MRI-Based Radiomic Signature as a Prognostic Biomarker for HER2-Positive Invasive Breast Cancer Treated with NAC.

Purpose To identify MRI-based radiomics signature (Rad-score) as a biomarker of risk stratification for disease-free survival (DFS) in patients with HER2-positive invasive breast cancer treated with trastuzumab-based neoadjuvant chemotherapy (NAC) and establish a radiomics-clinicoradiologic-based nomogram that combines Rad-score, MRI findings, and clinicopathological variables for DFS estimation. Patients and Methods A total of 127 patients were divided into a training set and testing set according to the ratio of 7:3. Radiomic features were extracted from multiphase CE-MRI (CEm). Rad-score was calculated using the LASSO (least absolute shrinkage and selection operator) regression analysis. The cutoff point of Rad-score to divide the patients into high- and low-risk groups was determined by receiver operating characteristic curve analysis. A Kaplan-Meier survival curves and the Log rank test were used to investigate the association of the Rad-score with DFS. Univariate and multivariate Cox proportional hazards model were used to determine the association of Rad-score, MRI features, and clinicopathological variables with DFS. A radiomics-clinicoradiologic-based nomogram combining the Rad-score, MRI features, and clinicopathological findings was plotted to validate the radiomic signatures for DFS estimation. Results The Rad-score stratified patients into high- and low-risk groups for DFS in the training set (P<0.0001) and was validated in the testing set (P=0.002). The radiomics-clinicoradiologic-based nomogram estimated DFS (training set: C-index=0.974, 95% confidence interval (CI)=0.954-0.994; testing set: C-index=0.917, 95% CI=0.842-0.991) better than the clinicoradiologic-based nomogram (training set: C-index=0.855, 95% CI=0.739-0.971; testing set: C-index=0.831, 95% CI=0.643-0.999). Conclusion The Rad-score is an independent biomarker for the estimation of DFS in invasive HER2-positive breast cancer with NAC and the radiomics-clinicoradiologic-based nomogram improved individualized DFS estimation.