Abstract:

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 .

Key words: Lung adenocarcinoma, High resolution CT, Epidermal grow th factor receptor, Ground-glass opacity