Comparison of porcine brain mechanical properties to potential tissue simulant materials in quasi-static and sinusoidal compression

Characterization and selection of a skull surrogate for the development of a biofidelic head model

This research paper explores the advancement of physical models simulating the human skull-brain complex, focusing on applications in simulating mild Traumatic Brain Injury (mTBI). Existing models, especially head forms, lack biofidelity in accurately representing the native structures of the skull, limiting the understanding of intracranial injury parameters beyond kinematic head accelerations. This study addresses this gap by investigating the use of additive manufacturing (AM) techniques to develop biofidelic skull surrogates. Materials such as Polylactic Acid (PLA), a bone-simulant PLA variant, and Hydroxyapatite-coated Poly(methyl methacrylate) (PMMA) were used to create models tested for their flexural modulus and strength. The trabecular bone regions were simulated by adjusting infill densities (30%, 50%, 80%) and print raster directions, optimizing manufacturing parameters for biofidelic performance. Among the tested materials, PLA and its bone-simulating variant printed at 80% infill density with a side (tangential) print orientation demonstrated the closest approximation to the mechanical properties of cranial bone, yielding a mean flexural modulus of 1337.2 MPa and a mean ultimate strength of 56.9 MPa. Statistical analyses showed that infill density significantly influenced the moduli and strength of the printed simulants. Digital Image Correlation (DIC) corroborated the comparable performance of the simulants, showing similar strain and displacement behaviors to native skull bone. Notably, the performance of the manufactured cortical and trabecular regions underscored their crucial role in achieving biofidelity, with the trabecular structure providing critical dampening effects when the native bone is loaded. This study establishes PLA, particularly its bone-simulant variant, as an optimal candidate for cranial bone simulants, offering significant potential for developing more accurate biofidelic head models in mTBI research.

Anatomical Features and Material Properties of Human Surrogate Head Models Affect Spatial and Temporal Brain Motion under Blunt Impact

Traumatic brain injury (TBI) is a biomechanical problem where the initiating event is dynamic loading (blunt, inertial, blast) to the head. To understand the relationship between the mechanical parameters of the injury and the deformation patterns in the brain, we have previously developed a surrogate head (SH) model capable of measuring spatial and temporal deformation in a surrogate brain under blunt impact. The objective of this work was to examine how material properties and anatomical features affect the motion of the brain and the development of injurious deformations. The SH head model was modified to study six variables independently under blunt impact: surrogate brain stiffness, surrogate skull stiffness, inclusion of cerebrospinal fluid (CSF), head/skull size, inclusion of vasculature, and neck stiffness. Each experimental SH was either crown or frontally impacted at 1.3 m/s (3 mph) using a drop tower system. Surrogate brain material, the Hybrid III neck stiffness, and skull stiffness were measured and compared to published properties. Results show that the most significant variables affecting changes in brain deformation are skull stiffness, inclusion of CSF and surrogate brain stiffness. Interestingly, neck stiffness and SH size significantly affected the strain rate only suggesting these parameters are less important in blunt trauma. While the inclusion of vasculature locally created strain concentrations at the interface of the artery and brain, overall deformation was reduced.

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.

Dermal tissue penetration of in-plane silicon microneedles evaluated in skin-simulating hydrogel, rat skin and porcine skin

Recently, microneedle-based sensors have been introduced as novel strategy for in situ monitoring of biomarkers in the skin. Here, in-plane silicon microneedles with different dimensions and shapes are fabricated and their ability to penetrate skin is evaluated. Arrays with flat, triangular, hypodermic, lancet and pencil-shaped microneedles, with lengths of 500-1000 μm, widths of 200-400 μm and thickness of 180-500 μm are considered. Fracture force is higher than 20 N for all microneedle arrays (MNA) confirming a high mechanical stability of the microneedles. Penetration force in skin-simulating hydrogels, excised rat abdominal skin and porcine ear skin is at least five times lower than the fracture force for all MNA designs. The lowest force for skin penetration is required for triangular microneedles with a low width and thickness. Skin tissue staining and histological analysis of rat abdominal skin and porcine ear skin confirm successful penetration of the epidermis for all MNA designs. However, the penetration depth is between 100 and 300 μm, which is considerably lower than the microneedle length. Tissue damage estimated by visual analysis of the penetration hole is smallest for triangular microneedles. Penetration ability and tissue damage are compared to the skin prick test (SPT) needle applied in allergy testing.

