Segmentation-based 3D volumetry and linear regression modeling for assessing the vertebral bone loss in pyogenic vertebral osteomyelitis
A 3D-volumetric approach and linear regression modeling offers an individualized method for quantifying VB destruction in PVO. Integrating automated segmentation and densitometric data may further enhance predictive accuracy and improve patient-specific treatment strategies.
Authors
- Michael Ardelt (ORCID: https://orcid.org/0000-0002-8764-9237)
- Markus Loibl (ORCID: https://orcid.org/0000-0001-7631-0476)
- Michael Haimerl
- Siegmund Lang (ORCID: https://orcid.org/0000-0003-0459-9092)
- Volker Alt (ORCID: https://orcid.org/0000-0003-0208-4650)
- Maximilian Kerschbaum (ORCID: https://orcid.org/0000-0003-4996-8808)
- Gerardo Napodano (ORCID: https://orcid.org/0009-0008-5411-0412)
- Susanne Baertl
- Josina Straub (ORCID: https://orcid.org/0009-0002-9592-4208)
- Jonas Krückel
- Michael Bachtler
Institutions
- Universität für Weiterbildung Krems (AT)
- University Hospital Regensburg (DE)
- Schulthess-Klinik (CH)
- Klinikum Würzburg Mitte (DE)
- Karl Landsteiner University of Health Sciences (AT)
Publication Details
- Journal
- European Spine Journal
- Published
- 2025-07-26
- DOI
- https://doi.org/10.1007/s00586-025-09163-7
- Primary Topic
- Infectious Diseases and Tuberculosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universitätsklinikum Regensburg