基于CT影像组学鉴别伴微乳头及实体型结构浸润性肺腺癌

with micropapillary or solid structure

目的探讨基于影像组学特征鉴别伴微乳头及实体型浸润性肺腺癌的价值。方法回顾性分析2016年4月—2019年8月南京医科大学第一附属医院及南京医科大学附属淮安第一医院收治的手术切除且病理证实为浸润性肺腺癌患者的临床资料,将数据集随机以7∶3的比例分为训练集[包括微乳头/实体型阳性组(阳性组)和微乳头/实体型阴性组(阴性组)]和测试集(包括阳性组和阴性组)。由两位医师分别在术前高分辨率CT薄层图上绘制感兴趣区并提取影像组学特征。在数据分析前通过组内相关系数评估观察者间一致性,以过采样技术均衡训练集数据,均值归一化处理后,通过最小绝对收缩与选择算子算法对组学特征进一步筛选及建模并进行5折交叉验证。在训练集及测试集分别绘制受试者工作特征(receiver operating characteristic,ROC)曲线以评估模型诊断效能。结果共纳入340例患者,其中男178例、女162例,平均年龄(60.31±6.69)岁,均为实性病变。训练集238例患者,其中阳性组120例、阴性组118例;测试集102例患者,其中阳性组52例、阴性组50例。组学模型共含107个特征,最终2个特征参与建模,即Original_glszm_SizeZoneNonUniformityNormalized及Original_shape_SurfaceVolumeRatio。构建的组学模型训练集和测试集的ROC曲线下面积分别为0.863[95%CI(0.815,0.912)]、0.857[95%CI(0.783,0.932)];敏感性分别为91.7%、73.7%,特异性分别为78.8%、84.0%,准确性分别为85.3%、78.4%。结论影像组学特征在有或无微乳头及实体型结构浸润性肺腺癌中存在差异,组学评估模型具有较好的诊断价值。

Objective To investigate the radiomics features to distinguish invasive lung adenocarcinoma with micropapillary or solid structure.Methods A retrospective analysis was conducted on patients who received surgeries and pathologically confirmed invasive lung adenocarcinoma in our hospital from April 2016 to August 2019.The dataset was randomly divided into a training set[including a micropapillary/solid structure positive group(positive group)and a micropapillary/solid structure negative group(negative group)]and a testing set(including a positive group and a negative group)with a ratio of 7∶3.Two radiologists drew regions of interest on preoperative high-resolution CT images to extract radiomics features.Before analysis,the intraclass correlation coefficient was used to determine the stable features,and the training set data were balanced using synthetic minority oversampling technique.After mean normalization processing,further radiomics features selection was conducted using the least absolute shrinkage and selection operator algorithm,and a 5-fold cross validation was performed.Receiver operating characteristic(ROC)curves were depicted on the training and testing sets to evaluate the diagnostic performance of the radiomics model.Results A total of 340 patients were enrolled,including 178 males and 162 females with an average age of 60.31±6.69 years.There were 238 patients in the training set,including 120 patients in the positive group and 118 patients in the negative group.There were 102 patients in the testing set,including 52 patients in the positive group and 50 patients in the negative group.The radiomics model contained 107 features,with the final 2 features selected for the radiomics model,that is,Original_glszm_SizeZoneNonUniformityNormalized and Original_shape_SurfaceVolumeRatio.The areas under the ROC curve of the training and the testing sets of the radiomics model were 0.863(95%CI 0.815-0.912)and 0.857(95%CI 0.783-0.932),respectively.The sensitivity was 91.7%and 73.7%,the specificity was 78.8%and 84.0%,and the accuracy was 85.3%and 78.4%,respectively.Conclusion There are differences in radiomics features between invasive pulmonary adenocarcinoma with or without micropapillary and solid structures,and the radiomics model is demonstrated to be with good diagnostic value.