Artificial intelligence image analysis for Hounsfield units in preoperative thoracolumbar CT scans: an automated screening for osteoporosis in patients undergoing spine surgery
The AI model demonstrated strong agreement with human experts in measuring HU values, validating its potential as a reliable tool for automated osteoporosis screening in spine surgery patients. This approach can enhance preoperative risk assessment and perioperative bone health optimization. Future research should focus on external validation and inclusion of diverse patient demographics to ensure broader applicability.
Authors
- Graham W. Johnson (ORCID: https://orcid.org/0000-0002-9154-4315)
- Nisha Jayasuriya (ORCID: https://orcid.org/0000-0003-4609-6063)
- Konstantinos Katsos
- Emily Feng (ORCID: https://orcid.org/0009-0006-0371-2400)
- Mohamad Bydon (ORCID: https://orcid.org/0000-0002-0543-396X)
- Karim Rizwan Nathani (ORCID: https://orcid.org/0000-0003-4134-7011)
- Laura A. Machlab
- Brett A. Freedman (ORCID: https://orcid.org/0000-0002-2036-769X)
Institutions
- Mayo Clinic (US)
- Orthopedic One (US)
Publication Details
- Journal
- Journal of Neurosurgery Spine
- Published
- 2025-04-18
- DOI
- https://doi.org/10.3171/2025.1.spine24900
- Citations
- 3
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.02