Towards clinical implementation of automated segmentation of vestibular schwannomas: a reliability study comparing AI and human performance
Models with excellent geometric-based metrics do not necessarily imply high clinimetric reliability, demonstrating the need to clinimetrically evaluate models as part of the clinical implementation process. The multi-center model displayed high reliability, warranting its possible future use in clinical practice. However, caution should be exercised when employing the model for small tumors, as the reliability was found to be volume-dependent.
Authors
- S. Cornelissen (ORCID: https://orcid.org/0000-0002-7333-6256)
- Peter H. N. de With (ORCID: https://orcid.org/0000-0002-7639-7716)
- Henricus P. M. Kunst (ORCID: https://orcid.org/0000-0003-1162-6394)
- Sammy M Schouten (ORCID: https://orcid.org/0009-0008-8098-1692)
- Patrick Langenhuizen
- Jeroen B. Verheul
Institutions
- Radboud University Nijmegen (NL)
- Maastricht University Medical Centre (NL)
- Radboud University Medical Center (NL)
- Elisabeth-TweeSteden Ziekenhuis (NL)
- Eindhoven University of Technology (NL)
Publication Details
- Journal
- Neuroradiology
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1007/s00234-025-03611-3
- Citations
- 2
- Primary Topic
- Meningioma and schwannoma management
- Type
- article
- Field-Weighted Citation Impact
- 2.71
Funders
- ZonMw