Skip to content
F~Healthtech

Prognostication and clinical opportunities with AI for coronary artery calcium: a scoping review

The Combine·1mo ago·68 views
Authors: McDonald VJF, Parsa S, Mastrodicasa D, Rodriguez F, Langlotz C, Maron DJ, Sandhu AT, Dudum R, Jain SSField: BMJ digital health & AIYear: 2026DOI: 10.1136/bmjdh-2026-000053

McDonald VJF(1)(2), Parsa S(1)(2), Mastrodicasa D(3), Rodriguez F(2)(4), Langlotz C(5)(6), Maron DJ(2)(7), Sandhu AT(8)(9), Dudum R(9), Jain SS(2). OBJECTIVE: Coronary artery calcium (CAC) scoring is an established marker of atherosclerotic burden and cardiovascular risk, yet its clinical use remains limited by access, cost and workflow constraints. Artificial intelligence-enabled CAC (AI-CAC) tools allow automated assessment of coronary calcification from chest CT performed for diverse clinical indications, creating opportunities for scalable, opportunistic cardiovascular disease risk stratification.We conducted a scoping review of AI-CAC models focused on prognostication and real-world deployment, emphasising outcomes, clinical value and implementation considerations. METHODS AND ANALYSIS: Peer-reviewed original studies using an AI model incorporating CAC from chest CT for clinical prognostication, risk prediction or assessment of clinical interventions, reporting clinical outcomes, prognostic metrics or implementation insights. Studies focused exclusively on technical AI-CAC development or validation without clinical context were excluded.PubMed/MEDLINE, Embase and Cochrane Library, searched through November 2025, supplemented by expert recommendations from study coauthors.A single reviewer screened all records. Data were extracted using a standardised 25-variable template and synthesised narratively using an AI translational maturity framework. RESULTS: Across diverse patient populations and imaging contexts, AI-CAC demonstrated consistent associations with all-cause mortality, cardiovascular mortality, major adverse cardiovascular events and obstructive coronary artery disease. Radiomics-based approaches incorporating high-dimensional imaging features may improve prognostic performance beyond Agatston scoring alone, demonstrating further methodological potential for assessing cardiovascular risk. Emerging prospective and implementation-focused studies suggest t…

View external link ↗ (opens in a new tab)
Score: 0

Related papers

Sharing this paper's topic and concept tags, via OpenAlex. These aren't in Graze — they link straight out to the source.

  • Machine Learning and Coronary Artery Calcium Scoring

    Heon Lee, Simon S. Martin, Jeremy R. Burt, Pooyan Sahbaee · Current Cardiology Reports · 2020

  • Coronary artery calcium scoring in 2026: strengths, limitations, and optimized clinical use

    Pierre François Sabouret, Domenico Mario Giamundo, Julien Rosencher, Stefano Figliozzi · Frontiers in Radiology · 2026

  • Coronary artery calcium clinical utilization: An update

    Ibrahim Mortada, Esosa Odigie‐Okon, Afaq Motiwala, Joseph Allencherril · Current Problems in Cardiology · 2026

  • Opportunistic AI-Derived Coronary Calcium on Non-Cardiac Chest CT and Mortality: Protocol for a Systematic Review and Meta-Analysis of Prognostic Factor Studies

    Isaac Eli Martinez Safar · Open Science Framework · 2026

0 Comments

The summary above is machine-written and the abstract is the authors' own pitch. This is where people who read the paper say what it actually found, what the summary missed, and which part is worth your time.

Log in to join the discussion.