联合双能量CT定量参数和形态学特征在鉴别良恶性肺实性结节的应用价值  

Application value of combined dual-energy computed tomography quantitative parameters and morphological features in differentiating malignant from benign lesions in solid pulmonary nodules

作　　者：林礼波 何长久[1] 刘杰克 李勇[1] 解超莲 周鹏[1] LIN Li-bo;HE Chang-Jiu;LIU Jie-ke(Department of Radiology,Sichuan Clinical Research Center for Cancer,Sichuan Cancer Hospital&Institute,Sichuan Cancer Center,Affiliated Cancer Hospital of University of Electronic Science and Technology of China,Chengdu 610041,China)

机构地区：[1]四川省肿瘤临床医学研究中心,四川省肿瘤医院研究所,四川省癌症防治中心,电子科技大学附属肿瘤医院影像科,成都610041

出　　处：《放射学实践》2023年第11期1392-1398,共7页Radiologic Practice

基　　金：四川省科技计划项目(2021YFS0075、2021YFS0225、2022YFSY0006)。

摘　　要：目的:探讨双能量CT定量参数和形态学特征在鉴别肺实性结节良恶性中的应用价值。方法:回顾性连续纳入144例经双期双能量CT(DECT)增强扫描患者的147个肺实性结节,包括76例肺癌和71例良性病变。纳入结节以下特征:基于直径或体积的Lung-RADS分级、形态学特征以及DECT定量参数[包括动脉期和静脉期的有效原子序数(Zeff_A、Zeff_V)、碘含量(IC_A、IC_V)和标准化碘含量(NIC_A、NIC_V)]。使用多因素Logistic回归筛选鉴别良恶性肺结节的独立预测因子,并构建组合模型。使用受试者操作特征曲线下面积(AUC)、敏感度、特异度评估Lung-RADS、形态学特征、DECT定量参数及组合模型的诊断效能。使用Delong对比AUC之间的差异。结果:基于分叶(OR:25.465,95%CI:6.988~92.797)、NIC_V(OR:1.100,95%CI:1.062~1.139)构建的组合模型,AUC、敏感性、特异性分别为0.942(0.890~0.974)、90.8%及81.7%,且组合模型的AUC均优于基于直径的Lung-RADS分级、单一形态学特征及DECT定量参数(均P<0.05)。结论:基于NIC_V和分叶构建的组合模型,鉴别良恶性肺实性结节的诊断效能较高,在临床上有良好的应用价值。Objective:This study aimed to assess the application value of quantitative parameters from dual-energy computed tomography(DECT)and morphological features in differentiating malignant from benign lesions in solid pulmonary nodules.Methods:A total of 147 solid pulmonary nodules,confirmed pathologically,were consecutively and retrospectively enrolled from 144 patients who underwent DECT scan.These nodules included 76 cases of lung cancer and 71 cases of benign lesions.The following features were included:Lung CT Screening Reporting and Data System(Lung-RADS)based on diameter or volume,morphology features,and DECT-derived quantitative parameters including effective atomic number(Zeff),iodine concentration(IC),and normalized iodine concentration(NIC)in arterial and venous phases.The multivariable logistic regression analysis was used to evaluate the independent predictors in differentiating malignant from benign lesions and to build the combined model.The diagnostic performances of Lung-RADS,morphology features,DECT-derived quantitative parameters,and the combined model were assessed using the area under curve(AUC)of the receiver operating characteristic curve,as well as sensitivity and specificity.The Delong test was used to compare the differences in AUCs.Results:Lobulation(OR:25.465,95%CI:6.988~92.797)and NIC_V(OR:1.100,95%CI:1.062~1.139)were used to establish the combined model.The AUC,sensitivity,and specificity were 0.942(0.890~0.974),90.8%,and 81.7%,respectively.The Delong test demonstrated that the diagnostic performance of the combined model was significantly higher than that of models based on diameter-based Lung-RADS,single morphology features,and DECT-derived quantitative parameters(all P<0.05).Conclusion:Based on NIC_V and lobulation,the combined model showed good application value in differentiating malignant from benign lesions in solid pulmonary nodules during clinical practice.

关 键 词：双能量CT 碘含量 肺肿瘤 恶性病灶 良性病灶 

分 类 号：R814.42[医药卫生—影像医学与核医学] R734.2[医药卫生—放射医学]