Artificial intelligence–based quantification of breast arterial calcifications to predict cardiovascular morbidity and mortality
Automatically quantified BAC is an independent predictor of MACE and mortality, adding prognostic value to the PREVENT score. This approach may provide an opportunistic cardiovascular risk assessment during routine mammography screening without additional radiation exposure to guide earlier and more effective preventive care for women.
Authors
- Laurence S. Sperling (ORCID: https://orcid.org/0000-0001-9417-6370)
- Aawez Mansuri
- Mohammadreza Chavoshi (ORCID: https://orcid.org/0000-0001-6598-7190)
- Chadi Ayoub (ORCID: https://orcid.org/0000-0001-5877-7478)
- Aisha Urooj Khan (ORCID: https://orcid.org/0000-0001-6521-2512)
- Chad J. Robichaux (ORCID: https://orcid.org/0009-0002-8403-5499)
- Theo Dapamede (ORCID: https://orcid.org/0000-0002-6264-2282)
- Reza Arsanjani (ORCID: https://orcid.org/0000-0001-7081-4286)
- Frank Li (ORCID: https://orcid.org/0000-0002-8205-3397)
- Marly van Assen (ORCID: https://orcid.org/0000-0003-4044-4426)
- Rohan Isaac (ORCID: https://orcid.org/0000-0002-6920-4744)
- Hari Trivedi (ORCID: https://orcid.org/0000-0001-6648-8334)
- Vedant Joshi
- Judy Wawira Gichoya (ORCID: https://orcid.org/0000-0002-1097-316X)
- Beatrice Brown-Mulry
- Gabrielle Gershon
- Imon Banerjee
- Charles O’Neill (ORCID: https://orcid.org/0000-0003-2586-6874)
Institutions
- Emory University (US)
- WinnMed (US)
- Mayo Clinic Hospital (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- European Heart Journal
- Published
- 2026-02-10
- DOI
- https://doi.org/10.1093/eurheartj/ehag128
- Citations
- 1
- Primary Topic
- Biomarkers in Disease Mechanisms
- Type
- article
- Field-Weighted Citation Impact
- 24.43