A New Colour-Coded Imaging Method to Diagnose Gout
Why Did We Do This Research?
Gout is a very painful type of arthritis that involves a build up of crystals (tophi) within the joints. Unfortunately, the only way that doctors can currently diagnose gout is to draw fluid from an inflamed joint, which can be quite painful and is often not very accurate. Recently, a new body scanner called Dual Energy CT (DECT) has been shown to produce easy-to-read images of gout that actually colour-code the tophi in green, offering the potential to quickly diagnose gout without having to tap into a joint. This study aimed to determine how well DECT can diagnose gout compared to the old method.
What Did We Do and What Did We Find?
We asked 80 volunteers with gout or other types of arthritis to come by the Vancouver General Hospital to get DECT scans of their arms and legs. We found:
- DECT was accurately able to determine whether volunteers had gout or another type of arthritis
- Scans are easy to interpret by any trained professionals, as two radiologists who read the scans came to the same conclusions
- DECT was able to determine how severe the crystal build-up was among volunteers with gout
How Will This Study Improve the Treatment of Gout?
This study has shown that DECT can be used reliably as a tool to help diagnose gout, and rule out other types of arthritis. Our evidence has shown that patients may not have to wait until they have a gout attack to have fluid drawn from their joints before getting a diagnosis and starting their treatment. DECT can help doctors determine how well treatment is working for patients with gout, and adjust treatment strategies accordingly.
The Research Team
Principal Investigator:
Hyon Choi, MD, DrPH, FRCPC, Research Scientist, Rheumatology, Arthritis Research Canada (University of British Columbia)
Co-investigators
Lindsay C. Burns, BSc Kamran Shojania, MD Nicole Koenig, BA Graham Reid, MB ChB Mohammed Abufayyah, MD Genevieve Law, MD Alison S. Kydd, MD PhD Hugue Ouellette, MD Savvas Nicolaou, MD
Who Funded This Research?
This was an industry-sponsored project, with funding from Takeda Pharmaceuticals Inc.