Multi-Physics Smoothed Particle Hydrodynamics Implementation to Enhance Vertebral Fracture Prediction in a Finite Element Model of a Lower Cervical Spine Segment Under Compression

Abstract

Events such as vehicle rollovers can lead to compression of the spine and vertebral fractures. Bone fragments from vertebral fracture displace, or occlude, the spinal canal, deforming the spinal cord and leading to the potential of a spinal cord injury (SCI). Finite element (FE) human body models (HBMs) provide an opportunity to predict vertebral fractures and investigate SCIs. Models such as the Global Human Body Models Consortium (GHBMC) model use strain-based element erosion to model hard tissue fracture by removing elements from the simulation upon reaching threshold strains. While strain-based element erosion allows for the prediction of fracture initiation, the method results in the loss of hard tissue material. Under compression, the loss of hard tissue material limits the post-fracture predictive ability of the model due to the loss of structural support and absence of fractured material that may occlude the spinal canal. The objective of the work in this thesis was the implementation of a multi-physics modelling approach to combine strain-based element erosion with smoothed particle hydrodynamics (SPH) to preserve hard tissue material and simulate the movement of fractured material under central compression in a C5-C6-C7 cervical segment FE model. The implementation of SPH was then assessed by comparing the response of the segment model to experimental results and by evaluating SPH particle dependency. Finally, a parametric study was conducted using the model with the SPH implementation to investigate the response of the FE segment model under varied impact severities, aged hard tissue material parameters, and eccentric loading. The model with the SPH implementation was numerically stable and was found to improve the prediction of the trend and magnitude of the force-displacement response, with the area under the curve compared to the experimental response improving from a 34% difference to a 4% difference. Additionally, the implementation of SPH allowed for modelling the flow of hard tissue material and, consequently, occlusion of the spinal canal. The prediction of maximum occlusion in the model compared to the experiments improved from a 137% difference to a 5% difference. Increasing the number of SPH particles generated for each solid element showed numerical instability, illustrating a need for compatibility between the size of the solid element and the number of SPH particles. Varying the impact severity of the central compression load showed that the occlusion in the FE segment model appeared to have a greater dependency on the maximum displacement applied in compression rather than the maximum velocity of the impact due to the amount of fractured material in the simulation. Applying hard tissue material parameters representative of an older age group resulted in higher occlusion and a lower force-displacement response, in agreement with experimental data. The resulting multi-physics approach improved the model predictive capabilities in all cases. Future research will include a spinal cord in the FE segment model to more accurately assess changes in the spinal canal geometry and potential for SCI.