Key result
AI-based opportunistic CAC scoring on non-gated chest CT accurately matches dedicated ECG-gated scans.
Why the study?
Although artificial intelligence can quantify coronary artery calcium on routine non-gated chest CT, its performance at treatment-relevant thresholds and its effects on preventive care are uncertain.
Does AI-based opportunistic coronary artery calcium assessment on routine non-gated chest CT accurately quantify CAC at treatment-relevant thresholds, predict major adverse cardiovascular events, and improve preventive statin prescribing?
Meta-Analysis
Reference standard blinded to AI result in ideal trial benchmark
Does AI-based opportunistic coronary artery calcium assessment on routine non-gated chest CT accurately quantify CAC at treatment-relevant thresholds, predict major adverse cardiovascular events, and improve preventive statin prescribing?
AI-based opportunistic CAC assessment on routine non-gated chest CT demonstrates high specificity for substantial CAC, predicts cardiovascular events, and increases statin prescribing when coupled with notification, though low AI-derived categories frequently underestimate disease burden.
Answers are grounded in this paper and cite their sources.
Supports AI CAC alerts on routine non-gated CT to raise statin initiation; confirms high specificity, MACE prediction, and diagnostic thresholds in meta-analysis.
Coronary artery calcium (CAC) on routine non-gated chest CT can be quantified by artificial intelligence (AI), but performance at treatment-relevant thresholds and effects on preventive care are uncertain. We systematically reviewed 110 reports of AI-based CAC assessment on non-gated chest CT; 59 contributed to meta-analyses. Against paired ECG-gated CT, pooled sensitivity and specificity were 87.1% and 92.3% for CAC > 0 and 83.1% and 96.3% for CAC ≥ 100, with specificity above 97% at ≥ 300 and ≥ 400. Category disagreement was mainly underestimation: 30.7% of gated CAC 1–99 was classified as 0 and 40.3% of CAC 100–299 below 100. Adjusted hazard ratios for major adverse cardiovascular events rose from 1.60 (CAC 1–100) to 3.39 (> 400) versus CAC 0. In two randomised trials, AI-enabled notification increased six-month statin prescribing (51.2% vs 6.9% and 44.0% vs 9.8%). Substantial AI-detected CAC should prompt review of preventive treatment, whereas low AI-derived categories can underestimate disease burden.
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Chen et al. (2026) conducted a meta-analysis in Coronary artery calcium (CAC). AI-based opportunistic coronary artery calcium (AI-CAC) assessment on non-gated chest CT vs. Paired dedicated ECG-gated calcium-scoring CT, same-scan manual reference, or expert visual reference was evaluated on Diagnostic accuracy for Agatston CAC categories (>0, ≥100, ≥300, ≥400), prognostic association with MACE, and 6-month statin prescribing. AI-based opportunistic coronary artery calcium assessment on non-gated chest CT was evaluated across 78 paired ECG-gated, 73 same-scan manual, and 4 expert visual diagnostic estimates.
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