Deep multi-instance learning model based on gadoxetic acid-enhanced MRI for predicting microvascular invasion of hepatocellular carcinoma: a multicenter, retrospective study
The DL model that selects all axial slices of intratumor and peritumor as input shows robust capability in predicting MVI, which is expected to help clinical decision-making of individualized treatment for HCC.
Authors
- Genwen Hu (ORCID: https://orcid.org/0000-0002-7032-7581)
- Shuyuan Zhong
- Xianyue Quan (ORCID: https://orcid.org/0000-0003-2293-9345)
- Changzheng Shi (ORCID: https://orcid.org/0000-0002-9728-6062)
- Ge Zhang (ORCID: https://orcid.org/0000-0002-7807-7695)
- Xinming Li (ORCID: https://orcid.org/0000-0002-7844-8417)
- Yi Luo (ORCID: https://orcid.org/0009-0004-6954-5938)
- Shaofang Chen (ORCID: https://orcid.org/0009-0009-4323-2251)
Institutions
- Southern University of Science and Technology (CN)
- Zhujiang Hospital (CN)
- First Affiliated Hospital of Jinan University (CN)
Publication Details
- Journal
- BMC Cancer
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1186/s12885-025-14971-7
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China