The Predictive Value of Multiparameter Characteristics of Coronary Computed Tomography Angiography for Coronary Stent Implantation
The integration of AI-derived multiparameter features from one-stop CCTA significantly enhances the accuracy of predicting PCI in angina pectoris patients, evaluating at the plaque, vessel, and patient levels.
Authors
- Peiji Song (ORCID: https://orcid.org/0000-0001-8384-0264)
- Ximing Wang (ORCID: https://orcid.org/0000-0001-5136-8057)
- Zekai Zhao (ORCID: https://orcid.org/0000-0002-3816-5471)
- Xiaodie Xu
- Lin‐Bing Sun (ORCID: https://orcid.org/0000-0002-6395-312X)
- Tiantian Yang (ORCID: https://orcid.org/0000-0003-2845-5413)
- Hairong Yu
- Ying Wang (ORCID: https://orcid.org/0000-0002-7852-386X)
- Ting Li (ORCID: https://orcid.org/0000-0001-7901-5288)
- Chu Chu (ORCID: https://orcid.org/0000-0003-2938-7862)
- Zengkun Wang
Institutions
- Qingdao University (CN)
- Weifang Medical University (CN)
- Jinan Central Hospital (CN)
- Shandong Provincial Hospital (CN)
- Affiliated Hospital of Qingdao University (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Journal of Computer Assisted Tomography
- Published
- 2025-06-06
- DOI
- https://doi.org/10.1097/rct.0000000000001770
- Primary Topic
- Cardiovascular Disease and Adiposity
- Type
- article
- Field-Weighted Citation Impact
- 0.00