Radiomics-driven prediction of pathologic complete response in non-mass breast cancer using post-neoadjuvant chemotherapy preoperative dynamic contrast-enhanced magnetic resonance imaging
Accurate early prediction of pCR could help identify patients most likely to benefit from NAC and avoid ineffective treatment in non-responders. The developed radiomics model offers an interpretable and reproducible tool; upon successful external validation, it has the potential to support personalized treatment planning in patients with NML-type breast cancer.
Authors
- Cheng Liu (ORCID: https://orcid.org/0000-0003-3952-3696)
- Tao Ai (ORCID: https://orcid.org/0000-0002-0459-1798)
- Yang Liu (ORCID: https://orcid.org/0000-0002-7734-5635)
- O. Moroz
- XingRui Li
- Qian Yin
Institutions
- Central South University (CN)
- Xiangya Hospital Central South University (CN)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Diagnostic and Interventional Radiology
- Published
- 2026-03-09
- DOI
- https://doi.org/10.4274/dir.2026.263773
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00