Integrating radiomics, pathomics, and biopsy-adapted immunoscore for predicting distant metastasis in locally advanced rectal cancer
The nomogram integrating macroscopic radiological information and microscopic pathological information is effective for risk stratification at baseline in LARC treated with nCRT.
Authors
- Rongxin Zhang (ORCID: https://orcid.org/0000-0002-4083-374X)
- Wenjing Peng
- Wenjuan Shen (ORCID: https://orcid.org/0000-0002-6193-825X)
- Xiaohang Liu (ORCID: https://orcid.org/0000-0002-2682-3369)
- Suqiong Wang
- Wen Zhao (ORCID: https://orcid.org/0000-0002-2530-7637)
- Hongmei Zhang (ORCID: https://orcid.org/0000-0002-6421-4126)
- Shuangmei Zou (ORCID: https://orcid.org/0000-0001-8539-6291)
- Shanshan Chen (ORCID: https://orcid.org/0000-0001-9723-2403)
- Rui Zhao (ORCID: https://orcid.org/0000-0002-5971-1638)
- Lijuan Wan
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- National Cancer Center (US)
- Tianjin Medical University (CN)
Publication Details
- Journal
- ESMO Open
- Published
- 2025-02-13
- DOI
- https://doi.org/10.1016/j.esmoop.2024.104102
- Citations
- 8
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 10.88
Funders
- National Natural Science Foundation of China