RESUMO
BACKGROUND AND OBJECTIVE: Distraction osteogenesis (DO) is a mechanobiological process of producing new bone by gradual and controlled distraction of the surgically separated bone segments. Mice have been increasingly used to study the role of relevant biological factors in regulating bone regeneration during DO. However, there remains a lack of in silico DO models and related mechano-regulatory tissue differentiation algorithms for mouse bone. This study sought to establish an in silico model based on in vivo experimental data to simulate the bone regeneration process during DO of the mouse femur. METHODS: In vivo micro-CT, including time-lapse morphometry was performed to monitor the bone regeneration in the distraction gap. A 2D axisymmetric finite element model, with a geometry originating from the experimental data, was created. Bone regeneration was simulated with a fuzzy logic-based two-stage (distraction and consolidation) mechano-regulatory tissue differentiation algorithm, which was adjusted from that used for fracture healing based on our in vivo experimental data. The predictive potential of the model was further tested with varied distraction frequencies and distraction rates. RESULTS: The computational simulations showed similar bone regeneration patterns to those observed in the micro-CT data from the experiment throughout the DO process. This consisted of rapid bone formation during the first 10 days of the consolidation phase, followed by callus reshaping via bone remodeling. In addition, the computational model predicted a faster and more robust bone healing response as the model's distraction frequency was increased, whereas higher or lower distraction rates were not conducive to healing. CONCLUSIONS: This in silico model could be used to investigate basic mechanobiological mechanisms involved in bone regeneration or to optimize DO strategies for potential clinical applications.
