Multiparametric MRI radiomics for noninvasive prediction of HER2 status in immunohistochemical 2+ breast cancer
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background Breast cancer (BC) patients with low expression of human epidermal growth factor receptor 2 (HER2), now classified as HER2-low, may benefit from new novel antibody-drug conjugates, such as trastuzumab deruxtecan. However, patients with immunohistochemistry (IHC) 2+ require further fluorescence in situ hybridization (FISH) to definitively determine HER2 status. Our study aims to explore the feasibility of radiomics models based on multiparametric magnetic resonance imaging (mpMRI) in predicting the HER2 status of IHC 2+ BC patients. Materials and methods 107 IHC 2+ BC patients, which composed of 65 (60.75%) FISH-negative and 42 (39.25%) FISH-positive, were enrolled in the retrospective study and divided into the training set (n = 74) and testing set (n = 33). The clinical and conventional MRI characteristics were used to build a clinical-imaging model. Radiomics features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and DCE phase3 and DCE phase7 in the dynamic contrast-enhanced T1-weighted imaging (DCE-T1WI), and radiomics models were built based on each individual sequence, mpMRI sequences, and a combination of mpMRI sequences with clinical-imaging characteristics. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were calculated. DeLong test was used to determine the differences among various models. p-value <0.05 was considered statistically significant. Results The clinical-imaging model achieved AUCs of 0.733 and 0.738 in the training and testing sets. Among the single-sequence radiomics models, the DCE phase7 model achieved the best predictive performance, with AUCs of 0.874 and 0.835 in the training and testing sets. The combined model C, composed of mpMRI model C (DCE phase7 +DWI+T2WI) and clinical-imaging model, showed the best predictive performance, with AUCs of 0.952 and 0.892 in the training and testing sets. Conclusion The mpMRI-based radiomics models had potential to noninvasively predict the HER2 status in IHC 2+ BC patients.
Source: Frontiers in Oncology
Authors: Xiaoguang Li, Qiujie Dong, Hong Guo, Chunlai Zhang, Jing Tian, Cheng Cheng, Peng Zhong, Shan Gui, Chao Cong, Yi Wang
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
Funder: Army Medical University
Award: G8330126308
OpenAlex ID: W7123569635
