MRI-based deep learning radiomics can predict HER2 expression and disease-free survival in breast cancer

To the best of our knowledge, our study is the first to non-invasively assess human epidermal growth factor receptor 2 (HER2) status, especially HER2-low-positive status in breast cancer. In this study, a deep learning radiomics (DLR) model based on contrast-enhanced MRI was constructed and showed high and stable performance in predicting HER2 status in both the training and validation cohorts, and the predicted status was an independently significant predictor of disease-free survival (DFS) in HER2-low-positive/HER2-zero breast cancers. The DLR model showed prospects as a computer-aided diagnostic tool to help more accurately identify HER2-low-positive breast cancers, thereby guiding patient treatment strategies.