Development of a continuum-based, meshless, finite element modeling approach for representation of trabecular bone indentation.

Implant subsidence into the underlying trabecular bone is a common problem in orthopaedic surgeries; however, the ability to pre-operatively predict implant subsidence remains limited. Current state-of-the-art computational models for predicting subsidence have issues addressing this clinical problem, often resulting from the size and complexity of existing subject-specific, image-based finite element (FE) models. The current study aimed to develop a simplified approach to FE modeling of subject-specific trabecular bone indentation resulting from implant penetration. Confined indentation experiments of human trabecular bone with flat- and sharp-tip indenters were simulated using FE analysis. A generalized continuum-level approach using a meshless smoothed particle hydrodynamics (SPH) approach and an isotropic crushable foam (CF) material model was developed for the trabecular bone specimens. Five FE models were generated with CF material parameters calibrated to cadaveric specimens spanning a range of bone mineral densities (BMD). Additionally, an alternative model configuration was developed that included consideration of bone marrow, with bone and marrow material parameters assigned to elements randomly according to bone volume (BV%) measurements of experimental specimens, owing to the non-uniform nature of trabecular bone tissue microstructure. Statistical analysis found significant correlation between the shapes of the numerical and experimental force-displacement curves. FE models accurately captured the bone densification patterns observed experimentally. Inclusion of marrow elements offered improved response prediction of the flat-tip indenter tests. Ultimately, the developed approach demonstrates the ability of a generalizable continuum-level SPH approach to capture bone variability using clinical bone imaging metrics without needing detailed image-based geometries, a significant step towards simplified subject-specific modeling of implant subsidence.

Brain Material Properties and Integration of Arachnoid Complex for Biofidelic Impact Response for Human Head Finite Element Model.

Finite element head models offer great potential to study brain-related injuries; however, at present may be limited by geometric and material property simplifications required for continuum-level human body models. Specifically, the mechanical properties of the brain tissues are often represented with simplified linear viscoelastic models, or the material properties have been optimized to specific impact cases. In addition, anatomical structures such as the arachnoid complex have been omitted or implemented in a simple lumped manner. Recent material test data for four brain regions at three strain rates in three modes of loading (tension, compression, and shear) was used to fit material parameters for a hyper-viscoelastic constitutive model. The material model was implemented in a contemporary detailed head finite element model. A detailed representation of the arachnoid trabeculae was implemented with mechanical properties based on experimental data. The enhanced head model was assessed by re-creating 11 ex vivo head impact scenarios and comparing the simulation results with experimental data. The hyper-viscoelastic model faithfully captured mechanical properties of the brain tissue in three modes of loading and multiple strain rates. The enhanced head model showed a high level of biofidelity in all re-created impacts in part due to the improved brain-skull interface associated with implementation of the arachnoid trabeculae. The enhanced head model provides an improved predictive capability with material properties based on tissue level data and is positioned to investigate head injury and tissue damage in the future.

Spinal Cord Boundary Conditions Affect Brain Tissue Strains in Impact Simulations.

Brain and spinal cord injuries have devastating consequences on quality of life but are challenging to assess experimentally due to the traumatic nature of such injuries. Finite element human body models (HBM) have been developed to investigate injury but are limited by a lack of biofidelic spinal cord implementation. In many HBM, brain models terminate with a fixed boundary condition at the brain stem. The goals of this study were to implement a comprehensive representation of the spinal cord into a contemporary head and neck HBM, and quantify the effect of the spinal cord on brain deformation during simulated impacts. Spinal cord tissue geometries were developed, based on 3D medical imaging and literature data, meshed, and implemented into the GHBMC 50th percentile male model. The model was evaluated in frontal, lateral, rear, and oblique impact conditions, and the resulting maximum principal strains in the brain tissue were compared, with and without the spinal cord. A new cumulative strain curve metric was proposed to quantify brain strain distribution. Presence of the spinal cord increased brain tissue strains in all simulated cases, owing to a more compliant boundary condition, highlighting the importance of the spinal cord to assess brain response during impact.

Comparison of numerical methods for cerebrospinal fluid representation and fluid-structure interaction during transverse impact of a finite element spinal cord model.

