Accurate determination of wear and loosening of knee prostheses from routine radiographs.
A statistical shape model approach
- Jochem Nagels, MD
- Edward R. Valstar, MSc, PhD
- Eric H. Garling, PhD
- Prof. J.H.C. Reiber, PhD (Image processing)
- Berend C. Stoel, PhD (Image processing)
- Boudewijn P.F. Leliefeldt, MSc, PhD (Image processing)
- Charl P. Botha, PhD (Med. Visualisation, Delft University of Technolgoy, Delft, The Netherlands)
Emiel van IJsseldijk
- Statistical Shape Models
- Model-based RSA
Dutch Arthritis Association (in dutch: Reumafonds)
Yearly, 750.000 knee prostheses are placed worldwide. It is expected that these numbers will increase significantly in the near future (14% / year) due to aging societies and a trend to treat younger osteoarthritis patients with a prosthesis. At ten year postoperatively, about 10% of these prostheses has to be replaced. Mostly because of wear of the bearing and/or loosening. It is of important to detect wear and loosening of the prosthesis in time since earlier surgery might be limited to replacement of the worn bearing, thus postponing or even preventing revision surgery replacing all components.
Current visual evaluation of radiographs to detect wear and loosening of knee prostheses has large variations, reducing its validity in clinical practice.
The research goal is to improve the routine diagnosis by objectively and accurately detecting wear and/or loosening of knee prostheses from routine roentgen radiographs at an early stage, (before the patient complains about pain). To this end a computer aided diagnostic system needs to be developed.
These objective data can be used in clinical studies aiming for improving the treatment of patients with knee prostheses. In addition to this, these measurements will also be used to distinguish prostheses “at-risk” for loosening and/or wear from “stable” prostheses. By this, the visits to the out patient clinic can be differentiated: A “stable” prosthesis is checked every 5 year, while a prosthesis “at-risk” is checked every year. In the end, the reduction in the number of radiological check-ups gives more efficiency, shorter waiting lists, prevention of unnecessary radiation to the patient, and a significant reduction of the costs.