Finite Element Head Model Research Articles

Understanding how a sport-helmet protects the head from closed injury by virtual impacttests.

Understanding how a helmet protects the head, especially the soft brain tissues, is the prerequisite for improving helmet design. Intracranial pressure and stresses/strains in the brain tissues are the direct indicators of traumatic brain injury and they can be used to measure helmet performance. In this study, the effects of helmet design parameters such as the helmet shell stiffness, liner compliance and thickness on the brain injury indicators were investigated by virtual impact tests. A finite element head model (FEHM) was first constructed from medical images; a personally-fitted helmet made of composite material and foam was virtually prototyped using geometric information extracted from the FEHM; a helmet-head finite element model was then assembled. Virtual impact tests were conducted using the resulting helmet-head model. The obtained results suggested that, if the helmet shell already has adequate strength to resist excessive deformation and fracture, further increasing shell stiffness and strength would not considerably reduce intracranial pressure and brain strains; to reach the maximum protection with the available materials, the key is to effectively use the second stage in the stress-strain history of the liner foam material.

Zoomed MRI Guided by Combined EEG/MEG Source Analysis: A Multimodal Approach for Optimizing Presurgical Epilepsy Work-up and its Application in a Multi-focal Epilepsy Patient Case Study

In recent years, the use of source analysis based on electroencephalography (EEG) and magnetoencephalography (MEG) has gained considerable attention in presurgical epilepsy diagnosis. However, in many cases the source analysis alone is not used to tailor surgery unless the findings are confirmed by lesions, such as, e.g., cortical malformations in MRI. For many patients, the histology of tissue resected from MRI negative epilepsy shows small lesions, which indicates the need for more sensitive MR sequences. In this paper, we describe a technique to maximize the synergy between combined EEG/MEG (EMEG) source analysis and high resolution MRI. The procedure has three main steps: (1) construction of a detailed and calibrated finite element head model that considers the variation of individual skull conductivities and white matter anisotropy, (2) EMEG source analysis performed on averaged interictal epileptic discharges (IED), (3) high resolution (0.5 mm) zoomed MR imaging, limited to small areas centered at the EMEG source locations. The proposed new diagnosis procedure was then applied in a particularly challenging case of an epilepsy patient: EMEG analysis at the peak of the IED coincided with a right frontal focal cortical dysplasia (FCD), which had been detected at standard 1 mm resolution MRI. Of higher interest, zoomed MR imaging (applying parallel transmission, ‘ZOOMit’) guided by EMEG at the spike onset revealed a second, fairly subtle, FCD in the left fronto-central region. The evaluation revealed that this second FCD, which had not been detectable with standard 1 mm resolution, was the trigger of the seizures.

Finite element head model simulation of the case suspected of diffuse axonal injury in the traffic accident

ABSTRACTA traumatic brain injury case that diffuses axonal injury was suspected in the physician's diagnosis was simulated using finite element head model based on medical information such as MRI and CT. First, the head model matched the subject's head dimensions and material properties of the skull from the subject's age. Next, the site of the subject's head collision was estimated from the contusion, and collision velocity was estimated from the presence or absence of skull fractures and from the presence or absence of intracranial microhaemorrhage. Finally, we predicted the region of onset and severity of the neurological injury from intracerebral von Mises stress, and the analytical result showed the possibility of mild and partly moderate neurological injury. Furthermore, we assessed the effect of each parameter on the severity of the neurological injury and ascertained that collision velocity is the factor with the greatest effect on von Mises stress.

An improved finite element modeling of thecerebrospinal fluid layer in the head impactanalysis.

The finite element (FE) method has been widely used to investigate the mechanism of traumatic brain injuries (TBIs), because it is technically difficult to quantify the responses of the brain tissues to the impact in experiments. One of technical challenges to build a FE model of a human head is the modeling of the cerebrospinal fluid (CSF) of the brain. In the current study, we propose to use membrane elements to construct the CSF layer. Using the proposed approach, we demonstrate that a head model can be built by using existing meshes available in commercial databases, without using any advanced meshing software tool, and with the sole use of native functions of the FE package Abaqus. The calculated time histories of the intracranial pressures at frontal, posterior fossa, parietal, and occipital positions agree well with the experimental data and the simulations in the literature, indicating that the physical effects of the CSF layer have been accounted for in the proposed modeling approach. The proposed modeling approach would be useful for bioengineers to solve practical problems.

