Artificial intelligence in osteoporosis assessment using CT imaging: a scoping review
Current evidence shows that AI-enhanced CT can achieve diagnostic and screening performance comparable to DXA and QCT, although fracture-risk prediction still requires improvement through multimodal data integration. However, methodological heterogeneity and the lack of standardized workflows limit cross-study comparability and clinical translation. Integrating AI into routine CT pipelines may reduce screening costs, enable earlier detection and intervention, and help mitigate the global burden of osteoporosis.
Authors
- Y Y zhang
- Yuhui Kou
- Yi Yang (ORCID: https://orcid.org/0000-0002-8917-2196)
- Meng Meng (ORCID: https://orcid.org/0009-0004-4293-786X)
- Yuyang Ran
- Hanwen Cheng
- Simin Liu
Institutions
- China Aerospace Science and Industry Corporation (China) (CN)
- Changzhi Medical College (CN)
- Peking University (CN)
- Second Affiliated Hospital of Guangzhou Medical University (CN)
- Peking University People's Hospital (CN)
- Guangzhou Medical University (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2026-02-24
- DOI
- https://doi.org/10.3389/fmed.2026.1779483
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00