A semi-automatic method of generating subject-specific pediatric head finite element models for impact dynamic responses to head injury

A sensor-enabled cloud-based computing platform for computational brain biomechanics

BACKGROUND AND OBJECTIVES

Driven by the risk of repetitive head trauma, sensors have been integrated into mouthguards to measure head impacts in contact sports and military activities. These wearable devices, referred to as "instrumented" or "smart" mouthguards are being actively developed by various research groups and organizations. These instrumented mouthguards provide an opportunity to further study and understand the brain biomechanics due to impact. In this study, we present a brain modeling service that can use information from these sensors to predict brain injury metrics in an automated fashion.

METHODS

We have built a brain modeling platform using several of Amazon's Web Services (AWS) to enable cloud computing and scalability. We use a custom-built cloud-based finite element modeling code to compute the physics-based nonlinear response of the intracranial brain tissue and provide a frontend web application and an application programming interface for groups working on head impact sensor technology to include simulated injury predictions into their research pipeline.

RESULTS

The platform results have been validated against experimental data available in literature for brain-skull relative displacements, brain strains and intracranial pressure. The parallel processing capability of the platform has also been tested and verified. We also studied the accuracy of the custom head surfaces generated by Avatar 3D.

CONCLUSION

We present a validated cloud-based computational brain modeling platform that uses sensor data as input for numerical brain models and outputs a quantitative description of brain tissue strains and injury metrics. The platform is expected to generate transparent, reproducible, and traceable brain computing results.

Approximating subject-specific brain injury models via scaling based on head-brain morphological relationships

Most human head/brain models represent a generic adult male head/brain. They may suffer in accuracy when investigating traumatic brain injury (TBI) on a subject-specific basis. Subject-specific models can be developed from neuroimages; however, neuroimages are not typically available in practice. In this study, we establish simple and elegant regression models between brain outer surface morphology and head dimensions measured from neuroimages along with age and sex information (N = 191; 141 males and 50 females with age ranging 14-25 years). The regression models are then used to approximate subject-specific brain models by scaling a generic counterpart, without using neuroimages. Model geometrical accuracy is assessed using adjusted [Formula: see text] and absolute percentage error (e.g., 0.720 and 3.09 ± 2.38%, respectively, for brain volume when incorporating tragion-to-top). For a subset of 11 subjects (from smallest to largest in brain volume), impact-induced brain strains are compared with those from "morphed models" derived from neuroimage-based mesh warping. We find that regional peak strains from the scaled subject-specific models are comparable to those of the morphed counterparts but could be considerably different from those of the generic model (e.g., linear regression slope of 1.01-1.03 for gray and white matter regions versus 1.16-1.19, or up to ~ 20% overestimation for the smallest brain studied). These results highlight the importance of incorporating brain morphological variations in impact simulation and demonstrate the feasibility of approximating subject-specific brain models without neuroimages using age, sex, and easily measurable head dimensions. The scaled models may improve subject specificity for future TBI investigations.

Research on the Dynamic Response Properties of Nonlethal Projectiles for Injury Risk Assessment

Based on the models already on the market, we have manufactured six types of nonlethal projectiles. We have made convex heads out of polyurethane foam (PUR) filled with mineral fillers like alumina (Al₂O₃) and montmorillonite (MMT). We chose a suitable holder for nonlethal projectiles. Also, we made a custom industrial model and used CAD modeling in SolidWorks to simulate the deformation of the nonlethal projectiles. The polymeric nonlethal projectile holders were then 3D-printed. We performed a dynamic mechanical analysis (DMA) and discussed the results. Likewise, we conducted ballistic impact experiments on nonlethal projectiles (XM1006) and nonlethal projectiles manufactured that were evaluated using a rigid wall and a pneumatic launcher. Furthermore, we looked at cell structure, the spread of the mean pore diameter, and the particle size distributions of the mineral fillers using scanning electron microscopy (SEM). We evaluated and discussed injury risks from nonlethal impacts. Data on nonlethal projectile lethality and safe impact speed are collected. This study explains how lab studies and real-world practice coexist through nonlethal projectile properties.