Spinal cord impacts can have devastating consequences. Computational models can investigate such impacts but require biofidelic numerical representations of the neural tissues and fluid-structure interaction with cerebrospinal fluid. Achieving this biofidelity is challenging, particularly for efficient implementation of the cerebrospinal fluid in full computational human body models. The goal of this study was to assess the biofidelity and computational efficiency of fluid-structure interaction methods representing the cerebrospinal fluid interacting with the spinal cord, dura, and pia mater using experimental pellet impact test data from bovine spinal cords. Building on an existing finite element model of the spinal cord and pia mater, an orthotropic hyperelastic constitutive model was proposed for the dura mater and fit to literature data. The dura mater and cerebrospinal fluid were integrated with the existing finite element model to assess four fluid-structure interaction methods under transverse impact: Lagrange, pressurized volume, smoothed particle hydrodynamics, and arbitrary Lagrangian-Eulerian. The Lagrange method resulted in an overly stiff mechanical response, whereas the pressurized volume method over-predicted compression of the neural tissues. Both the smoothed particle hydrodynamics and arbitrary Lagrangian-Eulerian methods were able to effectively model the impact response of the pellet on the dura mater, outflow of the cerebrospinal fluid, and compression of the spinal cord; however, the arbitrary Lagrangian-Eulerian compute time was approximately five times higher than smoothed particle hydrodynamics. Crucial to implementation in human body models, the smoothed particle hydrodynamics method provided a computationally efficient and representative approach to model spinal cord fluid-structure interaction during transverse impact.

A Hyper-Viscoelastic Continuum-Level Finite Element Model of the Spinal Cord Assessed for Transverse Indentation and Impact Loading.

Finite Element (FE) modelling of spinal cord response to impact can provide unique insights into the neural tissue response and injury risk potential. Yet, contemporary human body models (HBMs) used to examine injury risk and prevention across a wide range of impact scenarios often lack detailed integration of the spinal cord and surrounding tissues. The integration of a spinal cord in contemporary HBMs has been limited by the need for a continuum-level model owing to the relatively large element size required to be compatible with HBM, and the requirement for model development based on published material properties and validation using relevant non-linear material data. The goals of this study were to develop and assess non-linear material model parameters for the spinal cord parenchyma and pia mater, and incorporate these models into a continuum-level model of the spinal cord with a mesh size conducive to integration in HBM. First, hyper-viscoelastic material properties based on tissue-level mechanical test data for the spinal cord and hyperelastic material properties for the pia mater were determined. Secondly, the constitutive models were integrated in a spinal cord segment FE model validated against independent experimental data representing transverse compression of the spinal cord-pia mater complex (SCP) under quasi-static indentation and dynamic impact loading. The constitutive model parameters were fit to a quasi-linear viscoelastic model with an Ogden hyperelastic function, and then verified using single element test cases corresponding to the experimental strain rates for the spinal cord (0.32-77.22 s-1) and pia mater (0.05 s-1). Validation of the spinal cord model was then performed by re-creating, in an explicit FE code, two independent ex-vivo experimental setups: 1) transverse indentation of a porcine spinal cord-pia mater complex and 2) dynamic transverse impact of a bovine SCP. The indentation model accurately matched the experimental results up to 60% compression of the SCP, while the impact model predicted the loading phase and the maximum deformation (within 7%) of the SCP experimental data. This study quantified the important biomechanical contribution of the pia mater tissue during spinal cord deformation. The validated material models established in this study can be implemented in computational HBM.

Importance of passive muscle, skin, and adipose tissue mechanical properties on head and neck response in rear impacts assessed with a finite element model.

OBJECTIVE: The objective of this study was to improve head-neck kinematic predictions of a contemporary finite element (FE) head-neck model, assessed in rear impact scenarios (3-10 g), by including an accurate representation of the skin, adipose tissue, and passive muscle mechanical properties. The soft tissues of the neck have a substantial contribution to kinematic response, with the contribution being inversely proportional to the impact severity. Thus accurate representation of these passive tissues is critical for the assessment of kinematic response and the potential for crash induced injuries. Contemporary Human Body Models (HBMs) often incorporate overly stiff mechanical properties of passive tissues for numerical stability, which can affect the predicted kinematic response of the head and neck. METHODS: Soft tissue material properties including non-linearity, compression-tension asymmetry, and viscoelasticity were implemented in constitutive models for the skin, adipose, and passive muscle tissues, based on experimental data in the literature. A quasi-linear viscoelastic formulation was proposed for the skin, while a phenomenological hyper-viscoelastic model was used for the passive muscle and adipose tissues. A head-neck model extracted from a contemporary FE HBM was updated to include the new tissue models and assessed using head rotation angle for rear impact scenarios (3 g, 7 g, and 10 g peak accelerations), and compared to postmortem human surrogate (PMHS) data for 7 g impacts. RESULTS: The head rotation angle increased with the new material models for all three rear impact cases: (3 g: +43%, 7 g: +52%, 10 g: +71%), relative to the original model. The increase in head rotation was primarily attributed to the improved skin model, with the passive muscle being a secondary contributor to the increase in response. A 52% increase in head rotation for the 7 g impact improved the model response with respect to PMHS data, placing it closer to the experimental average, compared to the original model. CONCLUSIONS: The improved skin, adipose tissue, and passive muscle material model properties, based on published experimental data, increased the neck compliance in rear impact, with improved correspondence to published PMHS test data for medium severity impacts. Future studies will investigate the coupled effect of passive and active muscle tissue for low severity impacts.