ArticleNPJ digital medicine2024
Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Opportunistic Assessment of Coronary Artery Calcium Volume and Density From Non-Electrocardiogram-Gated Chest CT Using Artificial Intelligence: Prognostic Implications in a Screening Cohort.Korean journal of radiology · 2026Article
- Article
- AI-CVD-HF: A heart failure risk prediction model based on coronary artery calcium scans compared with PREVENT-HF.American journal of preventive cardiology · 2026Article
- Advanced Multimodality Cardiovascular Imaging in Patients at Very High Cardiovascular Risk Without a Previous Cardiovascular Event: Current Knowledge and Future Perspectives.Journal of cardiovascular development and disease · 2026Review
- Aortic and Cardiac Structure From Routine CT Predict Cardiovascular Risk Beyond PREVENT and Coronary Calcium.JACC. Cardiovascular imaging · 2026Article
- From Exposure to Atherosclerosis: Mechanistic Insights into Phthalate-Driven Ischemic Heart Disease and Prevention Strategies.Life (Basel, Switzerland) · 2026Review
- Artificial Intelligence-derived Measurements of Myosteatosis from Coronary Artery Calcium CT Scans to Predict COPD: The Multi-Ethnic Study of Atherosclerosis.Radiology. Cardiothoracic imaging · 2026Article
- Prognostication and clinical opportunities with AI for coronary artery calcium: a scoping review.BMJ digital health & AI · 2026Article
- Lung cancer screening with AI can discover cures for many early diseases. A public utility can make sure it happens.Frontiers in oncology · 2026Article
- Evolving strategies in cardiovascular disease prevention: 2025 American society for preventive cardiology highlights.American journal of preventive cardiology · 2025Review
- Review
- Integrating perfusion with AI-derived coronary calcium on CT attenuation scans to improve selection of low-risk studies for stress-only SPECT myocardial perfusion imaging.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2025Article
- Coronary Artery Calcium Scoring on Dedicated Cardiac CT and Noncardiac CT Scans.Radiology. Cardiothoracic imaging · 2025Review
- Artificial intelligence in carotid computed tomography angiography plaque detection: Decade of progress and future perspectives.World journal of radiology · 2025Review
- Inadequacy of coronary calcium scoring in evaluating coronary artery disease: A call to shifting to high-resolution CT coronary imaging.International journal of cardiology. Cardiovascular risk and prevention · 2025Article
- Artificial intelligence in coronary artery calcification scoring: Current progress and future directions.Global cardiology science & practice · 2025Review
- Application of non-invasive imaging in myocardial infarction: a bibliometric analysis from January 2003 to December 2022.Quantitative imaging in medicine and surgery · 2025Article
- Artificial Intelligence in Ischemic Heart Disease Prevention.Current cardiology reports · 2025Review
- Fully Automated Assessment of Cardiac Chamber Volumes and Myocardial Mass on Non-Contrast Chest CT with a Deep Learning Model: Validation Against Cardiac MR.Diagnostics (Basel, Switzerland) · 2024Article
- Artificial Intelligence-Driven Advances in Coronary Calcium Scoring: Expanding Preventive Cardiology.Cureus · 2024Review
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Authors and funding
21 authors.
Funding
Abstract
Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) in the multi-ethnic study of atherosclerosis during 15 years of follow-up, 1773 CVD events accrued. The AUC at 1-, 5-, 10-, and 15-year follow-up for AI-CAC vs. Agatston score was (0.784 vs. 0.701), (0.771 vs. 0.709), (0.789 vs. 0.712) and (0.816 vs. 0.729) (p < 0.0001 for all), respectively. AI-CAC plaque characteristics, including number, location, density, plus number of vessels, significantly improved CHD prediction in the CAC 1-100 cohort vs. Agatston Score. AI-CAC significantly improved the Agatston score for predicting all CVD events.
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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.