Diagnostic Model for Distinguishing Fresh or Old Osteoporotic Vertebral Compression Fractures Based on Modified CT Window: A Retrospective Cohort Study

Purpose To develop a nomogram-based diagnostic model using CT imaging for rapid differentiation of fresh versus old osteoporotic vertebral compression fractures (OVCFs), particularly for patients contraindicated for MRI (e.g., those with metallic implants), emergency settings requiring immediate diagnosis, and resource-limited hospitals. Methods A retrospective analysis was conducted on OVCF patients from The First Affiliated Hospital of Chongqing Medical University (August 2022–December 2023). Modified CT window parameters (width: 400; level: 200) were applied to quantify vertebral features, including CT values, height reduction, endplate integrity, trabecular sparsity, Schmorl's nodes, and high-density shadows. Predictive variables were identified through univariate and multivariate logistic regression, followed by nomogram construction. Model performance was evaluated via ROC curves, calibration plots, Hosmer-Lemeshow test, and decision curve analysis (DCA). Results The nomogram integrated seven key imaging biomarkers, demonstrating robust discrimination with AUCs of 0.941 (training cohort) and 0.974 (validation cohort). Calibration was excellent (Hosmer-Lemeshow χ²=3.30, P = 0.95), and DCA confirmed substantial clinical net benefit across threshold probabilities. Conclusion This CT-based nomogram achieves high diagnostic accuracy for fresh OVCFs without MRI dependency, offering a practical tool for clinical decision-making in time-sensitive or resource-constrained scenarios.