B-mode ultrasound and contrast-enhanced ultrasound-based radiomics interpretable analysis for the prediction of macrotrabecular-massive subtype of hepatocellular carcinoma
The AdaBoost-based BM + CEUS<sub>R</sub> model shows promise as a tool for preoperatively identifying MTM-HCC and may also be beneficial in predicting prognosis.
Authors
- Liping Sun (ORCID: https://orcid.org/0000-0001-8707-7446)
- Hui Shi (ORCID: https://orcid.org/0000-0003-1524-4553)
- Miao Yao (ORCID: https://orcid.org/0000-0001-6563-060X)
- Chong-Ke Zhao (ORCID: https://orcid.org/0000-0002-6865-7696)
- Huixiong Xu (ORCID: https://orcid.org/0000-0002-9878-8590)
- Lingling Li (ORCID: https://orcid.org/0000-0002-6130-2518)
- Dan Lu
- Jianhua Zhou (ORCID: https://orcid.org/0000-0002-9249-5252)
- Xin Guan (ORCID: https://orcid.org/0000-0001-6746-4385)
- Hong Han (ORCID: https://orcid.org/0000-0003-4355-0937)
- Yu Li (ORCID: https://orcid.org/0000-0002-1686-4415)
- Lifan Wang (ORCID: https://orcid.org/0000-0002-1806-3152)
- Cheng Qin
- Boyang Zhou
Institutions
- Shanghai University (CN)
- Tongji University (CN)
- Sun Yat-sen University (CN)
- Fudan University (CN)
- Zhongshan Hospital (CN)
- Shanghai Tenth People's Hospital (CN)
- Sun Yat-sen University Cancer Center (CN)
Publication Details
- Journal
- The Ultrasound Journal
- Published
- 2025-10-17
- DOI
- https://doi.org/10.1186/s13089-025-00452-2
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72
Funders
- National Natural Science Foundation of China
- Fudan University
- Fundamental Research Funds for the Central Universities