基于T2WI和DWI的磁共振影像组学在术前预测直肠癌壁外血管侵犯的价值研究

The value of radiomics based on T2WI and DWI of MRI in preoperative prediction of extramural vascular invasion in rectal cancer

目的:探讨基于磁共振(magnetic resonance imaging,MRI)T2加权成像(T2-weighted imaging,T2WI)和弥散加权成像(diffusion-weighted imaging,DWI)的影像组学,在术前预测直肠癌壁外血管侵犯(extramural vascular invasion,EMVI)的诊断效能。方法:回顾性收集2010年1月至2023年6月经术后病理证实为直肠腺癌且术前行直肠MRI扫描的患者168例,按7∶3随机分为训练集和验证集。提取T2WI、DWI的影像组学特征,采用最大相关最小冗余(the maximum relevance minimum redundancy,mRMR)和十倍交叉验证的最小绝对收缩与选择算子(the least absolute shrinkage and selection operator,LASSO)回归分析降维并选择影像组学特征,计算每例患者的影像组学总评分(Radscore),使用Radscore建立影像组学模型。在训练集中,研究纳入了3个临床特征[年龄、性别、术前癌胚抗原(carcinoembryonic antigen,CEA)]和6个磁共振影像学特征[ADC值、浸润深度、肿瘤长度、肿瘤部位、T分期、MRI壁外血管侵犯(magnetic resonance imaging-defined EMVI,mrEMVI)评分],通过单因素、多因素Logistic回归分析建立临床模型。联合Radscore和临床模型的独立危险因素,建立临床-影像组学模型(联合模型)。采用受试者操作特征(receiver operating characteristic,ROC)曲线评估各模型的诊断效能,通过DeLong检验比较不同模型的效能差异,采用校准曲线评估列线图术前预测结果与术后病理真实状况的拟合度,运用决策曲线分析(decision curve analysis,DCA)评价3种模型的临床应用价值。结果:联合模型、临床模型、影像组学模型ROC曲线在训练集和验证集中AUC分别为0.926、0.888、0.756和0.917、0.896、0.782,联合模型的诊断效能最佳。Delong检验显示,在训练集和验证集中,联合模型诊断效能高于影像组学模型(P<0.05);在训练集中,联合模型的诊断效能高于临床模型(P<0.05),但在验证集中差异无统计学意义(P>0.05)。校准曲线显示列线图术前预测结果与术后病理结果一致性良好(P<0.05)。DCA结果表明,当风险阈值概率在0.24~0.77时,联合模型在临床上的获益高于临床模型和影像组学模型。结论:基于T2WI和DWI的MRI影像组学模型术前预测直肠癌EMVI有较高的诊断效能,联合临床模型中独立危险因素构建的临床-影像组学MRI模型(联合模型)进一步提高了诊断效能。

Objective To investigate the diagnostic performance of radiomics based on T2-weighted imaging(T2WI) and diffusion-weighted imaging(DWI)of MRI for preoperative prediction of extramural vascular invasion(EMVI)in rectal cancer.Methods A total of 168 patients with pathology-confirmed rectal adenocarcinoma were enrolled during January 2010 to June 2023.The patients underwent preoperative rectal MRI scans,and they were randomly divided into training set and validation set at a 7∶3 ratio.Radiomic features from T2WI and DWI were extracted and selected by dimensionality reduction using the maximum relevance minimum redundancy(mRMR)method and the least absolute shrinkage and selection operator(LASSO)regression analysis with ten-fold cross-validation.The radiomic total score(Radscore)for each patient was calculated to make radiomics model.The training set enrolled three clinical features[gender,age and preoperative level of carcinoembryonic antigen(CEA)]and six magnetic resonance imaging features[ADC value,depth of infiltration,tumor length,tumor location,T staging and magnetic resonance imaging-defined extramural vascular invasion(mrEMVI)].The clinical model was established through univariable and multivariable logistic regression analysis based on above clinical and imaging features,and the clinical-radiomics model(combined model)was established with Radscore and independent risk factors from the clinical model.The diagnostic efficacy of each model was assessed using receiver operating characteristic(ROC)curve.The differences in performance among the models were compared using the DeLong test.The Calibration curves were employed to evaluate the consistence between the preoperative predictive results obtained from the nomogram and the postoperative pathological results.Additionally,decision curve analysis(DCA)was applied to evaluate the clinical utility of the three models.Results The area under the curve(AUC)of the ROC curve for the combined model,clinical model,and radiomics model in the training were 0.926,0.888,0.756,and were 0.917,0.896,0.782 in validation sets,respectively.The DeLong test showed that the diagnostic efficacy of combined model was higher than that of radiomics model in both training and validation sets(P<0.05).The diagnostic efficacy of combined model was better than that of clinical model in the training set(P<0.05).The calibration curve showed the consistency between the preoperative predictive results obtained from the nomogram and the postoperative pathological findings was satisfied.The DCA showed that the risk threshold probabilities between 0.24 and 0.77,the clinical benefit of combined model was higher than those of clinical model and the radiomics model.Conclusions For preoperative prediction of EMVI in rectal cancer,the radiomics model based on T2WI and DWI of MRI has a satisfied diagnostic efficiency,while the clinical-radiomics model(combined model)may further enhance the diagnostic efficiency.