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Comparative Study
. 2024 Jul-Aug;18(4):383-391.
doi: 10.1016/j.jcct.2024.04.005. Epub 2024 Apr 23.

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

Morteza Naghavi  1 , David Yankelevitz  2 , Anthony P Reeves  3 , Matthew J Budoff  4 , Dong Li  4 , Kyle Atlas  5 , Chenyu Zhang  5 , Thomas L Atlas  6 , Seth Lirette  5 , Jakob Wasserthal  7 , Sion K Roy  4 , Claudia Henschke  2 , Nathan D Wong  8 , Christopher Defilippi  9 , Susan R Heckbert  10 , Philip Greenland  11
Affiliations
Comparative Study

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

Morteza Naghavi et al. J Cardiovasc Comput Tomogr. 2024 Jul-Aug.

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: Artificial intelligence; Atrial fibrillation; CHARGE-AF; Coronary artery calcium; Left atrial volume; NT-proBNP.

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Conflict of interest statement

Conflict of Interest Summary:

Several members of the writing group are inventors of the AI tool mentioned in this paper. Dr. Naghavi is the founder of HeartLung.AI. Dr. Reeves, Dr. Atlas, Dr. Yankelevitz, Dr, Wong, and Dr. Li are consultants for HeartLung.AI. Chenyu Zhang is a research contractor of HeartLung.AI. Kyle Atlas is a graduate research associate of HeartLung.AI. The remaining authors have nothing to disclose.

Figures

Figure 1.
Figure 1.
Examples of AI-CAC all cardiac chambers segmentations in a cardiac CT scan.
Figure 2a-d.
Figure 2a-d.
Cumulative Incidence of Atrial Fibrillation (AF) in the Top Quartile of AI-CAC Left Atrial (LA) Volume, CHARGE-AF Score, NT-proBNP (and Agatston coronary artery calcium (CAC) over 5 years of follow-up.
Figure 2a-d.
Figure 2a-d.
Cumulative Incidence of Atrial Fibrillation (AF) in the Top Quartile of AI-CAC Left Atrial (LA) Volume, CHARGE-AF Score, NT-proBNP (and Agatston coronary artery calcium (CAC) over 5 years of follow-up.
Figure 2a-d.
Figure 2a-d.
Cumulative Incidence of Atrial Fibrillation (AF) in the Top Quartile of AI-CAC Left Atrial (LA) Volume, CHARGE-AF Score, NT-proBNP (and Agatston coronary artery calcium (CAC) over 5 years of follow-up.
Figure 2a-d.
Figure 2a-d.
Cumulative Incidence of Atrial Fibrillation (AF) in the Top Quartile of AI-CAC Left Atrial (LA) Volume, CHARGE-AF Score, NT-proBNP (and Agatston coronary artery calcium (CAC) over 5 years of follow-up.
Fig. 3. a–b
Fig. 3. a–b
Quartiles of AI-CAC Left Atrial (LA) Volume by predicted 5-year CHARGE-AF Risk and NT-proBNP Quartiles.
Fig. 3. a–b
Fig. 3. a–b
Quartiles of AI-CAC Left Atrial (LA) Volume by predicted 5-year CHARGE-AF Risk and NT-proBNP Quartiles.
Figure 4.
Figure 4.
1-year Follow-up Time-dependent area under the curve (AUC) for atrial fibrillation (AF) prediction between AI-CAC LA volume, NT-proBNP, (CHARGE-AF, and Agatston CAC Score.
Figure 4.
Figure 4.
1-year Follow-up Time-dependent area under the curve (AUC) for atrial fibrillation (AF) prediction between AI-CAC LA volume, NT-proBNP, (CHARGE-AF, and Agatston CAC Score.
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Update of

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