A Methodology to Compare Biomechanical Simulations With Clinical Brain Imaging Analysis Utilizing Two Blunt Impact Cases.

According to the US Defense and Veterans Brain Injury Center (DVBIC) and Centers for Disease Control and Prevention (CDC), mild traumatic brain injury (mTBI) is a common form of head injury. Medical imaging data provides clinical insight into tissue damage/injury and injury severity, and helps medical diagnosis. Computational modeling and simulation can predict the biomechanical characteristics of such injury, and are useful for development of protective equipment. Integration of techniques from computational biomechanics with medical data assessment modalities (e.g., magnetic resonance imaging or MRI) has not yet been used to predict injury, support early medical diagnosis, or assess effectiveness of personal protective equipment. This paper presents a methodology to map computational simulations with clinical data for interpreting blunt impact TBI utilizing two clinically different head injury case studies. MRI modalities, such as T1, T2, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), were used for simulation comparisons. The two clinical cases have been reconstructed using finite element analysis to predict head biomechanics based on medical reports documented by a clinician. The findings are mapped to simulation results using image-based clinical analyses of head impact injuries, and modalities that could capture simulation results have been identified. In case 1, the MRI results showed lesions in the brain with skull indentation, while case 2 had lesions in both coup and contrecoup sides with no skull deformation. Simulation data analyses show that different biomechanical measures and thresholds are needed to explain different blunt impact injury modalities; specifically, strain rate threshold corresponds well with brain injury with skull indentation, while minimum pressure threshold corresponds well with coup-contrecoup injury; and DWI has been found to be the most appropriate modality for MRI data interpretation. As the findings from these two cases are substantiated with additional clinical studies, this methodology can be broadly applied as a tool to support injury assessment in head trauma events and to improve countermeasures (e.g., diagnostics and protective equipment design) to mitigate these injuries.

Role of Interfacial Conditions on Blast Overpressure Propagation Into the Brain.

The complex interfacial condition between the human brain and the skull has been difficult to emulate in a surrogate system. Surrogate head models have typically been built using a homogeneous viscoelastic material to represent the brain, but the effect of different interfacial conditions between the brain and the skull on pressure transduction into the brain during blast has not been studied. In the present work, three interfacial conditions were generated in physical surrogate human head models. The first surrogate consisted of a gel brain separated from the skull by a layer of saline solution similar in thickness to the cerebrospinal fluid (CSF) layer in the human head: the fluid interface head model. The second surrogate head had the entire cranial cavity filled with the gel: the fixed interface head model. The third surrogate head contained a space-filling gel brain wrapped in a thin plastic film: the stick-slip interface head model. The human head surrogates were evaluated in a series of frontal blast tests to characterize the effect of skull-brain interfacial conditions on overpressure propagation into the gel brains. The fixed and the stick-slip interface head models showed nearly equal peak brain overpressures. In contrast, the fluid interface head model had much higher in-brain peak overpressures than the other two models, thus representing the largest transmission of forces into the gel brain. Given that the elevated peak overpressures occurred only in the fluid interface head model, the presence of the saline layer is likely responsible for this increase. This phenomenon is hypothesized to be attributed to the incompressibility of the saline and/or the impedance differences between the materials. The fixed interface head model showed pronounced high frequency energy content relative to the other two models, implying that the fluid and the stick-slip conditions provided better dampening. The cumulative impulse energy entering the three brain models were similar, suggesting that the interface conditions do not affect the total energy transmission over the positive phase duration of a blast event. This study shows that the fidelity of the surrogate human head models would improve with a CSF-emulating liquid layer.

On the Development of Interspecies Traumatic Brain Injury Correspondence Rules.

