A deep learning framework to stratify Nottingham histologic grade 2 breast tumors based on dynamic contrast-enhanced MRI
Question Difficulty in deciding between treatment options (neoadjuvant chemotherapy or primary surgery) in patients with intermediate risk breast cancer (Nottingham Grade 2). Findings Deep learning model reclassified grade 2 tumors into grade 1- and 3-like based on MRI. Patients with grade 3-like tumors had worse RFS: adjusted hazard ratio = 2.39 [95% CI: 1.29-4.45], p = 0.0059). Clinical relevance Risk stratification could inform treatment choice to minimize over- and under-treatment in patients with intermediate-risk breast cancer.
Authors
- Hien Nguyen (ORCID: https://orcid.org/0000-0002-1757-5359)
- Timothy Q. Duong (ORCID: https://orcid.org/0000-0001-6403-2827)
- A. Agrawal
- Susan Fineberg (ORCID: https://orcid.org/0000-0002-4769-7875)
- Della Makower (ORCID: https://orcid.org/0000-0002-8125-2474)
- Michael Z. Liu (ORCID: https://orcid.org/0000-0003-4618-3474)
- Roham Hadidchi (ORCID: https://orcid.org/0009-0007-2231-0172)
- Yihui Zhu (ORCID: https://orcid.org/0000-0002-5928-279X)
- Jinyu Lu
- Takouhie Maldijan
Institutions
- Albert Einstein College of Medicine (US)
- Montefiore Health System (US)
Publication Details
- Journal
- European Radiology
- Published
- 2025-12-17
- DOI
- https://doi.org/10.1007/s00330-025-12208-6
- Citations
- 2
- Primary Topic
- MRI in cancer diagnosis
- Type
- article
- Field-Weighted Citation Impact
- 2.72