期刊文献+

基于^(18)F-FDG PET/CT影像组学模型预测局部晚期宫颈癌的放疗敏感性 被引量:5

Prediction of radiosensitivity in locally advanced cervical cancer based on^(18)F⁃FDG PET/CT radiomics model
下载PDF
导出
摘要 目的构建基于^(18)F-FDG PET/CT图像的影像组学模型,并分析其预测局部晚期宫颈癌(locally advanced cervical cancer,LACC)放疗敏感性的效能。方法收集2018年1月至2022年12月于广西医科大学附属肿瘤医院妇科行根治性放疗的宫颈癌患者的临床资料,按8:2随机划分为训练集(169例)和测试集(43例),采集治疗前的PET/CT图像,手动勾画感兴趣区,提取影像组学特征。将特征正则化,采用组内相关系数、Pearson相关性分析、最小绝对收缩和选择算子回归进行组学特征筛选,获得组学特征及其系数加权并计算每个患者的Radscore值,比较放疗敏感组和抵抗组间Radscore值的差异。分别构建PET、CT及PE/CT联合的Logistic regression(LR)机器学习模型,通过受试者工作特征曲线(receiver operating characteristic,ROC)、校准曲线、决策曲线(decision curve analysis,DCA)分析对模型进行评估。结果本研究共纳入212例LACC患者,抵抗组的Radscore值显著高于敏感组,差异有统计学意义(P<0.001)。在训练集和测试集上,PET/CT联合模型的ROC曲线下面积分别为0.900(95%CI:0.832~0.968)、0.754(95%CI:0.569~0.939),预测效能均优于单一的PET或CT模型。DCA曲线显示,与不使用预测模型的情况相比,基于PET/CT的影像组学预测模型表现出显著的干预获益,在放疗前预测LACC敏感性方面具有较好的临床效益。绘制校准曲线显示,3种模型的预测值与实际观察值之间的一致性均良好。结论基于PET/CT的影像组学模型对LACC放疗敏感性具有良好的预测价值。 Objective To construct a radiomics model based on ^(18)F⁃FDG PET/CT images,and analyze its efficacy in predicting radio⁃therapy sensitivity of locally advanced cervical cancer(LACC).Methods The clinical data of cervical cancer patients who underwent radical radiotherapy in the Department of Gynecologic,Guangxi Medical University Cancer Hospital from January 2018 to December 2022 were collected and randomly divided into a training set(169 patients)and a test set(43 patients)in a ratio of 8:2.Pre⁃treatment ^(18)F⁃FDGPET/CT images of patients were collected,the areas of interest were manually delineated and the radiomics features were extracted.The features were regularized and screened by the intra⁃group correlation coefficient,Pearson correlation analysis and the least absolute shrinkage and the selection operator regression.The radiomics features and their weighting efficients obtained and Radscore values were calculated for each patient.The differences in Radscore between radiosensitive and radioresistant groups were compared.The Logistic regression machine learning model for PET,CT and combined PE/CT were constructed,respectively,and the model efficacy was evaluated based on the receive operating characteristic curve(ROC),calibration curve,and decision curve analysis.Results A total of 212 LACC patients were included in this study,and the Radscores of the radioresistant group were significantly higher than those of the radiosensitive group,with a statistically significant difference(P<0.001).In both the training and test sets,the area under the ROC curve of the combined PET/CT model was 0.900(95%CI:0.832-0.968)and 0.754(95%CI:0.569-0.939),respectively,and the predictive efficiency of the combined PET/CT model was better than that of the individual PET or CTmodel.TheDCAcurveshowedthatthe PET/CT⁃based radiomics models showed significant intervention benefits and had better clinical benefits in predicting LACC sensitivity before radiotherapy compared to those without the prediction model.The calibration curve showed that the predicted values of the three models were in good agreement with the observed values.Conclusions The PET/CT⁃based radiomics models has a good predictive value for the sensitivity of LACC to radiotherapy.
作者 陈小霞 蓝颖 吴能娴 宋红林 CHEN Xiaoxia;LAN Ying;WU Nengxian;SONG Honglin(Department of Gynecologic,Guangxi Medical University Cancer Hospital,Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor(Guangxi Medical University),Ministry of Education,Nanning 530021,China)
出处 《中国癌症防治杂志》 CAS 2023年第4期417-423,共7页 CHINESE JOURNAL OF ONCOLOGY PREVENTION AND TREATMENT
基金 广西重点研发计划项目(桂科AB20159017) 广西研究生教育创新计划项目(YCSW2023212)。
关键词 宫颈癌 局部晚期 放疗敏感性 PET/CT影像组学 机器学习模型 Cervical cancer Locally advanced Radiosensitivity PET/CT radiomics Machine learning model
  • 引文网络
  • 相关文献

参考文献2

二级参考文献30

共引文献4

同被引文献64

引证文献5

;
使用帮助 返回顶部