Predicting the cell differentiation of Pit-1 positivity of pituitary incidentaloma using radiomics analysis based on MRI
The findings of this study suggest that radiomics analysis combined with machine learning algorithms can effectively predict Pit-1 positivity in PIs using preoperative MRI images. This approach has the potential to identify high-risk PI subtypes at an earlier stage, thereby facilitating more timely clinical interventions.
Authors
- W Chen (ORCID: https://orcid.org/0000-0002-0579-6082)
- Chenfei Ye (ORCID: https://orcid.org/0000-0001-5265-3546)
- Xiaoxiao Zhao (ORCID: https://orcid.org/0000-0002-8006-6418)
- Mengqi Wang (ORCID: https://orcid.org/0000-0002-3565-0455)
- Xutao Guo (ORCID: https://orcid.org/0000-0001-6191-2204)
- Chengbin Duan
- Shun Yao
Institutions
- Sun Yat-sen University (CN)
- Shenzhen Institute of Information Technology (CN)
- Harbin Institute of Technology (CN)
- Sixth Affiliated Hospital of Sun Yat-sen University (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Shenzhen Second People's Hospital (CN)
Publication Details
- Journal
- Clinical Radiology
- Published
- 2025-10-30
- DOI
- https://doi.org/10.1016/j.crad.2025.107147
- Primary Topic
- Pituitary Gland Disorders and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00