Peer-Reviewed Publication
Arch Osteoporos2025;20(1):42.March 25, 2025Journal Article
Breaking the silence: AI's contribution to detecting vertebral fractures in opportunistic CT scans in the elderly-a validation study.
Anna Spångeus1,2,3,4, Tomas Bjerner5,6,7, Maria Lindblom7, Christoph Götz8, Allan Hummer8, Christoph Salzlechner8, Mischa Woisetschläger5,6,7
1Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden. anna.spangeus@liu.se.
2Department of Activity and Health, Linköping University Hospital, Linköping, Sweden. anna.spangeus@liu.se.
3Center for Medical Image Science and Visualization (CMIV), Linköping, Sweden. anna.spangeus@liu.se.
4Department of Acute Internal Medicine and Geriatrics and Department of Medical and Health Sciences, Linköping University, Campus US, 581 83, Linköping, Sweden. anna.spangeus@liu.se.
5Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
6Center for Medical Image Science and Visualization (CMIV), Linköping, Sweden.
7Department of Radiology, Linköping University Hospital, Linköping, Sweden.
8Department for Research and Development, IB Lab, Vienna, Austria.
Abstract
UNLABELLED: Vertebral fractures frequently go undetected in clinical practice. AI-assisted detection on CT scans demonstrates considerable promise, with a sensitivity of 86% and a specificity of 99%. The performance varied based on sex, and CT kernel, showing superior results in females and in scans using non-bone kernel protocols.
PURPOSE: Vertebral fractures (VFs) are highly underdiagnosed, nec…
Create a free account to keep reading
Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.
Want unlimited research access? See Pro plans