Diagnostic Accuracy and Robustness of AI-based Fully Automated CT-FFR for the Detection of Significant CAD in Patients With Transcatheter Aortic Valve Replacement
AI-based fully automated CT-FFR enables to improve the diagnostic performance of CCTA for the detection of significant CAD pre-TAVR and demonstrates robust stability post-TAVR.
Authors
- Lei Lv (ORCID: https://orcid.org/0000-0003-4820-3125)
- Tao Pan (ORCID: https://orcid.org/0000-0002-5055-5675)
- Leilei Zhou
- Tao Zhang (ORCID: https://orcid.org/0000-0002-5607-4610)
- Xinyu Zhang (ORCID: https://orcid.org/0000-0003-2051-2655)
- Qian Chen (ORCID: https://orcid.org/0000-0002-1487-5479)
- Huimin Xie (ORCID: https://orcid.org/0000-0002-5717-5034)
- Wen Kang (ORCID: https://orcid.org/0000-0001-6095-9879)
- Hui Xu (ORCID: https://orcid.org/0000-0001-5631-6264)
- Yu Gong (ORCID: https://orcid.org/0000-0002-9357-9503)
- Yunlei Fu (ORCID: https://orcid.org/0000-0002-0564-8469)
Institutions
- Nanjing Medical University (CN)
Publication Details
- Journal
- Journal of Computer Assisted Tomography
- Published
- 2025-10-03
- DOI
- https://doi.org/10.1097/rct.0000000000001808
- Primary Topic
- Cardiac Valve Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00