Application of Mechano-Regulatory Tissue Differentiation Theory in Tendon Attachment Scaffold Design - A Finite Element Study

The objective of this study was to investigate the reconstruction of tendon attachment to metallic implant. In order to mimic the structure, normal enthesis was first studied. A transition zone of multiple tissues including calcified and uncalcified fibrocartilage presents at most tendon entheses. Ingrowth of fibrous tissue into porous scaffold was studied using parametric finite element models as a potential method of attaching a tendon to a metal implant. The strongest attachment predicted by the model yielded a strength only 20% of the strength intact tendon attachment. To achieve attachment strength comparable to natural tendon attachment, a stronger transition zone simulating the normal tendon enthesis must be encouraged to form. The formation of different tissues from an initial population of stem cells after injury is referred to as tissue differentiation. Similar to adaptive tissue remodeling, the process is also regulated by mechanical stimuli. The quantitative biphasic mechano-regulatory tissue differentiation algorithm developed by Lacroix et al. [1] was studied in detail, and applied in three different situations. These studies discovered several aspects of the algorithms that could be improved. Addressing these issues, three major modifications of the tissue differentiation algorithm were proposed. First, tissue differentiation pathways observed in vivo were enforced. Second, a bone remodeling pathway based on the calculated strain energy density of the element was incorporated. Third, a dense fibrous tissue remodeling pathway based on the calculated tensile stress and hydrostatic pressure of the element was incorporated. The modified algorithm was applied to three situations and produced more accurate predictions compared with that made by the original algorithm. For example, the algorithm predicted full restoration of the bone morphology in the bone fracture healing simulation, and as micromotion at the bone-implant interface decreased, the algorithm predicted decrease of fibrous tissue formation and increase of bone ingrowth into the porous scaffold, which is consistent with previous experimental findings [2]. Taken together, the results of this research showed that mechano-regulatory models is capable of predicting tissue ingrowth into porous scaffold and can be useful for designing implant or ingrowth scaffold to stimulate ingrowth of different tissue, bone, dense fibrous tissue or fibrocartilage.