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Evaluation of Musculoskeletal Aging and Related Disorders Via Advanced Clinical Imaging
Sponsor: Peking University People's Hospital
Summary
Study Overview This clinical research focuses on the development and validation of a multimodal artificial intelligence (AI) platform designed for the automated diagnosis and precise staging of two major musculoskeletal conditions: Osteoporosis (OP) and Osteoarthritis (OA). By integrating diverse clinical imaging data, the study aims to provide a more objective and standardized approach to assessing bone and joint degeneration. Technological Core: Intelligent Staging Traditional diagnosis often relies on manual interpretation, which can lead to inter-observer variability. This study employs deep learning and multimodal imaging to: For Osteoporosis: Automatically quantify bone mineral density and micro-architectural changes to determine the stage of bone loss and evaluate fracture risk. For Osteoarthritis: Identify subtle radiological markers such as joint space narrowing and osteophyte formation to categorize the severity of joint degeneration according to international staging standards (e.g., Kellgren-Lawrence scale). Why This Matters Early Intervention: By identifying early-stage changes in bone density and joint integrity, clinicians can implement preventive treatments before significant disability occurs. Standardized Care: The intelligent diagnostic model provides a "digital second opinion," ensuring consistent staging across different healthcare settings. Efficiency: The automated workflow reduces the workload of radiologists while maintaining high diagnostic accuracy. Ethical Compliance The study is conducted at Peking University People's Hospital under the supervision of the Institutional Review Board (Approval No. 2026PHB097-001). It strictly adheres to international ethical standards, including the Declaration of Helsinki and Good Clinical Practice (GCP) guidelines, to ensure patient data privacy and safety.
Official title: A Comprehensive Evaluation of Musculoskeletal Aging and Degenerative Pathologies Using Multi-modal Clinical Imaging and Quantitative Analysis.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
2000
Start Date
2005-11-01
Completion Date
2026-12-31
Last Updated
2026-03-19
Healthy Volunteers
Yes
Conditions
Interventions
No Interventions
No Interventions
Locations (1)
Beijing, China