Development of a subject-specific finite element analysis workflow to assess local biomechanics during segmental bone defect healing

Longitudinal estimation of local strain distributions within the regenerative niche of segmental femoral fractures is important for understanding mechanobiology principles for bone healing to design more effective rehabilitation regimens and mitigate nonunion complications. Finite element (FE) modeling is the standard for investigating these biomechanical parameters, yet most existing models lack clinical relevance due to their use of generic data and computational inefficiency. This study developed a subject-specific FE workflow aimed at accurate biomechanical predictions based on subject-specific data while addressing the limitations of previous approaches. For the experimental study, near-critical-sized segmental bone defects were created in the femurs of Wistar rats and stabilized with internal fixators before rehabilitation. Subject-specific geometries of the defect were generated from in vivo micro-CT scans, which were also used to assign material coefficients. Generalized geometries of the cortical and trabecular bone and fixator were integrated to increase computational efficiency. In addition, axial strain data from strain gauges on the fixators were used to define subject-specific boundary conditions, enabling a longitudinal study of the healing process. Sensitivity analyses revealed that incorporating subject-specific boundary conditions significantly enhanced model accuracy, a factor often overlooked in conventional approaches. The workflow was used to build six defect models to approximate compressive strains within the defect and the joint contact force. Strain distributions correlated with experimentally observed mineralization and better predicted functional bone bridging (union) compared to bone volume metrics. This efficient workflow facilitates the assessment of local biomechanics during bone healing and highlights their influence on adaptive regeneration. Further, the findings support the potential application of the subject-specific modeling workflow to guide clinical decision-making and improve therapeutic outcomes for treating bone fractures.