Author:

Keywords:

Science & Technology, Life Sciences & Biomedicine, Technology, Biophysics, Engineering, Biomedical, Engineering, tissue differentiation, bone chamber, numerical simulation, mechanobiology, finite element analysis, ENDOTHELIAL GROWTH-FACTOR, TITANIUM IMPLANTS, MECHANO-REGULATION, BIOPHYSICAL STIMULI, ARTICULAR-CARTILAGE, TIBIAL FRACTURES, DIFFERENTIATION, REPAIR, REGENERATION, MICROMOTION, GROWTH-FACTOR, MARROW, CELLS, Animals, Biomechanical Phenomena, Bone and Bones, Cartilage, Cell Differentiation, Computer Simulation, Connective Tissue, Female, Finite Element Analysis, Guided Tissue Regeneration, Implants, Experimental, Models, Biological, Rabbits, Tibia, endothelial growth-factor, titanium implants, mechano-regulation, biophysical stimuli, articular-cartilage, tibial fractures, differentiation, repair, regeneration, micromotion, 0903 Biomedical Engineering, 0913 Mechanical Engineering, 1106 Human Movement and Sports Sciences, Biomedical Engineering, 4003 Biomedical engineering, 4207 Sports science and exercise

Abstract:

Several mechanoregulatory tissue differentiation models have been proposed over the last decade. Corroboration of these models by comparison with experimental data is necessary to determine their predictive power. So far, models have been applied with various success rates to different experimental set-ups investigating mainly secondary fracture healing. In this study, the mechanoregulatory models are applied to simulate the implant osseointegration process in a repeated sampling in vivo bone chamber, placed in a rabbit tibia. This bone chamber provides a mechanically isolated environment to study tissue differentiation around titanium implants loaded in a controlled manner. For the purpose of this study, bone formation around loaded cylindrical and screw-shaped implants was investigated. Histologically, no differences were found between the two implant geometries for the global amount of bone formation in the entire chamber. However, a significantly larger amount of bone-to-implant contact was observed for the screw-shaped implant compared to the cylindrical implant. In the simulations, a larger amount of bone was also predicted to be in contact with the screw-shaped implant. However, other experimental observations could not be predicted. The simulation results showed a distribution of cartilage, fibrous tissue and (im)mature bone, depending on the mechanoregulatory model that was applied. In reality, no cartilage was observed. Adaptations to the differentiation models did not lead to a better correlation between experimentally observed and numerically predicted tissue distribution patterns. The hypothesis that the existing mechanoregulatory models were able to predict the patterns of tissue formation in the in vivo bone chamber could not be fully sustained.