Development and validation of a dynamic contrast-enhanced magnetic resonance imaging-based habitat and peritumoral radiomic model to predict axillary lymph node metastasis in patients with breast cancer: a retrospective study
The optimal peritumoral region size based on DCE-MRI radiomics for predicting ALNM in breast cancer patients was 4 mm. The nomogram combining clinicopathological factors, Peri4mm radiomics, and habitat signatures derived from DCE-MRI demonstrates robust performance in predicting ALNM and may aid clinical decision-making.
Authors
- Shi‐Ting Feng (ORCID: https://orcid.org/0000-0002-0869-7290)
- Pei-Qi Wu
- Fen-Ling Guo
- Jie Ma (ORCID: https://orcid.org/0000-0003-3776-4429)
- Juan Wang (ORCID: https://orcid.org/0000-0002-5968-1395)
- Ya Gao (ORCID: https://orcid.org/0000-0002-6729-6374)
- Shilin Chen (ORCID: https://orcid.org/0000-0002-0449-236X)
- Yubao Liu (ORCID: https://orcid.org/0000-0001-5807-6487)
Institutions
- Sun Yat-sen University (CN)
- Southern University of Science and Technology (CN)
- Third Affiliated Hospital of Southern Medical University (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Southern Medical University Shenzhen Hospital (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-11-11
- DOI
- https://doi.org/10.21037/qims-24-558
- Citations
- 13
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.85
Funders
- National Natural Science Foundation of China
- Medical Device Innovation Center