目的

探讨早期肺腺癌患者高分辨率CT（HRCT）特征对表皮生长因子受体（EGFR）基因突变的预测价值。

方法

收集经手术治疗的早期肺腺癌患者208 例。 采用扩增阻滞突变系统（ARMS）法检测EGFR 热点突变基因（18、19、20、21 外显子）的突变情况。将患者临床资料、组织病理学结果、HRCT 特征纳入数据库。采用χ² 检验以及Fisher 精确概率法分析EGFR 基因突变与患者临床特征的关系，利用多变量Logistic 模型分析EGFR 基因突变与患者HRCT 特征的相关性。应用Logistic 回归模型对有统计学意义的临床和HRCT 特征进行多因素分析；绘制EGFR 基因突变的受试者工作特征曲线（ROC 曲线），计算相应的曲线下面积（AUC）。

结果

208 例早期肺腺癌中EGFR 基因突变98 例（47 .16% ），且多见于女性（P＝0 .008）、非吸烟（P＝0 .006）、贴壁为主型腺癌（P＝0 .032）的患者。 HRCT 特征中，EGFR 基因突变多见于病变含有磨玻璃影（GGO）（P ＝0 .018）和空泡征/空气支气管征（P＝0 .003）。多因素分析结果显示，非吸烟、贴壁为主型腺癌及病变含有GGO 和空泡征/空气支气管征是EGFR 基因突变的独立影响因子；ROC 曲线分析结果显示，AUC 为0 .746（P＜0 .001）。

结论

早期肺腺癌HRCT 特征中含有GGO 及空泡征/空气支气管征与EGFR 基因突变相关，临床病理特征结合HRCT 特征有助于预测EGFR 基因突变。

Objective

To retrospectively analyze the high resolution CT(HRCT) features and epidermal growth factor receptor(EGFR) mutation of early lung adenocarcinoma after surgical resection ,and to explore the value of predicting EGFR mutation by HRCT features in early lung adenocarcinoma .

Methods

The detailed data of 208 patients with early lung adenocarcinoma who underwent surgical resection were retrospectively analyzed . The mutation of EGFR hotspot mutation gene (exon 18 ,19 ,20 ,21) was detected by amplification refractory mutation system(ARMS) , and the CT features of EGFR gene mutation and tumor chest imaging were compared . .SPSS 20 .0 statistical analysis software was used to establish a database of clinical data ,histopathological features and chest CT features .Chisquare test and Fisher s exact probability test were used to analyze the correlation between patients EGFR mutation and their clinical features .Multivariate logistic model was used to analyze the correlation between EGFR mutation and CT features of lung adenocarcinoma .Logistic regression model was used to analyze the clinical and CT features with statistical differences .Relative risk (OR) and 95% confidence interval (CI) were calculated .The ROC curve of EGFR mutation in lung adenocarcinoma was drawn and the corresponding area under the curve (AUC) was calculated . When P＜ 0 .05 , it indicated the difference was statistically significant .

Results

There were 98 cases (47 .16% ) of EGFR mutation in 208 cases of lung adenocarcinoma . The mutation of EGFR gene was predominant in female ( P ＝ 0 .008) ,non-smoking ( P ＝0 .006) and adherent adenocarcinoma ( P ＝ 0 .032) . In chest CT features ,EGFR gene mutations were predominant in lesions with ground-glass opacity(GGO) ( P ＝0 .018) and vacuole sign/air bronchial sign ( P＝0 .003) .Multivariate analysis showed that non-smoking ,adherentpredominant adenocarcinoma and GGO and vacuole/air bronchial sign were independent factors for EGFR mutation .In the multiple logistic regression model ,the area under the four combined factor subject curve(ROC) was 0 .746 .

Conclusions

GGO and air bronchial sign/vacuole in HRCT features of early lung adenocarcinoma are associated with EGFR mutation status . Clinical features combined with HRCT features are helpful to predict EGFR mutation .