摘要
目的探讨多层螺旋CT在鉴别诊断小细胞肺癌(small cell lung cancer,SCLC)与肺鳞癌(squamous carcinoma,SC)中的应用。方法收集2014年2月—2017年2月108例确诊为中央型肺癌患者的临床资料。根据病理类型不同分为SCLC组56例和SC组52例,分析比较两组患者CT影像特征,并对SCLC发生的相关危险因素进行多因素Logistic回归分析。结果两组在形态、密度、强化方式、阻塞性改变、支气管形态、淋巴结肿大、淋巴结融合、大血管侵袭方面比较差异均具有统计学意义(P<0.05)。多因素Logistic回归分析显示,肿瘤均匀强化(OR=6.474,P=0.004)、支气管狭窄通畅(OR=5.532,P=0.011)和淋巴结融合(OR=6.428,P=0.004)是SCLC发生的独立危险因素。结论 SCLC和SC的多层螺旋CT影像具有一定差异,综合分析CT影像特征有助于SCLC和SC的鉴别诊断。
Objective To investigate multi slice spiral CT in application of differential diagnosis of small cell lung cancer(SCLC)and lung squamous carcinoma(SC).Methods Clinical data of108patients with central bronchogenic carcinoma during February2014and February2017was collected,and the patients were divided into SCLC group(n=56)and SC group(n=52)according to pathological types.In two groups,CT image features were analyzed and compared,and related risk factors of SCLC pathogenesy were analyzed by multivariate Logistic regression.Results There were significant differences in shape,density,enhancement mode,obstructive changes,bronchial shape,lymph node enlargement,lymph node fusion and large vascular invasion between two groups(P<0.05).Multivariate Logistic regression analysis showed that homogeneous enhancement tumor(OR=6.474,P=0.004),bronchial stenosis and smooth(OR=5.532,P=0.011)and lymph node fusion(OR=6.428,P=0.004)were independent risk factors of SCLC pathogenesy.Conclusion There are differences between SCLC and SC in multi slice spiral CT images,and therefore comprehensive analysis of CT findings is helpful for differential diagnosis of SCLC and SC.
作者
张全中
鲁际
ZHANG Quanzhong;LU Ji(Department of Medical Imaging,Yichang Mental Health CenterYichang Youfu Hospital,Yichang,Hubei 443005,China;Medical Imaging Certer,Yichang Central People's Hospital,Yichang,Hubei 443003,China)
出处
《解放军医药杂志》
CAS
2017年第12期21-24,共4页
Medical & Pharmaceutical Journal of Chinese People’s Liberation Army
基金
湖南省卫计委科技项目(B2016240)
关键词
小细胞肺癌
肺鳞癌
体层摄影术
螺旋计算机
诊断
鉴别
Small cell lung carcinoma
Lung squamous carcinoma
Tomography, spiral computed
Diagnosis
differential