Comparison of Experienced and Inexperienced Raters Using Automated Deep Learning Computed Tomography Analysis to Evaluate Tricuspid Valve and Right Heart Morphology
•Computed tomography (CT) is used to plan tricuspid valve interventions.•Deep learning-based CT analysis enables fast and accurate right heart assessment.•Results are independent of the users' experience.
Authors
- Elena Romero Dorta (ORCID: https://orcid.org/0000-0002-7641-4467)
- Cheng‐Ying Chiu (ORCID: https://orcid.org/0000-0002-7075-1446)
- Isabel Mattig (ORCID: https://orcid.org/0000-0001-8455-3750)
- Henryk Dreger (ORCID: https://orcid.org/0000-0003-1909-4329)
- Georg Böning (ORCID: https://orcid.org/0000-0002-8819-6209)
- Ann-Christine Stahl
- Marc Dewey (ORCID: https://orcid.org/0000-0002-4402-2733)
- Lars-Arne Schaafs (ORCID: https://orcid.org/0000-0002-2250-5419)
- Nanike Bühring
- Maximilian Eichenberg
Institutions
- Humboldt-Universität zu Berlin (DE)
- Deutsches Herzzentrum der Charité (DE)
- German Centre for Cardiovascular Research (DE)
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- Freie Universität Berlin (DE)
- Charité - Universitätsmedizin Berlin (DE)
Publication Details
- Journal
- Structural Heart
- Published
- 2025-05-06
- DOI
- https://doi.org/10.1016/j.shj.2025.100488
- Primary Topic
- Cardiac Valve Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Charité – Universitätsmedizin Berlin
- Berlin Institute of Health