ORIGINAL RESEARCH article
Front. Oncol.
Sec. Breast Cancer
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1539644
This article is part of the Research TopicAdvances in Oncological Imaging TechniquesView all 13 articles
Using Baseline MRI Radiomics to Predict the Tumor Shrinkage Patterns in HR-Positive, HER2-Negative Breast Cancer
Provisionally accepted
- 1Department of Medical Imaging, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
- 2Department of Breast Cancer Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
- 3Department of Pharmaceuticals Diagnostics, GE Healthcare, Beijing, China
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Introduction: This study aimed to develop and validate a predictive model for tumor shrinkage patterns in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer patients undergoing neoadjuvant chemotherapy (NAC).Methods: A retrospective analysis was conducted on 227 HR+/HER2- breast cancer patients with a desire for breast conservation, examining their clinicopathological characteristics, traditional MRI features, and radiomics features. Patients were divided into training and validation cohorts in a 7:3 ratio. Tumor shrinkage patterns were classified into Type I and Type II based on RECIST 1.1 criteria. A clinical model was established using Ki67 quantification and enhancement pattern. Radiomics features were extracted and analyzed using machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF). A combined clinical-radiomics model was also developed.Results: The clinical model achieved an area under the curve (AUC) of 0.624 in the training cohort and 0.551 in the validation cohort. The RF radiomics model showed the highest predictive performance with an AUC of 0.826 in the training cohort and 0.808 in the validation cohort. The combined clinical-radiomics model further improved prediction accuracy, with an AUC of 0.831 in the training cohort and 0.810 in the validation cohort.Conclusion: Radiomics features based on baseline MRI significantly enhance the prediction of tumor shrinkage patterns in HR+/HER2- breast cancer patients. This approach aids in the early identification of patients likely to benefit from breast-conserving surgery and facilitates timely treatment adjustments.
Keywords: breast cancer, Neoadjuvant chemotherapy, tumor shrinkage patterns, Radiomics, MRI
Received: 04 Dec 2024; Accepted: 07 Jul 2025.
Copyright: © 2025 Wang, Wang, Yang, Ren, Xu, Zhai and Zhou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Tao Zhou, Department of Breast Cancer Center, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
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