Bone remodelling prediction using mechanical stimulus with bone connectivity theory in porous implants

Abstract

Strain energy density (SED) is considered to be the primary remodelling stimulus influencing the process of bone growth into porous implants. A bone remodelling algorithm incorporating the concept of bone connectivity, that newly formed bone should only grow from existing bone, was developed to provide a more biologically realistic simulation of bone growth. Results showed that the new algorithm prevented the occurrence of unconnected mature bone within porous implants, an unrealistic phenomenon observed using conventional adaptive elasticity theories. The bone connectivity algorithm had minimal effect (0.67% difference) on the final bone density distribution for standard bending and torsional moment cases. For a porous implant model, both algorithms, with and without bone connectivity implementation, reached the same final stiffness, with a difference of less than 0.01%. The bone connectivity algorithm predicted a slower and more gradual bone remodelling process, requiring at least 50% additional time for full remodelling compared to the conventional adaptive elasticity algorithm, which should be accounted for in the planning of rehabilitation strategies. The developed modelling can be employed to improve porous implant designs to achieve better clinical outcomes.