Development and validation of a nomogram for the non-invasive prediction of human epidermal growth factor receptor 2 expression in gastric adenocarcinoma: an 18F-fluorodeoxyglucose positron emission tomography/computed tomography-based study.

BACKGROUND: Gastric cancer is a major global malignancy, and human epidermal growth factor receptor 2 (HER2) expression serves as a critical biomarker for guiding targeted treatment. However, current invasive biopsy methods have inherent limitations. This study aimed to explore the association between preoperative 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic parameters and HER2 expression in gastric adenocarcinoma, and to develop a preliminary nomogram as an exploratory tool for non-invasive prediction. METHODS: We retrospectively analyzed 231 gastric adenocarcinoma patients with preoperative 18F-FDG PET/CT. Tumor metabolic parameters were extracted following automated lesion segmentation using a threshold of 40% maximum standardized uptake value (SUVmax). Univariate and multivariate logistic regression identified independent predictors of HER2 status, which informed the construction of a visual nomogram. The model was evaluated with the area under the receiver operating characteristic curve for discrimination, calibration curves for goodness-of-fit, and decision curve analysis (DCA) for clinical net benefit. RESULTS: Of the 231 gastric adenocarcinoma patients enrolled, 30 (13%) were HER2-positive. Univariate logistic regression indicated positive correlations between HER2 positivity and higher primary tumor SUVmax [odds ratio (OR) =1.04, 95% confidence interval (CI): 1.00-1.08, P=0.07] and SUVmean (OR =1.07, 95% CI: 1.00-1.15, P=0.08). Multivariate analysis confirmed SUVmax, tumor location, and differentiation grade as independent predictors (all P<0.05). The combined nomogram attained an area under the curve (AUC) of 0.710 and a bootstrap-validated concordance index (C-index) of 0.686. Calibration analysis showed satisfactory predictive consistency, and DCA verified the clinical applicability of the model. CONCLUSIONS: 18F‑FDG PET/CT metabolic parameters are associated with HER2 positivity among patients with gastric adenocarcinoma. The integrated nomogram incorporating both PET metrics and clinical factors holds promise for noninvasive HER2 prediction and can act as an exploratory predictive tool, though its clinical performance awaits additional validation.