微小结节肺癌病理类型与影像学特点的研究

CT imaging features correlated with histologic subtype in small pulmonary nodulesCT imaging features correlated with histologic subtype in small pulmonary nodules

目的回顾性分析上海交通大学附属上海市胸科医院肺部肿瘤临床医学中心外科2007年6月—2013年3月手术切除明确肺癌并具有CT薄层和三维重建的≤20 mm微小结节的161例患者,观察影像学特征与病理类型之间的关系,从影像学角度探索具有侵袭性特征的病理类型的预测临界值。方法特定专家组根据既定的读片顺序分析影像结果,并与病理诊断对照,应用SPSS软件进行χ2、Pearson相关分析,ROC预测临界值。结果高危组与低危组影像学特征存在显著差异,主要表现在结节最大径、密度(磨玻璃密度影中实性病变所占比例)、血供、分叶、毛刺和胸膜凹陷征,其中以结节密度、结节最大径与病理亚型相关性最高。ROC分析显示,结节最大径的临界值为13.50 mm,结节密度的临界值为37.5%,曲线下面积分别是0.717和0.841。结论最大径和密度可能是判断微小肺癌侵袭性病理类型的预测值。

Objective To analyze the predicted value of invasive lung cancer in pulmonary small nodules(≤20 mm in diameter) by using three-dimensional(3D) reconstruction of CT imaging. Methods A reading group of physicians, radiologists and pathologists was established and checked the 3D-CT according to a predefined order. The image features were analyzed, and then compared with the pathological diagnosis. SPSS 19.0 software was used for statistical analysis, using χ2 test, Pearson and receiver operating characteristic curve(ROC). A total of 161 cases(176 nodules) with preoperative image data of three-dimensional reconstruction of CT were collected and analyzed retrospectively from June 2007 to March 2013. Results The analysis of 176 lesions showed that CT imaging characteristics were significantly different between high-risk lung cancer and low-risk lung cancer, mainly in tumor size, density(the proportion of solid lesions in ground-glass opacities), blood supply, lobulation, speculation and pleural indentation. The tumor density and diameter were highly related to pathologic subtype. ROC analysis showed that the threshold of nodule's diameter was 13.50 mm, with the value of area under the curve of 0.717, sensitivity of 61.6% and specificity of 71.6%. The threshold of density was 37.5%, with the value of area under the curve of 0.841, sensitivity of 79.4% and specificity of 79.7%. Conclusion The diameter and density of pulmonary small nodules in 3D reconstruction of CT may be predicted value of invasive NSCLC.