Traumatic brain injury analysis in human is exceedingly difficult due to the methods in which data can be collected, thus many researchers commonly implement animal surrogates. However, use of these surrogates is costly and restricted by ethical concerns and test logistics. Computational models and simulations do not have these constraints and can produce significant amounts of data in relatively short periods. This paper shows the development of a human head and neck model and a full body porcine model. Both models are developed from high-resolution CT and MRI scans and the latest low-to-high strain rate mechanical data available in the literature to represent tissue component material behaviors. Both models are validated against experiments from the literature and used to complete an initial interspecies correspondence rule development study for blast overpressure effects. The results indicate the similarities in the way injury develops in the pig brain and human brain but these similarities occur at very different insult levels. These results are extended by a study, which shows that blast peak pressure is the driving factor in injury prediction and, depending on the injury metric used, significantly different injuries could be predicted.

Towards Identification of Correspondence Rules to Relate Traumatic Brain Injury in Different Species.

Traumatic brain injury analysis in humans is exceedingly difficult due to the intrusive methods by which data can be collected; thus, many researchers commonly implement animal surrogates. However, ethical concerns and cost limit the scope of these tests on animal subjects too. Computational models, which provide an alternative method to data collection, are not constrained by these concerns and are able to generate significant amounts of data in relatively short time. This paper shows how the data generated from models of a human and pig head can be used towards developing interspecies correspondence rules for blast overpressure effects. The blast overpressure is simulated using an explosive of known weight and standoff distance and injury is evaluated using criteria in published literature. Results indicate that equivalent blasts in the human and pig produce significantly different injuries, and when equating total injured brain volume, the locations of injury in the brain vary between the species. Charge weight and total injured brain volume are related using a linear regression of the data such that a known injury in the pig or known blast can be used to predict injury or the blast experienced by a human, thus creating a correspondence between the species.

On the atomistic-based continuum viscoelastic constitutive relations for axonal microtubules.

Mechanical response of brain's interior during traumatic brain injury is primarily governed by the cytoskeleton (CSK) and occurs over multiple length scales starting from the axonal substructure level. The axonal cytoskeleton can be viewed as a nanofiber reinforced nanocomposite structure where nano-fibrous microtubules (MTs) are arranged in staggered arrays and cross-linked by Tau proteins. Each MT is made of thirteen laterally connected protofilaments (PFs), each of which is formed via linear polymerization of αß-heterodimer protein called tubulin. Recent studies suggest that the unique viscoelastic nature of axons governs the damage during traumatic brain injury. To understand how the internal substructures of axon influences the viscoelastic mechanical behavior of axon from a theoretical perspective, the viscoelastic properties of MTs need to be properly described. Since viscosity is a bulk property, the measurement methods are fairly consistent. On the other hand, the reported experimentally measured elastic properties of MTs vary by several orders of magnitude due to limitations of experimental tools. Alternatively, many have attempted to determine MT properties using theoretical and computational methods at different length scales ranging between the atomistic and the continuum level. The atomistic approaches capture the dynamics and interactions of a material at the atomic or atomic cluster level but these methods are computationally expensive and can model only a very small physical scale. On the other hand, the continuum theories lack finer scale details. Here, we present an atomistic-based continuum viscoelastic constitutive relation for microtubules (MTs) based on the interatomic potential for proteins and continuum homogenization method. The interaction potential includes both van der Waals and electrostatic interactions between the protein molecules. The calculated Young's modulus of 3.385 GPa agrees reasonably well with the range of experimentally measured value without any parameter fitting. We have then investigated the viscoelastic response of MT based on the estimated viscosity using atomistic simulation and evaluated Young's modulus using our method. The current theory suggests that MT behaves like a viscoelastic material when applied loading rate is extremely high, otherwise it acts like an elastic solid material.

Cavitation nucleation in gelatin: Experiment and mechanism.

