Cardiovascular Research

AI-derived left-to-right cardiac chamber volume ratios in coronary artery calcium scans strongly predict heart failure.

Authors: Morteza Naghavi|||Seyed Reza Mirjalili|||Kyle Atlas|||Anthony P Reeves|||Chenyu Zhang|||Jakob Wasserthal|||Amir Azimi|||Ali Hashemi|||Mohammadhossein Mozafarybazargany|||Thomas Atlas|||Claudia I Henschke|||David F Yankelevitz|||Javier J Zulueta|||Jeffrey I Mechanick|||Andrea D Branch|||Rowena Yip|||Sion K Roy|||Khurram Nasir|||Zahi Fayad|||Michael V McConnell|||Ioannis A Kakadiaris|||Jamal S Rana|||Rozemarijn Vliegenthart|||David J Maron|||Jagat Narula|||Kim Williams|||Prediman K Shah|||Matthew J Budoff|||Daniel Levy|||Roxana Mehran|||Robert A Kloner|||Nathan D Wong

Affiliations: + Expand

Abstract

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.

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Reference List

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