Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters
The cRadiomics model can predict intrahepatic recurrence of colorectal cancer liver metastases (CRLM) after curative hepatectomy. Machine learning with data integration of ultrasound radiomics and clinicopathological parameters enables better prediction of intrahepatic recurrence for CRLM after curative hepatectomy. The developed model holds great potential to improve clinical decision-making and personalized management for CRLM patients.
Authors
- Pengpeng Kuang
- Haitian Zhang (ORCID: https://orcid.org/0000-0002-1122-8647)
- Zhong Liu
- Yunyun Li
- Wei Zheng
- Ruhai Zou
- Weixuan Kong
- Ting Hu
- Xin Chen
- Guangjian Liu
- Jianjun Li
Institutions
- Sun Yat-sen University (CN)
- Kunming Medical University (CN)
- Sixth Affiliated Hospital of Sun Yat-sen University (CN)
- Institute of Acoustics (CN)
- Shenzhen University Health Science Center (CN)
- Guangdong Academy of Medical Sciences (CN)
- Sun Yat-sen University Cancer Center (CN)
- Guangdong Provincial People's Hospital (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2026-03-16
- DOI
- https://doi.org/10.1186/s13244-026-02227-2
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation