TY - JOUR
T1 - AI-derived left-to-right cardiac chamber volume ratios in coronary artery calcium scans strongly predict heart failure
AU - Naghavi, Morteza
AU - Mirjalili, Seyed Reza
AU - Atlas, Kyle
AU - Reeves, Anthony P.
AU - Zhang, Chenyu
AU - Wasserthal, Jakob
AU - Azimi, Amir
AU - Hashemi, Ali
AU - Mozafarybazargany, Mohammadhossein
AU - Atlas, Thomas
AU - Henschke, Claudia I.
AU - Yankelevitz, David F.
AU - Zulueta, Javier J.
AU - Mechanick, Jeffrey I.
AU - Branch, Andrea D.
AU - Yip, Rowena
AU - Roy, Sion K.
AU - Nasir, Khurram
AU - Fayad, Zahi
AU - McConnell, Michael V.
AU - Kakadiaris, Ioannis A.
AU - Rana, Jamal S.
AU - Vliegenthart, Rozemarijn
AU - Maron, David J.
AU - Narula, Jagat
AU - Williams, Kim
AU - Shah, Prediman K.
AU - Budoff, Matthew J.
AU - Levy, Daniel
AU - Mehran, Roxana
AU - Kloner, Robert A.
AU - Wong, Nathan D.
N1 - Publisher Copyright:
© The Author(s) 2026. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact [email protected] for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact [email protected].
PY - 2026/4
Y1 - 2026/4
N2 - Aims: The AI-CVD initiative seeks to extract actionable insights from coronary artery calcium (CAC) scans beyond the traditional CAC score. We previously demonstrated that AI-derived cardiac chamber volumes from CAC scans predict incident heart failure (HF). We aimed to evaluate whether left-to-right cardiac chamber volume ratios outperform chamber volumes in predicting HF. Methods and results: We used AI-CVD cardiac chambers volumetry data from CAC scans of 5732 asymptomatic Multi-Ethnic Study of Atherosclerosis (MESA) participants (age 62.2 ± 10.3 years; 47.7% male). Left-to-right ventricular (LV/RV), atrial (LA/RA), and left atrial-to-right ventricular (LA/RV) volume ratios were evaluated using multivariable Cox models and feature selection techniques. External validation was performed in the Framingham Heart Study Offspring (FHS-O) cohort (N = 1,052, age:58.3 ± 8.3, 42.9% male). During a median follow-up of 17.7 years in MESA, 369 participants (6.3%) developed HF. Elevated ratios (≥75th & ≥95th percentile) of LV/RV, LA/RA, and LA/RV were strongly associated with incident HF: hazard ratio (HR) for ≥95th percentile were 4.04 (95% CI: 2.89–5.65), 2.90 (95% CI: 2.07–4.06), and 2.61 (95% CI: 1.87–3.46), respectively. Among participants with normal LV sizes (interquartile-range), LV/RV ≥95th significantly predicted HF (HR: 2.34; 95% CI: 1.29–4.25). In FHS-O (median follow-up 14.4 years), 56 HF events (5.3%) occurred. LV/RV ≥75th percentile was significantly associated with HF (HR: 2.23; 95% CI: 1.16–4.30), whereas LA/RA was not (HR: 1.22; 95% CI: 0.65–2.29). Feature selection techniques identified LV/RV as the strongest predictor. Conclusion: In these two prospective cohorts, AI-derived LV/RV ratio from CAC scans strongly predicted HF. New clinical trials guided by these imaging biomarkers are warranted to establish their clinical utility.
AB - Aims: The AI-CVD initiative seeks to extract actionable insights from coronary artery calcium (CAC) scans beyond the traditional CAC score. We previously demonstrated that AI-derived cardiac chamber volumes from CAC scans predict incident heart failure (HF). We aimed to evaluate whether left-to-right cardiac chamber volume ratios outperform chamber volumes in predicting HF. Methods and results: We used AI-CVD cardiac chambers volumetry data from CAC scans of 5732 asymptomatic Multi-Ethnic Study of Atherosclerosis (MESA) participants (age 62.2 ± 10.3 years; 47.7% male). Left-to-right ventricular (LV/RV), atrial (LA/RA), and left atrial-to-right ventricular (LA/RV) volume ratios were evaluated using multivariable Cox models and feature selection techniques. External validation was performed in the Framingham Heart Study Offspring (FHS-O) cohort (N = 1,052, age:58.3 ± 8.3, 42.9% male). During a median follow-up of 17.7 years in MESA, 369 participants (6.3%) developed HF. Elevated ratios (≥75th & ≥95th percentile) of LV/RV, LA/RA, and LA/RV were strongly associated with incident HF: hazard ratio (HR) for ≥95th percentile were 4.04 (95% CI: 2.89–5.65), 2.90 (95% CI: 2.07–4.06), and 2.61 (95% CI: 1.87–3.46), respectively. Among participants with normal LV sizes (interquartile-range), LV/RV ≥95th significantly predicted HF (HR: 2.34; 95% CI: 1.29–4.25). In FHS-O (median follow-up 14.4 years), 56 HF events (5.3%) occurred. LV/RV ≥75th percentile was significantly associated with HF (HR: 2.23; 95% CI: 1.16–4.30), whereas LA/RA was not (HR: 1.22; 95% CI: 0.65–2.29). Feature selection techniques identified LV/RV as the strongest predictor. Conclusion: In these two prospective cohorts, AI-derived LV/RV ratio from CAC scans strongly predicted HF. New clinical trials guided by these imaging biomarkers are warranted to establish their clinical utility.
KW - artificial intelligence
KW - cardiovascular disease
KW - computed tomography
KW - heart atria
KW - heart ventricle
UR - https://www.scopus.com/pages/publications/105034457338
U2 - 10.1093/ehjci/jeag027
DO - 10.1093/ehjci/jeag027
M3 - Article
C2 - 41591983
AN - SCOPUS:105034457338
SN - 2047-2404
VL - 27
SP - 791
EP - 802
JO - European Heart Journal Cardiovascular Imaging
JF - European Heart Journal Cardiovascular Imaging
IS - 4
ER -