Prediction of EGFR Gene Mutation Status in Lung Adenocarcinoma Based on CT Image Omics Model
Objective:To study the prediction of epidermal growth factor receptor(EGFR)gene mutation status in lung adenocarcinoma based on computer tomography(CT)imaging omics models.Methods:100 patients with lung adenocarcinoma admitted from January 2020 to January 2023 were selected,including 55 cases of mutant type and 45 cases of wild-type.Through CT imaging detection and combined with clinical data,the CT imaging indicators and clinical characteristics of EGFR mutant group and wild-type group patients were analyzed.Results:From the perspective of clinical characteristics,there were significant differences in gender,smoking history,and carcinoembryonic antigen levels between the mutant group and the wild-type group(P<0.05);There was no significant difference in age,bone metastasis,brain metastasis,and KI67 between the two groups of patients(P>0.05).From the perspective of CT imaging,there was a significant difference in the presence of spicule sign and pleural effusion between the two groups of patients(P<0.05);There was no significant difference in CT density,tumor size,lobulation,and cavity between the two groups of patients(P>0.05).According to univariate analysis,it was found that gender,smoking history,carcinoembryonic antigen,spicules,pleural effusion,and EGFR gene mutations in lung adenocarcinoma are related.Through multivariate analysis,it was found that gender,carcinoembryonic antigen,and spicules can predict EGFR gene mutations in lung adenocarcinoma.Conclusion:By using CT imaging omics models,the EGFR gene mutation status in lung adenocarcinoma can be predicted.
CT image omics modellung adenocarcinomaepidermal growth factor receptorgene mutationforecast result