Radiomics-based MRI models for predicting breast cancer axillary lymph node involvement in comparison with Node-RADS: a proof-of-concept study
Radiomics uses MRI to predict breast cancer LN involvement non-invasively and accurately. Radiomics and Node-RADS showed comparable performance. Radiomics could reduce invasive procedures, supporting personalized treatments in breast cancer care.
Authors
- Roberto Maroncelli (ORCID: https://orcid.org/0009-0006-6626-2478)
- Chiara De Nardo (ORCID: https://orcid.org/0000-0001-5288-1098)
- Federica Pediconi (ORCID: https://orcid.org/0000-0002-1432-2137)
- Veronica Rizzo (ORCID: https://orcid.org/0000-0003-1781-3174)
- Carlo Catalano (ORCID: https://orcid.org/0000-0003-4208-9691)
- Marcella Pasculli (ORCID: https://orcid.org/0000-0003-3633-649X)
- Sara Coppola
- Marco Moschetta (ORCID: https://orcid.org/0000-0003-1771-8337)
Institutions
- University of Bari Aldo Moro (IT)
- Sapienza University of Rome (IT)
Publication Details
- Journal
- European Radiology Experimental
- Published
- 2025-12-02
- DOI
- https://doi.org/10.1186/s41747-025-00660-4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00