AI-enabled left atrial volumetry in coronary artery calcium scans (AI-CAC) predicts atrial fibrillation as early as one year, improves CHARGE-AF, and outperforms NT-proBNP:

The multi-ethnic study of atherosclerosis

Naghavi M, Yankelevitz D, Reeves AP, Budoff MJ, Li D, Atlas K, Zhang C, Atlas TL, Lirette S, Wasserthal J, Roy SK, Henschke C, Wong ND, Defilippi C, Heckbert SR, Greenland P. AI-enabled left atrial volumetry in coronary artery calcium scans (AI-CACTM) predicts atrial fibrillation as early as one year, improves CHARGE-AF, and outperforms NT-proBNP: The multi-ethnic study of atherosclerosis. J Cardiovasc Comput Tomogr. 2024 Jul-Aug;18(4):383-391. doi: 10.1016/j.jcct.2024.04.005. Epub 2024 Apr 23. PMID: 38653606; PMCID: PMC11216863.

Abstract

Background

Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported.

Methods

We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CACTM) to 5535 asymptomatic individuals (52.2% women, ages 45–84) that were previously obtained for CAC scoring in the baseline examination (2000–2002) of the Multi-Ethnic Study of Atherosclerosis (MESA). AI-CAC took on average 21 ​s per CAC scan. We used the 5-year outcomes data for incident atrial fibrillation (AF) and assessed discrimination using the time-dependent area under the curve (AUC) of AI-CAC LA volume with known predictors of AF, the CHARGE-AF Risk Score and NT-proBNP. The mean follow-up time to an AF event was 2.9 ​± ​1.4 years.

Results

At 1,2,3,4, and 5 years follow-up 36, 77, 123, 182, and 236 cases of AF were identified, respectively. The AUC for AI-CAC LA volume was significantly higher than CHARGE-AF for Years 1, 2, and 3 (0.83 vs. 0.74, 0.84 vs. 0.80, and 0.81 vs. 0.78, respectively, all p ​< ​0.05), but similar for Years 4 and 5, and significantly higher than NT-proBNP at Years 1–5 (all p ​< ​0.01), but not for combined CHARGE-AF and NT-proBNP at any year. AI-CAC LA significantly improved the continuous Net Reclassification Index for prediction of AF over years 1–5 when added to CHARGE-AF Risk Score (0.60, 0.28, 0.32, 0.19, 0.24), and NT-proBNP (0.68, 0.44, 0.42, 0.30, 0.37) (all p ​< ​0.01).

Conclusion

AI-CAC LA volume enabled prediction of AF as early as one year and significantly improved on risk classification of CHARGE-AF Risk Score and NT-proBNP.

Keywords

Coronary artery calcium, Atrial fibrillation, Left atrial volume, Artificial intelligence, CHARGE-AF, NT-proBNP

Fig. 1. Two case examples of AI-CAC detection of enlarged LA along with all cardiac chambers segmentations in a coronary artery calcium CT scan. Both cases fall in the top quartile of LA volume who were flagged by the AutoChamber component of AI-CAC for further investigation. Case 1 developed atrial fibrillation (AFib), while Case 2 developed AFib and stroke.