BMC Musculoskeletal Disorders (Dec 2023)

Predicting efficacy and guiding procedure choice in non-vascularized bone grafting: a CT Radiomics and clinical predictor approach

  • Hao Chen,
  • Peng Xue,
  • Hongzhong Xi,
  • Shuai He,
  • Guangquan Sun,
  • Xin Liu,
  • Bin Du

DOI
https://doi.org/10.1186/s12891-023-07095-1
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 13

Abstract

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Abstract Objectives There is no practical approach for accurately predicting the efficacy of non-vascularized bone grafting (NVBG) and guiding its optimal procedure. Materials and methods This study enrolled 153 patients with 182 hips that underwent NVBG procedures. The patients were randomly divided into a training cohort (n = 130) and a validation cohort (n = 52). In the training cohort, radiomics model, clinical model, and combined radiomics-clinical (C-R) model were constructed using Rad-scores and clinical predictors to predict the efficacy of NVBG. The optimal model was visualized by a nomogram and assessed by decision curve analysis (DCA). 128 hips that underwent successful NVBG were then randomized into a new training cohort (n = 92) and a new validation cohort (n = 36), and three models were constructed and validated to predict the choice of NVBG procedure. Results Japanese Investigation Committee (JIC) classification, exposure to risk factors postoperative, and Rad-scores consisting of four radiomics features were independent predictors for the efficacy of NVBG (P < 0.05). The C-R model provided better performance in both the training cohort (AUC: 0.818) and validation cohort (AUC: 0.747). To predict the choice of NVBG procedure, the C-R model built by JIC classification and Rad-scores consisting of five radiomics features showed the finest performance in both cohorts (AUC: 0.860 and 0.800, respectively). DCA showed great benefit using the C-R model for the choice of NVBG procedure. Conclusion The approach integrated by CT radiomics and clinical predictors can be visually and quantitatively applied to predict the efficacy and guide the choice of NVBG procedure with great predictive accuracy.

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