Quantification and statistical analysis on the cranial vault morphology for Chinese children 3-10 years old

BACKGROUND AND OBJECTIVE

Head injury is the leading cause of fatalities and disabilities in children. Characterizing the variation in cranial size/shape and thickness during growth is important for developing finite element models of child heads and evaluating head injury risk at different ages. However, the quantitative morphological features of the cranial vault (size/shape and non-uniform thickness distribution) have not been accounted for in children aged between 3 and 10 years old (YO).

METHODS

Geometrically equivalent discrete points were identified on 42 head CT scans of 3-10 YO children by separation, curve dividing, and point fitting. Based on discrete points, the principal component analysis and regression (PCA&R) method was used to develop a statistical model of the cranial vault as a function of age and head circumference.

RESULTS

The ontogeny of three-dimensional cranial morphology and non-uniform thickness from 3 to 10 years of age was quantified and cranial vault morphologies for 3-10 YO children were generated in 1 year intervals.

CONCLUSIONS

The automatic method, the procedure of identifying discrete points from CT scans, and the developed quantitative cranial vault model are reliable and accurate.

Experimental and numerical study on the mechanical properties of cortical and spongy cranial bone of 8-week-old porcines at different strain rates

Pediatric porcines have widely been used as substitute for children in biomechanical research. Previous studies have used entire piglet cranium when testing their properties. Here, the piglet craniums from the frontal and parietal locations were carefully dissected into spongy and cortical part, and tensile tests at different strain rates were then conducted on these two bone types. It is found that the elastic modulus, yield stress, and ultimate stress of the cortical bone were all significantly higher than those of the spongy bone. The ultimate strains of the cortical and spongy bone were similar. Overall, the effect of the position on the mechanical properties did not reach significance. Cortical bone strength from the frontal location was slightly higher than that obtained from the parietal location; however, spongy bone did not show this location difference. The mechanical properties of both the cortical and spongy bone are significantly strain-rate dependent. Specifically, the elastic modulus, yield stress, and the ultimate stress of the cortical bone increased by approximately 123%, 63%, and 50%, respectively, with strain rates ranging from 0.001 to 10/s. For spongy bone, increases were approximately 128%, 73%, and 77%, respectively. Ultimate strain decreased by approximately 37% and 7% for cortical and spongy bone, respectively. An elastic-plastic constitutive model incorporating with strain rate based on a combined exponential and logarithmic function was proposed and implemented into LS-DYNA through user-defined material. The developed model and the subroutine code successfully simulated the strain-rate characteristics and the fracture process of the bone samples.

A comprehensive study on the mechanical properties of different regions of 8-week-old pediatric porcine brain under tension, shear, and compression at various strain rates

Young porcine brain is often used as a surrogate for studying the mechanical factors affecting traumatic brain injury in children. However, the mechanical properties of pediatric brain tissue derived from humans and piglets are very scarce, and this seriously detracts from the biofidelity of the developed finite element (FE) models of the pediatric head/brain. The present study addresses this issue by subjecting the cerebrum (white matter and gray matter), cerebellum, and brainstem specimens derived from 8-week-old piglets to tension and shear testing at strain rates of 0.01, 1, and 50/s. The experimental data are combined with the corresponding data derived from a previous study under compression to obtain comprehensive stress-strain curves of the pediatric porcine cerebrum, cerebellum, and brainstem tissue specimens. In general, the average stress level of the white matter is somewhat higher than that of the gray matter under the tension, shear and compression conditions, however, this difference does not reach a significant level. The stiffness of the cerebellum and the cerebrum does not differ significantly under tension and shear conditions, but the stiffness of the cerebellum is greater than that of the cerebrum under compression. The brainstem has significantly higher stiffness than the cerebrum and the cerebellum under all loading modes. In addition, the mechanical properties of brain tissue exhibit significant strain-rate dependences. With increasing strain rate from 0.01/s to 50/s, the average stress at a strain of 0.5 for all of the brain tissue increased by about 2.2 times under tension, about 2.4 times under shearing and about 2.2 times under compression. The variations in the stress as a function of the strain rate for brain tissue specimens were well characterized by exponential functions at strains of 0.25 and 0.5 under all three loading modes. The results of this study are useful for developing biofidelic FE models of the pediatric brain.

