Machine learning-based radiomic features of perivascular adipose tissue in coronary computed tomography angiography predicting inflammation status around atherosclerotic plaque: a retrospective cohort study
CCTA-based PVAT radiomics effectively distinguished coronary artery segments with and without plaques. The combined model and nomogram demostrated clinical utility, offering a novel approach for early diagnosis and risk stratification in coronary heart disease.
Authors
- Xukai Mo
- Kunlin Ye
- Hao Zhou (ORCID: https://orcid.org/0009-0000-1276-0080)
- Changzheng Shi (ORCID: https://orcid.org/0000-0003-4582-0769)
- Lingtao Zhang (ORCID: https://orcid.org/0009-0003-9873-4570)
Institutions
- Jinan University (CN)
- First Affiliated Hospital of Jinan University (CN)
- Imaging Center (US)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2024-12-12
- DOI
- https://doi.org/10.1080/07853890.2024.2431606
- Primary Topic
- Cardiovascular Disease and Adiposity
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Fundamental Research Funds for the Central Universities