Dynamic cavitation in soft materials is becoming increasingly relevant due to emerging medical implications such as the potential of cavitation-induced brain injury or cavitation created by therapeutic medical devices. However, the current understanding of dynamic cavitation in soft materials is still very limited, mainly due to lack of robust experimental techniques. To experimentally characterize cavitation nucleation under dynamic loading, we utilize a recently developed experimental instrument, the integrated drop tower system. This technique allows quantitative measurements of the critical acceleration (acr) that corresponds to cavitation nucleation while concurrently visualizing time evolution of cavitation. Our experimental results reveal that acr increases with increasing concentration of gelatin in pure water. Interestingly, we have observed the distinctive transition from a sharp increase (pure water to 1% gelatin) to a much slower rate of increase (∼10× slower) between 1% and 7.5% gelatin. Theoretical cavitation criterion predicts the general trend of increasing acr, but fails to explain the transition rates. As a likely mechanism, we consider concentration-dependent material properties and non-spherical cavitation nucleation sites, represented by pre-existing bubbles in gels, due to possible interplay between gelatin molecules and nucleation sites. This analysis shows that cavitation nucleation is very sensitive to the initial configuration of a bubble, i.e., a non-spherical bubble can significantly increase acr. This conclusion matches well with the experimentally observed liquid-to-gel transition in the critical acceleration for cavitation nucleation. STATEMENT OF SIGNIFICANCE: From a medical standpoint, understanding dynamic cavitation within soft materials, i.e., tissues, is important as there are both potential injury implications (blast-induced cavitation within the brain) as well as treatments utilizing the phenomena (lithotripsy). In this regard, the main results of the present work are (1) quantitative characterization of cavitation nucleation in gelatin samples as a function of gel concentration utilizing well-controlled mechanical impacts and (2) mechanistic understanding of complex coupling between cavitation and liquid-/solid-like material properties of gel. The new capabilities of testing soft gels, which can be tuned to mimic material properties of target organs, at high loading rate conditions and accurately predicting their cavitation behavior are an important step towards developing reliable cavitation criteria in the scope of their biomedical applications.

Characterization and detection of acceleration-induced cavitation in soft materials using a drop-tower-based integrated system.

The material response of biologically relevant soft materials, e.g., extracellular matrix or cell cytoplasm, at high rate loading conditions is becoming increasingly important for emerging medical implications including the potential of cavitation-induced brain injury or cavitation created by medical devices, whether intentional or not. However, accurately probing soft samples remains challenging due to their delicate nature, which often excludes the use of conventional techniques requiring direct contact with a sample-loading frame. We present a drop-tower-based method, integrated with a unique sample holder and a series of effective springs and dampers, for testing soft samples with an emphasis on high-rate loading conditions. Our theoretical studies on the transient dynamics of the system show that well-controlled impacts between a movable mass and sample holder can be used as a means to rapidly load soft samples. For demonstrating the integrated system, we experimentally quantify the critical acceleration that corresponds to the onset of cavitation nucleation for pure water and 7.5% gelatin samples. This study reveals that 7.5% gelatin has a significantly higher, approximately double, critical acceleration as compared to pure water. Finally, we have also demonstrated a non-optical method of detecting cavitation in soft materials by correlating cavitation collapse with structural resonance of the sample container.

Identifying the dynamic compressive stiffness of a prospective biomimetic elastomer by an inverse method.

Soft elastomeric materials that mimic real soft human tissues are sought to provide realistic experimental devices to simulate the human body's response to blast loading to aid the development of more effective protective equipment. The dynamic mechanical behavior of these materials is often measured using a Kolsky bar because it can achieve both the high strain rates (>100s(-1)) and the large strains (>20%) that prevail in blast scenarios. Obtaining valid results is challenging, however, due to poor dynamic equilibrium, friction, and inertial effects. To avoid these difficulties, an inverse method was employed to determine the dynamic response of a soft, prospective biomimetic elastomer using Kolsky bar tests coupled with high-speed 3D digital image correlation. Individual tests were modeled using finite elements, and the dynamic stiffness of the elastomer was identified by matching the simulation results with test data using numerical optimization. Using this method, the average dynamic response was found to be nearly equivalent to the quasi-static response measured with stress-strain curves at compressive strains up to 60%, with an uncertainty of ±18%. Moreover, the behavior was consistent with the results in stress relaxation experiments and oscillatory tests although the latter were performed at lower strain levels.