AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis

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];