A Biphasic Fluid-Structure Interaction Model of Backflow During Infusion Into Agarose Gel

The efficacy of convection-enhanced delivery as a technique to treat disorders of the central nervous system is limited by backflow, in which the infused fluid flows backward along surface of the catheter rather than toward the targeted area. In order to improve treatment protocols, finite element models of backflow have been developed to understand the underlying physics. García et al. (2013, "Description and Validation of a Finite Element Model of Backflow During Infusion Into a Brain Tissue Phantom," ASME J. Comput. Nonlinear Dyn., 8(1), p. 011017) presented a finite element model that accounted for the flow in the annular gap that develops between the tissue and the outer surface of the catheter by using a layer of biphasic elements with a formula for the axial hydraulic conductivity to represent annular Poiseuille flow. In this study, we present a generalization of that model using fluid-FSI and biphasic-FSI elements that are recently available in febio. We demonstrate that our model of a 0.98 mm radius catheter is able to reproduce experimental backflow lengths and maximum fluid pressures for infusions into a brain tissue surrogate and that it agrees well with the previous model by García et al. (2013, "Description and Validation of a Finite Element Model of Backflow During Infusion Into a Brain Tissue Phantom," ASME J. Comput. Nonlinear Dyn., 8(1), p. 011017). The model predicts that the backflow length and the total amount of flow into the hemispherical region forward of the catheter tip is comparable for two different catheter sizes, albeit at a higher fluid pressure for the smaller catheter. This biphasic-FSI model has the potential to be extended to a stepped catheter geometry, which has been shown in experiments to be successful in controlling backflow.

Rate- and Region-Dependent Mechanical Properties of Göttingen Minipig Brain Tissue in Simple Shear and Unconfined Compression

Traumatic brain injury (TBI), particularly from explosive blasts, is a major cause of casualties in modern military conflicts. Computational models are an important tool in understanding the underlying biomechanics of TBI but are highly dependent on the mechanical properties of soft tissue to produce accurate results. Reported material properties of brain tissue can vary by several orders of magnitude between studies, and no published set of material parameters exists for porcine brain tissue at strain rates relevant to blast. In this work, brain tissue from the brainstem, cerebellum, and cerebrum of freshly euthanized adolescent male Göttingen minipigs was tested in simple shear and unconfined compression at strain rates ranging from quasi-static (QS) to 300 s-1. Brain tissue showed significant strain rate stiffening in both shear and compression. Minimal differences were seen between different regions of the brain. Both hyperelastic and hyper-viscoelastic constitutive models were fit to experimental stress, considering data from either a single loading mode (unidirectional) or two loading modes together (bidirectional). The unidirectional hyper-viscoelastic models with an Ogden hyperelastic representation and a one-term Prony series best captured the response of brain tissue in all regions and rates. The bidirectional models were generally able to capture the response of the tissue in high-rate shear and all compression modes, but not the QS shear. Our constitutive models describe the first set of material parameters for porcine brain tissue relevant to loading modes and rates seen in blast injury.

Influence of surrogate scalp material and thickness on head impact responses: Toward a biofidelic head-brain physical model

Advanced physical head models capable of replicating both global kinematics and intracranial mechanics of the human head are required for head injury research and safety gear assessment. These head surrogates require a complex design to accommodate realistic anatomical details. The scalp is a crucial head component, but its influence on the biomechanical response of such head surrogates remains unclear. This study aimed to evaluate the influence of surrogate scalp material and thickness on head accelerations and intraparenchymal pressures using an advanced physical head-brain model. Scalp pads made from four materials (Vytaflex20, Vytaflex40, Vytaflex50, PMC746) and each material with four thicknesses (2, 4, 6, and 8 mm) were evaluated. The head model attached to the scalp pad was dropped onto a rigid plate from two heights (5 and 19.5 cm) and at three head locations (front, right side, and back). While the selected materials' modulus exhibited a relatively minor effect on head accelerations and coup pressures, the effect of scalp thickness was shown to be major. Moreover, by decreasing the thickness of the head's original scalp by 2 mm and changing the original scalp material from Vytaflex 20 to Vytaflex 40 or Vytaflex 50, the head acceleration biofidelity ratings could improve by 30% and approached the considered rating (0.7) of good biofidelity. This study provides a potential direction for improving the biofidelity of a novel head model that might be a useful tool in head injury research and safety gear tests. This study also has implications for selecting appropriate surrogate scalps in the future design of physical and numerical head models.

