TY - JOUR
T1 - AI-enabled opportunistic measurement of liver steatosis in coronary artery calcium scans predicts cardiovascular events and all-cause mortality
T2 - An AI-CVD study within the Multi-Ethnic Study of Atherosclerosis (MESA)
AU - Naghavi, Morteza
AU - Atlas, Kyle
AU - Reeves, Anthony
AU - Zhang, Chenyu
AU - Wasserthal, Jakob
AU - Atlas, Thomas
AU - Henschke, Claudia I.
AU - Yankelevitz, David F.
AU - Zulueta, Javier J.
AU - Budoff, Matthew J.
AU - Branch, Andrea D.
AU - Ma, Ning
AU - Yip, Rowena
AU - Fan, Wenjun
AU - Roy, Sion K.
AU - Nasir, Khurram
AU - Molloi, Sabee
AU - Fayad, Zahi
AU - Mcconnell, Michael V.
AU - Kakadiaris, Ioannis
AU - Maron, David J.
AU - Narula, Jagat
AU - Williams, Kim
AU - Shah, Prediman K.
AU - Abela, George
AU - Vliegenthart, Rozemarijn
AU - Levy, Daniel
AU - Wong, Nathan D.
N1 - Publisher Copyright:
© Author(s) (or their employer(s)) 2025.
PY - 2025/4/12
Y1 - 2025/4/12
N2 - Introduction: About one-third of adults in the USA have some grade of hepatic steatosis. Coronary artery calcium (CAC) scans contain more information than currently reported. We previously reported new artificial intelligence (AI) algorithms applied to CAC scans for opportunistic measurement of bone mineral density, cardiac chamber volumes, left ventricular mass, and other imaging biomarkers collectively referred to as AI-cardiovascular disease (CVD). In this study, we investigate a new AI-CVD algorithm for opportunistic measurement of liver steatosis. Methods: We applied AI-CVD to CAC scans from 5702 asymptomatic individuals (52% female, age 62±10 years) in the Multi-Ethnic Study of Atherosclerosis. Liver attenuation index (LAI) was measured using the percentage of voxels below 40 Hounsfield units. We used Cox proportional hazards regression to examine the association of LAI with incident CVD and mortality over 15 years, adjusted for CVD risk factors and the Agatston CAC score. Results: A total of 751 CVD and 1343 deaths accrued over 15 years. Mean±SD LAI in females and males was 38±15% and 43±13%, respectively. Participants in the highest versus lowest quartile of LAI had greater incidence of CVD over 15 years: 19% (95% CI 17% to 22%) vs 12% (10% to 14%), respectively, p<0.0001. Individuals in the highest quartile of LAI (Q4) had a higher risk of CVD (HR 1.43, 95% CI 1.08 to 1.89), stroke (HR 1.77, 95% CI 1.09 to 2.88), and all-cause mortality (HR 1.36, 95% CI 1.10 to 1.67) compared with those in the lowest quartile (Q1), independent of CVD risk factors. Conclusion: AI-enabled liver steatosis measurement in CAC scans provides opportunistic and actionable information for early detection of individuals at elevated risk of CVD events and mortality, without additional radiation.
AB - Introduction: About one-third of adults in the USA have some grade of hepatic steatosis. Coronary artery calcium (CAC) scans contain more information than currently reported. We previously reported new artificial intelligence (AI) algorithms applied to CAC scans for opportunistic measurement of bone mineral density, cardiac chamber volumes, left ventricular mass, and other imaging biomarkers collectively referred to as AI-cardiovascular disease (CVD). In this study, we investigate a new AI-CVD algorithm for opportunistic measurement of liver steatosis. Methods: We applied AI-CVD to CAC scans from 5702 asymptomatic individuals (52% female, age 62±10 years) in the Multi-Ethnic Study of Atherosclerosis. Liver attenuation index (LAI) was measured using the percentage of voxels below 40 Hounsfield units. We used Cox proportional hazards regression to examine the association of LAI with incident CVD and mortality over 15 years, adjusted for CVD risk factors and the Agatston CAC score. Results: A total of 751 CVD and 1343 deaths accrued over 15 years. Mean±SD LAI in females and males was 38±15% and 43±13%, respectively. Participants in the highest versus lowest quartile of LAI had greater incidence of CVD over 15 years: 19% (95% CI 17% to 22%) vs 12% (10% to 14%), respectively, p<0.0001. Individuals in the highest quartile of LAI (Q4) had a higher risk of CVD (HR 1.43, 95% CI 1.08 to 1.89), stroke (HR 1.77, 95% CI 1.09 to 2.88), and all-cause mortality (HR 1.36, 95% CI 1.10 to 1.67) compared with those in the lowest quartile (Q1), independent of CVD risk factors. Conclusion: AI-enabled liver steatosis measurement in CAC scans provides opportunistic and actionable information for early detection of individuals at elevated risk of CVD events and mortality, without additional radiation.
KW - coronary artery calcium
KW - CVD
KW - fatty liver
KW - non-alcoholic fatty liver disease
UR - https://www.scopus.com/pages/publications/105002780555
U2 - 10.1136/bmjdrc-2024-004760
DO - 10.1136/bmjdrc-2024-004760
M3 - Article
C2 - 40221147
AN - SCOPUS:105002780555
SN - 2052-4897
VL - 13
JO - BMJ Open Diabetes Research and Care
JF - BMJ Open Diabetes Research and Care
IS - 2
M1 - e004760
ER -