Nomogram for reducing unnecessary biopsies of breast lesions based on MRI and clinical features: a multi-center retrospective cohort study
We have established a nomogram based on DCE-MRI radiomics and clinical risk factors to distinguish malignant from benign breast lesions, and demonstrated potential to reduce unnecessary biopsies, serving as a supplementary tool for BI-RADS-based clinical decision-making.
Authors
- Min‐Ying Su (ORCID: https://orcid.org/0000-0002-3069-0271)
- Youfan Zhao
- Huiru Liu (ORCID: https://orcid.org/0000-0002-2448-9918)
- Shuxin Ye (ORCID: https://orcid.org/0009-0004-4683-3910)
- Meihao Wang (ORCID: https://orcid.org/0000-0002-7055-993X)
- Zhen Wang (ORCID: https://orcid.org/0000-0002-2516-4752)
- Fang Ye (ORCID: https://orcid.org/0000-0002-1322-7365)
- Zhongwei Chen (ORCID: https://orcid.org/0000-0002-1411-6675)
- Haiwei Miao
- Yaru Wei
- Jiejie Zhou
Institutions
- Sun Yat-sen University (CN)
- University of California, Irvine (US)
- Fudan University (CN)
- Wenzhou Medical University (CN)
- First Affiliated Hospital of Wenzhou Medical University (CN)
- Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University (CN)
- Zhongshan Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Second Affiliated Hospital of Zhejiang University (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2025-12-06
- DOI
- https://doi.org/10.1186/s40644-025-00972-z
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00