Contrast-enhanced CT-based radiomics for predicting visceral pleural invasion in early-stage non-small cell lung cancer
VPI affects the tumor-node-metastasis (TNM) staging of tumors and subsequent treatment strategies. The radiomics model outperformed the CT-feature model in predicting VPI. The contrast-enhanced CT-based radiomics model may be valuable for optimizing clinical decision-making.
Authors
- Hanting Li (ORCID: https://orcid.org/0009-0004-1536-5958)
- You Lü (ORCID: https://orcid.org/0000-0002-7524-4179)
- Xiaoyu Han
- Qinyue Luo
- Yuting Zheng
- Jun Fan
- Lin Teng
- Heshui Shi
Institutions
- Union Hospital (HK)
- Jianghan University (CN)
- Zhengzhou University (CN)
- Hubei Provincial Center for Disease Control and Prevention (CN)
- Precision for Medicine (United States) (US)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
- Wuhan Union Hospital (CN)
- Henan Provincial People's Hospital (CN)
- Huangshi Central Hospital (CN)
- Union Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2026-01-26
- DOI
- https://doi.org/10.1186/s13244-025-02184-2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Bayer HealthCare
- National Natural Science Foundation of China