双层探测器光谱CT定量参数联合常规CT特征列线图评估含高级别亚型成分肺浸润性非黏液腺癌的价值  

Value of nomogram based on dual-layer detector spectral CT quantitative parameters and conventional CT features for evaluating high-grade pattern of pulmonary invasive non-mucinous adenocarcinoma

作　　者：洪榕 平小夏[1] 胡粟[1] 熊星 于洋 胡春洪[1] Hong Rong;Ping Xiaoxia;Hu Su;Xiong Xing;Yu Yang;Hu Chunhong(Department of Radiology,the First Affiliated Hospital of Soochow University,Suzhou 215006,China)

机构地区：[1]苏州大学附属第一医院放射科,苏州215006

出　　处：《中华放射学杂志》2024年第2期187-193,共7页Chinese Journal of Radiology

基　　金：江苏省科教能力提升工程-江苏省重点学科建设项目(JSDW202242);苏州市姑苏卫生人才计划项目(GSWS2020003)。

摘　　要：目的探讨双层探测器光谱CT定量参数联合常规CT特征列线图评估含高级别亚型(HGP)成分肺浸润性非黏液腺癌的价值。方法该研究为病例对照研究。回顾性分析2022年2月至2023年5月苏州大学附属第一医院71例经手术切除且病理证实为肺浸润性非黏液腺癌患者的临床及影像学资料, 将其分为HGP组和非HGP(non-HGP)组。分析病灶的大小、形状、密度、内部征象、边缘、胸膜牵拉征等常规CT特征, 并测量动脉期(AP)及静脉期(VP)病灶的碘浓度(IC)、电子云密度(ED)、标准化碘浓度(NIC)等光谱CT定量参数。2组指标比较采用独立样本t检验、Mann-WhitneyU或χ^(2)检验。将单因素分析中差异有统计学意义的参数纳入多因素logistic回归分析, 筛选出预测含HGP成分肺浸润性非黏液腺癌的独立影响因素, 然后构建常规CT特征模型、光谱CT定量参数模型及联合模型, 并绘制列线图。采用受试者操作特征曲线下面积(AUC)评估各模型性能, AUC比较采用DeLong检验。以决策曲线(DCA)评估模型的临床净获益。结果 HGP组与non-HGP组在病灶密度、分叶征、毛刺征、ICAP、ICVP、NICAP、EDAP及EDVP差异均有统计学意义(P均<0.05)。多因素logistic回归分析表明, 实性结节(OR=15.452, 95%CI 4.246~56.235, P<0.001)、分叶征(OR=7.069, 95%CI 1.618~30.883, P=0.009)、EDAP(OR=1.183, 95%CI 1.064~1.315, P=0.002)和ICVP(OR=0.231, 95%CI 0.072~0.744, P=0.014)是预测含HGP成分肺浸润性非黏液腺癌的独立影响因素。常规CT特征模型、光谱CT定量参数模型及联合模型预测含HGP成分肺浸润性非黏液腺癌的AUC分别为0.835、0.890和0.915, 其中联合模型的AUC优于常规CT特征模型(Z=2.67, P=0.008)。DCA分析表明以联合模型构建的列线图较常规CT特征模型临床获益率更高。结论基于双层探测器光谱CT定量参数及常规CT特征的列线图预测含HGP成分肺浸润性非黏液腺癌有较好的效能, 可以作为术前无Objective To explore the value of nomogram based on dual-layer detector spectral CT quantitative parameters and conventional CT feature in evaluating high-grade pattern(HGP)of pulmonary invasive non-mucinous adenocarcinoma.Methods This study was a case-control study.A total of 71 patients with pathologically confirmed pulmonary invasive non-mucinous adenocarcinoma in the First Affiliated Hospital of Soochow University from February 2022 to May 2023 were retrospectively enrolled,which were divided into HGP and non-HGP groups according to pathological results.Conventional CT features were analyzed,including size,shape,density,internal signs,margins,and pleural retraction.The iodine concentration(IC),electron density(ED),and normalized iodine concentration(NIC)of the lesions in both the arterial phase(AP)and venous phase(VP)were measured.Differences between the two groups were analyzed using independent sample t-test,Mann-Whitney U test,orχ^(2) test.Multivariate logistic regression analysis was used to select the independent influencing factors of HGP in pulmonary invasive non-mucinous adenocarcinoma,and the conventional CT feature model,the spectral CT quantitative parameter model,and the combined model were constructed and expressed in a nomogram.The area under the curve(AUC)of receiver operating characteristic curve was used to assess the performance of each model,and was compared by DeLong test.Decision curves(DCA)was used to assess the clinical net benefit of the models.Results There were significant differences between HGP group and non-HGP group in terms of density,lobulation,spiculation,ICAP,ICVP,NICAP,EDAP and EDVP(all P<0.05).The multivariate logistic regression analysis showed that the solid nodule(OR=15.452,95%CI 4.246-56.235,P<0.001),lobulation(OR=7.069,95%CI 1.618-30.883,P=0.009),EDAP(OR=1.183,95%CI 1.064-1.315,P=0.002)and ICVP(OR=0.231,95%CI 0.072-0.744,P=0.014)were independent influencing factors for predicting HGP in pulmonary invasive non-mucinous adenocarcinoma.The AUC of the conventional CT feat

关 键 词：肺肿瘤 浸润性非黏液腺癌 体层摄影术 X线计算机 列线图 

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