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Background  The relationship between epidermal growth factor receptor ( EGFR)  gene mutation status, preoperative computed tomography ( CT),  and clinical features in patients with small peripheral lung adenocarcinoma (<3 cm) was investigated.    Methods  We included 209 patients who underwent surgical resection for stage  I  or  II  lung adenocarcinoma at  N anjing General Hospital between  D ecember 2010 and  M ay 2016. 171 cases of patients underwent a pretreatment chest CT. Eleven different  CT  descriptors were assessed. Multiple logistic regression analyses were performed to identify independent risk factors for the prediction of  EGFR  mutation.  R eceiver operating characteristic analysis was used to evaluate the performance of the logistic regression model.    Results   EGFR  mutation was determined in 126 patients (60.3%) and appeared more frequently in women (  P   = 0.025), never‐smokers (  P   < 0.001), and patients with a carcinoembryonic antigen level <2.6 ng/ml (  P   = 0.045). Papillary predominant adenocarcinomas (  P   = 0.014), intermediate/low pathologic grade tumors (  P   = 0.003), tumors in the upper lobe (  P   = 0.028), and showing ground‐glass opacity ( GGO ) or mixed  GGO  on  CT  (  P   = 0.039) also more frequently harbored  EGFR  mutations.  GGO  on  CT , acinar or papillary predominant adenocarcinoma, and non‐smoker were identified in multivariable analyses as significantly independent risk factors. The multiple logistic regression model showed high predictive power for identifying  EGFR  mutations. The  CT  features were similar between the  L 858 R  and 19  d eletion mutations.    Conclusions  Combined  CT  and clinical features may be helpful for determining the presence of  EGFR  mutations in patients with small peripheral lung adenocarcinoma, particularly in patients where mutational profiling is not available or possible.

Computed tomography and clinical features associated with epidermal growth factor receptor mutation status in stage I/II l ung adenocarcinoma