Fusion model integrating multi-sequence MRI radiomics and habitat imaging for predicting pathological complete response in breast cancer treated with neoadjuvant therapy
Integrating multi-dimensional MRI features with habitat imaging enhances pCR prediction in breast cancer. The fusion model offers a robust, non-invasive tool for guiding individualized treatment strategies while providing transparent interpretability through SHAP and LIME analyses.
Authors
- Xingyin Li (ORCID: https://orcid.org/0009-0004-9232-6987)
- Tao Ai (ORCID: https://orcid.org/0000-0002-3735-7500)
- Qilan Hu (ORCID: https://orcid.org/0000-0002-0990-9283)
- Yue Liu (ORCID: https://orcid.org/0000-0003-2880-3609)
- Qing Ye (ORCID: https://orcid.org/0000-0002-6756-0630)
- Yulin Li (ORCID: https://orcid.org/0009-0007-1140-3066)
- Hao Xiong
- Xingrui Li (ORCID: https://orcid.org/0000-0001-7640-9142)
- Shaojie Xu (ORCID: https://orcid.org/0009-0004-7875-5064)
- Yaying Du
- Yanyan Chen (ORCID: https://orcid.org/0000-0003-0184-577X)
- Yushi Ying
Institutions
- Union Hospital (HK)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1186/s40644-025-00929-2
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- Bethune Charitable Foundation