|▼ 110 (fortgesetzt)|
As a first step preceding the development of the differentiation model, during the analysis of the bone-joint behavior, it was demonstrated that bone quality is an important aspect to be considered. There are two possibilities of exploring the influence of this parameter on healing exist. It is possible to analyze the effect produced after changes in the initial elastic modulus of Young of the subchondral bone region, either by modeling the subchondral bone as a continuous field and to compare the amount and quality of the predicted tissues, or by constructing a detailed subchondral bone architecture with bone density distribution of different knee specimens. Independently of the selected way, the influence of the bone quality could clearly be established.
The healing of osteochondral defects is strongly influenced by mechanical conditions. Although the tissue differentiation model developed in this project used a simplified geometrical representation of the knee to analyze 1. the effect of changes in the defect size, 2. the influence of the local joint curvature and 3. the effect of using biomaterials to fill the defect, the results obtained were sufficient to predict the type of the newly differentiated tissues formed during healing. In every case, alterations in the mechanical environment produced measurable changes in the healing outcome. The defect was always filled with a mixture of hyaline and fibrous cartilage and never solely with hyaline cartilage, which was confirmed by clinical studies.
The results suggest that the mechanical environment required for osteochondral healing changes when the joint curvature is varied. It seems that the concave model resulted in the formation of cartilage of a higher quality (i.e. more hyaline cartilage was formed and the mechanical stiffness was higher) than with the convex model, but the rate of differentiation of the cancellous bone was slower than with the convex model. Comparing the stiffnesses of the surrounding tissues, the concave model resulted in tissues of a higher quality than with the convex model. However, no large differences were observed between the simulated healing patterns of the defects on concave and convex surfaces.
The algorithm meant that it was possible to find a mechanical explanation for the less favorable clinical outcome of defects localized on convex surfaces in comparison to those on concave ones. However, further analyses (for example in the form of longer, well documented animal experimentation) are necessary before such an algorithm can be applied to clinical cases. The effects of stiffness on healing should be taken into account when designing a biomaterial for filling osteochondral defects. The appropriate stiffness of this biomaterial could be determined preoperatively depending on the quantity and quality of predicted healing.
The differentiation model developed in this project could play a role in evaluating clinical situations by comparing the predicted healing and the observed process after surgery; thus detailed documentation of the healing process over a long time can be obtained.
This technique could be developed even further for use in conjunction with patient-specific data to predict the outcome of osteochondral repair. Although osteochondral repair is a very complex biological process, it appears to be important to consider mechanical factors that affect healing and that the process can be predicted accurately.
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