Congress:
ECR25
Poster Number:
C-16938
Type:
Poster: EPOS Radiologist (scientific)
Authorblock:
M. Woisetschlager1, T. Bjerner1, M. Lindblom1, C. Götz2, A. Hummer2, C. Salzlechner2, A. Spångeus1; 1Linköping/SE, 2Vienna/AT
Disclosures:
Mischa Woisetschlager:
Nothing to disclose
Tomas Bjerner:
Nothing to disclose
Maria Lindblom:
Nothing to disclose
Christoph Götz:
Employee: IB lab GmbH
Allan Hummer:
Employee: IB lab GmbH
Christoph Salzlechner:
Employee: IB lab GmbH
Anna Spångeus:
Advisory Board: UCB Consultant: Giddeon Richter Speaker: Amgen, Tromp Medical
Keywords:
Abdomen, Artificial Intelligence, Computer applications, CT, Computer Applications-General, Osteoporosis
This study validates the high accuracy, sensitivity, and specificity of an AI algorithm in detecting moderate to severe vertebral fractures in a geriatric cohort. The AI demonstrated particularly high accuracy in females and in scans using non-bone kernel protocols. These findings highlight the potential of AI-based solutions to enhance opportunistic screening for vertebral fractures, addressing a critical gap in osteoporosis management.