RESUMEN
PURPOSE: To compare the mechanical stress applied to our grafted defect area according to the diameter of the plugs used in the treatment of osteochondral lesion with osteochondral autograft transplantation (OAT) procedure. METHODS: A biomechanical study was conducted on eight cadaveric knees. A 20-mm defect was created in the weight-bearing zone on the medial femoral condyle then filled either with three plugs of 8 mm, or with four plugs of 6 mm, or with 6 plugs of 4 mm diameter. After the preparation of the specimens, each knee was installed on a mechanical test bench (Instron 5566A). A continuous axial compression of 700 N at 10 mm.min-1 was exerted on the joint. A K-scan 4000-type pressure sheet was used to record the contact area (mm2), the mean pressure (MPa), and the maximum pressure (MPa) on the area of interest. RESULTS: The differences found between the conditions were not statistically significant but showed tendencies. Filling the defect with six plugs of 4 mm restores a larger contact surface compared with the other plugs. The use of 8- and 6-mm grafts lead to a respective increase of 12% and 52% of the mean pressure compared with the 4 mm grafts. This difference was also found for the maximum pressure (36% and 129%). Regardless of the diameter of the plugs used, filling the lesion reduces the mean pressure exerted on the healthy cartilage by 19%. DISCUSSION: A trend emerged towards a better restoration of the cartilage surface and a more harmonious distribution of the pressures exerted in favour of the grafts of smaller diameter. A larger study is needed to obtain a statistically significant result.
Asunto(s)
Cartílago Articular , Cartílago , Humanos , Autoinjertos , Cartílago/trasplante , Articulación de la Rodilla/cirugía , Trasplante Autólogo , Rodilla , Cartílago Articular/cirugíaRESUMEN
Osteoarthritis (OA) is a common degenerative disease whose early management includes promising mechanical treatments. New treatments are initially validated using an animal model in which OA is induced. The MMT (mechanical induction) and MIA (chemical induction) models of OA induction are widespread, but their use to generate early OA is poorly documented. We analyzed and compared early-stage knee OA-induction via these two methods in 16 rats divided into two groups. After 4 weeks of induction, the knees were sampled and studied using both histology (Toluidine Blue and Sirius Red) and surface topology, an innovative technique for characterizing osteoarthritic cartilage. The Mankin-modified score confirms that the two OA-induction models evolved at the same speed. At this early stage, the two models can be differentiated morphologically, although no significant differences were revealed by either cellularity or birefringence analysis. However, the topological analysis generated two forms of quantitative data, the deformation ratio and the cohesion index, that differentiated between the two groups. Thus, the early-stage OA induced by these two models is revealed to differ. The patterns of cartilage damage induced point to MMT as the better choice to assess mechanical approaches to clinical OA treatment.
Asunto(s)
Artritis Experimental/patología , Osteoartritis de la Rodilla/patología , Animales , Cartílago Articular/patología , Modelos Animales de Enfermedad , Masculino , Ratas , Ratas Sprague-DawleyRESUMEN
Increasing use of patient-specific surgical procedures in orthopaedics means that patient-specific anatomical coordinate systems (ACSs) need to be determined. For knee bones, automatic algorithms constructing ACSs exist and are assumed to be more reliable than manual methods, although both approaches are based on non-unique numerical reconstructions of true bone geometries. Furthermore, determining the best algorithms is difficult, as algorithms are evaluated on different datasets. Thus, in this study, we developed 3 algorithms, each with 3 variants, and compared them with 5 from the literature on a dataset comprising 24 lower-limb CT-scans. To evaluate algorithms' sensitivity to the operator-dependent reconstruction procedure, the tibia, patella and femur of each CT-scan were each reconstructed once by three different operators. Our algorithms use principal inertia axis (PIA), cross-sectional area, surface normal orientations and curvature data to identify the bone region underneath articular surfaces (ASs). Then geometric primitives are fitted to ASs, and the ACSs are constructed from the geometric primitive points and/or axes. For each bone type, the algorithm displaying the least inter-operator variability is identified. The best femur algorithm fits a cylinder to posterior condyle ASs and a sphere to the femoral head, average axis deviations: 0.12°, position differences: 0.20â¯mm. The best patella algorithm identifies the AS PIAs, average axis deviations: 0.91°, position differences: 0.19â¯mm. The best tibia algorithm finds the ankle AS center and the 1st PIA of a layer around a plane fitted to condyle ASs, average axis deviations: 0.38°, position differences: 0.27â¯mm.