ArticleNature communications2025
Biological age model using explainable automated CT-based cardiometabolic biomarkers for phenotypic prediction of longevity.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Lifetime non-relational traumatic experiences are associated with biological ageing.GeroScience · 2026Article
- Longitudinal evaluation of intra-patient changes in computed tomography-based body composition measures.Abdominal radiology (New York) · 2026Article
- Prediction of Overall Survival in Patients With Oesophageal Cancer Using AI-Based 3D CT Body Composition Analysis.Journal of cachexia, sarcopenia and muscle · 2026Article
- Deep Learning-Derived Retinal Age Detects Cognitive Impairment.Ophthalmology science · 2026Article
- Hierarchical organ aging signatures from routine abdominal CT add incremental disease risk stratification beyond blood biomarkers.medRxiv : the preprint server for health sciences · 2026Article
- Anatomical dynamics define cancer cachexia subtypes and identify systemic inflammation as a marker of lethal wasting.medRxiv : the preprint server for health sciences · 2026Article
- Automated CT-Based Muscle Density Predicts Mortality Regardless of Muscle Area.Journal of cachexia, sarcopenia and muscle · 2026Article
- Ratio of visceral-to-subcutaneous fat area improves long-term mortality prediction over either measure alone: automated CT-based AI measures with longitudinal follow-up in a large adult cohort.Abdominal radiology (New York) · 2026Article
- Tumor-Derived Polyamines Initiate Fat Wasting in Cancer Cachexia.bioRxiv : the preprint server for biology · 2025Article
- Segmentation of visceral and subcutaneous adipose tissue in abdominal CT-datasets with and without contrast medium: Influence of iterative reconstruction on 2D- and 3D-segmentation.European journal of radiology open · 2025Article
- Accelerated Biological Aging and Genetic Pleiotropy in Age-Related Eye Diseases: A Population-Based Cohort and Integrative Genetic Analysis.Investigative ophthalmology & visual science · 2025Article
- Methodology for a fully automated pipeline of AI-based body composition tools for abdominal CT.Abdominal radiology (New York) · 2025Article
- Association of advanced lung cancer inflammation index with all-cause and cardiovascular mortality in metabolic dysfunction associated steatotic liver disease.Scientific reports · 2025Article
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9 authors.
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Abstract
We derive and test a CT-based biological age model for predicting longevity, using an automated pipeline of explainable AI algorithms that quantifies skeletal muscle, abdominal fat, aortic calcification, bone density, and solid abdominal organs. We apply these AI tools to abdominal CT scans from 123,281 adults (mean age, 53.6 years; 47% women; median follow-up, 5.3 years). The final weighted CT biomarker selection was based on the index of prediction accuracy. The CT model significantly outperforms standard demographic data for predicting longevity (IPA = 29.2 vs. 21.7; 10-year AUC = 0.880 vs. 0.779; p < 0.001). Age- and sex-corrected survival hazard ratio for the highest-vs-lowest risk quartile was 8.73 (95% CI,8.14-9.36) for the CT biological age model, and increased to 24.79 after excluding cancer diagnoses within 5 years of CT. Muscle density, aortic plaque burden, visceral fat density, and bone density contributed the most. Here we show a personalized phenotypic CT biological age model that can be opportunistically-derived, regardless of clinical indication, to better inform risk assessment.
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