Abstract 4369683: AI-driven Measurement of Myosteatosis in Coronary Artery Calcium Scans Predicts Atrial Fibrillation and Heart Failure. An AI-CVD Study within the Multi-Ethnic Study of Atherosclerosis (MESA)
Abstract
Introduction: New innovations in AI allow opportunistic detection of non-coronary features on coronary artery calcium (CAC) scans, enabling screening for a range of conditions, and improved cardiovascular disease (CVD) prediction. Myosteatosis, excessive fat infiltration into skeletal muscle, is increasingly recognized as a marker of systemic metabolic dysfunction and can be quantified in CT using the mean attenuation of skeletal muscle. We evaluated AI-measured myosteatosis in thoracic skeletal muscle for predicting future atrial fibrillation (AF), heart failure (HF), and total CVD. Methods: We used baseline CAC scans and 15-year follow-up data from 5,489 asymptomatic participants (47.8% male) in the Multi-Ethnic Study of Atherosclerosis (MESA). Myosteatosis was operationally defined as the lowest quartile of thoracic skeletal muscle mean attenuation (males<33 Hounsfield Units (HU) and females<27 HU). Hazard ratios [HR] for bottom vs top quartile of mean muscle CT density were evaluated using proportional hazards regression models adjusted for CVD risk factors, inflammatory markers, and social determinants of health. Results: Myosteatosis was associated with worse outcomes in both sexes: HRs in males were 4.59 (95% CI, 3.52–5.99) for AF, 8.46 (4.61–15.52) for HF, and 3.56 (2.89–4.37) for total CVD, with corresponding HRs in females of 4.68 (3.48–6.29), 8.01 (3.62–17.72), and 4.37 (3.42–5.57), respectively. After full adjustment, associations remained significant for HF (1.93 [1.31–2.82]), AF (1.78 [1.26–2.50]), and total CVD (1.44 [1.09–1.91]) in males, and for AF (1.69 [1.17–2.45]) and total CVD (1.75 [1.29–2.39]) in females. Individuals in the top quartile of CAC (>89.5 HU) who also had myosteatosis had greater 15-year incidence of AF (45.4%) and HF (21.8%) than those in either group alone (CAC, AF: 29%, HF: 9.5%; myosteatosis, AF: 20.9%, HF: 5.3%). Conclusion: Thoracic skeletal myosteatosis in CAC scans is an independent predictor of AF, HF, and total CVD over 15 years. Improving clinical outcomes through the detection of myosteatosis, and other opportunistic findings in CAC scans as part of the AI-CVD initiative, merits further investigation.
Article Details
Authors (30)
Morteza Naghavi
HeartLung Technologies, Houston, Texas, United States
Amir Azimi
Kyle Atlas
HeartLung Technologies, Houston, Texas, United States
Chenyu Zhang
Anthony Reeves
Cornell University, Ithaca , New York, United States
Thomas Atlas
Tustin Teleradiology, Tustin, California, United States
David Yankelevitz
Mount Sinai Hospital, New York, New York, United States
Seyed Reza Mirjalili
HeartLung Technologies, Houston, Texas, United States
Claudia Henschke
Mount Sinai Hospital, New York, New York, United States
Nathan Wong
Rozemarijn Vliegenthart
Michael McConnell
Stanford University, Palo Alto, California, United States
David Maron
Stanford University, Stanford, California, United States
Andrea Branch
Mount Sinai Hospital, New York, New York, United States
Robert Kloner
Huntington Medical Research Inst., Pasadena, California, United States
Jeffrey mechanick
icahn school of med at mount siani, New York, New York, United States
Ning Ma
Rowena Yip
Icahn School of Med at Mt Sinai, New York, New York, United States
Wenjun Fan
State Key Laboratory of Catalysis, Dalian Institute of Chemical Physics
Sion Roy
UCLA Harbor, Malibu, California, United States
Khurram Nasir
Sabee Molloi
University of California, Irvine, Irvine, California, United States
Zahi Fayad
MOUNT SINAI MEDICAL CENTER, New York, New York, United States
Ioannis Kakadiaris
UNIVERSITY OF HOUSTON, Houston, Texas, United States
George Abela
MICHIGAN STATE UNIV, East Lansing, Michigan, United States
Jagat Narula
Kim Williams
Prediman Shah
Cedars-Sinai Medical Center, Los Angeles, California, United States
Emelia Benjamin
Boston University School Medicine, Brookline, Massachusetts, United States
Daniel Levy
Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.