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Abstract
Economic costs of osteoarthritis (OA) are considerable. However, there are no clinical tools to predict the progression of OA or guide patients to a correct treatment for preventing OA. We tested the ability of our cartilage degeneration algorithm to predict the subject-specific development of OA and separate groups with different OA levels. The algorithm was able to predict OA progression similarly with the experimental follow-up data and separate subjects with radiographical OA (Kellgren-Lawrence (KL) grade 2 and 3) from healthy subjects (KL0). Maximum degeneration and degenerated volumes within cartilage were significantly higher (p < 0.05) in OA compared to healthy subjects, KL3 group showing the highest degeneration values. Presented algorithm shows a great potential to predict subject-specific progression of knee OA and has a clinical potential by simulating the effect of interventions on the progression of OA, thus helping decision making in an attempt to delay or prevent further OA symptoms.
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1 Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
2 Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland; Medical Research Center, University of Oulu and Oulu University Hospital, Oulu, Finland
3 Department of Physical and Rehabilitation Medicine, Helsinki University Hospital, Helsinki, Finland; University of Helsinki, Helsinki, Finland
4 Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland; Medical Research Center, University of Oulu and Oulu University Hospital, Oulu, Finland; Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland
5 Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Centre, Kuopio University Hospital, Kuopio, Finland