Objective To investigate the value of traditional metabolic parameters,CT features and intratumoral heterogeneity parameters measured by 18 F-FDG PET/CT in predicting the mutation status of the epidermal growth factor receptor(EGFR)gene in patients with adenocarcinoma.Methods A total of 147 patients(73 males,74 females,age(59.8±10.2)years)with pathological confirmed adenocarcinoma be-tween January 2016 and June 2020 in the Affiliated Hospital of Jining Medical University were retrospectively included.The differences of clinical data(smoking history,tumor location and clinical stage),CT features(maximum diameter,ground-glass opacity content,lobulation,speculation,cavitation,air-bronchogram,pleural retraction and bronchial cut-off sign),18F-FDG PET/CT traditional metabolic parameters(SUVmax,SUVmean,metabolic tumor volume(MTV)and total lesion glycolysis(TLG))and intratumoral heterogenei-ty parameters(CV,heterogeneity index(HI))were analyzed between patients with EGFR mutation and pa-tients with EGFR wild-type.Independent-sample t test,Mann-Whitney U test and x2 test were used to ana-lyze the data.Multivariate logistic regression was used to analyze the predictors of EGFR mutation.ROC curve analysis was used to evaluate the predictive value of clinical and PET/CT information.Results Among 147 patients,87 were with EGFR mutation and 60 were with EGFR wild-type.There were significant differ-ences in gender(male/female),smoking history(with/without),location(peripheral lesion/central lesion),pleural retraction(with/without),SUVmax,SUVmean,TLG,CV and HI(x2 values:4.72-23.89,z values:from-2.31 to 5.74,all P＜0.05).Multivariate logistic regression analysis showed that smoking history(odds ratio(OR)=0.167,95％CI:0.076-0.366;P＜0.001),pleural retraction(OR=1.404,95％CI:1.115-3.745;P=0.012),SUVmax(OR=0.922,95％CI:0.855-0.995;P=0.003),TLG(OR=0.991,95％CI:0.986-0.996;P=0.001)and HI(OR=0.796,95％CI:0.700-0.859;P＜0.001)were predictors of EGFR mutation.ROC curve analysis showed the AUC of HI was 0.779,with the sensitivity of 76.67％(46/60)and the specificity of 79.31％(69/87).The predictive model was constructed by combining smoking history,pleural retraction,TLG,SUVmax and HI,and the AUC was 0.908,with the sensitivity of 88.33％(53/60)and the specificity of 68.97％(60/87).The difference of AUCs between HI and the predictive model was statistically significant(z=3.71,P＜0.001).Conclusion HI can predict EGFR mutations better,and the predictive value for EGFR mutations can be enhanced when combining HI with smoking history,pleural re-traction,TLG and SUVmax.
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