Establishment of a predictive nomogram for breast cancer lympho-vascular invasion based on radiomics obtained from digital breast tomography and clinical imaging features
The predictive nomogram, derived from both radiomics and clinical imaging features, was highly accurate in identifying future LVI occurrence in breast cancer, demonstrating its potential as an assistive tool for clinicians to devise individualized treatment regimes.
Authors
- Caixian Yang (ORCID: https://orcid.org/0000-0002-7228-1599)
- Zengyu Jiang
- Li-Zhen Li (ORCID: https://orcid.org/0000-0002-4062-9351)
- Yuan Liang (ORCID: https://orcid.org/0000-0002-1861-4479)
- Yiquan Zheng
- Wenqing Chen (ORCID: https://orcid.org/0000-0003-2557-8960)
- Sheng He (ORCID: https://orcid.org/0000-0003-2918-1549)
- Gang Liang (ORCID: https://orcid.org/0000-0001-6691-505X)
- Jian‐Ding Li (ORCID: https://orcid.org/0000-0002-9178-3498)
- Suxin Zhang (ORCID: https://orcid.org/0000-0003-3896-9565)
- Yumeng Dong (ORCID: https://orcid.org/0000-0001-9190-5902)
Institutions
- Shanxi Medical University (CN)
- First Hospital of Shanxi Medical University (CN)
- Shanxi Provincial People’s Hospital (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1186/s12880-025-01607-2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China