Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction

Morteza Naghavi; Anthony P. Reeves; Kyle Atlas; Chenyu Zhang; Thomas Atlas; Claudia I. Henschke; David F. Yankelevitz; Matthew J. Budoff; Dong Li; Sion K. Roy; Khurram Nasir; Sabee Molloi; Zahi Fayad; Michael V. McConnell; Ioannis Kakadiaris; David J. Maron; Jagat Narula; Kim Williams; Prediman K. Shah; Daniel Levy; Nathan D. Wong

doi:10.1038/s41746-024-01308-0

Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction

Morteza Naghavi, Anthony P. Reeves, Kyle Atlas, Chenyu Zhang, Thomas Atlas, Claudia I. Henschke, David F. Yankelevitz, Matthew J. Budoff, Dong Li, Sion K. Roy, Khurram Nasir, Sabee Molloi, Zahi Fayad, Michael V. McConnell, Ioannis Kakadiaris, David J. Maron, Jagat Narula, Kim Williams, Prediman K. Shah, Daniel LevyNathan D. Wong

Research output: Contribution to journal › Article › peer-review

Abstract

Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) in the multi-ethnic study of atherosclerosis during 15 years of follow-up, 1773 CVD events accrued. The AUC at 1-, 5-, 10-, and 15-year follow-up for AI-CAC vs. Agatston score was (0.784 vs. 0.701), (0.771 vs. 0.709), (0.789 vs. 0.712) and (0.816 vs. 0.729) (p < 0.0001 for all), respectively. AI-CAC plaque characteristics, including number, location, density, plus number of vessels, significantly improved CHD prediction in the CAC 1–100 cohort vs. Agatston Score. AI-CAC significantly improved the Agatston score for predicting all CVD events.

Original language	English
Article number	309
Journal	npj Digital Medicine
Volume	7
Issue number	1
DOIs	https://doi.org/10.1038/s41746-024-01308-0
State	Published - Dec 2024

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Naghavi, M., Reeves, A. P., Atlas, K., Zhang, C., Atlas, T., Henschke, C. I., Yankelevitz, D. F., Budoff, M. J., Li, D., Roy, S. K., Nasir, K., Molloi, S., Fayad, Z., McConnell, M. V., Kakadiaris, I., Maron, D. J., Narula, J., Williams, K., Shah, P. K., ... Wong, N. D. (2024). Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction. npj Digital Medicine, 7(1), Article 309. https://doi.org/10.1038/s41746-024-01308-0

@article{b7030b9b9433469fa4fbe3d07a9dac54,

title = "Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction",

abstract = "Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) in the multi-ethnic study of atherosclerosis during 15 years of follow-up, 1773 CVD events accrued. The AUC at 1-, 5-, 10-, and 15-year follow-up for AI-CAC vs. Agatston score was (0.784 vs. 0.701), (0.771 vs. 0.709), (0.789 vs. 0.712) and (0.816 vs. 0.729) (p < 0.0001 for all), respectively. AI-CAC plaque characteristics, including number, location, density, plus number of vessels, significantly improved CHD prediction in the CAC 1–100 cohort vs. Agatston Score. AI-CAC significantly improved the Agatston score for predicting all CVD events.",

author = "Morteza Naghavi and Reeves, {Anthony P.} and Kyle Atlas and Chenyu Zhang and Thomas Atlas and Henschke, {Claudia I.} and Yankelevitz, {David F.} and Budoff, {Matthew J.} and Dong Li and Roy, {Sion K.} and Khurram Nasir and Sabee Molloi and Zahi Fayad and McConnell, {Michael V.} and Ioannis Kakadiaris and Maron, {David J.} and Jagat Narula and Kim Williams and Shah, {Prediman K.} and Daniel Levy and Wong, {Nathan D.}",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2024.",

year = "2024",

month = dec,

doi = "10.1038/s41746-024-01308-0",

language = "English",

volume = "7",

journal = "npj Digital Medicine",

issn = "2398-6352",

publisher = "Nature Publishing Group",

number = "1",

}

Naghavi, M, Reeves, AP, Atlas, K, Zhang, C, Atlas, T, Henschke, CI, Yankelevitz, DF, Budoff, MJ, Li, D, Roy, SK, Nasir, K, Molloi, S, Fayad, Z, McConnell, MV, Kakadiaris, I, Maron, DJ, Narula, J, Williams, K, Shah, PK, Levy, D & Wong, ND 2024, 'Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction', npj Digital Medicine, vol. 7, no. 1, 309. https://doi.org/10.1038/s41746-024-01308-0

TY - JOUR

T1 - Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction

AU - Naghavi, Morteza

AU - Reeves, Anthony P.

AU - Atlas, Kyle

AU - Zhang, Chenyu

AU - Atlas, Thomas

AU - Henschke, Claudia I.

AU - Yankelevitz, David F.

AU - Budoff, Matthew J.

AU - Li, Dong

AU - Roy, Sion K.

AU - Nasir, Khurram

AU - Molloi, Sabee

AU - Fayad, Zahi

AU - McConnell, Michael V.

AU - Kakadiaris, Ioannis

AU - Maron, David J.

AU - Narula, Jagat

AU - Williams, Kim

AU - Shah, Prediman K.

AU - Levy, Daniel

AU - Wong, Nathan D.

PY - 2024/12

Y1 - 2024/12

N2 - Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) in the multi-ethnic study of atherosclerosis during 15 years of follow-up, 1773 CVD events accrued. The AUC at 1-, 5-, 10-, and 15-year follow-up for AI-CAC vs. Agatston score was (0.784 vs. 0.701), (0.771 vs. 0.709), (0.789 vs. 0.712) and (0.816 vs. 0.729) (p < 0.0001 for all), respectively. AI-CAC plaque characteristics, including number, location, density, plus number of vessels, significantly improved CHD prediction in the CAC 1–100 cohort vs. Agatston Score. AI-CAC significantly improved the Agatston score for predicting all CVD events.

AB - Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.2% women, age 61.7 ± 10.2 years) in the multi-ethnic study of atherosclerosis during 15 years of follow-up, 1773 CVD events accrued. The AUC at 1-, 5-, 10-, and 15-year follow-up for AI-CAC vs. Agatston score was (0.784 vs. 0.701), (0.771 vs. 0.709), (0.789 vs. 0.712) and (0.816 vs. 0.729) (p < 0.0001 for all), respectively. AI-CAC plaque characteristics, including number, location, density, plus number of vessels, significantly improved CHD prediction in the CAC 1–100 cohort vs. Agatston Score. AI-CAC significantly improved the Agatston score for predicting all CVD events.

UR - http://www.scopus.com/inward/record.url?scp=85208726191&partnerID=8YFLogxK

U2 - 10.1038/s41746-024-01308-0

DO - 10.1038/s41746-024-01308-0

M3 - Article

AN - SCOPUS:85208726191

SN - 2398-6352

VL - 7

JO - npj Digital Medicine

JF - npj Digital Medicine

IS - 1

M1 - 309

ER -

Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction

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