Opportunistic assessment of abdominal aortic calcification using artificial intelligence (AI) predicts coronary artery disease and cardiovascular events
Using opportunistic abdominal CTs, assessment of AAC using a fully automated AI algorithm, predicted CAC and was independently associated with cardiovascular events. These data support the use of opportunistic imaging for cardiovascular risk assessment. Future studies should investigate whether opportunistic imaging can help guide appropriate cardiovascular prevention strategies.
Authors
- Bari R. Dane (ORCID: https://orcid.org/0000-0003-2205-3309)
- Malte Westerhoff (ORCID: https://orcid.org/0009-0001-2516-6029)
- Michael Recht (ORCID: https://orcid.org/0000-0002-2805-1016)
- Soterios Gyftopoulos (ORCID: https://orcid.org/0000-0001-5987-6363)
- Miriam A. Bredella (ORCID: https://orcid.org/0000-0001-5482-0440)
- Chen Lyu
- Eduardo Iturrate (ORCID: https://orcid.org/0000-0001-6434-2518)
- Judy Zhong (ORCID: https://orcid.org/0000-0002-2163-8447)
- Jeffrey S. Berger (ORCID: https://orcid.org/0000-0002-5525-2171)
Institutions
- Cornell University (US)
- NYU Langone Health (US)
- Cancer Research And Biostatistics (US)
- New York University (US)
Publication Details
- Journal
- American Heart Journal
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1016/j.ahj.2025.04.019
- Citations
- 3
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- National Institutes of Health
- National Institute on Aging
- National Heart, Lung, and Blood Institute
- U.S. National Library of Medicine
- National Center for Advancing Translational Sciences