Assessment of model-based image-matching for future reconstruction of unhelmeted sport head impact kinematics

Player-to-player contact inherent in many unhelmeted sports means that head impacts are a frequent occurrence. Model-Based Image-Matching (MBIM) provides a technique for the assessment of three-dimensional linear and rotational motion patterns from multiple camera views of a head impact event, but the accuracy is unknown for this application. The goal of this study is to assess the accuracy of the MBIM method relative to reflective marker-based motion analysis data for estimating six degree of freedom head displacements and velocities in a staged pedestrian impact scenario at 40 km/h. Results showed RMS error was under 20 mm for all linear head displacements and 0.01–0.04 rad for head rotations. For velocities, the MBIM method yielded RMS errors between 0.42 and 1.29 m/s for head linear velocities and 3.53–5.38 rad/s for angular velocities. This method is thus beneficial as a tool to directly measure six degree of freedom head positional data from video of sporting head impacts, but velocity data is less reliable. MBIM data, combined in future with velocity/acceleration data from wearable sensors could be used to provide input conditions and evaluate the outputs of multibody and finite element head models for brain injury assessment of sporting head impacts.

On the mechanical behaviour of PEEK and HA cranial implants under impact loading

The human head can be subjected to numerous impact loadings such as those produced by a fall or during sport activities. These accidents can result in skull fracture and in some complex cases, part of the skull may need to be replaced by a biomedical implant. Even when the skull is not damaged, such accidents can result in brain swelling treated by decompressive craniectomy. Usually, after recovery, the part of the skull that has been removed is replaced by a prosthesis. In such situations, a computational tool able to analyse the choice of prosthesis material depending on the patient's specific activity has the potential to be extremely useful for clinicians. The work proposed here focusses on the development and use of a numerical model for the analysis of cranial implants under impact conditions. In particular, two main biomaterials commonly employed for this kind of prosthesis are polyether-ether-ketone (PEEK) and macroporous hydroxyapatite (HA). In order to study the suitability of these implants, a finite element head model comprising scalp, skull, cerebral falx, cerebrospinal fluid and brain tissues, with a cranial implant replacing part of the skull has been developed from magnetic resonance imaging data. The human tissues and these two biocompatible materials have been independently studied and their constitutive models are provided here. A computational model of the human head under impact loading is then implemented and validated, and a numerical comparison of the mechanical impact response of PEEK and HA implants is presented. This comparison was carried out in terms of the effectiveness of both implants in ensuring structural integrity and preventing traumatic brain injury. The results obtained in this work highlight the need to take into account environmental mechanical considerations to select the optimal implant depending on the specific patient: whereas HA implants present attractive biointegration properties, PEEK implant can potentially be a much more appropriate choice in a demanding mechanical life style. Finally, a novel methodology is proposed to assess the need for further clinical evaluation in case of impact with both implants over a large range of impact conditions.

Clarification of Traffic Accidents involving Elderly Cyclistsusing Actual Traffic Accident Data and a Finite Element Head Model

Clarification of Traffic Accidents involving Elderly Cyclistsusing Actual Traffic Accident Data and a Finite Element Head Model

근육 모델이 고려된 두부 및 경추 유한요소모델을 이용한 비관통 피탄 충격에 의한 인체 상해 해석

근육 모델이 고려된 두부 및 경추 유한요소모델을 이용한 비관통 피탄 충격에 의한 인체 상해 해석

Finite element simulations of the head-brain responses to the top impacts of a construction helmet: Effects of the neck and body mass.

Traumatic brain injuries are among the most common severely disabling injuries in the United States. Construction helmets are considered essential personal protective equipment for reducing traumatic brain injury risks at work sites. In this study, we proposed a practical finite element modeling approach that would be suitable for engineers to optimize construction helmet design. The finite element model includes all essential anatomical structures of a human head (i.e. skin, scalp, skull, cerebrospinal fluid, brain, medulla, spinal cord, cervical vertebrae, and discs) and all major engineering components of a construction helmet (i.e. shell and suspension system). The head finite element model has been calibrated using the experimental data in the literature. It is technically difficult to precisely account for the effects of the neck and body mass on the dynamic responses, because the finite element model does not include the entire human body. An approximation approach has been developed to account for the effects of the neck and body mass on the dynamic responses of the head-brain. Using the proposed model, we have calculated the responses of the head-brain during a top impact when wearing a construction helmet. The proposed modeling approach would provide a tool to improve the helmet design on a biomechanical basis.