Correlating the microstructural architecture and macrostructural behaviour of the brain

The computational simulation of pathological conditions and surgical procedures, for example the removal of cancerous tissue, can contribute crucially to the future of medicine. Especially for brain surgery, these methods can be important, as the ultra-soft tissue controls vital functions of the body. However, the microstructural interactions and their effects on macroscopic material properties remain incompletely understood. Therefore, we investigated the mechanical behaviour of brain tissue under three different deformation modes, axial tension, compression, and semi-confined compression, in different anatomical regions, and for varying axon orientation. In addition, we characterised the underlying microstructure in terms of myelin, cells, glial cells and neuron area fraction, and density. The correlation of these quantities with the material parameters of the anisotropic Ogden model reveals a decrease in shear modulus with increasing myelin area fraction. Strikingly, the tensile shear modulus correlates positively with cell and neuronal area fraction (Spearman's correlation coefficient of r_s=0.40 and r_s=0.33), whereas the compressive shear modulus decreases with increasing glial cell area (r_s=-0.33). Our study finds that tissue non-linearity significantly depends on the myelin area fraction (r_s=0.47), cell density (r_s=0.41) and glial cell area (r_s=0.49). Our results provide an important step towards understanding the micromechanical load transfer that leads to the non-linear macromechanical behaviour of the brain. STATEMENT OF SIGNIFICANCE: Within this article, we investigate the mechanical behaviour of brain tissue under three different deformation modes, in different anatomical regions, and for varying axon orientation. Further, we characterise the underlying microstructure in terms of various constituents. The correlation of these quantities with the material parameters of the anisotropic Ogden model reveals a decrease in shear modulus with increasing myelin area fraction. Strikingly, the tensile shear modulus correlates positively with cell and neuronal area fraction, whereas the compressive shear modulus decreases with increasing glial cell area. Our study finds that tissue non-linearity significantly depends on the myelin area fraction, cell density, and glial cell area. Our results provide an important step towards understanding the micromechanical load transfer that leads to the non-linear macromechanical behaviour of the brain.

Tissue-Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models

Brain tissue is one of the most complex and softest tissues in the human body. Due to its ultrasoft and biphasic nature, it is difficult to control the deformation state during biomechanical testing and to quantify the highly nonlinear, time-dependent tissue response. In numerous experimental studies that have investigated the mechanical properties of brain tissue over the last decades, stiffness values have varied significantly. One reason for the observed discrepancies is the lack of standardized testing protocols and corresponding data analyses. The tissue properties have been tested on different length and time scales depending on the testing technique, and the corresponding data have been analyzed based on simplifying assumptions. In this review, we highlight the advantage of using nonlinear continuum mechanics based modeling and finite element simulations to carefully design experimental setups and protocols as well as to comprehensively analyze the corresponding experimental data. We review testing techniques and protocols that have been used to calibrate material model parameters and discuss artifacts that might falsify the measured properties. The aim of this work is to provide standardized procedures to reliably quantify the mechanical properties of brain tissue and to more accurately calibrate appropriate constitutive models for computational simulations of brain development, injury and disease. Computational models can not only be used to predictively understand brain tissue behavior, but can also serve as valuable tools to assist diagnosis and treatment of diseases or to plan neurosurgical procedures. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

Cavitation nucleation and its ductile-to-brittle shape transition in soft gels under translational mechanical impact

Cavitation bubbles in the human body, when subjected to impact, are being increasingly considered as a possible brain injury mechanism. However, the onset of cavitation and its complex dynamics in biological materials remain unclear. Our experimental results using soft gels as a tissue simulant show that the critical acceleration (a_cr) at cavitation nucleation monotonically increases with increasing stiffness of gelatin A/B, while a_cr for agarose and agar initially increases but is followed by a plateau or even decrease after stiffness reach to ∼100 kPa. Our image analyses of cavitation bubbles and theoretical work reveal that the observed trends in a_cr are directly linked to how bubbles grow in each gel. Gelatin A/B, regardless of their stiffness, form a localized damaged zone (tens of nanometers) at the gel-bubble interface during bubble growth. In contrary, the damaged zone in agar/agarose becomes significantly larger (> 100 times) with increasing shear modulus, which triggers the transition from formation of a small, damaged zone to activation of crack propagation. STATEMENT OF SIGNIFICANCE: We have studied cavitation nucleation and bubble growth in four different types of soft gels (i.e., tissue simulants) under translational impact. The critical linear acceleration for cavitation nucleation has been measured in the simulants by utilizing a recently developed method that mimics acceleration profiles of typical head blunt events. Each gel type exhibits significantly different trends in the critical acceleration and bubble shape (e.g., A gel-specific sphere-to-saucer transition) with increasing gel stiffness. Our theoretical framework, based on the concepts of a damaged zone and crack propagation in each gel, explains underlying mechanisms of the experimental observations. Our in-depth studies shed light on potential links between traumatic brain injuries and cavitation bubbles induced by translational acceleration, the overlooked mechanism in the literature.

