Prediction of lymphovascular invasion in esophageal squamous cell carcinoma by computed tomography-based radiomics analysis: 2D or 3D ?
Both 2D and 3D radiomics features can be employed as potential biomarkers to predict the LVI in ESCC. The performance of the 3D radiomics model is better than that of the 2D radiomics model for the prediction of the LVI in ESCC.
Authors
- Jialiang Ren (ORCID: https://orcid.org/0000-0001-5616-7035)
- Xiaosheng Xu
- Qi Wang (ORCID: https://orcid.org/0000-0003-0858-9393)
- Xiaolong Gu (ORCID: https://orcid.org/0000-0001-8549-342X)
- Mengdi Cong (ORCID: https://orcid.org/0000-0002-1371-2301)
- Ming‐Bo Wang (ORCID: https://orcid.org/0000-0002-3979-3103)
- Andu Zhang
- Yang Li (ORCID: https://orcid.org/0000-0002-1909-2174)
- Xiangming Wang (ORCID: https://orcid.org/0000-0002-1039-3974)
- Wei Ren (ORCID: https://orcid.org/0000-0002-5245-451X)
- Yue Meng (ORCID: https://orcid.org/0000-0003-1058-054X)
- Gaofeng Shi (ORCID: https://orcid.org/0000-0001-5832-1462)
Institutions
- Hebei Medical University (CN)
- Hospital of Hebei Province (CN)
- Fourth Hospital of Hebei Medical University (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1186/s40644-024-00786-5
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.81