Assessment of Non-Lethal Projectile Head Impacts

Anti-personnel NLW (Non-Lethal Weapons) are used to impart sufficient effect onto a person in order to deter uncivil, suspect or hazardous behaviour with a low probability of permanent or fatal injury. In many situations of conflict, where the army and law-enforcement units are involved, the use of such weapons can ensure a minimal risk of collateral damage. The most used NLW are Kinetic Energy Non-Lethal Weapons (KENLW) that involve the shooting of a deformable or breakable projectile. Since their first use, real cases indicate that the injuries inflicted by such projectiles may be irreversible and sometimes lead to death, especially for the head impacts. Therefore, there is a necessity to assess the head impacts in order to allow a safer use of such projectiles. This article concludes a 4-year study where three methods, independently developed, are considered to be applicable for the head risk assessment. The first method links force measurements on rigid wall structure with cadaveric and animal impact test results. Lesional thresholds, in terms of the maximum impact force and intracranial pressure, are proposed for unconsciousness, meningeal damages and bone damages, respectively. The second one is based on direct impact force measurements on a specific mechanical surrogate. The third method makes use of numerical simulations using a validated finite element head model. The numerical model allows the prediction of different kind of injuries. Firstly, the necessity of the assessment of the non-lethal head impacts is highlighted through some examples taken from literature. Secondly, the three different methods are detailed and illustrated for different projectiles. Outstanding results are given and a comparison between the different methods is proposed including some correlations between different criteria. Finally, some discussions and remarks conclude the present article.

A female head–neck model for rear impact simulations

Several mathematical cervical models of the 50th percentile male have been developed and used for impact biomechanics research. However, for the 50th percentile female no similar modelling efforts have been made, despite females being subject to a higher risk of soft tissue neck injuries. This is a limitation for the development of automotive protective systems addressing Whiplash Associated Disorders (WADs), most commonly caused in rear impacts, as the risk for females sustaining WAD symptoms is double that of males.In this study, a finite element head and neck model of a 50th percentile female was validated in rear impacts. A previously validated ligamentous cervical spine model was complemented with a rigid body head, soft tissues and muscles. In both physiological flexion-extension motions and simulated rear impacts, the kinematic response at segment level was comparable to that of human subjects. Evaluation of ligament stress levels in simulations with varied initial cervical curvature revealed that if an individual assumes a more lordotic posture than the neutral, a higher risk of WAD might occur in rear impact.The female head and neck model, together with a kinematical whole body model which is under development, addresses a need for tools for assessment of automotive protection systems for the group which is at the highest risk to sustain WAD.

The importance of nonlinear tissue modelling in finite element simulations of infant head impacts

Despite recent efforts on the development of finite element (FE) head models of infants, a model capable of capturing head responses under various impact scenarios has not been reported. This is hypothesized partially attributed to the use of simplified linear elastic models for soft tissues of suture, scalp and dura. Orthotropic elastic constants are yet to be determined to incorporate the direction-specific material properties of infant cranial bone due to grain fibres radiating from the ossification centres. We report here on our efforts in advancing the above-mentioned aspects in material modelling in infant head and further incorporate them into subject-specific FE head models of a newborn, 5- and 9-month-old infant. Each model is subjected to five impact tests (forehead, occiput, vertex, right and left parietal impacts) and two compression tests. The predicted global head impact responses of the acceleration–time impact curves and the force–deflection compression curves for different age groups agree well with the experimental data reported in the literature. In particular, the newly developed Ogden hyperelastic model for suture, together with the nonlinear modelling of scalp and dura mater, enables the models to achieve more realistic impact performance compared with linear elastic models. The proposed approach for obtaining age-dependent skull bone orthotropic material constants counts both an increase in stiffness and decrease in anisotropy in the skull bone—two essential biological growth parameters during early infancy. The profound deformation of infant head causes a large stretch at the interfaces between the skull bones and the suture, suggesting that infant skull fractures are likely to initiate from the interfaces; the impact angle has a profound influence on global head impact responses and the skull injury metrics for certain impact locations, especially true for a parietal impact.

On the assessment of bridging vein rupture associated acute subdural hematoma through finite element analysis

Acute subdural hematoma (ASDH) is a type of intracranial haemorrhage following head impact, with high mortality rates. Bridging vein (BV) rupture is a major cause of ASDH, which is why a biofidelic representation of BVs in finite element (FE) head models is essential for the successful prediction of ASDH. We investigated the mechanical behavior of BVs in the KTH FE head model. First, a sensitivity study quantified the effect of loading conditions and mechanical properties on BV strain. It was found that the peak rotational velocity and acceleration and pulse duration have a pronounced effect on the BV strains. Both Young’s modulus and diameter are also negatively correlated with the BV strains. A normalized multiple linear regression model using Young’s modulus, outer diameter and peak rotational velocity to predict the BV strain yields an adjusted -value of 0.81. Secondly, cadaver head impact experiments were simulated with varying sets of mechanical properties, upon which the amount of successful BV rupture predictions was evaluated. The success rate fluctuated between 67 and 75%. To further increase the predictive capability of FE head models w.r.t. BV rupture, future work should be directed towards improvement of the BV representation, both geometrically and mechanically.

