An MRI-based Radiomics Approach to Improve Breast Cancer Histological Grading

Rationale and Objectives: Nottingham histological grade (NHG) 2 breast cancer has an intermediate risk of recurrence, which is not infor-mative for therapeutic decision-making. We sought to develop and independently validate an MRI-based radiomics signature (Rad-Grade) to improve prognostic re-stratification of NHG 2 tumors. Materials and Methods: Nine hundred-eight subjects with invasive breast cancer and preoperative MRI scans were retrospectively obtained. The NHG 1 and 3 tumors were randomly split into training and independent test cohort, with the NHG 2 as the prognostic valida-tion set. From MRI image features, a radiomics-based signature predictive of the histological grade was built by use of the LASSO logistic regression algorithm. The model was developed for identifying NHG 1 and 3 radiological patterns, followed with re-stratification of NHG 2 tumors into Rad-Grade (RG)2-low (NHG 1-like) and RG2-high (NHG 3-like) subtypes using the learned patterns, and the prognostic value was assessed in terms of recurrence-free survival (RFS).Results: The Rad-Grade showed independent prognostic value for re-stratification of NHG 2 tumors, where RG2-high had an increased risk for recurrence (HR 2.20, 1.10-4.40, p = 0.026) compared with RG2-low after adjusting for established risk factors. RG2-low shared similar phenotypic characteristics and RFS outcomes with NHG 1, and RG2-high with NHG 3, revealing that the model captures radiomic features in NHG 2 that are associated with different aggressiveness. The prognostic value of Rad-Grade was further validated in the NHG2 ER+ (HR 2.53, 1.13-5.56, p = 0.023) and NHG 2 ER+LN-(HR 5.72, 1.24-26.44, p = 0.025) subgroups, and in specific treatment contexts.Conclusion: The radiomics-based re-stratification of NHG 2 tumors offers a cost-effective promising alternative to gene expression profil -ing for tumor grading and thus may improve clinical decisions. & COPY; 2023 Published by Elsevier Inc. on behalf of The Association of University Radiologists.

Automated summary

This study aimed to develop and independently validate an MRI-based radiomics signature (Rad-Grade) to improve prognostic re-stratification of Nottingham histological grade (NHG) 2 breast cancer. A radiomics-based signature predictive of the histological grade was built using MRI image features, and NHG 2 tumors were re-stratified into Rad-Grade (RG)2-low and RG2-high subtypes. The Rad-Grade showed independent prognostic value for re-stratification of NHG 2 tumors.