Non-invasive prediction of EGFR gene mutations in non-small cell lung cancer by multi-parameter CT perfusion imaging
BV, TTP, and PS were independent predictors of EGFR mutation in patients with NSCLC. The combined CTPI parameter model (BV + TTP + PS) had the highest predictive performance and could be more reliable than any single parameter in clinical auxiliary diagnosis.
Authors
- Anlvna Li
- Qianyi Xie
- C. Chen (ORCID: https://orcid.org/0000-0002-6562-6659)
- Xiongjian Zhang
- Qi Liang
- Wěi Li (ORCID: https://orcid.org/0000-0003-0471-2382)
- Xiao Liu (ORCID: https://orcid.org/0000-0002-8073-0534)
- Xiao-ping Tang (ORCID: https://orcid.org/0000-0003-3252-2850)
Institutions
- Central South University (CN)
- Nanchang University (CN)
- Second Affiliated Hospital of Nanchang University (CN)
- Third Xiangya Hospital (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-10-03
- DOI
- https://doi.org/10.3389/fmed.2025.1660923
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00