分子影像学杂志2024，Vol.47Issue(8)：811-819,9.DOI:10.12122/j.issn.1674-4500.2024.08.06
双能量CT定量参数联合CT征象预测中晚期肺腺癌表皮生长因子受体基因突变
Dual-energy CT quantitative parameters combined with CT signs in predicting epidermal growth factor receptor gene mutation in advanced lung adenocarcinoma
摘要
Abstract
Objective To explore the correlation between the quantitative parameters of dual-energy CT combined with CT signs,clinical characteristics and epidermal growth factor receptor(EGFR)gene mutations in patients with advanced lung adenocarcinoma,and to predict the mutation in patients with advanced lung adenocarcinoma.Methods A retrospective collection was performed for 172 cases of advanced lung adenocarcinoma(clinical stage Ⅲ～Ⅳ)diagnosed by pathology(fiber bronchoscopy,lymph node,percutaneous lung puncture)biopsy in the First People's Hospital of Yancheng City from January 2022 to June 2023.The patient's general clinical features,CT signs,and dual-energy CT(DECT)parameters were collected.According to the results of EGFR gene testing,they were divided into positive group and negative group.The independent samples t-test or rank-sum test were used to analyze the differences between the groups,and a binary logistic regression model based on clinical characteristics,conventional CT signs,DECT quantitative parameters and combination was gradually established for statistically significant parameters,and the prediction performance of the combined model was evaluated.Results A total of 172 patients with lung adenocarcinoma during the study period were identified,including 80 positive for EGFR gene expression patients and 92 negative patients.There were significant differences in IC,NIC,slope K40-100kev in arterial phase and IC in venous phase between the two groups(P<0.001);There were significant differences in air bronchogram sign and pleural traction sign between the two EGFR groups(P<0.05);Univariate logistic regression analysis showed that arterial phase IC,NIC,slope K40-100 keV,venous phase IC,air bronchogram sign,and pleural traction sign were associated with EGFR gene mutations.The AUC for the DECT model,the DECT model combined with clinical characteristics,and the DECT model combined with clinical characteristics and CT signs were 0.746(sensitivity 63.75％,specificity 92.39％),0.787(sensitivity 65.00％,specificity 91.30％),and 0.819(sensitivity 77.50％,specificity 82.61％),respectively.According to the DeLong test,there was no significant difference in AUC among the three models(P>0.05).Conclusion The combined DECT model,incorporating clinical characteristics and CT signs,effectively predicts EGFR mutations and performs better than the single model in patients with advanced-stage lung adenocarcinoma.关键词
表皮因子生长受体/双能量CT/肺腺癌/基因突变/预测模型Key words
epidermal factor growth receptor/dual-energy CT/adenocarcinoma of the lung/gene mutation/prediction model引用本文复制引用
于蕾,陈望,孙乾,焦志云..双能量CT定量参数联合CT征象预测中晚期肺腺癌表皮生长因子受体基因突变[J].分子影像学杂志,2024,47(8):811-819,9.基金项目
江苏省扬州市科技计划项目(YZ2022107) （YZ2022107）
红十字基金会医学赋能公益专项基金领航菁英临床科研项目(XM_LHJY2022_05_33) （XM_LHJY2022_05_33）
