Three-Dimensional Radiomics and Machine Learning for Predicting Postoperative Outcomes in Laminoplasty for Cervical Spondylotic Myelopathy: A Clinical-Radiomics Model
This study validates the feasibility and superiority of three-dimensional radiomics combined with machine learning in predicting postoperative prognosis for CSM. The combination of radiomics features based on the narrowest segment and clinical features can yield a highly accurate prognosis prediction model, providing new insights for clinical assessment and individualized treatment decisions. Future studies need to further validate the stability and generalizability of this model in multicenter, large-sample cohorts.
Authors
- Ke Ma (ORCID: https://orcid.org/0000-0003-1257-6034)
- Haiying Liu (ORCID: https://orcid.org/0009-0001-4972-8719)
- Zhenqi Zhu (ORCID: https://orcid.org/0000-0001-7441-1433)
- Yan Liang (ORCID: https://orcid.org/0000-0002-5512-4030)
- Bin Zheng (ORCID: https://orcid.org/0000-0001-6001-3071)
Institutions
- Hebei North University (CN)
- Peking University (CN)
- Hospital of Hebei Province (CN)
- Zhangjiakou Academy of Agricultural Sciences (CN)
- Peking University People's Hospital (CN)
Publication Details
- Journal
- World Neurosurgery
- Published
- 2025-09-12
- DOI
- https://doi.org/10.1016/j.wneu.2025.124464
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00