Integrating intratumoral, peritumoral, and clinical features in an ultrasound-based radiomics model: contributions and synergies for predicting microvascular invasion in hepatocellular carcinoma
This study demonstrates that combining intratumoral, peritumoral, and clinical features enhances the predictive accuracy for MVI in HCC. The findings underscore the value of feature integration and interactions, providing insights for personalized treatment planning and advancing the clinical utility of ultrasound-based radiomics.
Authors
- Difan Zhou
- Chuanling Hou
- Hongwei Qian (ORCID: https://orcid.org/0000-0002-6724-9826)
- Baochun Lu
- Luohang Xu
- Hong Fu
- Yanhua Huang (ORCID: https://orcid.org/0000-0002-5732-0203)
- Jianhua Yu (ORCID: https://orcid.org/0000-0002-6661-6647)
Institutions
- Shaoxing University (CN)
- Shaoxing People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-09-01
- DOI
- https://doi.org/10.3389/fonc.2025.1566105
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Zhejiang Province