Intratumoral and peritumoral PET/CT-based radiomics for non-invasively and dynamically predicting immunotherapy response in NSCLC
The radiomic model holds promise as a precise, personalized, and dynamic decision support tool for the treatment of NSCLC patients.
Authors
- Xianwen Lin (ORCID: https://orcid.org/0009-0004-2983-3636)
- Na Huang (ORCID: https://orcid.org/0000-0001-7961-0677)
- Wei Zeng (ORCID: https://orcid.org/0000-0002-3111-9579)
- Yulin Liao (ORCID: https://orcid.org/0000-0001-5961-390X)
- Wenlan Zhou (ORCID: https://orcid.org/0000-0001-9056-4835)
- Wangjun Liao (ORCID: https://orcid.org/0000-0002-1364-8442)
- Tingting Shu
- Genjie Huang (ORCID: https://orcid.org/0009-0001-7777-910X)
- Jianping Bin (ORCID: https://orcid.org/0000-0003-4799-1502)
- Minmin Shi (ORCID: https://orcid.org/0000-0001-7692-2624)
- Zhiwei Liu (ORCID: https://orcid.org/0000-0002-1287-2274)
- Hao Zhang (ORCID: https://orcid.org/0000-0001-5038-0126)
- Yuanyuan Wang (ORCID: https://orcid.org/0000-0003-0240-1521)
- Kun Zhou (ORCID: https://orcid.org/0000-0002-0222-0301)
- Zhenhua Huang (ORCID: https://orcid.org/0000-0002-6072-0566)
- Jing Li (ORCID: https://orcid.org/0000-0003-2760-0092)
Institutions
- Foshan University (CN)
- Nanfang Hospital (CN)
- Southern Medical University (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- British Journal of Cancer
- Published
- 2025-02-10
- DOI
- https://doi.org/10.1038/s41416-025-02948-z
- Citations
- 24
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 32.64