AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CACTM) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis

J Cardiovasc Comput Tomogr. 2024 Jul-Aug;18(4):392-400. doi: 10.1016/j.jcct.2024.04.006. Epub 2024 Apr 24.

Abstract

Introduction: Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF).

Methods: We applied AI-CAC to 5750 CAC scans of asymptomatic individuals (52% female, White 40%, Black 26%, Hispanic 22% Chinese 12%) free of known cardiovascular disease at the MESA baseline examination (2000-2002). We used the 15-year outcomes data and compared the time-dependent area under the curve (AUC) of AI-CAC volumetry versus NT-proBNP, Agatston score, and 9 known clinical risk factors (age, gender, diabetes, current smoking, hypertension medication, systolic and diastolic blood pressure, LDL, HDL for predicting incident HF over 15 years.

Results: Over 15 years of follow-up, 256 HF events accrued. The time-dependent AUC [95% CI] at 15 years for predicting HF with AI-CAC all chambers volumetry (0.86 [0.82,0.91]) was significantly higher than NT-proBNP (0.74 [0.69, 0.77]) and Agatston score (0.71 [0.68, 0.78]) (p ​< ​0.0001), and comparable to clinical risk factors (0.85, p ​= ​0.4141). Category-free Net Reclassification Index (NRI) [95% CI] adding AI-CAC LV significantly improved on clinical risk factors (0.32 [0.16,0.41]), NT-proBNP (0.46 [0.33,0.58]), and Agatston score (0.71 [0.57,0.81]) for HF prediction at 15 years (p ​< ​0.0001).

Conclusion: AI-CAC volumetry significantly outperformed NT-proBNP and the Agatston CAC score, and significantly improved the AUC and category-free NRI of clinical risk factors for incident HF prediction.

Keywords: Artificial intelligence; Coronary artery calcium; Heart failure; Left ventricular volume; NT-proBNP.

Publication types

  • Multicenter Study
  • Comparative Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Artificial Intelligence*
  • Asymptomatic Diseases
  • Biomarkers* / blood
  • Computed Tomography Angiography*
  • Coronary Angiography*
  • Coronary Artery Disease* / diagnostic imaging
  • Coronary Artery Disease* / ethnology
  • Female
  • Heart Failure* / diagnostic imaging
  • Heart Failure* / ethnology
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Multidetector Computed Tomography
  • Natriuretic Peptide, Brain* / blood
  • Peptide Fragments* / blood
  • Predictive Value of Tests*
  • Prognosis
  • Radiographic Image Interpretation, Computer-Assisted
  • Reproducibility of Results
  • Risk Assessment
  • Risk Factors
  • Time Factors
  • United States
  • Vascular Calcification* / diagnostic imaging
  • Vascular Calcification* / ethnology

Substances

  • Peptide Fragments
  • Natriuretic Peptide, Brain
  • pro-brain natriuretic peptide (1-76)
  • Biomarkers