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Abstract
Osteoarthritis (OA) is a degenerative and the most common joint disease that is affecting a large population nowadays. The cartilage surfaces affected by OA contain information about its degradation process and the different factors that cause this process. Studying the surface topography of human cartilage in different OA grade conditions, using 3D texture parameters, will reveal the surface features of diseased cartilage in a quantitative and objective manner and assist in understanding the degradation process. The purposes of this project were (a) to develop sample preparation procedures for imaging hydrated human cartilage samples using laser scanning confocal microscopy, and (b) to identify the numerical parameters that could effectively describe the distinct cartilage surface morphologies for each OA grade. Human knee cartilage samples with three different OA grades (OA I, II and III) were imaged using laser scanning microscopy (LSM) and analysed using 35 numerical parameters. A statistical method called two-stage nested design was used to determinate the most effective numerical parameters that could describe changes in the surface conditions of human knee cartilage affected by OA. The most effective and reliable numerical parameter describing the progression of the degraded cartilage surface was the Sdc10_50 parameter followed by the Sq and Sa parameters. This study has demonstrated that the changes in the surface morphologies of OA cartilage can be characterised quantitatively and the distinctive surface feature is a bearing area related property. The surface feature described by the Sdc10_50 parameter can be used not only to describe the OA grade progression of human knee cartilage, but also to identify the influence of the different factor that increase the OA and to reveal any dependence of the surface topography and the structural condition of the articular cartilage.