Graduate from the Department of Biomedical Engineering New York University Westlake, Ohio, United States
Introduction: : Traumatic brain injury (TBI) is an injury to the brain as a result of an applied external force, such as a blow to the head. More than 2.8 x 10⁶ patients in the United States experience TBI with over 60,000 TBI-related deaths. The trauma experienced by the brain after injury can be classified as a dynamic loading event, inducing rapid deformation of brain tissue. Researchers have used a range of experimental setups to measure intracranial deformation including surrogate head models equipped with accelerometers and strain gages to measure skull deformation and head kinematics. Previous research by Hanna et al. documented the development of a full-scale half-skull model mounted on a Hybrid III neck subjected to frontal and crown impact from a drop tower. Finite element analysis (FEA) is a valuable tool for researchers to investigate TBI, allowing for the simulation of complex mechanical responses of brain tissue during and following impacts. While FEA can bridge the gap between mechanical impact and brain tissue response providing excellent spatial and temporal resolution, the model must be validated against experimental data such as through previous research utilizing surrogate head models. This investigation documents the development of an FEA model utilizing Fusion based on the experimental model by Hanna et al. After initial static stress simulations modeling impact as a single 500 N load, dynamic simulations were performed utilizing a full sized, magnesium impactor incorporating initial linear velocity and acceleration values measured by Hanna et al.
Materials and
Methods: : The constructed FEA model included a half skull made of modeled polyether ether ketone (PEEK) housing a half brain composed of 20% ballistics gel, mounted on a modeled Hybrid III neck. The modeled vertebrae were composed of steel with butyl rubber inserts between each plate modeling the intervertebral discs. The end of the connecting rod and the C4 vertebrae plate was fixed to mimic how the base of the model was fixed in Hanna et al. Key differences between the FEA model and the experimental model include a simplified ellipsoid geometry for the skull and brain based on previous literature. Elements corresponding to the half skull and brain were determined from the analyzed data using ParaView and MATLAB. A thin slice at the frontal plane of approximately 2 mm was made to isolate elements of the brain with the highest maximum shear strain. Equivalent strain was defined as the magnitude from the combination of six strain tensor components. Maximum principal shear strain was calculated as the absolute value of the difference between the maximum and minimum principal strains: γ = |ε₁ – ε₃|. Measured velocities used in the simulations were 1.34 m/s (3 mph) and 2.23 m/s (5 mph), comparable to head impacts in low-speed pedestrian accidents. A proposed head injury risk threshold of 15% strain correlates with preclinical models associated with a 50% risk of diffuse axonal injury (DAI), so the percentage area of brain with shear strains above 0.15 for each scenario was calculated and compared.
Results, Conclusions, and Discussions:: Calculated maximum shear data experienced within the half skull components of the model following coronal impact was also successfully pulled based on quantitatively filtered elements utilizing MATLAB. The heat maps generated from the 5 mph crown and frontal impact simulations compare well to the deformation pattern and maximum shear strain experienced in the experimental model. The statistical distribution of the surrogate brain response following each injury simulation is within range of the results achieved experimentally. In running ANOVA amongst the four groups of maximum shear strain for each injury scenario, it was found that all impact scenarios were found to be significantly different p < 0.05. Further, the distribution of the percentage area of shear strains greater than 0.15 found within the compared simulated impacts matches very well with the percentage distribution in the experimental modeled impact comparison. The dynamic event simulations experience similar shear strain values in the surrogate brain to that of the experimental model. This demonstrates the potential that FEA possesses to enhance experimental efforts in quantifying brain deformation under impact and how further refinement of these dynamic simulations can contribute to the development of more accurate and predictive tools for researchers studying TBI mechanisms. Ultimately with a more robust FEA software able to handle longer simulation durations than 3 ms, better comparisons can be made to the experimental model. Although previous literature had successfully shown that the use of a simplified skull model is satisfactory in characterizing the mechanical properties of the skull and brain, incorporation of the actual half skull and brain model used experimentally within these dynamic event simulations will provide greater and truer comparison. However, this investigation provides a starting point and successful proof of concept in FEA validating experimental impact testing. Additional simulations should be run to gain a greater sample pool of data to more accurately compare the experiment’s multiple impact trials for each injury scenario. Further modeling and development of a dynamic collision simulation will help in the development of a more accurate and predictive tool for researchers to utilize towards investigating TBI and clinical outcomes/treatment.
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