Purpose <p>Fractures are significant complications linked to type 2 diabetes mellitus (T2DM). In this study, we investigated the role of a computed tomography (CT)-based bone radiomic model for predicting vertebral fractures (VFs) in older patients with T2DM.</p> Methods <p>A cohort of 1486 T2DM patients over the age of 50 years who were free from VFs from 2019 to 2021 were included and subsequently followed up until 2024. A total of 135 new cases of VFs were identified. A control group of 270 individuals without VFs during the follow-up was selected. Radiomic features were gathered from the main domains of the CT scans.</p> Results <p>Radiomics score (Radscore) (adjusted risk ratio (aHR) = 12.04; 95% confidence interval (CI): 5.88–24.64) was independently associated with VFs in T2DM patients. The radiomic model had an acceptable performance in predicting VF risk (area under the curve = 0.752 (95% CI: 0.712–0.792) for 2-year risk, 0.765 (95% CI: 0.714–0.816) for 3-year risk, and 0.811 (95% CI: 0.727–0.894) for 4-year risk). A combined model of the Radscore and bone CT attenuation demonstrated a greater AUC (AUC = 0.795 (95% CI: 0.747–0.843) for 2-year risk; 0.789 (95% CI: 0.730–0.837) for 3-year risk; and 0.842 (95% CI: 0.757–0.927) for 4-year risk) than models based on the Radscore or bone CT attenuation alone. The calibration and decision curves demonstrated the excellent predictive accuracy of the model.</p> Conclusions <p>Bone radiomics has great potential in predicting VFs in older patients with T2DM.</p>

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A CT-based radiomic model for predicting vertebral fractures in older patients with type 2 diabetes mellitus: A longitudinal study

  • Zicheng Wei,
  • Rui Yu,
  • Yiping Zhang,
  • Yu Wang,
  • Jianhua Wang,
  • Cao Xie,
  • Xiao Chen

摘要

Purpose

Fractures are significant complications linked to type 2 diabetes mellitus (T2DM). In this study, we investigated the role of a computed tomography (CT)-based bone radiomic model for predicting vertebral fractures (VFs) in older patients with T2DM.

Methods

A cohort of 1486 T2DM patients over the age of 50 years who were free from VFs from 2019 to 2021 were included and subsequently followed up until 2024. A total of 135 new cases of VFs were identified. A control group of 270 individuals without VFs during the follow-up was selected. Radiomic features were gathered from the main domains of the CT scans.

Results

Radiomics score (Radscore) (adjusted risk ratio (aHR) = 12.04; 95% confidence interval (CI): 5.88–24.64) was independently associated with VFs in T2DM patients. The radiomic model had an acceptable performance in predicting VF risk (area under the curve = 0.752 (95% CI: 0.712–0.792) for 2-year risk, 0.765 (95% CI: 0.714–0.816) for 3-year risk, and 0.811 (95% CI: 0.727–0.894) for 4-year risk). A combined model of the Radscore and bone CT attenuation demonstrated a greater AUC (AUC = 0.795 (95% CI: 0.747–0.843) for 2-year risk; 0.789 (95% CI: 0.730–0.837) for 3-year risk; and 0.842 (95% CI: 0.757–0.927) for 4-year risk) than models based on the Radscore or bone CT attenuation alone. The calibration and decision curves demonstrated the excellent predictive accuracy of the model.

Conclusions

Bone radiomics has great potential in predicting VFs in older patients with T2DM.