Explainable multi-modal radiomics for early prediction of liver metastasis in rectal cancer: a multicentric study
Pre-metastatic liver CT radiomics features could predict the liver metastasis development of rectal cancer. Integrating primary tumor and pre-metastatic liver radiomics improved liver metastasis prediction accuracy. The model demonstrated favorable interpretability through SHAP method.
Authors
- Jing Gong
- Yanfen Cui (ORCID: https://orcid.org/0000-0001-6631-5687)
- Yaru Feng (ORCID: https://orcid.org/0009-0009-7997-7220)
- Yanyan Wang (ORCID: https://orcid.org/0000-0002-6312-206X)
- Tong Tong (ORCID: https://orcid.org/0000-0002-9180-8181)
Institutions
- Fudan University Shanghai Cancer Center (CN)
- Shanxi Provincial Cancer Hospital (CN)
- Cancer Hospital of Chinese Academy of Medical Sciences (CN)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1186/s13244-025-02010-9
- 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
- Shanghai Hospital Development Center