Developing tools to predict and understand patterns of knee pain
Official title: Computational Tools for Predicting and Understanding Knee Pain Spatial Patterns
Funded at University of Arizona · NIH-10984178 · Data updated 2026-11-12
This study is looking at how knee pain from osteoarthritis can change over time and how it relates to what doctors see in MRI scans, with the goal of helping people manage their knee pain better.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Arizona NIH-funded |
| Lab location | 1 site (Tucson, United States) |
| Project start | September 26, 2024 |
| Project end | August 31, 2026 |
| Funding year | 2024 |
| Award (this year) | $348,680 |
| NIH project number | 1R21AR083495-01A1 |
| Project ID | NIH-10984178 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals diagnosed with osteoarthritis who experience knee pain.
✕Less likely to help
Patients without knee pain or those not diagnosed with osteoarthritis may not benefit from this research.
What this research studies
This research focuses on osteoarthritis, a common condition affecting knee joints and causing significant pain and disability. The project aims to create computational tools that can accurately predict different patterns of knee pain and understand how these patterns relate to structural changes in the knee, as seen in MRI scans. By analyzing data on knee pain reporting and structural abnormalities, the researchers hope to provide insights that can lead to better management of knee pain in patients. The study emphasizes the importance of early detection and interpretation of knee pain patterns to improve patient outcomes.
Why it matters
Potential benefit: If successful, this research could lead to more effective treatments and management strategies for patients suffering from knee pain due to osteoarthritis.
How similar studies have gone: Previous research has shown promise in using computational tools for pain prediction, indicating that this approach could yield valuable insights.
Where this research is happening
-
University of Arizona
Tucson, United States Active
Researchers
- Principal investigator: Sun, Xiaoxiao — University of Arizona
- Study coordinator: Sun, Xiaoxiao
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.