Development and validation of a model predicting adrenal lipid-poor adenoma based on the minimum attenuation value from non-contrast CT: a dual-center retrospective study
The XGBoost predictive model based on minAVs demonstrates effective discrimination between adrenal lipid-poor adenomas and non-adenomas. The minAV variable is easily obtainable, and its diagnostic performance is comparable to that of the CTh model. This provides a basis for patient diagnosis and treatment plan selection.
Authors
- Hanlin Zhu (ORCID: https://orcid.org/0000-0001-6010-8505)
- Mengwei Wu
- Bo Feng (ORCID: https://orcid.org/0000-0002-1764-8028)
- Zhijiang Han
- Chunfeng Hu (ORCID: https://orcid.org/0000-0001-6804-7401)
- Haifeng Zhang (ORCID: https://orcid.org/0000-0002-9890-8345)
- Tong Zhang (ORCID: https://orcid.org/0009-0007-3940-356X)
Institutions
- Wenzhou Medical University (CN)
- Westlake University (CN)
- Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
- Hangzhou Red Cross Hospital (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2024-08-12
- DOI
- https://doi.org/10.1186/s12880-024-01392-4
- Primary Topic
- Adrenal and Paraganglionic Tumors
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Westlake University