Key result
Non-gated CT chamber volumetry matches gated CT for predicting incident AF and HF.
Why the study?
AI-derived cardiac chamber volumetry in ECG-gated CT scans predicts AF and HF, and most chest CTs are non-gated. This study evaluated whether AI-derived chamber volumetry from non-gated CTs can reliably predict HF and AF to enable large-scale population screening.
Does AI-derived cardiac chamber volumetry from non-gated chest CT scans reliably predict incident heart failure and atrial fibrillation compared to ECG-gated chest CT scans in MESA participants?
Cohort (n=2,053)
Does AI-derived cardiac chamber volumetry from non-gated chest CT scans reliably predict incident heart failure and atrial fibrillation compared to ECG-gated chest CT scans in MESA participants?
AI-based cardiac chamber volumetry from routine non-gated chest CTs shows excellent agreement with ECG-gated CTs and comparable predictive performance for incident heart failure and atrial fibrillation, supporting its use for opportunistic screening.
Non-gated CT volumetry may enable opportunistic AF/HF risk assessment; extends gated CT evidence but leaves open prospective validation.
Background We previously demonstrated that AI-derived cardiac chamber volumetry in ECG-gated CT scans predicts atrial fibrillation (AF) and heart failure (HF). Since most chest CTs are non-gated, and the American Heart Association recently highlighted their value for opportunistic cardiovascular risk assessment using AI-based coronary artery calcium scoring, we extended this concept to evaluate whether AI-derived chamber volumetry from non-gated CTs can reliably predict HF and AF, enabling large-scale population screening. Methods We compared AI-derived chamber volumetry from non-gated and ECG-gated chest CTs in 2,053 Multi-Ethnic Study of Atherosclerosis (MESA) Exam 5 participants using mean and standard-deviation of absolute differences, intraclass correlation coefficients (ICC), and Cohen's κ. Variability between paired ECG-gated scans was determined by analyzing scans acquired 2 minutes apart in 5,749 MESA Exam 1 participants. Predictive performance for incident HF and AF was compared using cumulative incidence curves, age- and sex-adjusted C-indices, and non-inferiority testing (δ=0.05). Results Non-gated scans showed excellent agreement with ECG-gated scans for detecting chamber enlargement (98.8–99.2%, κ=0.76–0.84), comparable to paired ECG-gated scans (98.6–98.9%, κ=0.72–0.77). Cumulative incidence curves for HF and AF stratified by quartiles showed substantial overlap. Age- and sex-adjusted C-indices were comparable for left atrial volume (0.75 vs 0.74, p=0.001, non-inferiority p<0.001), ventricular volume (both 0.77, p=0.97, non-inferiority p<0.001), and ventricular ratio (both 0.74, p=0.57, non-inferiority p<0.001) in predicting AF and HF. Conclusion AI-based evaluation of non-gated chest CT may provide reliable cardiac chamber volumetry and cardiovascular outcome prediction, enabling opportunistic screening for HF and AF prevention.
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Mirjalili et al. (2026) conducted a cohort in Incident heart failure and atrial fibrillation (n=2,053). AI-derived cardiac chamber volumetry from non-gated chest CT vs. AI-derived cardiac chamber volumetry from ECG-gated chest CT was evaluated on Prediction of incident heart failure and atrial fibrillation (age- and sex-adjusted C-indices for left atrial volume, ventricular volume, and ventricular ratio) (C-index 0.75 vs 0.74 (LA volume); 0.77 vs 0.77 (ventricular volume); 0.74 vs 0.74 (ventricular ratio), p=<0.001 for non-inferiority). AI-derived chamber volumetry from non-gated chest CTs was non-inferior to ECG-gated CTs in predicting incident AF and HF (C-indices 0.74–0.77 vs 0.74–0.77; all non-inferiority p<0.001).
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