Abstract

Introduction: The integrity of the posterior ligamentous complex (PLC) is a key determinant of spinal stability and treatment strategy in AO Spine A3–A4 burst fractures of the thoracolumbar junction. While MRI remains the reference standard for PLC assessment, its availability in the acute trauma setting is frequently limited, necessitating CT-based diagnostic approaches. The aim of the study was to develop and internally validate a quantitative CT-based prognostic model for PLC injury in AO Spine A3–A4 thoracolumbar junction fractures and to translate it into a clinically applicable point-based score and nomogram. Material and methods: A retrospective observational study included 47 patients with AO Spine A3 (n = 13) or A4 (n = 34) fractures at the Th11–L2 level who underwent both CT and MRI in the acute post-traumatic period. PLC status verified by MRI and/or intraoperative findings served as the reference standard. Quantitative morphometric analysis encompassed eleven CT parameters reflecting vertebral body geometry, degree of fragmentation, and posterior structure involvement. A binary classification model was developed using extreme gradient boosting (XGBoost) and internally validated by repeated stratified 5-fold cross-validation (20 repeats). Feature importance was quantified using a composite integral weight metric. An interval-based point score and nomogram were derived from the model to enable bedside risk estimation. Results: PLC injury was confirmed in 22 patients (46.8%). The XGBoost model achieved an in-sample AUC of 0.949 and a cross-validated AUC of 0.894. The dominant predictors were AVH ratio, A/P ratio, and the presence of free bone fragments, whereas angular parameters contributed moderately. The point-based logistic model retained high discriminative performance (AUC = 0.880) with good calibration (Brier score 0.103; slope 1.00). Each additional point on the scale was associated with a 20% increase in the odds of PLC injury (OR 1.20; 95% CI 1.14–1.27). A total score exceeding 15–18 points was identified as a threshold indicating high instability risk. Conclusion: The developed quantitative CT-based score and nomogram enable reliable risk stratification of PLC injury in AO Spine A3–A4 fractures. The model demonstrated high predictive accuracy, biomechanical interpretability, and practical applicability in settings where MRI is unavailable. External validation in an independent prospective cohort is required before routine clinical implementation.

Keywords

thoracolumbar junction, spinal trauma, burst fractures, posterior ligamentous complex, CT morphometry, machine learning, prognostic model, nomogram