国际医学放射学杂志2024，Vol.47Issue(4)：441-446,6.DOI:10.19300/j.2024.L21285
基于X线影像组学特征的预测模型对膝关节周围骨肿瘤的诊断价值
Value of a predictive model based on X-ray radiomic features for diagnosing bone tumors around the knee
摘要
Abstract
Objective To investigate the clinical application value of a predictive model constructed based on the radiomic features of digital X-ray images and combined with routine clinical information for distinguishing between benign and malignant nature of peripheral bone tumors of knee joint.Methods Preoperative X-ray images and clinical data of 433 patients with benign and malignant bone tumors around the knee joint confirmed by surgical pathology were retrospectively collected.According to the WHO bone tumor classification,patients were divided into benign group(303 cases)and malignant group(130 cases).Patients were randomly divided into training set(303 cases)and test set(130 cases)in a 7∶3 ratio.ITK-SNAP software was used to manually outline the region of interest(ROI)in the lesion area on the preoperative frontal and lateral knee X-ray images and extract radiomic features.The least absolute shrinkage and selection operator(LASSO)regression algorithm was utilized for feature selection.Decision tree(DT),random forest(RF),extreme gradient boosting(XGB),logistic regression(LR),support vector machine(SVM),and k-nearest neighbor(KNN)classifiers were used to construct radiomic models and combined prediction models integrating clinical information.The predictive efficacy of each model was assessed using the area under the curve(AUC)of the subject operating characteristic(ROC),and the DeLong test was used to compare the differences in predictive efficacy between the models.SHAP values were utilized to assess the importance of each feature included in the models for diagnostic outcomes.Results The erythrocyte sedimentation rate(ESR)of the malignant group was higher than that of the benign group,and the joint mobility was more restricted than that of the benign group(both P＜0.05).ESR and joint mobility were used as clinical features.Based on the six classifiers,the radiomic model(18 radiomic features)and the combined prediction model(16 radiomic features and two clinical features)were constructed.The diagnostic efficacy of all the radiomic and combined model built by the six classifiers were high(all AUC＞0.8),and the highest AUC value(0.905)observed for the XGB combined model.The results of DeLong test showed that the AUC values of the combined XGB,LR,and SVM models were higher than those of the corresponding radiomic models(all P＜0.05),indicating that the XGB combined model had the optimal performance.SHAP values indicated that the gray-level dependence matrix(GLDM)among the radiomic features provided significant predictive information for the model.Conclusion A combined XGB model based on knee X-ray radiomic features and clinical features can effectively distinguish benign and malignant bone tumors preoperatively.关键词
膝关节/骨肿瘤/数字化X线摄影/影像组学Key words
Knee/Bone tumor/Digital radiography/Radiomics分类
医药卫生引用本文复制引用
潘德润,刘仁懿,曾辉,陈卫国..基于X线影像组学特征的预测模型对膝关节周围骨肿瘤的诊断价值[J].国际医学放射学杂志,2024,47(4):441-446,6.基金项目
国家自然科学基金(82171929) （82171929）
广东省医学科研基金项目(B2021043) （B2021043）
