Abstract
BackgroundMultiple studies describing human head finite element (FE) models have established the importance of including the major cerebral vasculature to improve the accuracy of the model predictions. However, a more detailed network of cerebral vasculature, including the major veins and arteries as well as their branch vessels, can further enhance the model-predicted biomechanical responses and help identify correlates to observed blunt-induced brain injury.MethodsWe used an anatomically accurate three-dimensional geometry of a 50th percentile U.S. male head that included the skin, eyes, sinuses, spine, skull, brain, meninges, and a detailed network of cerebral vasculature to develop a high-fidelity model. We performed blunt trauma simulations and determined the intracranial pressure (ICP), the relative displacement (RD), the von Mises stress, and the maximum principal strain. We validated our detailed-vasculature model by comparing the model-predicted ICP and RD values with experimental measurements. To quantify the influence of including a more comprehensive network of brain vessels, we compared the biomechanical responses of our detailed-vasculature model with those of a reduced-vasculature model and a no-vasculature model.ResultsFor an inclined frontal impact, the predicted ICP matched well with the experimental results in the fossa, frontal, parietal, and occipital lobes, with peak-pressure differences ranging from 2.4% to 9.4%. For a normal frontal impact, the predicted ICP matched the experimental results in the frontal lobe and lateral ventricle, with peak-pressure discrepancies equivalent to 1.9% and 22.3%, respectively. For an offset parietal impact, the model-predicted RD matched well with the experimental measurements, with peak RD differences of 27% and 24% in the right and left cerebral hemispheres, respectively. Incorporating the detailed cerebral vasculature did not influence the ICP but redistributed the brain-tissue stresses and strains by as much as 30%. In addition, our detailed-vasculature model predicted strain reductions by as much as 28% when compared to current reduced-vasculature FE models that only include the major cerebral vessels.ConclusionsOur study highlights the importance of including a detailed representation of the cerebral vasculature in FE models to more accurately estimate the biomechanical responses of the human brain to blunt impact.
Highlights
The Centers for Disease Control and Prevention (CDC) has identified traumatic brain injury (TBI) as one of the major causes of mortality in the U.S, annually contributing to nearly 30% of all injury-related deaths [1]
Translation of the head resulting from a normal or tangential impact can potentially increase the pressure in the head [3], which is hypothesized to cause focal injuries depending on the maximum pressure experienced by the head over the duration of the blunt impact
Comparisons of the reduced- and no-vasculature models with the detailed-vasculature model revealed no differences in the magnitude or time course of the simulated intracranial pressure (ICP)
Summary
The Centers for Disease Control and Prevention (CDC) has identified traumatic brain injury (TBI) as one of the major causes of mortality in the U.S, annually contributing to nearly 30% of all injury-related deaths [1]. In a 2013 study, the CDC reported approximately 2.8 million cases of TBI resulting from motor vehicle accidents, falls, and other blunt loads to the head, including 282,000 TBI-related hospitalizations and 56,000 deaths [2]. Tangential impacts occur frequently in motor vehicle accidents and falls, and cause both translation and rotation of the head [4]. Translation of the head resulting from a normal or tangential impact can potentially increase the pressure in the head [3], which is hypothesized to cause focal injuries depending on the maximum pressure experienced by the head over the duration of the blunt impact. A more detailed network of cerebral vasculature, including the major veins and arteries as well as their branch vessels, can further enhance the model-predicted biomechanical responses and help identify correlates to observed blunt-induced brain injury
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