Radiomics Integration of Mammography and DCE-MRI for Predicting Molecular Subtypes in Breast Cancer Patients
The radionics model utilizing multimodal fusion features from breast mammography combined with DCE-MRI images showed high performance in distinguishing molecular subtypes of breast cancer. It is of significance to accurately predict prognosis and determine treatment strategy of breast cancer by molecular classification.
Authors
- Hang Sun (ORCID: https://orcid.org/0000-0002-3460-9354)
- Jin Xie (ORCID: https://orcid.org/0000-0001-6453-1618)
- Jing Li (ORCID: https://orcid.org/0000-0003-2504-1629)
- Jing Chen (ORCID: https://orcid.org/0000-0001-8863-2843)
- Ying-Jie Peng (ORCID: https://orcid.org/0000-0001-9049-0987)
- Xianwei Yang (ORCID: https://orcid.org/0000-0003-4388-9674)
- Tinsu Pan (ORCID: https://orcid.org/0000-0002-8511-3746)
- Tao Shang (ORCID: https://orcid.org/0009-0009-8321-3776)
Institutions
- Shenyang Ligong University (CN)
- Guiyang Medical University (CN)
- Affiliated Hospital of Guizhou Medical University (CN)
Publication Details
- Journal
- Breast Cancer Targets and Therapy
- Published
- 2025-02-01
- DOI
- https://doi.org/10.2147/bctt.s488200
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- National Natural Science Foundation of China