AI-assisted computed tomography analysis for pre-procedural planning prior to TAVI
In this retrospective analysis, a deep learning-based analysis of pre-procedural CT datasets showed good to excellent correlation with conventional assessment for the preprocedural TAVI CT measurements. AI-based fully automated CT analysis could emerge to a valuable alternative to conventional CT assessment in the pre-procedural-planning for TAVI.
Authors
- David M. Leistner (ORCID: https://orcid.org/0000-0002-4351-420X)
- Philipp Seppelt (ORCID: https://orcid.org/0000-0003-4743-6920)
- F. Hecker
- Stephan Fichtlscherer
- Mani Arsalan
- Hanna Schneider
- Thomas Walther
- Arnaud Van Linden
Institutions
- Goethe University Frankfurt (DE)
- Justus-Liebig-Universität Gießen (DE)
- Universitätsklinikum Würzburg (DE)
- University Hospital Frankfurt (DE)
- Segeberger Kliniken (DE)
Publication Details
- Journal
- Clinical Research in Cardiology
- Published
- 2025-11-12
- DOI
- https://doi.org/10.1007/s00392-025-02790-6
- Citations
- 1
- Primary Topic
- Cardiac Valve Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.39