Modeling Traumatic Brain Injury in Human Cerebral Organoids

Traumatic brain injury (TBI) is a head injury that disrupts the normal brain structure and function. TBI has been extensively studied using various in vitro and in vivo models. Most of the studies have been done with rodent models, which may respond differently to TBI than human nerve cells. Taking advantage of the recent development of cerebral organoids (COs) derived from human induced pluripotent stem cells (iPSCs), which resemble the architecture of specific human brain regions, here, we adapted the controlled cortical impact (CCI) model to induce TBI in human COs as a novel in vitro platform. To adapt the CCI procedure into COs, we have developed a phantom brain matrix, matching the mechanical characteristics of the brain, altogether with an empty mouse skull as a platform to allow the use of the stereotactic CCI equipment on COs. After the CCI procedure, COs were histologically prepared to evaluate neurons and astrocyte populations using the microtubule-associated protein 2 (MAP2) and the glial fibrillary acidic protein (GFAP). Moreover, a marker of metabolic response, the neuron-specific enolase (NSE), and cellular death using cleaved caspase 3 were also analyzed. Our results show that human COs recapitulate the primary pathological changes of TBI, including metabolic alterations related to neuronal damage, neuronal loss, and astrogliosis. This novel approach using human COs to model TBI in vitro holds great potential and opens new alternatives for understanding brain abnormalities produced by TBI, and for the development and testing of new therapeutic approaches.

Prediction of subdural haematoma based on a detailed numerical model of the cerebral bridging veins

Traumatic brain injury is one of the major causes of death and disability in the world. One of the most frequent and deadly injury resulted from a head trauma is acute subdural haematoma (ASDH), which consists on the rupture of a bridging vein (BV). Given the importance of this type of injury, it is necessary to correctly assess thresholds and damage criteria, which is difficult to perform on human cadavers or animals, due to ethical and economical issues. Finite element (FE) models are a very good and cost-effective alternative. Once properly validated, a finite element head model (FEHM) becomes a valuable tool, that can be used in the development of head protective gear as a design tool and in the reconstruction of head traumas by predicting brain injuries under impact conditions. The YEt Another Head Model (YEAHM) is one example of a FE model that can be used to assist/replace the experimental tests. In this study, the bridging veins model from YEAHM was improved and validated by comparing its results with others reported in literature and estimating the success rate. At the end, it was developed a pressurised tubular shaped FE model of BVs, considering the blood pressure in cerebral veins. Results showed a maximum success rate of 90%, which in comparison with other FE models available in the literature, presents an equal or even better ASDH prediction success rate.

Ballistic gelatine-what we see and what we get

Since decades, 10% gelatine is used to visualize and estimate the energy transfer of projectiles. The study performed investigates the correlation of the temporary cavity (TC) recorded by high-speed video (HSV) and the cracks in gelatine slices. A total of 36 shots were performed from distance using form-stable bullets (FMJ), 12 using deforming bullets (HP) in the calibres .32 auto, .38 special and 9 mm Luger. The target models were prepared according to Fackler's standard as 10% gelatine cubes with 12 cm edge length doped with a paint pad beneath the front cover ("reference cube"). Scaled images of the TC were recorded with 40.000 fps. The cubes were cut into 1-cm-thick gelatine cross sections, which were scanned. The evaluation of the destruction (cracks) was performed by the mean of image analysis measuring the longest crack, the wound profile according to Fackler and applying the polygon method. The height of the TC was measured each cm along the bullet path. The energy deposited ranged between 54 and 269 J. FMJ caused tubular, HP provoked pear-like TC. The tubular aspect was consistent with the quasi-constant deceleration of FMJ; however, the pear-like TC did not metrically represent the deceleration of HP. The profiles of destruction parameters were convex for both projectile types and did not match the profile of bullet deceleration. The maximum of TC stretching observed in HSV did not coincide with maximum gelatine destruction (crack lengths). The total energy transfer correlated with all considered destruction parameters in their sum; however, the cross-sectional parameters did not reflect the energy transfer per centimetre bullet path. The sum of the TC's heights correlated with the energy deposited, but differently for FMJ and HP. Obviously, the 12-cm reference cube reflects the energy transfer by a bullet as a whole.