Patient-specific numerical simulation of the bone healing process including implant materials and gait conditions

Numerical simulations in biomechanics, particularly in bone healing, present a cost-effective option compared to experiments that demand prolonged observations with human or with animal models. However, to define in-silico simulations of the bone healing process requires considering multiple factors, such as the implant design and patient’s characteristics. As a result, the current challenge is integrating different numerical methodologies to simulate bone healing, aiming to facilitate the emergence of innovative clinical treatments and new implant designs.

In this paper, we present a patient-specific numerical methodology to simulate the bone healing process, able to consider patient’s load conditions and bone density distribution provided by CT-scans. The main novelty is the combination of the Cartesian grid Finite Element Method (cgFEM) with a bone callus healing model, complemented by a load-condition optimisation scheme to relate implant materials and load conditions while ensuring successful healing outcome.

This numerical methodology creates a finite element model based on the patient’s medical image, serving as a virtual testing tool for investigating the influence of implant materials on gait pattern requirements to ensure an optimal healing outcome. In practice, a personalised bone fracture model was employed to evaluate four distinct implant materials: two conventional materials (stainless steel and titanium) and two bioabsorbable candidates (polylactic acid plastic (PLA) and magnesium). The results offer personalised optimal load conditions for each studied material, showcasing the potential of in-silico studies in minimising uncertainties associated with exploring new clinical treatments.