Tissue-Level Regeneration and Remodeling Dynamics are Driven by Mechanical Stimuli in the Microenvironment in a Post-Bridging Loaded Femur Defect Healing Model in Mice

Mechanoregulation analysis of bone formation in tissue engineered constructs requires a volumetric method using time-lapsed micro-computed tomography

Bone can adapt its microstructure to mechanical loads through mechanoregulation of the (re)modeling process. This process has been investigated in vivo using time-lapsed micro-computed tomography (micro-CT) and micro-finite element (FE) analysis using surface-based methods, which are highly influenced by surface curvature. Consequently, when trying to investigate mechanoregulation in tissue engineered bone constructs, their concave surfaces make the detection of mechanoregulation impossible when using surface-based methods. In this study, we aimed at developing and applying a volumetric method to non-invasively quantify mechanoregulation of bone formation in tissue engineered bone constructs using micro-CT images and FE analysis. We first investigated hydroxyapatite scaffolds seeded with human mesenchymal stem cells that were incubated over 8 weeks with one mechanically loaded and one control group. Higher mechanoregulation of bone formation was measured in loaded samples with an area under the curve for the receiver operating curve (AUCformation) of 0.633-0.637 compared to non-loaded controls (AUCformation: 0.592-0.604) during culture in osteogenic medium (p<0.05). Furthermore, we applied the method to an in vivo mouse study investigating the effect of loading frequencies on bone adaptation. The volumetric method detected differences in mechanoregulation of bone formation between loading conditions (p<0.05). Mechanoregulation in bone formation was more pronounced (AUCformation: 0.609-0.642) compared to the surface-based method (AUCformation: 0.565-0.569, p<0.05). Our results show that mechanoregulation of formation in bone tissue engineered constructs takes place and its extent can be quantified with a volumetric mechanoregulation method using time-lapsed micro-CT and FE analysis. STATEMENT OF SIGNIFICANCE: Many efforts have been directed towards optimizing bone scaffolds for tissue growth. However, the impact of the scaffolds mechanical environment on bone growth is still poorly understood, requiring accurate assessment of its mechanoregulation. Existing surface-based methods were unable to detect mechanoregulation in tissue engineered constructs, due to predominantly concave surfaces in scaffolds. We present a volumetric approach to enable the precise and non-invasive quantification and analysis of mechanoregulation in bone tissue engineered constructs by leveraging time-lapsed micro-CT imaging, image registration, and finite element analysis. The implications of this research extend to diverse experimental setups, encompassing culture conditions, and material optimization, and investigations into bone diseases, enabling a significant stride towards comprehensive advancements in bone tissue engineering and regenerative medicine.

An in silico micro-multiphysics agent-based approach for simulating bone regeneration in a mouse femur defect model

Bone defects represent a challenging clinical problem as they can lead to non-union. In silico models are well suited to study bone regeneration under varying conditions by linking both cellular and systems scales. This paper presents an in silico micro-multiphysics agent-based (micro-MPA) model for bone regeneration following an osteotomy. The model includes vasculature, bone, and immune cells, as well as their interaction with the local environment. The model was calibrated by time-lapsed micro-computed tomography data of femoral osteotomies in C57Bl/6J mice, and the differences between predicted bone volume fractions and the longitudinal in vivo measurements were quantitatively evaluated using root mean square error (RMSE). The model performed well in simulating bone regeneration across the osteotomy gap, with no difference (5.5% RMSE, p = 0.68) between the in silico and in vivo groups for the 5-week healing period - from the inflammatory phase to the remodelling phase - in the volume spanning the osteotomy gap. Overall, the proposed micro-MPA model was able to simulate the influence of the local mechanical environment on bone regeneration, and both this environment and cytokine concentrations were found to be key factors in promoting bone regeneration. Further, the validated model matched clinical observations that larger gap sizes correlate with worse healing outcomes and ultimately simulated non-union. This model could help design and guide future experimental studies in bone repair, by identifying which are the most critical in vivo experiments to perform.