The Role of Multiparametric MRI Radiomics for Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Invasive Breast Cancer: A Comparative Study
The combined radiomics model outperformed single-sequence models in predicting ALNM. The combined MRI model demonstrated the highest performance, improving diagnostic accuracy and showing potential for prognostic prediction.
Authors
- Yi Sui (ORCID: https://orcid.org/0000-0002-2898-7877)
- Yuan Guo (ORCID: https://orcid.org/0000-0001-5115-1624)
- Si‐Yi Chen (ORCID: https://orcid.org/0009-0009-1384-963X)
- Jianning Chen (ORCID: https://orcid.org/0000-0002-0770-0697)
- Xiangjun Lv
- Zhidan Zhong (ORCID: https://orcid.org/0000-0003-2360-7908)
- Yongxin Chen (ORCID: https://orcid.org/0000-0002-1459-6365)
- Lei Zhang (ORCID: https://orcid.org/0000-0003-3536-8692)
- Xiaomeng Yu
- Wei Tang (ORCID: https://orcid.org/0009-0004-5346-8368)
- Jie Qin (ORCID: https://orcid.org/0000-0002-5792-5464)
- Kuiming Jiang
- Qingcong Kong
Institutions
- University of Maryland, Baltimore (US)
- Sun Yat-sen University (CN)
- Guangzhou Women and Children Medical Center (CN)
- Guangzhou First People's Hospital (CN)
- Guangdong Province Women and Children Hospital (CN)
- Third Affiliated Hospital of Sun Yat-sen University (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- Cancer Innovation
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1002/cai2.70022
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- National Natural Science Foundation of China
- Guangdong Medical Research Foundation
- Guangzhou First People's Hospital
- Basic and Applied Basic Research Foundation of Guangdong Province