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

  • 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

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)791-802
Number of pages12
JournalEuropean Heart Journal Cardiovascular Imaging
Volume27
Issue number4
DOIs
StatePublished - Apr 2026

Keywords

  • artificial intelligence
  • cardiovascular disease
  • computed tomography
  • heart atria
  • heart ventricle

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