Integration of dual-energy CT parameters and radiomics features for non-invasive prediction of α-SMA and CD8 + T cell in non-small cell lung cancer
The integration of DECT and radiomics presents a feasible, non-invasive strategy to assess specific TME components in NSCLC, underscoring the complementary value of different imaging data types towards developing biomarkers for personalized oncology.
Authors
- Rong Hou (ORCID: https://orcid.org/0000-0002-8236-6318)
- Xiaoyan Qu
- Gangfeng Li (ORCID: https://orcid.org/0000-0003-1602-9468)
- Y. Ma (ORCID: https://orcid.org/0000-0002-3577-9347)
- Yan Zhang
- Ying Yu
- Guang-Bin Cui
- Nan Jiang
- Yang Yang
- Wen-Xiu Wang
Institutions
- Institute of Molecular Functional Materials (CN)
- Tang Du Hospital (CN)
- Air Force Medical University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2026-03-11
- DOI
- https://doi.org/10.3389/fmed.2026.1792692
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00