瘤内和瘤周动态对比增强MRI影像组学模型预测宫颈鳞癌同步放化疗反应  

Intra-and peri-tumoral radiomics model for predicting the response to concurrent chemoradiotherapy in cervical squamous cell carcinoma based on dynamic contrast-enhanced MRI

作　　者：苏亚英 赵丹 庞智英 杨飞[3] 崔书君[3] SU Yaying;ZHAO Dan;PANG Zhiying;YANG Fei;CUI Shujun(Department of Nuclear Medicine,the First Affiliated Hospital of Hebei North University,Zhangjiakou,Hebei Province 075000,China;Graduate School,Hebei North University,Zhangjiakou,Hebei Province O75000,China;Department of Medical Imaging,the First Affiliated Hospital of Hebei North University,Zhangjiakou,Hebei Province 075000,China)

机构地区：[1]河北北方学院附属第一医院核医学科,河北张家口075000 [2]河北北方学院研究生院,河北张家口075000 [3]河北北方学院附属第一医院医学影像部,河北张家口075000

出　　处：《实用放射学杂志》2024年第3期411-416,共6页Journal of Practical Radiology

摘　　要：目的探讨瘤内和瘤周影像组学特征与宫颈鳞癌同步放化疗(CCRT)反应的相关性及2D和3D影像组学模型预测效能的差异.方法回顾性分析132例患者的影像资料并随机分为训练集(n=92)和验证集(n=40),基于动态对比增强磁共振成像(DCE-MRI)提取影像组学特征,使用相关性分析和最小绝对收缩和选择算子(LASSO)算法进行降维筛选,计算影像组学评分并建立logistic模型.采用受试者工作特征(ROC)曲线、Bootstrap内部验证和Brier分数评价模型的区分度和校准度,以综合判别改善指数(IDI)评估3D模型较2D模型预测效能的改善情况.结果训练集中,ROC曲线显示模型(2D瘤内、3D瘤内、3D瘤周、3D联合)曲线下面积(AUC)的范围为0.774~0.893,Bootstrap内部验证显示AUC分别为0.772、0.860、0.847和0.888,而在验证集中AUC分别为0.757、0.849、0.824和0.887,Brier分数表明模型均具有良好的校准度.IDI值在训练集和验证集中分别为0.155和0.179,差异有统计学意义(P<0.05).结论基于肿瘤容积进行影像组学分析可全面挖掘肿瘤异质性,瘤内-瘤周影像组学联合模型显示出最佳预测效能,对辅助临床医师制订个性化诊疗方案具有重要意义.Objective To investigate the correlation between intra-and peri-tumoral radiomics features and the response to con-current chemoradiotherapy(CCRT)in cervical squamous cell carcinoma,and to explore the difference of predictive performance between 2D and 3D radiomics models.Methods The imaging data of 132 patients were analyzed retrospectively and randomly divided into training set(n=92)and validation set(n=40).Radiomics features were extracted based on the dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI),the correlation analysis and least absolute shrinkage and selection operator(LASSO)algorithm were used for dimensionality reduction and screening,then the radiomics score was calculated and the logistic model was constructed.The receiver operating characteristic(ROC)curve,internal validation of Bootstrap and Brier score were used to evaluate the discrimina-tion and calibration of the model,and the improvement in predictive performance of 3D model compared with 2D model was evaluated by the integrated discrimination improvement(IDI).Results In the training set,the ROC curve showed that the area under the curve(AUC)of the models(2D-intratumoral,3D-intratumoral,3D-peritumoral,3D-combined)ranged from 0.774 to 0.893.The internal validation of Bootstrap showed the AUC were 0.772,0.860,0.847 and 0.888,respectively,while in the validation set,the AUC were 0.757,0.849,0.824 and 0.887,respectively.The Brier scores indicated that the models were well calibrated.In the training set and the validation set,the IDI values were 0.155 and 0.179,respectively,and the differences were statistically significant(P<0.05).Conclusion The radiomics analysis based on the tumor volume can fully explore the tumor heterogeneity.The intra-and peri-tumoral radiomics combined model shows the best predictive performance,which is important to assist clinicians in developing individualized therapies.

关 键 词：影像组学 宫颈癌 同步放化疗 机器学习 

分 类 号：R445.2[医药卫生—影像医学与核医学] R737.33[医药卫生—诊断学] R730.5[医药卫生—临床医学]