Modeling the mechanics of axonal fiber tracts using the embedded finite element method.

A subject-specific human head finite element model with embedded axonal fiber tractography obtained from diffusion tensor imaging was developed. The axonal fiber tractography finite element model was coupled with the volumetric elements in the head model using the embedded element method. This technique enables the calculation of axonal strains and real-time tracking of the mechanical response of the axonal fiber tracts. The coupled model was then verified using pressure and relative displacement-based (between skull and brain) experimental studies and was employed to analyze a head impact, demonstrating the applicability of this method in studying axonal injury. Following this, a comparison study of different injury criteria was performed. This model was used to determine the influence of impact direction on the extent of the axonal injury. The results suggested that the lateral impact loading is more dangerous compared to loading in the sagittal plane, a finding in agreement with previous studies. Through this analysis, we demonstrated the viability of the embedded element method as an alternative numerical approach for studying axonal injury in patient-specific human head models.

Development of an Unbiased Validation Protocol to Assess the Biofidelity of Finite Element Head Models used in Prediction of Traumatic Brain Injury.

This study describes a method to identify laboratory test procedures and impact response requirements suitable for assessing the biofidelity of finite element head models used in prediction of traumatic brain injury. The selection of the experimental data and the response requirements were result of a critical evaluation based on the accuracy, reproducibility and relevance of the available experimental data. A weighted averaging procedure was chosen in order to consider different contributions from the various test conditions and target measurements based on experimental error. According to the quality criteria, 40 experimental cases were selected to be a representative dataset for validation. Based on the evaluation of response curves from four head finite element models, CORA was chosen as a quantitative method to compare the predicted time history response to the measured data. Optimization of the CORA global settings led to the recommendation of performing curve comparison on a fixed time interval of 0-30 ms for intracranial pressure and at least 0-40 ms for brain motion and deformation. The allowable maximum time shift was adjusted depending on the shape of the experimental curves (DMAX = 0.12 for intracranial pressure, DMAX = 0.40 for brain motion and DMAX = 0.25 for brain deformation). Finally, bigger penalization of ratings was assigned to curves with fundamentally incorrect shape compared to those having inaccuracies in amplitude or time shift (cubic vs linear). This rigorous approach is necessary to ensure confidence in the model results and progress in the usage of finite element head models for traumatic brain injury prediction.

Head injury assessment of non-lethal projectile impacts: A combined experimental/computational method

The main objective of this study is to develop a methodology to assess this risk based on experimental tests versus numerical predictive head injury simulations. A total of 16 non-lethal projectiles (NLP) impacts were conducted with rigid force plate at three different ranges of impact velocity (120, 72 and 55m/s) and the force/deformation–time data were used for the validation of finite element (FE) NLP. A good accordance between experimental and simulation data were obtained during validation of FE NLP with high correlation value (>0.98) and peak force discrepancy of less than 3%. A state-of-the art finite element head model with enhanced brain and skull material laws and specific head injury criteria was used for numerical computation of NLP impacts. Frontal and lateral FE NLP impacts to the head model at different velocities were performed under LS-DYNA. It is the very first time that the lethality of NLP is assessed by axonal strain computation to predict diffuse axonal injury (DAI) in NLP impacts to head. In case of temporo-parietal impact the min-max risk of DAI is 0–86%. With a velocity above 99.2m/s there is greater than 50% risk of DAI for temporo-parietal impacts. All the medium- and high-velocity impacts are susceptible to skull fracture, with a percentage risk higher than 90%. This study provides tool for a realistic injury (DAI and skull fracture) assessment during NLP impacts to the human head.

The development of a whole-head human finite-element model for simulation of the transmission of bone-conducted sound.

