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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
Purpose

Osteoporotic vertebral fractures (VF) are associated with significant morbidity, mortality, and an increased risk of subsequent fractures. Today, there are effective treatment alternatives available that significantly lower the risk of subsequent fractures. Despite this, over two-thirds of VFs remain undetected by radiologists, underscoring the necessity for enhanced detection methods. Opportunistic screening for VFs is a high priority in the field of osteoporosis. Recently, AI-based solutions for automating vertebral fracture detection in CT examinations have emerged, which could be highly valuable in opportunistic settings. This study aimed to validate the performance of an AI algorithm in detecting vertebral fractures within a geriatric cohort.

GALLERY