Anna Spångeus, Tomas Bjerner, Maria Lindblom, Christoph Götz, Allan Hummer, Christoph Salzlechner, Mischa Woisetschläger
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引用次数: 0
Abstract
Summary
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, necessitating the development of new identification methods for opportunistic screening in computed tomography (CT) scans. This study validated an AI algorithm (ImageBiopsy Lab [IBL], FLAMINGO) for detecting VFs in a geriatric cohort, with various subgroup analyses including different CT protocols.
Methods
The performance of the AI in detecting VFs was compared to assessments by two experienced radiologists. A total of 246 thoracic or abdominal CT scans, primarily conducted for purposes other than skeletal examination, were included in the study.
Results
The patients had a mean age of 84 years (range 62 to 103), with 42% being female. The AI demonstrated high accuracy (0.93), sensitivity (0.86), and specificity (0.99) in detecting moderate to severe VFs. Subgroup analysis revealed accuracy ranging from 0.88 to 0.96, with higher accuracy in females compared to males (0.96 vs. 0.89, p = 0.03) and in scans performed with non-bone kernel versus bone kernel protocols (0.96 vs. 0.88, p = 0.02). No significant differences were found for age, contrast phase, or spinal region.
Conclusion
The results indicate that the AI algorithm exhibits high performance in a geriatric setting. If effectively integrated with a fracture liaison service, this could enhance VF detection considerable in the future.
期刊介绍:
Archives of Osteoporosis is an international multidisciplinary journal which is a joint initiative of the International Osteoporosis Foundation and the National Osteoporosis Foundation of the USA. The journal will highlight the specificities of different regions around the world concerning epidemiology, reference values for bone density and bone metabolism, as well as clinical aspects of osteoporosis and other bone diseases.