A whole head finite element model for simulation of bone conducted (BC) sound transmission was developed. The geometry and structures were identified from cryosectional images of a female human head and eight different components were included in the model: cerebrospinal fluid, brain, three layers of bone, soft tissue, eye, and cartilage. The skull bone was modeled as a sandwich structure with an inner and outer layer of cortical bone and soft spongy bone (diploë) in between. The behavior of the finite element model was validated against experimental data of mechanical point impedance, vibration of the cochlear promontories, and transcranial BC sound transmission. The experimental data were obtained in both cadaver heads and live humans. The simulations showed multiple low-frequency resonances where the first was caused by rotation of the head and the second was close in frequency to average resonances obtained in cadaver heads. At higher frequencies, the simulation results of the impedance were within one standard deviation of the average experimental data. The acceleration response at the cochlear promontory was overall lower for the simulations compared with experiments but the overall tendencies were similar. Even if the current model cannot predict results in a specific individual, it can be used for understanding the characteristic of BC sound transmission in general.

Effect of helmet liner systems and impact directions on severity of head injuries sustained in ballistic impacts: a finite element (FE) study.

The current study aims to investigate the effectiveness of two different designs of helmet interior cushion, (Helmet 1: strap-netting; Helmet 2: Oregon Aero foam-padding), and the effect of the impact directions on the helmeted head during ballistic impact. Series of ballistic impact simulations (frontal, lateral, rear, and top) of a full-metal-jacketed bullet were performed on a validated finite element head model equipped with the two helmets, to assess the severity of head injuries sustained in ballistic impacts using both head kinematics and biomechanical metrics. Benchmarking with experimental ventricular and intracranial pressures showed that there is good agreement between the simulations and experiments. In terms of extracranial injuries, top impact had the highest skull stress, still without fracturing the skull. In regard to intracranial injuries, both the lateral and rear impacts generally gave the highest principal strains as well as highest shear strains, which exceed the injury thresholds. Off-cushion impacts were found to be at higher risk of intracranial injuries. The study also showed that the Oregon Aero foam pads helped to reduce impact forces. It also suggested that more padding inserts of smaller size may offer better protection. This provides some insights on future's helmet design against ballistic threats.

Evaluation of brain tissue responses because of the underwash overpressure of helmet and faceshield under blast loading.

Head protective tools such as helmets and faceshields can induce a localized high pressure region on the skull because of the underwash of the blast waves. Whether this underwash overpressure can affect the brain tissue response is still unknown. Accordingly, a computational approach was taken to confirm the incidence of underwash with regards to blast direction, as well as examine the influence of this effect on the mechanical responses of the brain. The variation of intracranial pressure (ICP) as one of the major injury predictors, as well as the maximum shear stress were mainly addressed in this study. Using a nonlinear finite element (FE) approach, generation and interaction of blast waves with the unprotected, helmeted, and fully protected (helmet and faceshield protected) FE head models were modeled using a multi-material arbitrary Lagrangian-Eulerian (ALE) method and a fluid-structure interaction (FSI) coupling algorithm. The underwash incidence overpressure was found to greatly change with the blast direction. Moreover, while underwash induced ICP (U-ICP) did not exceed the peak ICP of the unprotected head, it was comparable and even more than the peak ICP imposed on the protected heads by the primary shockwaves (Coup-ICP). It was concluded that while both helmet and faceshield protected the head against blast waves, the underwash overpressure affected the brain tissue response and altered the dynamic load experienced by the brain as it led to increased ICP levels at the countercoup site, imparted elevated skull flexure, and induced high negative pressure regions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Transcranial Electrical Neuromodulation Based on the Reciprocity Principle.

A key challenge in multi-electrode transcranial electrical stimulation (TES) or transcranial direct current stimulation (tDCS) is to find a current injection pattern that delivers the necessary current density at a target and minimizes it in the rest of the head, which is mathematically modeled as an optimization problem. Such an optimization with the Least Squares (LS) or Linearly Constrained Minimum Variance (LCMV) algorithms is generally computationally expensive and requires multiple independent current sources. Based on the reciprocity principle in electroencephalography (EEG) and TES, it could be possible to find the optimal TES patterns quickly whenever the solution of the forward EEG problem is available for a brain region of interest. Here, we investigate the reciprocity principle as a guideline for finding optimal current injection patterns in TES that comply with safety constraints. We define four different trial cortical targets in a detailed seven-tissue finite element head model, and analyze the performance of the reciprocity family of TES methods in terms of electrode density, targeting error, focality, intensity, and directionality using the LS and LCMV solutions as the reference standards. It is found that the reciprocity algorithms show good performance comparable to the LCMV and LS solutions. Comparing the 128 and 256 electrode cases, we found that use of greater electrode density improves focality, directionality, and intensity parameters. The results show that reciprocity principle can be used to quickly determine optimal current injection patterns in TES and help to simplify TES protocols that are consistent with hardware and software availability and with safety constraints.