Machine learning model based on preoperative MRI and clinical data for predicting pancreatic fistula after pancreaticoduodenectomy
The machine learning model using preoperative multi-sequence MRI radiomic features showed moderate predictive value for CR-POPF risk, which was significantly enhanced by integrating BMI.
Authors
- Yan Piao (ORCID: https://orcid.org/0000-0002-4668-1193)
- Zhenhao Liu (ORCID: https://orcid.org/0000-0003-4465-5925)
- Zhenghan Yang (ORCID: https://orcid.org/0000-0003-3986-1732)
- Hui Xu (ORCID: https://orcid.org/0000-0002-0932-5026)
- Zhixiang Wang (ORCID: https://orcid.org/0000-0002-9091-2673)
- Xiaoyang Li (ORCID: https://orcid.org/0000-0002-0238-3848)
- Tianxin Cheng (ORCID: https://orcid.org/0009-0009-0503-7877)
- Hongwei Wu (ORCID: https://orcid.org/0009-0001-0987-4391)
- Kun Liu (ORCID: https://orcid.org/0000-0002-7077-6117)
- Kuinan Tong
Institutions
- Changzhi Medical College (CN)
- Beijing Friendship Hospital (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1186/s12880-025-01951-3
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China