A CT-based radiomics nomogram for prediction of human epidermal growth factor receptor 2 status in patients with gastric cancer

更新时间:2023-05-28

【摘要】Objective: To develop and validate a computed tomography(CT)-based radiomics nomogram for predicting human epidermal growth factor receptor 2(HER2) status in patients with gastric cancer.Methods: This retrospective study included 134 patients with gastric cancer(HER2-negative: n=87; HER2-positive: n=47) from April 2013 to March 2018, who were then randomly divided into training(n=94) and validation(n=40) cohorts. Radiomics features were obtained from the CT images showing gastric cancer. Least absolute shrinkage and selection operator(LASSO) regression analysis was utilized for building the radiomics signature. A multivariable logistic regression method was applied to develop a prediction model incorporating the radiomics signature and independent clinicopathologic risk predictors, which were then visualized as a radiomics nomogram. The predictive performance of the nomogram was assessed in the training and validation cohorts.Results: The radiomics signature was significantly associated with HER2 status in both training(P<0.001) and validation(P=0.023) cohorts. The prediction model that incorporated the radiomics signature and carcinoembryonic antigen(CEA) level demonstrated good discriminative performance for HER2 status prediction,with an area under the curve(AUC) of 0.799 [95% confidence interval(95% CI): 0.704-0.894] in the training cohort and 0.771(95% CI: 0.607-0.934) in the validation cohort. The calibration curve of the radiomics nomogram also showed good calibration. Decision curve analysis showed that the radiomics nomogram was useful.Conclusions: We built and validated a radiomics nomogram with good performance for HER2 status prediction in gastric cancer. This radiomics nomogram could serve as a non-invasive tool to predict HER2 status and guide clinical treatment.

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