Bi-parametric MRI-based quantification radiomics model for the noninvasive prediction of histopathology and biochemical recurrence after prostate cancer surgery: a multicenter study
The combined model developed in this study, which is not dependent on pathologic biopsies, can noninvasively predict postoperative histopathology and BCR after PCa, therefore may provide decision support for follow-up and treatment strategies for patients in the postoperative period.
Authors
- Fan Ping (ORCID: https://orcid.org/0000-0001-7650-6612)
- Si Wu (ORCID: https://orcid.org/0000-0001-8056-4997)
- Tianqi Xu (ORCID: https://orcid.org/0000-0003-3256-3820)
- Pengxi Han
- Ximing Wang (ORCID: https://orcid.org/0000-0003-0185-2988)
- Ying Wang (ORCID: https://orcid.org/0000-0002-1407-2668)
- Mian Zhang (ORCID: https://orcid.org/0000-0003-2464-361X)
- Yiming Song (ORCID: https://orcid.org/0000-0002-6934-5395)
- Yan Deng (ORCID: https://orcid.org/0000-0002-9215-3244)
Institutions
- Weifang Medical University (CN)
- Shandong University (CN)
- Shandong Provincial Hospital (CN)
- Shandong Provincial QianFoShan Hospital (CN)
- Qilu Hospital of Shandong University (CN)
Publication Details
- Journal
- Abdominal Radiology
- Published
- 2025-03-17
- DOI
- https://doi.org/10.1007/s00261-025-04873-4
- Citations
- 5
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 6.80
Funders
- National Natural Science Foundation of China