| CT和检验指标对浸润倾向肺腺癌的诊断模型建立 |
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| 引用本文： | 黄国,蒋蓓蓓,解学乾,陆惠良,高晓龙.CT和检验指标对浸润倾向肺腺癌的诊断模型建立[J].CT理论与应用研究,2021,30(1):81-90. |
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| 作者姓名： | 黄国 蒋蓓蓓 解学乾 陆惠良 高晓龙 |
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| 作者单位： | 1. 上海大学附属罗店医院放射科, 上海 201908; |
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| 基金项目： | 上海市第一人民医院临床研究创新团队建设项目;科技部重点国际合作项目;上海交通大学医学院高峰学科—临床医学研究型医师项目 |
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| 摘 要： | 目的:根据多排螺旋CT肺部亚实性结节（SSN）三维重建的定量参数、血液肿瘤标志物和血常规指标，建立用于判断有浸润倾向肺腺癌的多参数诊断模型。材料与方法:回顾性纳入107例接受薄层CT扫描，术后行组织学检查，并做了血液肿瘤标志物和血常规检查的患者。评估指标包括患者年龄、性别；SSN在CT三维重建中的最大径、总体积、实性成分占比和平均CT值；以及血液实验室指标:CEA、CYFRA21-1、NSE、CA125、CA153、CA242、CA199、CA724、SCC、CRP、WBC、NEUT和NEUT%。建立多元logistic回归模型，采用受试者工作特征曲线下面积（AUC）评价该模型对有浸润倾向SSN的诊断能力。结果:在良性和浸润前病变组（51例），以及微浸润腺癌和浸润性腺癌组（56例）之间，年龄、SSN最大径、总体积、实性成分占比和平均CT值有显著差异（P<0.05）。上述参数建立的多元回归模型中，SSN最大径（P=0.007）和实性成分占比（P=0.004）具有显著性。SSN最大径、实性成分占比和多元模型预测有浸润倾向SSN的AUC分别为0.764、0.749和0.801。结论:在体检可以获得的CT定量和一些血液肿瘤标志物和血常规参数中，使用SSN最大径和实性成分占比建立综合诊断模型，能有效预测SSN的浸润性，有助于在肺癌筛查中发现需要手术的患者。
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| 关 键 词： | CT 肺亚实性结节 肺腺癌 |
| 收稿时间： | 2020-06-09 |
Establishment of a Diagnostic Model for Lung Adenocarcinoma with Invasive Tendency by CT and Laboratory Indexes |
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| HUANG Guo,JIANG Beibei,XIE Xueqian,LU Huiliang,GAO Xiaolong.Establishment of a Diagnostic Model for Lung Adenocarcinoma with Invasive Tendency by CT and Laboratory Indexes[J].Computerized Tomography Theory and Applications,2021,30(1):81-90. |
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| Authors: | HUANG Guo JIANG Beibei XIE Xueqian LU Huiliang GAO Xiaolong |
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| Affiliation: | 1. Department of Radiology, Luodian Hospital, Shanghai University, Shanghai 201908, China;2. Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China |
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| Abstract: | Objective: To establish a multi-parameter diagnostic model to determine lung adenocarcinoma with an invasive tendency, based on 3D CT quantitative parameters of subsolid nodules(SSNs), blood tumor markers and blood routine parameters. Materials and methods: One hundred and seven patients were retrospectively included, who had thin-slice CT scan, postsurgery histological examination, and blood tumor markers, and routine blood tests. The evaluated parameters included age and gender of patients, the maximum diameter, total volume, proportion of solid components, and average CT value of SSN in CT 3D-reconstruction, as well as blood laboratory indicators: CEA, CYFRA21-1, NSE, CA125, CA153, CA242, CA199, CA724, SCC, CRP, WBC, NEUT, and NEUT%. A multiple logistic regression model was established, and the area under the receiver operating characteristic curve(AUC) was used to evaluate the diagnostic capability of the model for SSN with an invasive tendency. Results: There were significant differences in age, maximum SSN diameter, total volume, the proportion of solid components, and mean CT values between the benign and preinvasive lesion groups(51 cases) and minimally invasive and invasive adenocarcinoma groups(56 cases)(P<0.05). In the multiple regression model established by the above parameters, the maximum diameter of SSN(P=0.007) and the proportion of solid components(P=0.004) were significant. The AUCs of maximum diameter, the proportion of solid components and the regression model to determine SSNs with an invasive tendency were 0.764, 0.749, and 0.801, respectively. Conclusion: In terms of CT quantification and some blood tumor markers and blood routine parameters that can be obtained in health check examination, the establishment of a comprehensive diagnostic model using SSN maximum diameter and proportion of solid components can effectively predict the invasiveness of SSN, which is helpful for the detection of patients requiring surgery in lung cancer screening. |
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