CT影像组学参数结合CEA,CYFRA21-1,SCC和NSE在肺癌分型及预后评估的应用价值  

Application value of CT imaging parameters combined with CEA,CYFRA21-1,SCC and NSE in the classification and prognosis of lung cancer

作　　者：范小波 郭静 李文 亓燕 湛玉静[2] FAN Xiaobo;GUO Jing;LI Wen;QI Yan;ZHAN Yujing(Imaging Department,People′s Hospital Affiliated to Shandong First Medical University(People′s Hospital of Jinan City),Jinan,Shandong 271199,China;Imaging Department,Shandong Tumor Hospital Affiliated to Shandong First Medical University,Jinan,Shandong 250117,China)

机构地区：[1]山东第一医科大学附属人民医院(济南市人民医院)影像科,山东济南271199 [2]山东第一医科大学附属山东省肿瘤医院影像科,山东济南250117

出　　处：《临床肺科杂志》2025年第4期513-519,共7页Journal of Clinical Pulmonary Medicine

基　　金：济南市卫生健康委员会科技计划项目(2023-2-50)。

摘　　要：目的探讨计算机断层摄影术(CT)影像组学参数结合癌胚抗原(CEA)、细胞角蛋白19(CYFRA21-1)、鳞状细胞癌抗原(SCC)、神经元特异性烯醇化酶(NSE)在肺癌分型及预后评估的应用价值。方法回顾性分析本院在2022年2月-2024年2月收治的122例肺癌患者的临床资料,收集患者CEA,CYFRA21-1,SCC和NSE等指标水平,并分析患者CT影像组学特征,测量并计算患者CT能谱成像的定量参数,包括碘浓度(IC)、病灶在40keV、140keV的CT值[CT40keV、CT140keV]、能谱衰减曲线斜率(K)、归一化碘浓度(NIC);比较不同肺癌分型及预后分期患者间各指标差异;绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC)评估CT影像组学特征各参数及各指标对肺癌分型及预后评估诊断效能。结果122例肺癌患者中,小细胞癌有32例,占比为26.23%,腺癌有46例,占比为37.70%,鳞癌有44例,占比为36.07%。小细胞癌组CT40keV、IC、NIC、K低于腺癌组、鳞癌组,CT140keV高于腺癌组、鳞癌组,差异有统计学意义(P<0.05);腺癌组CT40keV、IC、NIC、K与鳞癌组相比无统计学意义(P>0.05)。小细胞肺癌组的CEA、NSE显著高于腺癌组、鳞癌组,鳞癌组的SCC高于小细胞癌组、腺癌组,差异均有统计学意义(P<0.05),小细胞癌组、腺癌组、鳞癌组的CYFRA21-1水平比较差异无统计学意义(P>0.05)。小细胞癌组-vs-鳞癌组中结果显示,NSE、CEA是小细胞癌的独立性预测因子,小细胞癌组-vs-腺癌组中筛选出NSE、CEA是小细胞癌的独立性预测因子,在非小细胞癌患者中,鳞癌组-vs-腺癌组中结果显示,CYFRA21-1和SCC对鳞癌诊断效能较好,应用SPSS直接绘制各因素ROC曲线,通过二元Logistics回归计算出联合检测的预测概率,将联合应用视为一个整体,绘制出联合应用的ROC曲线,结果显示,联合各指标诊断具有最高的诊断效能。CT40keV<200、CT140keV≥28、NIC<0.4、CEA≥10ng/mL、CYFRA21-1≥5ng/mL、SCC≥2ng/mL、NSE≥15ng/mL均为影响肺Objective To investigate the application value of computed tomography(CT)image parameters combined with carcinoembryonic antigen(CEA),cytokeratin 19(CYFRA21-1),squamous cell carcinoma antigen(SCC)and neuron-specific enolase(NSE)in the classification and prognosis of lung cancer.Methods The clinical data of 122 patients with lung cancer admitted to our hospital from February 2022 to February 2024 were retrospectively analyzed.CEA,CYFRA21-1,SCC,NSE and other indicators of the patients were collected,CT imaging omics characteristics were analyzed,and quantitative parameters of CT energy spectrum imaging were measured and calculated,including iodine concentration(IC),CT values of lesions at 40keV and 140keV[CT40 KeV,CT140keV],slope of energy spectrum decay curve(K),and normalized iodine concentration(NIC).The difference of various indexes were compared among patients with different lung cancer types and prognosis stages.Receiver operating characteristic(ROC)curve was drawn,and the area under the curve(AUC)was calculated to evaluate the diagnostic efficacy of each parameter and index of CT image omics characteristics for lung cancer classification and prognosis.Results Among the 122 patients with lung cancer,there were 32 cases of small cell carcinoma,accounting for 26.22%,46 cases of adenocarcinoma,accounting for 37.70%,and 44 cases of squamous cell carcinoma,accounting for 36.06%.CT40keV,IC,NIC and K in the small cell carcinoma group were lower than those in the adenocarcinoma group and the squamous cell carcinoma group,and CT140keV was higher than those in the adenocarcinoma group and the squamous cell carcinoma group(P<0.05).There was no significant difference in CT40keV,IC,NIC and K between the adenocarcinoma group and the squamous cell carcinoma group(P>0.05).CEA and NSE in the small cell lung cancer group were significantly higher than those in the adenocarcinoma group and the squamous cell carcinoma group.SCC in the squamous cell carcinoma group was higher than that in the small cell carcinoma group and the ad

关 键 词：癌胚抗原 细胞角蛋白19 鳞状细胞癌抗原 CT 神经元特异性烯醇化酶 肺癌 

分 类 号：R73[医药卫生—肿瘤]