Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction
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.
Authors
- Jagat Narula (ORCID: https://orcid.org/0000-0002-0280-3996)
- Kim A. Williams (ORCID: https://orcid.org/0000-0001-9858-5761)
- Morteza Naghavi (ORCID: https://orcid.org/0000-0001-8112-175X)
- Prediman K. Shah (ORCID: https://orcid.org/0000-0002-6351-8291)
- Claudia I. Henschke (ORCID: https://orcid.org/0000-0002-6085-5305)
- Ioannis A. Kakadiaris (ORCID: https://orcid.org/0000-0002-0591-1079)
- David J. Maron (ORCID: https://orcid.org/0000-0002-4867-8588)
- Anthony P. Reeves (ORCID: https://orcid.org/0000-0002-1451-3080)
- Michael V. McConnell (ORCID: https://orcid.org/0000-0001-8743-0932)
- Daniel A Levy (ORCID: https://orcid.org/0000-0003-1843-8724)
- Matthew Jay Budoff (ORCID: https://orcid.org/0000-0002-9616-1946)
- Nathan D. Wong (ORCID: https://orcid.org/0000-0003-1102-7324)
- Sabee Molloi (ORCID: https://orcid.org/0000-0003-1852-4913)
- Zahi A. Fayad (ORCID: https://orcid.org/0000-0002-3439-7347)
- Thomas Atlas
- K. Atlas
- Dong Li (ORCID: https://orcid.org/0000-0002-3897-7322)
- Khurram Nasir
- Chenyu Zhang (ORCID: https://orcid.org/0000-0002-9799-8772)
- David F. Yankelevitz
- Sion Roy
Institutions
- Cedars-Sinai Medical Center (US)
- Houston Methodist (US)
- National Institutes of Health (US)
- University of Louisville (US)
- University of California, Irvine (US)
- Cornell University (US)
- Mount Sinai Hospital (US)
- National Heart, Lung, and Blood Institute (US)
- Methodist Hospital (US)
- Stanford Medicine (US)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1038/s41746-024-01308-0
- Citations
- 22
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 8.89
Funders
- U.S. Department of Health and Human Services
- National Institutes of Health
- National Heart, Lung, and Blood Institute
- National Center for Advancing Translational Sciences