment scores can detect AD-related brain changes, the targeted brain regions may differ. Additionally, given AD's strong association with aging, we propose that specific brain regions are influenced by both AD pathology and aging, exhibiting strong correlations with both. To test these hypotheses, we developed a 3D convolutional network with a mixed-attention mechanism to recognize AD subjects from structural magnetic resonance imaging (sMRI) data and utilize 3D convolutional methods to pinpoint brain regions significantly correlated with the AD, MMSE, CDR and age. All models were trained and internally validated on 417 samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI), and the classification model was externally validated on 382 samples from the Australian Imaging and Lifestyle flagship (AIBL). This approach provided robust support for using MMSE and CDR in assessing AD progression and visually illustrated the relationship between aging and AD. The analysis revealed correlations among the four identification tasks (AD, MMSE, CDR and age) and highlighted asymmetric brain lesions in both AD and aging. Notably, we found that AD can accelerate aging to some extent, and a significant correlation exists between the rate of aging and cognitive assessment scores. This offers new insights into the relationship between AD and aging.
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