ArticleBMC musculoskeletal disorders2026
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.
Article in BMC musculoskeletal disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundOsteonecrosis 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.
objectiveTo 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.
methodsWe 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.
resultsFusion 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.
conclusionCT-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.
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