Development and validation of a semi-automatic landmark extraction method for mesh morphing

Currently, landmark-based mesh morphing technology is widely used to rapidly obtain meshes with specific geometry, which is suitable to develop parametric human finite element (FE) models. However it takes too much time for landmark extraction to obtain high geometric accuracy. The purpose of this study is to develop and validate a semi-automatic landmark extraction method to reduce the time of manual selection of landmarks without sacrificing the accuracy of identifying landmarks in the process of mesh morphing. A few contour edge landmarks were extracted manually. Mathematical landmarks and pseudo-landmarks were extracted automatically by user-defined algorithm. The radial basis function (RBF) was used to morph the baseline FE model into the target geometry based on these landmarks. The cervical vertebra (C5), rib (R7) and femur were selected as the target geometries to verify the effectiveness of the method. The maximum mean geometric error of the three types of target geometries was less than 1 mm. The mesh quality of the morphed FE model was similar to that of the baseline FE model. Compared to the traditional manual method, 2/3 to 3/4 of the time for landmark extraction was saved by the semi-automatic method.

Finite element models and material data for analysis of infant head impacts

Finite element (FE) models of the infant human head may be used to discriminate injury patterns resulting from accidents (e.g. falls) and from abusive head trauma (AHT). Existing FE models of infant head impacts are reviewed. Reliability of the material models is the major limitation currently. Infant head tissue properties differ from adults (notably in suture stiffness and strain-to-failure), change with age, and experimental data is scarce. The available data on scalp, cranial bone, dura, and brain are reviewed. Data is most scarce for living brain. All infant head model to date, except one, have used linear elastic models for all tissues except the brain (viscoelastic or Ogden hyperelastic), and do not capture the full complexity of tissue response, but the predicted whole-head response may be of acceptable accuracy. Recent work by Li, Sandler and Kleiven has used hyperelastic models for scalp and dura, and an orthotropic model for bone. There is a need to simulate falls from greater than one metre, and blunt force impacts.

Development of a child head analytical dynamic model considering cranial nonuniform thickness and curvature - Applying to children aged 0-1 years old

BACKGROUND AND OBJECTIVE

Although analytical models have been used to quickly predict head response under impact condition, the existing models generally took the head as regular shell with uniform thickness which cannot account for the actual head geometry with varied cranial thickness and curvature at different locations. The objective of this study is to develop and validate an analytical model incorporating actual cranial thickness and curvature for child aged 0-1YO and investigate their effects on child head dynamic responses at different head locations.

METHODS

To develop the new analytical model, the child head was simplified into an irregular fluid-filled shell with non-uniform thickness and the cranial thickness and curvature at different locations were automatically obtained from CT scans using a procedure developed in this study. The implicit equation of maximum impact force was derived as a function of elastic modulus, thickness and radius of curvature of cranium.

RESULTS

The proposed analytical model are compared with cadaver test data of children aged 0-1 years old and it is shown to be accurate in predicting head injury metrics. According to this model, obvious difference in injury metrics were observed among subjects with the same age, but different cranial thickness and curvature; and the injury metrics at forehead location are significant higher than those at other locations due to large thickness it owns.

CONCLUSIONS

The proposed model shows good biofidelity and can be used in quickly predicting the dynamics response at any location of head for child younger than 1 YO.

Cranial thickness changes in early childhood

The neurocranium changes rapidly in early childhood to accommodate the developing brain. However, developmental disorders may cause abnormal growth of the neurocranium, the most common one being craniosynostosis, affecting about 1 in 2000 children. It is important to understand how the brain and neurocranium develop together to understand the role of the neurocranium in neurodevelopmental outcomes. However, the neurocranium is not as well studied as the human brain in early childhood, due to a lack of imaging data. CT is typically employed to investigate the cranium, but, due to ionizing radiation, may only be used for clinical cases. However, the neurocranium is also visible on magnetic resonance imaging (MRI). Here, we used a large dataset of MRI images from healthy children in the age range of 1 to 2 years old and extracted the neurocranium. A conformal geometry based analysis pipeline is implemented to determine a set of statistical atlases of the neurocranium. A growth model of the neurocranium will help us understand cranial bone and suture development with respect to the brain, which will in turn inform better treatment strategies for neurocranial disorders.

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.