MRI-based habitat and peritumoral radiomics for predicting HER2 status in breast cancer: a multicenter study.

MRI-based radiomics has shown potential for differentiating HER2-zero, HER2-low, and HER2-positive breast cancers; however, the added value of integrating intratumor heterogeneity (ITH) and peritumoral habitat features remains unclear. In this retrospective retrospective study, 515 patients from five hospitals were included and divided into training, internal testing, and external validation cohorts. Radiomic features were extracted from intratumor, peritumor, and habitat regions. Habitat subregions were generated using a Gaussian mixture model, and an ITH index was constructed. Three radiomics models (intratumor+peritumor, ITH, and peritumor + ITH) and a combined clinical-radiomics model were developed. Model performance was evaluated using receiver operating characteristic analysis and decision curve analysis. Among all models, the peritumor + ITH model showed comparatively better performance among the evaluated models. For Task 1 (HER2-positive vs. HER2-negative), the model yielded AUCs ranging from 0.713 to 0.791 across different cohorts. For Task 2 (HER2-low vs. HER2-zero), it achieved an AUC of 0.839 in the training cohort, 0.831 in the internal testing cohort, and 0.799 and 0.734 in the external validation cohorts, respectively. The combined model further improved predictive performance, achieving an AUC of 0.802 in external validation cohort 1 and 0.760 in cohort 2. Decision curve analysis demonstrated superior clinical utility of the combined model compared with other approaches. MRI-based habitat radiomics integrating intratumor heterogeneity and peritumoral features provides a promising non-invasive complementary tool for predicting HER2 status and supporting clinical decision-making.