基于增强CT影像组学列线图在膀胱尿路上皮癌肌层浸润中的预测价值  

Predictive value of enhanced CT radiomics nomogram in muscular invasion of bladder urothelial carcinoma

作　　者：张志雅 孟影 刘信信 岳凤辉 周欣冉 张玉文 朱广辉[1] ZHANG Zhiya;MENG Ying;LIU Xinxin;YUE Fenghui;ZHOU Xinran;ZHANG Yuwen;ZHU Guanghui(Department of Radiology,the First Affiliated Hospital of Bengbu Medical College,Bengbu 233004,China;Department of Radiology,Fuyang Hospital of Anhui Medical University,Fuyang 236000,China)

机构地区：[1]蚌埠医学院第一附属医院放射科,安徽蚌埠233004 [2]安徽医科大学附属阜阳医院放射科,安徽阜阳236000

出　　处：《分子影像学杂志》2023年第6期1028-1034,共7页Journal of Molecular Imaging

摘　　要：目的 探讨基于增强CT影像组学列线图在术前预测膀胱尿路上皮癌肌层浸润的价值。方法 回顾性分析2018年8月~2023年4月于蚌埠医学院第一附属医院确诊为膀胱尿路上皮癌患者175例。将所有病例按7:3随机分为训练组(n=122)与验证组(n=53)。对增强CT多期图像进行手动勾画病灶感兴趣区并提取影像组学特征,通过最小绝对收缩和选择算子降维,采用支持向量机分类器对提取的特征进行机器学习,筛选出最优影像组学特征并构建影像组学评分模型。通过单因素分析及多因素二元Logistic回归分析筛选出膀胱尿路上皮癌肌层浸润的独立预测因素,构建临床-CT征象模型。将影像组学模型和临床-CT征象模型联合,构建联合模型。绘制ROC曲线,计算曲线下面积(AUC)、敏感度及特异性评估不同模型的预测效能,将最佳模型可视化构建列线图。结果 联合模型的诊断效能最高(AUC=0.891),均高于影像组学模型(AUC=0.777)和临床-CT征象模型(AUC=0.829)。决策曲线分析及校正曲线证实了列线图有较高的预测性能。结论 增强CT影像组学列线图在术前预测膀胱尿路上皮癌肌层浸润方面具有较高价值。Objective To investigate the value of enhanced CT imaging nomogram in preoperative prediction of muscular infiltration in urinary tract carcinoma of bladder.Methods A retrospective analysis was performed on 175 patients diagnosed with bladder urothelial carcinoma from August 2018 to April 2023 in the First Affiliated Hospital of Bengbu Medical College.All cases were randomly divided into training group(n=122)and verification group(n=53)according to 7:3.The region of interest was manually defined and the image omics features were extracted from the multi-phase enhanced CT images.The dimensionality was reduced by minimum absolute contraction and selection operator,and machine learning was performed on the extracted features using support vector machine classifier to screen out the optimal image omics features and construct the image omics scoring model.The independent predictors of muscular infiltration of bladder urothelial carcinoma were screened by univariate analysis and multivariate binary logistic regression analysis,and the clinical-CT signs model was constructed.Combining the imaging omics model with the clinical-CT sign model,the combined model was constructed.The ROC curve is plotted,the area under the curve(AUC),sensitivity,and specificity were calculated to evaluate the predictive efficacy of different models,and then the best model was visualized to construct a nomogram.Results The diagnostic efficacy of the combined model was the highest(AUC=0.891),which was higher than that of the imaging model(AUC=0.777)and the clinical-CT sign model(AUC=0.829).Decision curve analysis and correction curve confirm that the nomogram has high predictive performance.Conclusion Enhanced CT image nomogram has a high value in predicting myoinfiltration of bladder urothelial carcinoma before operation.

关 键 词：膀胱癌 肌层浸润 影像组学 对比增强CT 

分 类 号：R737.14[医药卫生—肿瘤] R730.44[医药卫生—临床医学]