ArticleTranslational psychiatry2024
A multi-cohort study of the hippocampal radiomics model and its associated biological changes in Alzheimer's Disease.
Article in Translational psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Imaging biomarkers of glymphatic system dysfunction in Alzheimer's disease: a systematic review and meta-analysis with a focus on DTI-ALPS index.Frontiers in aging neuroscience · 2026Pooled it
- Hippocampal Radiomic Signatures in Multiple Sclerosis Subtypes: A Machine Learning-Based MRI Study.Journal of imaging informatics in medicine · 2026Article
- Review
- Contributions of the Alzheimer's Disease Neuroimaging Initiative to advancing AD research: a targeted review of recent publications.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Review
- Integration of glymphatic system function and hippocampal radiomics for diagnosis and conversion prediction of Alzheimer's disease.BMC medical imaging · 2026Article
- Predicting cognitive frailty in older adults: an explainable machine learning model integrating radiomics and clinical features.BMC medical informatics and decision making · 2026Article
- Review
- Association of choroid plexus volume with white matter microstructure, glymphatic function, and peripheral systemic inflammation in Alzheimer's disease.Translational psychiatry · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
There have been no previous reports of hippocampal radiomics features associated with biological functions in Alzheimer's Disease (AD). This study aims to develop and validate a hippocampal radiomics model from structural magnetic resonance imaging (MRI) data for identifying patients with AD, and to explore the mechanism underlying the developed radiomics model using peripheral blood gene expression. In this retrospective multi-study, a radiomics model was developed based on the radiomics discovery group (n = 420) and validated in other cohorts. The biological functions underlying the model were identified in the radiogenomic analysis group using paired MRI and peripheral blood transcriptome analyses (n = 266). Mediation analysis and external validation were applied to further validate the key module and hub genes. A 12 radiomics features-based prediction model was constructed and this model showed highly robust predictive power for identifying AD patients in the validation and other three cohorts. Using radiogenomics mapping, myeloid leukocyte and neutrophil activation were enriched, and six hub genes were identified from the key module, which showed the highest correlation with the radiomics model. The correlation between hub genes and cognitive ability was confirmed using the external validation set of the AddneuroMed dataset. Mediation analysis revealed that the hippocampal radiomics model mediated the association between blood gene expression and cognitive ability. The hippocampal radiomics model can accurately identify patients with AD, while the predictive radiomics model may be driven by neutrophil-related biological pathways.
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