The aim of this work was to develop a novel, accessible and low-cost method, which is sufficient to measure changes in meniscal position in a whole-knee joint model performing dynamic motion in a knee simulator.

An optical tracking method using motion markers, MATLAB (MATLAB, The MathWorks Inc.) and a miniature camera system (Raspberry Pi, UK) was developed. Method feasibility was assessed on porcine whole joint knee samples (n = 4) dissected and cemented to be used in the simulator (1). Markers were placed on three regions (medial, posterior, anterior) of the medial meniscus with corresponding reference markers on the tibial plateau, so the relative meniscal position could be calculated. The Leeds high kinematics gait profile scaled to the parameters of a pig (1, 2) was driven in displacement control at 0.5 Hz. Videos were recorded at cycle-3 and cycle-50. Conditions tested were the capsule retained (intact), capsule removed and a medial posterior root tear. Mean relative displacement values were taken at time-points relating to the peaks of the axial force and flexion-extension gait inputs, as well as the range between the maximum and minimum values. A one-way ANOVA followed by Tukey post hoc analysis were used to assess differences (p = 0.05).

The method was able to measure relative meniscal displacement for all three meniscal regions. The medial region showed the greatest difference between the conditions. A significant increase (p < 0.05) for the root tear condition was found at 0.28s and 0.90s (axial load peaks) during cycle-3. Mean relative displacement for the root tear condition decreased by 0.29 mm between cycle-3 and cycle-50 at the 0.28s time-point. No statistically significant differences were found when ranges were compared at cycle-3 and cycle-50.

The method was sensitive to measure a substantial difference in medial-lateral relative displacement between an intact and a torn state. Meniscus extrusion was detected for the root tear condition throughout test duration. Further work will progress onto human specimens and apply an intervention condition.

A pre-clinical experimental simulation model has been previously successfully developed, and was shown to have the potential for investigation of the biomechanical and tribological performance of early stage knee therapies. In order to investigate interventions that may necessitate sacrifice of the natural ligaments, it is necessary to replicate their function. This study investigated the most effective spring constraint conditions for the porcine knee model with the aim of replicating the natural ligament function.

The replication of natural ligament function was achieved through the use of physical springs in the anterior-posterior (AP) axis. Spring-9 (9 N/mm) and spring-20 (20 N/mm) were set at different free lengths in a natural knee simulator. The A/P displacement and shear force outputs from porcine knee samples (N=6) were measured and the most appropriate spring setting was determined by comparing the outputs at different spring settings with intact knee.

The A/P displacement of both spring-9 and spring-20 showed similar shapes to the all ligament control. Spring-9 with a free length of 4 mm and spring-20 with a free length of 5 mm showed minimal differences in A/P displacement output compared to the all ligament controls. There was no statistical difference between the two minimal differences either in A/P displacement or in shear force (paired t-test, p>0.05), which indicated that both conditions were appropriate spring constraint settings for the natural porcine knee model.

A porcine knee simulation model with refined spring constraint conditions was successfully developed in this study. Human knee model is currently under investigation using the methodology developed in porcine knee model, which will be more appropriate to investigate the effect of early stage knee therapies on the tribological function of the natural knee.

Objectives

Given the function of adiponectin (ADIPOQ) on the inflammatory condition of obesity and osteoarthritis (OA), we hypothesized that the ADIPOQ gene might be a candidate gene for a marker of susceptibility to OA.