青岛大学学报（医学版）2023，Vol.59Issue(5)：693-697,5.DOI:10.11712/jms.2096-5532.2023.59.173
MRI列线图模型对软组织肉瘤病理分级预测价值
VALUE OF PREOPERATIVE NOMOGRAM MODEL BASED ON MRI FEATURES FOR PREDICTING THE PATHOLOGICAL GRADE OF SOFT TISSUE SARCOMA
摘要
Abstract
Objective To investigate the value of the preoperative magnetic resonance imaging(MRI)features-based no-mogram model for predicting the pathological grade of soft tissue sarcoma(STS).Methods Preoperative MRI data from 137 pa-tients with STS confirmed by postoperative pathology were retrospectively collected.According to the French Federation of Cancer Centers Histologic Grading System,82 patients were defined as low-grade STS(grades Ⅰ-Ⅱ),and 55 patients were defined as high-grade STS(grade Ⅲ).Univariate and multivariate Logistic regression analyses were applied to screen out the predictors for the pathological grade of STS.The MRI features-based predictive nomogram model was established based on the predictors.The 10-fold cross validation was applied to evaluate the model performance,and the median area under the receiver operating characte-ristic curve(AUC)and median accuracy were used to evaluate the prediction efficiency of the model.Results According to the result of univariate and multivariate Logistic regression analyses,N-stage,depth,heterogeneous signal intensity at T2WI,and pe-ritumoral enhancement were identified as predictors for the pathological grade of STS.The predictive nomogram model showed the median AUC value of 0.898 and median accuracy of 82.1％.Conclusion The preoperative MRI-features-based nomogram model can predict the pathological grade of STS effectively.关键词
磁共振成像/软组织肿瘤/肉瘤/列线图/病理学,临床Key words
magnetic resonance imaging/soft tissue neoplasms/sarcoma/nomograms/pathology,clinical分类
医药卫生引用本文复制引用
梁皓昱,王鹤翔,侯峰,王童语,李琪媛,高传平..MRI列线图模型对软组织肉瘤病理分级预测价值[J].青岛大学学报（医学版）,2023,59(5):693-697,5.基金项目
山东省自然科学基金资助项目(ZR2021MH159) （ZR2021MH159）
