The value of intratumoral and peritumoral radiomics features based on multiparametric MRI for predicting molecular staging of breast cancer

Yuxuan Han ¹ Manxia Huang ^1* Lizhi Xie ² Yuhai Cao ^1* Yang Dong ^1*

• ¹ Second Affiliated Hospital of Dalian Medical University, Dalian, China
• ² MRI Research, GE Healthcare (China), Beijing, China

Purpose: A model for preoperative prediction of molecular subtype of breast cancer using tumor and peritumor radiomics features from multiple magnetic resonance imaging (mMRI) sequences, combined with semantic features. Materials and methods: A total of 254 female patients with breast cancer confirmed by pathology were enrolled in this study. Preoperative mMRI, including T2-Weighted Imaging (T2WI), Diffusion Weighted Imaging (DWI) and Dynamic Contrast-Enhanced MRI (DCE) sequences, covered the whole breast. To analyze the MRI semantic features of different molecular subtypes of breast cancer and obtain independent predictive risk factors. Thirty-three binary classification models were established based on radiomics features of different sequences and peritumoral ranges. By comparing the performance of the above radiomics models, the best radiomics model was selected. At the same time, the best sequence and the best peritumoral extent were extracted from the target features, the radiomics score was calculated, and the independent risk factors were predicted. Finally, a nomogram was established for preoperative prediction of Triple-Negative Breast Cancer (TNBC), Hormone Receptor (HR) positive and HER2 negative (HR+/HER2−), and HER2+ molecular staging types of breast cancer. Results: Tumor length, edge enhancement and peritumoral edema are independent risk factors for predicting different molecular types of breast cancer. The best MRI sequence was DCE, and the best peritumoral margin was 6mm. The AUC of the nomogram based on the optimal sequence(DCE) and the optimal peritumoral range (6mm) combined with independent risk factors were 0.910, 0.909 and 0.845, respectively. Conclusion: The nomogram based on independent predictors combined with intratumoral and peritumoral radiomics scores can be used as an auxiliary diagnostic tool for molecular subtype prediction of breast cancer.