Dual-Region Ultrasound Radiomics for the Non-Invasive Prediction of HER2 Status in Breast Cancer Patients with Equivocal Immunohistochemistry

Abstract Objective To assess the potential of ultrasound (US) radiomics, incorporating intratumoral and peritumoral regions, in predicting human epidermal growth factor receptor 2 (HER2) status in breast cancer patients with uncertain immunohistochemical (IHC) results. Methods This retrospective study included 410 breast cancer patients with an IHC HER2 score of 2+, confirmed by fluorescence in situ hybridization (FISH). US images were analyzed using 3D Slicer software to delineate regions of interest (ROI) in the tumor and surrounding peritumoral areas. Radiomics features were extracted from intratumoral regions and peritumoral areas (3mm, 6mm, 9mm) and divided into four groups. Feature selection was conducted via Spearman correlation, Mann-Whitney U test, and least absolute shrinkage and selection operator (LASSO) regression. Six machine learning classifiers were trained and validated. The best-performing model was evaluated in an independent test cohort, and SHAP (SHapley Additive exPlanations) analysis was used to interpret predictions. Results The logistic regression (LR) model, utilizing intratumoral and 6mm peritumoral features, achieved the highest area under the curve (AUC) of 0.794 in the training set and 0.712 in the test set. Decision curve analysis demonstrated net benefit across a range of thresholds, particularly at lower levels. SHAP analysis highlighted key radiomics features in predicting HER2 status. Conclusion US radiomics, particularly when incorporating both intratumoral and peritumoral regions, offers a promising approach for predicting HER2 status in breast cancer patients with equivocal IHC results, potentially aiding clinical decision-making. Clinical trial number Not applicable.