Artificial intelligence-based radiomics on computed tomography of lumbar spine in subjects with fragility vertebral fractures

• Published in: Journal of endocrinological investigation Vol. 45; no. 10; pp. 2007 - 2017
• Main Authors: Biamonte, E., Levi, R., Carrone, F., Vena, W., Brunetti, A., Battaglia, M., Garoli, F., Savini, G., Riva, M., Ortolina, A., Tomei, M., Angelotti, G., Laino, M. E., Savevski, V., Mollura, M., Fornari, M., Barbieri, R., Lania, A. G., Grimaldi, M., Politi, L. S., Mazziotti, G.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.10.2022; Springer Nature B.V
• Subjects: Artificial intelligence; Bone mineral density; Bone strength; Computed tomography; Dual energy X-ray absorptiometry; Endocrinology; Fractures; Internal Medicine; Medicine; Medicine & Public Health; Metabolic Diseases; Original Article; Osteoporosis; Radiomics; Spine (lumbar); Tomography; Vertebrae; Osteoporosis; Vertebral fractures; Artificial intelligence; Radiomics

Purpose There is emerging evidence that radiomics analyses can improve detection of skeletal fragility. In this cross-sectional study, we evaluated radiomics features (RFs) on computed tomography (CT) images of the lumbar spine in subjects with or without fragility vertebral fractures (VFs). Methods...