A comprehensive analysis of magnetic resonance imaging and laboratory features in pyogenic, tuberculous, brucellar, and fungal spondylitis
A predictive model integrating imaging and clinical features effectively differentiates the four major types of infectious spondylitis, enhancing diagnostic accuracy. The online application extends the practical utility of our findings.
Authors
- Pengying Li
- Gang Wu (ORCID: https://orcid.org/0000-0002-4764-8272)
- Zhihao Xu
- Wei Xiong (ORCID: https://orcid.org/0000-0003-3189-4767)
- Shen Zhou (ORCID: https://orcid.org/0000-0001-5682-2589)
- Weijian Zhu (ORCID: https://orcid.org/0000-0002-2120-5860)
- Fei Zhao (ORCID: https://orcid.org/0009-0004-7792-5607)
Institutions
- Jinan University (CN)
- Shanxi Medical University (CN)
- Second Hospital of Shanxi Medical University (CN)
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-09-24
- DOI
- https://doi.org/10.21037/qims-2025-605
- Citations
- 1
- Primary Topic
- Sarcoidosis and Beryllium Toxicity Research
- Type
- article
- Field-Weighted Citation Impact
- 1.16