Predicting treatment response and prognosis of immune checkpoint inhibitors-based combination therapy in advanced hepatocellular carcinoma using a longitudinal CT-based radiomics model: a multicenter study
The proposed LWCTR model performs well in predicting treatment response and prognosis in patients with HCC receiving ICIs-based combination therapy, potentially contributing to personalized and timely treatment decisions.
Authors
- Jun Xu
- Zhenglin Zhang (ORCID: https://orcid.org/0000-0002-5490-6815)
- Zhangxiang Zhu (ORCID: https://orcid.org/0000-0003-0452-770X)
- Lizhuang Yang (ORCID: https://orcid.org/0000-0002-0192-4323)
- Hongzhi Wang (ORCID: https://orcid.org/0000-0003-3834-6050)
- Junjun Li (ORCID: https://orcid.org/0000-0002-7473-4918)
- Tengfei Wang (ORCID: https://orcid.org/0000-0002-4742-5298)
- Yong Wang (ORCID: https://orcid.org/0000-0002-0123-228X)
- Hai Li (ORCID: https://orcid.org/0000-0002-3645-6232)
- Xin Luo (ORCID: https://orcid.org/0000-0002-4592-6734)
- Ruipeng Song
- Stephen Wong
- Yimou Wang
Institutions
- University of Science and Technology of China (CN)
- Anhui Medical University (CN)
- Chinese Academy of Sciences (CN)
- Cornell University (US)
- Hefei Institutes of Physical Science (CN)
- Huzhou Normal University (CN)
- Methodist Hospital (US)
- Methodist Hospital (US)
- First Affiliated Hospital of Anhui Medical University (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1186/s12885-025-13978-4
- Citations
- 7
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 9.52
Funders
- John S. Dunn Foundation
- National Natural Science Foundation of China
- Anhui Medical University
- University of Science and Technology of China
- Wannan Medical College
- National Key Research and Development Program of China
- Anhui Provincial Key Research and Development Plan