摘要
目的:探讨CT特征预测肺纯磨玻璃结节(pGGN)在2021年组织学新分类中浸润性和浸润程度的价值。方法:回顾性分析山东第一医科大学附属省立医院2018年12月至2021年1月经手术病理证实的pGGN患者281例(304个病灶)。根据病理类型分为前驱病变组(包括不典型腺瘤样增生、原位腺癌)129个、微浸润组(微浸润性腺癌)116个、浸润组(浸润性腺癌)59个。记录临床资料(年龄、性别、吸烟史、肿瘤家族史)及CT参数[形态、边界、分叶、毛刺、空泡征、支气管异常征、内部血管征、胸膜牵拉征、最长径、最短径、平扫CT值、增强动脉期CT值、静脉期CT值、强化程度ΔCT A-N(CT值动脉期-CT值平扫)、ΔCT V-N(CT值静脉期-CT值平扫)]。采用单因素方差分析、Kruskal-Wallis H检验、χ2检验比较3组差异。运用二元logistic回归分析评估pGGN浸润性[前驱病变与浸润性病变(包括微浸润性腺癌和浸润性腺癌)]及浸润程度(微浸润性腺癌和浸润性腺癌)的独立预测因素,并对各参数进行受试者操作特征(ROC)曲线分析。结果:前驱病变组、微浸润组、浸润组之间年龄、pGGN形态、分叶、空泡征、支气管异常征、内部血管征、胸膜牵拉征、最长径、最短径、平扫CT值、动脉期CT值、静脉期CT值差异均有统计学意义(P<0.05)。二元logistic回归分析显示,空泡征(OR=2.832,95%CI 1.363~5.887,P=0.005)、内部血管征(OR=3.021,95%CI 1.909~4.779,P<0.001)和平扫CT值(OR=1.003,95%CI 1.001~1.006,P=0.019)是pGGN浸润性的独立危险因素;分叶(OR=5.739,95%CI 2.735~12.042,P<0.001)、内部血管征(OR=1.968,95%CI 1.128~3.433,P=0.017)和平扫CT值(OR=1.004,95%CI 1.001~1.008,P=0.012)是pGGN浸润程度的独立危险因素。ROC曲线分析结果表明,内部血管征区分pGGN前驱病变与浸润性病变的效能最高,曲线下面积(AUC)为0.757,灵敏度为50.3%,特异度为89.8%;分叶区分pGGN微浸润性腺癌与浸润性腺癌的效能最高(AUC=0.702),灵敏度为61.0%,特异度为79.3%。结论:CT特征预测肺pGGN在2021年组织学新分类中浸润性和浸润程度具有一定价值,内部血管征对pGGN浸润性的预测效能更高;分叶对pGGN浸润程度的预测效能更高。
Objective To investigate the value of CT features in predicting the invasion and degree of invasiveness of lung pure ground-glass nodules(pGGN)in the new histological classification in 2021.Methods A total of 281 patients(304 lesions)with pGGN confirmed by surgical pathology from December 2018 to January 2021 in Shandong Provincial Hospital Affiliated to Shandong First Medical University were retrospectively analyzed.According to the pathological types,the patients were divided into prodromal lesion group[atypical adenomatous hyperplasia(AAH)and adenocarcinoma in situ(AIS),129 cases],minimally invasive group[minimally invasive adenocarcinoma(MIA),116 cases]and invasive group[invasive adenocarcinoma(IAC),59 cases].Clinical data(age,gender,smoking history,family history of cancer),and CT parameters[shape,boundary,lobulation,burr,vacuolar sign,bronchial abnormality sign,internal vessel sign,pleural traction sign,longest diameter,shortest diameter,unenhanced CT value,contrast-enhanced CT value in arterial phase,contrast-enhanced CT values in venous phase,the degree of enhancement(ΔCTA-N,ΔCTV-N)]were recorded and measured.The ANOVA,Kruskal-Wallis H andχ2 test were used to compare the differences among the three groups.Binary logistic regression analysis was used to evaluate the independent risk factors of nodular invasion[prodromal lesion and invasive lesion(MIA and IAC)]and the degree of nodular invasion(MIA and IAC),and receiver operating characteristic(ROC)curve analysis was performed for each parameter.Results There were statistically significant differences in age,pGGN morphology,lobulation,vacuolar sign,bronchial abnormality sign,internal vascular sign,pleural traction sign,longest diameter,shortest diameter,unenhanced CT value,contrast-enhanced CT value in arterial phase,contrast-enhanced CT value in venous phase among the precursor lesion group,minimally invasive group and invasive group(P<0.05).Binary logistic regression analysis showed that vacuole sign(OR=2.832,95%CI 1.363-5.887,P=0.005),internal vascular sign(OR=3.021,95%CI 1.909-4.779,P<0.001)and unenhanced CT value(OR=1.003,95%CI 1.001-1.006,P=0.019)were independent risk factors for invasion.Lobulation(OR=5.739,95%CI 2.735-12.042,P<0.001),internal vascular sign(OR=1.968,95%CI 1.128-3.433,P=0.017)and unenhanced CT value(OR=1.004,95%CI 1.001-1.008,P=0.012)were independent risk factors for the degree of invasiveness.ROC curve analysis showed that the efficiency of internal vascular sign was the highest in distinguishing precursor lesion and the invasive,the area under the curve(AUC)was 0.757,the sensitivity was 50.3%,the specificity was 89.8%.The efficiency of lobulation was the highest in distinguishing MIA and IAC(AUC=0.702),with a sensitivity of 61.0%and specificity of 79.3%.Conclusions CT features are of certain value in predicting the invasion and degree of invasiveness of lung pGGN in the new histological classification in 2021,and internal vascular sign is more effective in predicting the invasion of lung pGGN.Lobulation can predict the degree of invasiveness of pGGN better.
作者
高琳
张晶
顾慧
康冰
于鑫鑫
张帅
高艳
蔡凡凡
王箬芃
王锡明
Gao Lin;Zhang Jing;Gu Hui;Kang Bing;Yu Xinxin;Zhang Shuai;Gao Yan;Cai Fanfan;Wang Ruopeng;Wang Ximing(Department of Radiology,Shandong Provincial Hospital Affiliated to Shandong First Medical University,Jinan 250021,China;Department of Ultrasonic Diagnosis,Breast Cancer Center,Taian City Central Hospital Affiliated to Qingdao University,Taian 271000,China)
出处
《中华放射学杂志》
CAS
CSCD
北大核心
2022年第6期616-622,共7页
Chinese Journal of Radiology
基金
国家自然科学基金(81871354,81571672,81901740)
山东省泰山学者专项经费
山东第一医科大学学术提升计划(2019QL023)。