Traumatic brain injury is a leading cause of disability and mortality. Finite element-based head models are promising tools for enhanced head injury prediction, mitigation and prevention. The reliability of such models depends heavily on adequate representation of the brain-skull interaction. Nevertheless, the brain-skull interface has been largely simplified in previous three-dimensional head models without accounting for the fluid behaviour of the cerebrospinal fluid (CSF) and its mechanical interaction with the brain and skull. In this study, the brain-skull interface in a previously developed head model is modified as a fluid-structure interaction (FSI) approach, in which the CSF is treated on a moving mesh using an arbitrary Lagrangian-Eulerian multi-material formulation and the brain on a deformable mesh using a Lagrangian formulation. The modified model is validated against brain-skull relative displacement and intracranial pressure responses and subsequently imposed to an experimentally determined loading known to cause acute subdural haematoma (ASDH). Compared to the original model, the modified model achieves an improved validation performance in terms of brain-skull relative motion and is able to predict the occurrence of ASDH more accurately, indicating the superiority of the FSI approach for brain-skull interface modelling. The introduction of the FSI approach to represent the fluid behaviour of the CSF and its interaction with the brain and skull is crucial for more accurate head injury predictions.

Periventricular injury is frequently noted as one aspect of severe traumatic brain injury (TBI) and the presence of the ventricles has been hypothesized to be a primary pathogenesis associated with the prevalence of periventricular injury in patients with TBI. Although substantial endeavors have been made to elucidate the potential mechanism, a thorough explanation for this hypothesis appears lacking. In this study, a three-dimensional (3D) finite element (FE) model of the human head with an accurate representation of the cerebral ventricles is developed accounting for the fluid properties of the intraventricular cerebrospinal fluid (CSF) as well as its interaction with the brain. An additional model is developed by replacing the intraventricular CSF with a substitute with brain material. Both models are subjected to rotational accelerations with magnitudes suspected to induce severe diffuse axonal injury. The results reveal that the presence of the ventricles leads to increased strain in the periventricular region, providing a plausible explanation for the vulnerability of the periventricular region. In addition, the strain-exacerbation effect associated with the presence of the ventricles is also noted in the paraventricular region, although less pronounced than that in the periventricular region. The current study advances the understanding of the periventricular injury mechanism as well as the detrimental effects that the ventricles exert on the periventricular and paraventricular brain tissue.

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Acute subdural hematoma (ASDH) due to bridging vein (BV) rupture is a frequent and lethal head injury, especially in the elderly. Brain atrophy has been hypothesized to be a primary pathogenesis associated with the increased risk of ASDH in the elderly. Though decades of biomechanical endeavours have been made to elucidate the potential mechanisms, a thorough explanation for this hypothesis appears lacking. Thus, a recently improved finite element head model, in which the brain-skull interface was modelled using a fluid-structure interaction (FSI) approach with special treatment of the cerebrospinal fluid as arbitrary Lagrangian-Eulerian fluid formulation, is used to partially address this understanding gap. Models with various degrees of atrophied brains and thereby different subarachnoid thicknesses are generated and subsequently exposed to experimentally determined loadings known to cause ASDH or not. The results show significant increases in the cortical relative motion and BV strain in the atrophied brain, which consequently exacerbates the ASDH risk in the elderly. Results of this study are suggested to be considered while developing age-adapted protecting strategies for the elderly in the future.

Wearable devices have been shown to effectively measure the head's movement during impacts in sports like American football. When a head impact occurs, the device is triggered to collect and save the kinematic measurements during a predefined time window. Then, based on the collected kinematics, finite element (FE) head models can calculate brain strain, which is used to evaluate the risk of mild traumatic brain injury. To find a time window that can provide a sufficient duration of kinematics for FE analysis, we investigated 118 on-field video-confirmed head impacts collected by the Stanford Instrumented Mouthguard. Because the individual differences in brain geometry influence these calculations, we included six representative brain geometries and found that larger brains need a longer time window of kinematics for accurate calculation. Among the different sizes of brains, a pre-trigger time of 20 ms and a post-trigger time of 70 ms were found to yield calculations of brain strain and strain rate that were not significantly different from calculations using the original 200 ms time window recorded by the mouthguard.

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Hippocampal injury is common in traumatic brain injury (TBI) patients, but the underlying pathogenesis remains elusive. In this study, we hypothesize that the presence of the adjacent fluid-containing temporal horn exacerbates the biomechanical vulnerability of the hippocampus. Two finite element models of the human head were used to investigate this hypothesis, one with and one without the temporal horn, and both including a detailed hippocampal subfield delineation. A fluid-structure interaction coupling approach was used to simulate the brain-ventricle interface, in which the intraventricular cerebrospinal fluid was represented by an arbitrary Lagrangian-Eulerian multi-material formation to account for its fluid behavior. By comparing the response of these two models under identical loadings, the model that included the temporal horn predicted increased magnitudes of strain and strain rate in the hippocampus with respect to its counterpart without the temporal horn. This specifically affected cornu ammonis (CA) 1 (CA1), CA2/3, hippocampal tail, subiculum, and the adjacent amygdala and ventral diencephalon. These computational results suggest that the presence of the temporal horn exacerbate the vulnerability of the hippocampus, highlighting the mechanobiological dependency of the hippocampus on the temporal horn.

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