Abstract
Multiple finite-element (FE) models to predict the biomechanical responses in the human brain resulting from the interaction with blast waves have established the importance of including the brain-surface convolutions, the major cerebral veins, and using non-linear brain-tissue properties to improve model accuracy. We hypothesize that inclusion of a more detailed network of cerebral veins and arteries can further enhance the model-predicted biomechanical responses and help identify correlates of blast-induced brain injury. To more comprehensively capture the biomechanical responses of human brain tissues to blast-wave exposure, we coupled a three-dimensional (3-D) detailed-vasculature human-head FE model, previously validated for blunt impact, with a 3-D shock-tube FE model. Using the coupled model, we computed the biomechanical responses of a human head facing an incoming blast wave for blast overpressures (BOPs) equivalent to 68, 83, and 104 kPa. We validated our FE model, which includes the detailed network of cerebral veins and arteries, the gyri and the sulci, and hyper-viscoelastic brain-tissue properties, by comparing the model-predicted intracranial pressure (ICP) values with previously collected data from shock-tube experiments performed on cadaver heads. In addition, 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 for the same blast-loading conditions. For the three BOPs, the predicted ICP values matched well with the experimental results in the frontal lobe, with peak-pressure differences of 4–11% and phase-shift differences of 9–13%. As expected, incorporating the detailed cerebral vasculature did not influence the ICP, however, it redistributed the peak brain-tissue strains by as much as 30% and yielded peak strain differences of up to 7%. When compared to existing reduced-vasculature FE models that only include the major cerebral veins, our high-fidelity model redistributed the brain-tissue strains in most of the brain, highlighting the importance of including a detailed cerebral vessel network in human-head FE models to more comprehensively account for the biomechanical responses induced by blast exposure.
Highlights
Blast-induced injuries resulting from exposure to improvised explosive devices are a major cause of mortality and morbidity of United States Service members deployed to Iraq and Afghanistan (Hoge et al, 2008; Elder and Cristian, 2009; Ritenour et al, 2010)
One way to assess the effects of blast-wave exposure on brain tissues is to use computational models to predict blast-induced biomechanical responses of the brain, such as pressure, stress, and strain, which we expect to correlate with observations of brain-tissue changes and damage (Morrison et al, 2011; Meaney et al, 2014)
Using a high-fidelity human-head FE model, we showed that inclusion of a detailed network of cerebral veins and arteries decreased brain-tissue strains in the human brain by as much as 28% for blunt impacts (Subramaniam et al, 2021)
Summary
Blast-induced injuries resulting from exposure to improvised explosive devices are a major cause of mortality and morbidity of United States Service members deployed to Iraq and Afghanistan (Hoge et al, 2008; Elder and Cristian, 2009; Ritenour et al, 2010). Mild primary injury can result from the interaction of a blast wave with the brain (Elder and Cristian, 2009), possibly caused by stress-wave propagation through the brain (Taylor and Ford, 2009), skull flexure (Bolander et al, 2011), cavitation effects (Goeller et al, 2012), or acceleration of the head (Gullotti et al, 2014). The model developed by Rodríguez-Millán et al contributed toward improving the anatomical description of the human head, they used linear viscoelastic material properties of the brain tissues, which could possibly limit the accuracy of the modelpredicted brain-tissue strains (de Rooij and Kuhl, 2016). Sarvghad-Moghaddam et al (2017), who used hyper-viscoelastic brain-tissue properties in their FE model to more precisely represent the non-linear material responses of human-brain tissues, found that the peak brain-tissue strains were one order of magnitude larger than those reported by Rodríguez-Millán et al for similar BOPs
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