AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.
A, A., K, A., AP, R., C, Z., J, W., SR, M., T, A., CI, H., DF, Y., & JJ, Z. (2026). AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.. Radiology. Cardiothoracic imaging. https://doi.org/10.1148/ryct.250214
A A, K A, AP R, C Z, J W, SR M, et al. AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.. Radiology. Cardiothoracic imaging. 2026; doi: 10.1148/ryct.250214
A A, K A, AP R, et al. AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.[J]. Radiology. Cardiothoracic imaging. 2026. DOI: 10.1148/ryct.250214.
@article{a2026,
author = {Azimi A and Atlas K and Reeves AP and Zhang C and Wasserthal J and Mirjalili SR and Atlas T and Henschke CI and Yankelevitz DF and Zulueta JJ},
title = {AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.},
journal = {Radiology. Cardiothoracic imaging},
year = {2026},
doi = {10.1148/ryct.250214},
note = {PMID: 42390348},
}
TY - JOUR AU - Azimi A AU - Atlas K AU - Reeves AP AU - Zhang C AU - Wasserthal J AU - Mirjalili SR AU - Atlas T AU - Henschke CI AU - Yankelevitz DF AU - Zulueta JJ TI - AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis. T2 - Radiology. Cardiothoracic imaging PY - 2026 DO - 10.1148/ryct.250214 AN - PMID:42390348 ER -
Purpose To evaluate whether the artificial intelligence (AI)-quantified mean thoracic skeletal muscle (TSM) attenuation from coronary artery calcium (CAC) scans predicts incident cardiovascular disease (CVD), with a focus on atrial fibrillation (AF) and heart failure (HF). Materials and Methods Data from the Multi-Ethnic Study of Atherosclerosis, including participants without baseline CVD who underwent CAC scanning, were retrospectively analyzed. Myosteatosis was defined by sex-specific, AI-quantified mean TSM attenuation cutoffs. The Cox proportional hazards model was used to compare total CVD, AF, and HF risks between the bottom and top quartiles of TSM attenuation after adjusting for CVD risk factors, inflammatory markers, insulin resistance, Agatston score, TSM volume, and social determinants of health. Results Among 5739 participants (mean age, 62.1 years ± 10.3 [SD]; 3002 [52.3%] female), 1826 CVD events occurred over 19 years, including 1139 AF and 359 HF events. Myosteatosis was independently associated with increased risks of total CVD (hazard ratio [HR], 1.48 [95% CI: 1.25, 1.75]; P = .001), AF (HR, 1.68 [95% CI: 1.37, 2.07]; P < .001), and HF (HR, 1.61 [95% CI: 1.18, 2.19]; P < .002). Participants with both myosteatosis and high Agatston scores had markedly higher cumulative incidences compared with those with high Agatston scores alone (total CVD: 84.6% vs 68.6%; AF: 52.9% vs 42.4%; HF: 22.6% vs 16.1%). Adding myosteatosis to the Agatston score significantly improved prediction (time-dependent area under the receiver operating characteristic curve, total CVD: 0.74 vs 0.80, P < .001; AF: 0.68 vs 0.76, P < .001; HF: 0.73 vs 0.78, P = .007). Conclusion AI-quantified mean TSM attenuation on CAC scans independently predicted AF and HF and enhanced the Agatston score's predictive value. Keywords: Myosteatosis, Coronary Artery Calcium Scan, Atrial Fibrillation, Heart Failure, Artificial Intelligence, Applications-CT, Cardiac, Thorax, Muscular, Heart ClinicalTrials.gov NCT00005487 Supplemental material is available for this article. © RSNA, 2026.