AI-derived LA volume index, LA/RA and LA/LV volume ratios from coronary artery calcium scans predict long-term atrial fibrillation and stroke

Background The AI-CVD initiative aims to extract actionable insights from coronary artery calcium (CAC) scans beyond the traditional CAC score. While AI-derived cardiac chamber volumes predict atrial fibrillation (AF) and stroke, the long-term prognostic value of chamber ratios is less established. We evaluated the predictive value of AI-derived left atrial volume index (LAVI) and related chamber ratios (LA/RA, LA/LV) from routine CAC scans for incident AF and stroke, and their incremental value beyond established risk scores. Methods Pooled participant-level data from two prospective cohorts, the Multi-Ethnic Study of Atherosclerosis (MESA, n=5,670) and the Framingham Heart Study Offspring cohort (FHS, n=1,142), were analyzed. AI-enabled volumetry (AutoChamber, AI-CVD platform) quantified cardiac chamber metrics from non-contrast CAC scans. Cox proportional hazards models, net reclassification improvement (NRI), time-dependent area under the curve (AUC), calibration metrics, and LASSO regression were applied to evaluate predictive performance. Results Over a median 17-year follow-up, 1,302 participants developed AF, and 365 experienced stroke events. Individuals in the ≥95th percentile of chamber metrics had significantly increased risk. Adjusted hazard ratios for AF were 2.66 (95% CI 2.23–3.17) for LAVI, 2.04 (95% CI 1.71–2.45) for LA/LV ratio, and 1.87 (95% CI 1.55–2.26) for LA/RA ratio. For stroke, corresponding hazard ratios were 1.96 (95% CI 1.38–2.77), 1.64 (95% CI 1.15–2.33), and 1.83 (95% CI 1.29–2.59), respectively. AI-derived metrics improved reclassification beyond CHARGE-AF and Framingham Stroke Risk Profile (FSRP), with greatest improvements for AF from LAVI (NRI 0.48) and stroke from LA/RA ratio (NRI 0.39), driven mainly by non-event classification. While discrimination improvements (AUC) were modest, chamber measurements substantially improved FSRP calibration (slope: 0.448 to 0.834–0.902). Among all chamber metrics (including volumes and ratios), LASSO identified LAVI as the strongest predictor for AF, and LA/RA ratio as the strongest for stroke. Conclusion AI-enabled left atrial volumetric and ratio-based metrics derived opportunistically from CAC scans provide incremental predictive value for AF and stroke prediction.Graphical AbstractLASOO Analysis