Computed tomography radiomics to predict microsatellite instability status and immunotherapy response in gastric cancer
A CT-based radiomics model was constructed to noninvasively predict gastric cancer (GC) microsatellite instability status. This immune-related radiomics model can effectively predict immunotherapy outcomes in GC. This noninvasive method can serve as a supplement for treatment decisions.
Authors
- Hong Qiu
- Fangyuan Zhang (ORCID: https://orcid.org/0000-0003-4695-9797)
- Pengbo Hu
- Lei Wang (ORCID: https://orcid.org/0000-0001-6604-3175)
- Zhou Li (ORCID: https://orcid.org/0000-0002-9401-1012)
- Yan Luo (ORCID: https://orcid.org/0009-0000-1494-5097)
- Zixuan Ding
- Yongqing Liu (ORCID: https://orcid.org/0000-0003-1090-0865)
- Yongping Lian (ORCID: https://orcid.org/0009-0008-2297-1728)
Institutions
- Xiangyang Central Hospital (CN)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2025-08-14
- DOI
- https://doi.org/10.1186/s13244-025-02050-1
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- National Natural Science Foundation of China