磨玻璃结节早期贴壁生长为主型浸润性肺腺癌与其他病理亚型的CT特征分析  

Analysis of CT features of lepidic predominant subtype and other pathological subtypes in early-stage invasive lung adenocarcinoma appearing as ground-glass nodule

作　　者：张鹏举 李天然[2] 陶雪敏 金鑫[1] 赵绍宏[1] Zhang Pengju;Li Tianran;Tao Xuemin;Jin Xin;Zhao Shaohong(Department of Radiology,First Medical Center of PLA General Hospital,Beijing 100853,China;Department of Radiology,Fourth Medical Center of PLA General Hospital,Beijing 100048,China)

机构地区：[1]解放军总医院第一医学中心放射诊断科,北京100853 [2]解放军总医院第四医学中心放射诊断科,北京100048

出　　处：《中华放射学杂志》2021年第7期739-744,共6页Chinese Journal of Radiology

基　　金：国家重点研发计划(2017YFC1308703);军队保健专项课题(17BJZ33)。

摘　　要：目的探讨磨玻璃结节早期(T1N0M0)浸润性肺腺癌中贴壁为主型(LPA)与其他病理亚型的CT特征,为临床手术决策提供影像帮助。方法回顾性分析解放军总医院第一医学中心2019年1至12月经手术病理证实的表现为纯磨玻璃结节和实性肿瘤比(CTR)<0.5的混合磨玻璃结节的早期浸润性肺腺癌患者的临床和CT资料。按照病理亚型分为LPA组和非LPA(n-LPA)组。采用单因素分析对2组的临床资料及CT特征进行比较,对差异有统计学意义的指标进行多因素分析,采用逆向消元法,生成多因素模型。利用ROC曲线下的面积(AUC)评价该模型对LPA和n-LPA的鉴别效能。结果共纳入589例患者630个GGN,其中LPA组367个GGN,n-LPA组263个GGN。在单因素分析中,LPA组直径[(14±5)mm]、CT值[(-566±98)HU]、CTR[13.9%(0,27.3%)]小于n-LPA组[分别为(15±5)mm、(-499±111)HU、27.8%(7.7%,40%)],差异具有统计学意义(P<0.05)。n-LPA组出现mGGN、深分叶征、毛刺、血管改变、支气管改变以及清晰瘤肺界面的频率明显高于LPA组(P<0.05)。多因素分析显示平均CT值、CTR、深分叶征、毛刺、血管改变、支气管改变是预测n-LPA的独立预测因素(P<0.05),并将其纳入logistic模型。以logistic回归模型的最佳截断值3.958预测LPA与n-LPA的灵敏度为76.4%、特异度为78.7%,曲线下面积为0.840。结论CT特征可以有效帮助鉴别诊断表现为GGN的早期LPA与其他病理亚型。Objective To investigate the CT features of lepidic predominant adenocarcinoma(LPA)and other pathological subtypes in early-stage invasive pulmonary adenocarcinoma appearing as ground glass nodule(GGN);and to provide imaging-derived information for the clinical management of GGN.Methods The clinical and CT data of patients with early-stage invasive pulmonary adenocarcinoma in the First Medical Center of PLA General Hospital from January to December 2019 were retrospectively reviewed.All patients presented with pure GGNs or mixed GGNs with a consolidation-to-tumor ratio(CTR)<0.5,with the pathological results confirmed by surgery.GGNs were divided into LPA and non-LPA(n-LPA)groups according to pathological subtypes.Univariate analysis was used to compare the clinical data and CT characteristics between the two groups.The multivariate analysis was performed for the indicators with statistically significant differences and a multivariate model was generated using the reverse elimination method.The area under the ROC curve(AUC)was used to evaluate the discriminatory power of this model for differentiation of LPA from n-LPA.Results A total of 630 GGNs from 589 patients were analyzed,with 367 GGNs in LPA group and 263 GGNs in n-LPA group.In univariate analysis,the diameter[(14±5)mm],CT value[(-566±98)HU],and CTR[13.9%(0,27.3%)]in the LPA group were significantly smaller than those in the n-LPA group[(15±5)mm,(-499±111)HU,27.8%(7.7%,40%)],respectively,P<0.05].The frequency of mGGN,deep lobulation sign,burrs,vascular changes,bronchial changes,and clear tumor-lung interface were significantly higher in the n-LPA group than those in the LPA group(P<0.05).Multivariate analysis results showed that mean CT values,CTR,deep lobulation sign,burr,vascular changes,and bronchial changes were independent predictors for predicting n-LPA(P<0.05),which were included in the logistic model.Using the optimal cutoff value of 3.958,the logistic regression model for differentiate LPA from n-LPA had a sensitivity of 76.4%,a specificity of

关 键 词：肺肿瘤 磨玻璃密度结节 体层摄影术 X线计算机 病理学 

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