A Computed Tomography-based Radiomics Nomogram for Predicting Osteoporotic Vertebral Fractures: A Longitudinal Study

CONTEXT: Fractures are a serious consequence of osteoporosis in older adults. However, few longitudinal studies have shown the role of computed tomography (CT)-based radiomics in predicting osteoporotic fractures. OBJECTIVE: We evaluated the performance of a CT radiomics-based model for osteoporotic vertebral fractures (OVFs) in a longitudinal study. METHODS: A total of 7906 individuals without OVF older than 50 years, and who underwent CT scans between 2016 and 2019 were enrolled and followed up until 2021. Seventy-two cases of new OVF were identified. A total of 144 people without OVF during follow-up were selected as controls. Radiomics features were extracted from baseline CT images. CT values of trabecular bone, and area and density of erector spinae were determined. Cox regression analysis was used to identify the independent associated factors. The predictive performance of the nomogram was assessed using the receiver operating characteristic curve, calibration curve, and decision curve. RESULTS: CT value of vertebra (adjusted hazard ratio (aHR) = 2.04; 95% CI, 1.07-3.89), radiomics score (aHR = 6.56; 95% CI, 3.47-12.38), and area of erector spinae (aHR = 1.68; 95% CI, 1.02-2.78) were independently associated with OVF. Radscore was associated with severe OVF (aHR = 6.00; 95% CI, 2.78-12.93). The nomogram showed good discrimination with a C-index of 0.82 (95% CI, 0.77-0.87). The area under the curve of nomogram and radscore were both higher than osteoporosis + muscle area for 3-year and 4-year risk of fractures (P < .05). The decision curve also demonstrated that the radiomics nomogram was useful. CONCLUSION: Bone radiomics is associated with OVF, and the nomogram based on radiomics signature and muscle provides a tool for the prediction of OVF.