首页|基于计算机体层成像影像组学模型预测肺腺癌表皮生长因子受体基因突变状态

基于计算机体层成像影像组学模型预测肺腺癌表皮生长因子受体基因突变状态

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目的:研究基于计算机体层成像(CT)影像组学模型预测肺腺癌表皮生长因子受体(EGFR)基因突变状态.方法:选择2020年1月~2023年1月收治的100例肺腺癌患者,其中突变型有55例,野生型45例,通过CT影像学检测,结合临床资料,分析EGFR突变组和野生型组患者的CT影像学指标以及临床特征.结果:从临床特征角度来看,突变型组与野生型组患者中性别、吸烟史、癌胚抗原水平比较(P<0.05),差异有显著性意义;两组患者的年龄、骨转移、脑转移、KI67比较(P>0.05),差异无显著性意义.从CT影像学角度来看,两组患者的肿瘤伴有毛刺征、胸腔积液比较(P<0.05),差异有显著性意义;两组患者的CT密度、肿瘤大小、分叶、空洞比较(P>0.05),差异无显著性意义.根据单因素分析发现:性别、吸烟史、癌胚抗原、毛刺、胸腔积液和肺腺癌EGFR基因突变有关,通过多因素分析发现,可通过性别、癌胚抗原、毛刺预测肺腺癌EGFR的基因突变.结论:通过CT影像组学模型,能够对肺腺癌EGFR基因突变状态进行预测.
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

金海蛟、张强

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包头市肿瘤医院放射影像科 (内蒙古 包头 014000)

计算机体层成像影像组学模型 肺腺癌 表皮生长因子受体 基因突变 预测结果

2024

中国医疗器械信息
中国医疗器械行业协会

中国医疗器械信息

影响因子:0.375
ISSN:1006-6586
年,卷(期):2024.30(13)