基于CT影像组学的列线图术前预测胃癌淋巴结转移的价值  

Value of preoperative prediction of lymph node metastasis in gastric cancer based on CT radiomics nomogram

作　　者：王科佳 汪国祥[1] 陈基明[1] 张成孟 方世武 谢伶俐 刘奇峰 WANG Kejia;WANG Guoxiang;CHEN Jiming;ZHANG Chengmeng;FANG Shiwu;XIE Lingli;LIU Qifeng(Department of Radiology,Yijishan Hospital of Wannan Medical College,Wuhu 241001,China)

机构地区：[1]皖南医学院弋矶山医院放射科,安徽芜湖241001

出　　处：《中国中西医结合影像学杂志》2024年第3期255-261,共7页Chinese Imaging Journal of Integrated Traditional and Western Medicine

摘　　要：目的:探讨CT影像组学列线图术前预测胃癌淋巴结转移的价值。方法:回顾性收集208例经手术病理证实为胃癌患者的临床和影像资料,按7∶3的比例随机分为训练集147例和验证集61例,2个数据集再根据有无淋巴结转移进行分组。分别在CT平扫、动脉期、静脉期、延迟期图像上逐层勾画病灶ROI,经三维融合后导入FAE v.3.7.7z软件提取每个病灶的纹理特征。采用最小冗余最大相关(mRMR)和最小绝对值收缩和选择算子(LASSO)算法分别对上述单一序列及联合序列(平扫+动脉期+静脉期+延迟期)的组学特征进行筛选,建立相应影像组学模型并计算影像组学评分。通过多因素logostic回归分析筛选出独立预测因子,构建临床和影像组学的综合模型,绘制列线图,分析其预测概率。分别采用ROC曲线、Hosmer-Lemeshow检验及决策曲线分析评估模型的预测效能、校准度和临床应用价值。结果:在训练集中CT平扫、动脉期、静脉期、延迟期及联合序列影像组学模型预测胃癌淋巴结转移的AUC分别为0.80、0.76、0.81、0.76、0.79,以静脉期模型预测效能最高。临床模型在训练集和验证集中的AUC分别为0.79和0.81,而综合模型为0.86和0.82,明显优于临床模型,静脉期影像组学评分为独立预测因子(OR=2.45,P<0.05)。决策曲线分析显示,风险阈值为26%~88%时,综合模型的净收益高于临床模型和静脉期影像组学模型。结论:CT报告淋巴结转移、肿瘤厚度、静脉期影像组学评分是胃癌淋巴结转移的独立预测因子,三者联合诊断效能更高;基于静脉期CT增强扫描影像组学特征建立的列线图对胃癌的淋巴结转移有较高的预测效能。Objective:To explore the value of preoperative prediction of lymph node metastasis(LNM)in gastric cancer based on CT radiomics nomogram.Methods:Clinical and imaging data of 208 patients with gastric cancer were retrospectively collected.All patients were divided into a training cohort(147 cases)and a validation cohort(61 cases)at a 7∶3 ratio,and the patients in each cohorts were divided into the LNM and non-LNM groups.The lesions’ROIs were manually delineated on plain scan,arterial phase,venous phase and delayed phase images using ITK-SNAP software,and the lesions’VOIs were obtained.Then,the texture features of VOIs were extracted using FAE v.3.7.7z software.The minimal-Redundancy-Maximal-Relevance(mRMR)and LASSO methods were used to screen the radiomics features of plain scan,arterial phase,venous phase,delayed phase and the combined multiple phases for predicting LNM in gastric cancer,and the radiomics models were established and the the rad-scores were calculated.Multivariate logistic regression analysis was used for the independent predictors.The combined clinical and radiomics model was constructed,and the nomogram was drawn and used to analyze the prediction probability.The predictive efficiency,calibration and clinical application value of these models were evaluated using ROC curve,Hosmer-Lemeshow test and decision curve analysis(DCA).Results:The AUCs of the radiomics models of plain scan,arterial phase,venous phase,delayed phase and the combined multiple phases in prediction LNM in the training cohort were 0.80,0.76,0.81,0.76 and 0.79,respectively,with the venous phase radiomics model having the highest predictive efficiency.The AUCs of clinical model in the training cohort and validation cohort were 0.79 and 0.81,and those of the combined clinical and radiomics model were 0.86 and 0.82,which were significantly superior to clinical model,and the venous rad-score was an independent risk factor(OR=2.45,P<0.05).DCA showed the net return of the combined clinical and radiomics model was higher than that

关 键 词：胃肿瘤 淋巴结 列线图 影像组学 体层摄影术 X线计算机 

分 类 号：R735.2[医药卫生—肿瘤] R730.44[医药卫生—临床医学]