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Background <p>Osteonecrosis of the femoral head (ONFH) may progress to collapse and disability. While total hip arthroplasty (THA) is standard in older patients, surgical decision-making in younger adults remains heterogeneous. CT provides high spatial resolution for evaluating late-stage ONFH, and radiomics may offer quantitative support.</p> Objective <p>To investigate whether the predictive value of CT-based radiomics for surgical choice under routine practice is age-dependent and whether clinical variables add value across age subgroups.</p> Methods <p>We retrospectively analyzed 160 patients (201 hips) with ARCO stage III ONFH who underwent hip-preserving surgery or THA. Radiomics features were extracted from preoperative CT images and used to build radiomics-only and fusion models with four classifiers. Repeated k-fold cross-validation and bootstrap validation were applied. Three-level age stratification (&lt; 65 years, &lt; 50 years, and 20–35 vs. 36–50 years) and SHAP analysis were used.</p> Results <p>Fusion models outperformed radiomics-only models in patients younger than 65 years. In younger subgroups, radiomics-only models achieved comparable or superior performance, while the contribution of clinical variables decreased. SHAP analysis showed diminishing importance of age and disease duration, with texture-based radiomics features dominating in younger patients.</p> Conclusion <p>CT-based radiomics, combined with interpretable machine learning, may provide quantitative decision support for modeling and supporting routine surgical decision-making between hip-preserving procedures and THA, particularly in younger patients.</p>

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CT-based radiomics for modeling surgical decision-making in young and middle-aged patients with ARCO stage III osteonecrosis of the femoral head: an age-stratified retrospective study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月12日

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  • Xinran Zhang,
  • Pei Qiu,
  • Guoji Shi,
  • Tianwei Xia,
  • Nan Zhang,
  • Tong Xu,
  • Yun Li,
  • Zhitao Wang,
  • Jirong Shen,
  • Ting Wu

摘要

Background

Osteonecrosis of the femoral head (ONFH) may progress to collapse and disability. While total hip arthroplasty (THA) is standard in older patients, surgical decision-making in younger adults remains heterogeneous. CT provides high spatial resolution for evaluating late-stage ONFH, and radiomics may offer quantitative support.

Objective

To investigate whether the predictive value of CT-based radiomics for surgical choice under routine practice is age-dependent and whether clinical variables add value across age subgroups.

Methods

We retrospectively analyzed 160 patients (201 hips) with ARCO stage III ONFH who underwent hip-preserving surgery or THA. Radiomics features were extracted from preoperative CT images and used to build radiomics-only and fusion models with four classifiers. Repeated k-fold cross-validation and bootstrap validation were applied. Three-level age stratification (< 65 years, < 50 years, and 20–35 vs. 36–50 years) and SHAP analysis were used.

Results

Fusion models outperformed radiomics-only models in patients younger than 65 years. In younger subgroups, radiomics-only models achieved comparable or superior performance, while the contribution of clinical variables decreased. SHAP analysis showed diminishing importance of age and disease duration, with texture-based radiomics features dominating in younger patients.

Conclusion

CT-based radiomics, combined with interpretable machine learning, may provide quantitative decision support for modeling and supporting routine surgical decision-making between hip-preserving procedures and THA, particularly in younger patients.