Predicting major adverse cardiovascular events in angina patients using radiomic features of pericoronary adipose tissue based on CCTA
The CCTA-based PCAT radiomics model is an effective tool for predicting MACE in patients with angina pectoris, assisting clinicians in optimizing risk stratification for individual patients. The CCTA-based radiomics model significantly surpasses traditional FAI and clinical models in predicting major adverse cardiovascular events in patients with angina pectoris.
Authors
- Xinyi Feng (ORCID: https://orcid.org/0000-0001-5960-1028)
- Ningbei Yin (ORCID: https://orcid.org/0000-0002-4657-3723)
- Y Li (ORCID: https://orcid.org/0000-0001-6963-0957)
- Hui Luo (ORCID: https://orcid.org/0000-0001-5611-4099)
- Yanfang Luo
- Zheng Zhou (ORCID: https://orcid.org/0000-0003-2585-0418)
- Ying Yang
- Weisheng Zhan
Institutions
- Affiliated Hospital of North Sichuan Medical College (CN)
- Nanchong Central Hospital (CN)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2024-10-31
- DOI
- https://doi.org/10.3389/fcvm.2024.1462451
- Citations
- 5
- Primary Topic
- Cardiovascular Disease and Adiposity
- Type
- article
- Field-Weighted Citation Impact
- 2.01