CT特征预测胸膜下临床ⅠA期周围型肺腺癌脏层胸膜侵犯的价值  

The value of CT features in predicting visceral pleural invasion in clinical stage ⅠA peripheral lung adenocarcinoma under the pleura

作　　者：望云 吕登 涂文婷 樊荣荣 范丽 萧毅 刘士远 Wang Yun;Lyu Deng;Tu Wenting;Fan Rongrong;Fan Li;Xiao Yi;Liu Shiyuan(Department of Radiology,Changzheng Hospital of Naval Medical University,Shanghai 200003,China)

机构地区：[1]海军军医大学长征医院放射诊断科,上海200003

出　　处：《中华放射学杂志》2022年第10期1103-1109,共7页Chinese Journal of Radiology

基　　金：国家重点研发计划(2022YFC2010000);国家自然科学基金(81930049,81871405);上海市青年科技英才扬帆计划(20YF1449000);上海市科技创新行动计划项目(19411951300)。

摘　　要：目的探讨CT特征预测胸膜下临床ⅠA期周围型肺腺癌脏层胸膜侵犯(VPI)的价值。方法回顾性分析2015年1月至2021年11月于海军军医大学长征医院诊断为胸膜下临床ⅠA期周围型肺腺癌274例患者的CT征象。按照6∶4的比例,将2015年1月至2019年8月收集的164例患者作为训练组,将2019年8月至2021年11月收集的110例患者作为验证组。定量测量肿瘤最大径、实性成分最大径、病灶与胸膜间最小距离,计算实性成分占比;并分析肿瘤的CT征象,如肿瘤与胸膜的关系分型、是否存在桥征、病灶的位置、密度类型、形状、边缘、边界等。采用单因素分析找出与VPI相关的变量,再进行多因素logistic回归分析,明确VPI的独立危险因素,建立二元logistic回归模型。在训练组和验证组中使用受试者操作特征曲线评估模型的预测效能。结果274例肺腺癌中有VPI 121例,无VPI 153例。训练组中有VPI 79例、无VPI 85例。单因素分析发现训练组中实性成分最大径、实性成分占比、密度类型、毛刺征、血管集束征、肿瘤与胸膜关系、桥征在有VPI与无VPI肺腺癌患者间差异有统计学意义(P<0.05)。多因素logistic回归分析发现训练组中肿瘤与胸膜关系[以Ⅰ型为参照,Ⅱ型(OR=6.662,95%CI 2.364~18.571,P<0.001),Ⅲ型(OR=34.488,95%CI 8.923~133.294,P<0.001)]及血管集束征(OR=4.257,95%CI 1.334~13.581,P=0.014)是VPI的独立危险因素。以0.504为训练组logistic回归模型的最佳截断值,其预测VPI的灵敏度为62.03%、特异度为89.41%,曲线下面积为0.826。该模型在验证组中以0.449为最佳截断值,其预测VPI的灵敏度为92.86%、特异度为47.06%,曲线下面积为0.713。结论CT特征中肿瘤与胸膜关系、血管集束征有助于鉴别胸膜下的临床ⅠA期周围型肺腺癌是否发生VPI。Objective To investigate the value of CT features in predicting visceral pleural invasion(VPI)in clinical stageⅠA peripheral lung adenocarcinoma under the pleura.Methods The CT signs of 274 patients with clinical stageⅠA peripheral lung adenocarcinoma under the pleura diagnosed in Changzheng Hospital of Naval Medical University from January 2015 to November 2021 were retrospectively analyzed.According to the ratio of 6∶4,164 patients collected from January 2015 to August 2019 were used as the training group,and 110 patients collected from August 2019 to November 2021 were used as the validation group.The maximum diameter of the tumor(T),the maximum diameter of the consolidation part(C),and the minimum distance between the lesion and the pleura(DLP)were quantitatively measured,and the proportion of the consolidation part was calculated(C/T ratio,CTR).The CT signs of the tumor were analyzed,such as the relationship between the tumor and the pleura classification,the presence of a bridge tag sign,the location of the lesion,density type,shape,margin,boundary and so on.Variables with significant difference in the univariate analysis were entered into multivariate logistic regression analysis to explore predictors for VPI,and a binary logistic regression model was established.The predictive performance of the model was analyzed by receiver operating characteristic curve in the training and validation group.Results There were 121 cases with VPI and 153 cases without VPI among the 274 patients with lung adenocarcinoma.There were 79 cases with VPI and 85 cases without VPI in the training group.Univariate analysis found that the maximum diameter of the consolidation part,CTR,density type,spiculation sign,vascular cluster sign,relationship of tumor and pleura and bridge tag sign between patients with VPI and those without VPI were significantly different in the training group(P<0.05).Multivariate logistic regression analysis found the relationship between tumor and pleura[taking typeⅠas reference,typeⅡ(OR=6.662,95

关 键 词：肺肿瘤 腺癌 体层摄影术 X线计算机 脏层胸膜侵犯 

分 类 号：R734.2[医药卫生—肿瘤] R730.44[医药卫生—临床医学]