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[Preprint]. 2024 Jan 24:2024.01.22.24301384.
doi: 10.1101/2024.01.22.24301384.

AI-enabled Left Atrial Volumetry in Cardiac CT Scans Improves CHARGE-AF and Outperforms NT-ProBNP for Prediction of Atrial Fibrillation in Asymptomatic Individuals: Multi-Ethnic Study of Atherosclerosis

Morteza Naghavi  1 , David Yankelevitz  2 , Anthony P Reeves  3 , Matthew J Budoff  4 , Dong Li  4 , Kyle C Atlas  1 , Chenyu Zhang  1 , Thomas L Atlas  5 , Seth Lirette  1 , Jakob Wasserthal  6 , Claudia Henschke  2 , Christopher Defilippi  7 , Susan R Heckbert  8 , Philip Greenland  9
Affiliations

AI-enabled Left Atrial Volumetry in Cardiac CT Scans Improves CHARGE-AF and Outperforms NT-ProBNP for Prediction of Atrial Fibrillation in Asymptomatic Individuals: Multi-Ethnic Study of Atherosclerosis

Morteza Naghavi et al. medRxiv. .

Update in

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-CAC), taking on average 21 seconds per CAC scan, 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). We used the 5-year outcomes data for incident atrial fibrillation (AF) and compared the time-dependent AUC of AI-CAC LA volume with known predictors of AF, the CHARGE-AF Risk Score and NT-proBNP (BNP). 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 or BNP at year 1 (0.836, 0.742, 0.742), year 2 (0.842, 0.807,0.772), and year 3 (0.811, 0.785, 0.745) (p<0.02), but similar for year 4 (0.785, 0.769, 0.725) and year 5 (0.781, 0.767, 0.734) respectively (p>0.05). AI-CAC LA volume significantly improved the continuous Net Reclassification Index for prediction of AF over years 1-5 when added to CAC score (0.74, 0.49, 0.53, 0.39, 0.44), CHARGE-AF Risk Score (0.60, 0.28, 0.32, 0.19, 0.24), and BNP (0.68, 0.44, 0.42, 0.30, 0.37) respectively (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 BNP.

Keywords: CHARGE-AF; Coronary artery calcium; artificial intelligence; atrial fibrillation; left atrial volume.

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Figures

Figure 1.
Figure 1.
Examples of AI-CAC segmentations in a cardiac CT scan.
Figure 2
Figure 2
a-d. Cumulative Incidence of Atrial Fibrillation (AF) in the Top Quartile of AI-CAC Left Atrial (LA) Volume, CHARGE-AF Score, NT-proBNP (BNP) and coronary artery calcium (CAC) over 5 years of follow-up.
Figure 2
Figure 2
a-d. Cumulative Incidence of Atrial Fibrillation (AF) in the Top Quartile of AI-CAC Left Atrial (LA) Volume, CHARGE-AF Score, NT-proBNP (BNP) and coronary artery calcium (CAC) over 5 years of follow-up.
Figure 2
Figure 2
a-d. Cumulative Incidence of Atrial Fibrillation (AF) in the Top Quartile of AI-CAC Left Atrial (LA) Volume, CHARGE-AF Score, NT-proBNP (BNP) and coronary artery calcium (CAC) over 5 years of follow-up.
Figure 2
Figure 2
a-d. Cumulative Incidence of Atrial Fibrillation (AF) in the Top Quartile of AI-CAC Left Atrial (LA) Volume, CHARGE-AF Score, NT-proBNP (BNP) and coronary artery calcium (CAC) over 5 years of follow-up.
Figure 3.
Figure 3.
Quartiles of AI-CAC Left Atrial (LA) Volume by predicted 5-year CHARGE-AF Risk
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