The aim of this study is to evaluate all the 58 available NFL cases and compare various predictors for mild traumatic brain injuries using a detailed and extensively validated finite element model of the human head. Global injury measures such as magnitude in angular and translational acceleration, change in angular velocity, head impact power (HIP) and HIC were also investigated with regard to their ability to predict the intracranial pressure and strains associated with injury. The brain material properties were modeled using a hyperelastic and viscoelastic constitutive law. Also, three different stiffness parameters, encompassing a range of published brain tissue properties, were tested. 8 tissue injury predictors were evaluated for 6 different regions, covering the entire cerebrum, as well as for the whole brain. In addition, 10 head kinematics based predictors were evaluated both for correlation with injury as well as with strain and pressure. When evaluating the results, a statistical correlation between strain, strain rate, product of strain and strain rate, Cumulative Strain Damage Measure (CSDM), strain energy density, maximum pressure, magnitude of minimum pressure, as well as von Mises effective stress, with injury was found when looking into specific regions of the brain. However, the maximal pressure in the gray matter showed a higher correlation with injury than other evaluated measures. On the other hand, it was possible, through the reconstruction of a motocross accident, to re-create the injury pattern in the brain of the injured rider using maximal principal strain. It was also found that a simple linear combination of peak change in rotational velocity and HIC showed a high correlation (R=0.98) with the maximum principal strain in the brain, in addition to being a significant predictor of injury. When applying the rotational and translational kinematics separately for one of the cases, it was found that the translational kinematics contribute very little to the intracranial distortional strains while the rotational kinematics contributes insignificantly to the pressure response. This study underlines that the strain based brain tissue injury predictors are very sensitive to the choice of stiffness for the brain tissue.

Predictors for traumatic brain injuries evaluated through accident reconstructions.

The mammalian brain is composed of an outer layer of gray matter, consisting of cell bodies, dendrites, and unmyelinated axons, and an inner core of white matter, consisting primarily of myelinated axons Recent evidence suggests that microstructural differences between gray and white matter play an important role during neurodevelopment While brain tissue as a whole is rheologically well characterized, the individual features of gray and white matter remain poorly understood Here we quantify the mechanical properties of gray and white matter using a robust, reliable, and repeatable method, flat-punch indentation To systematically characterize gray and white matter moduli for varying indenter diameters, loading rates, holding times, post-mortem times, and locations we performed a series of n = 192 indentation tests We found that indenting thick, intact coronal slices eliminates the common challenges associated with small specimens: it naturally minimizes boundary effects, dehydration, swelling, and structural degradation When kept intact and hydrated, brain slices maintained their mechanical characteristics with standard deviations as low as 5% throughout the entire testing period of five days post mortem White matter, with an average modulus of 1895 kPa±0592 kPa, was on average 39% stiffer than gray matter, p 001 , with an average modulus of 1389 kPa±0289 kPa, and displayed larger regional variations It was also more viscous than gray matter and responded less rapidly to mechanical loading Understanding the rheological differences between gray and white matter may have direct implications on diagnosing and understanding the mechanical environment in neurodevelopment and neurological disorders

Mechanical properties of gray and white matter brain tissue by indentation.

After X-radiography, ultrasound is now the most common of all the medical imaging technologies. For millennia, manual palpation has been used to assist in diagnosis, but it is subjective and restricted to larger and more superficial structures. Following an introduction to the subject of elasticity, the elasticity of biological soft tissues is discussed and published data are presented. The basic physical principles of pulse-echo and Doppler ultrasonic techniques are explained. The history of ultrasonic imaging of soft tissue strain and elasticity is summarized, together with a brief critique of previously published reviews. The relevant techniques—low-frequency vibration, step, freehand and physiological displacement, and radiation force (displacement, impulse, shear wave and acoustic emission)—are described. Tissue-mimicking materials are indispensible for the assessment of these techniques and their characteristics are reported. Emerging clinical applications in breast disease, cardiology, dermatology, gastroenterology, gynaecology, minimally invasive surgery, musculoskeletal studies, radiotherapy, tissue engineering, urology and vascular disease are critically discussed. It is concluded that ultrasonic imaging of soft tissue strain and elasticity is now sufficiently well developed to have clinical utility. The potential for further research is examined and it is anticipated that the technology will become a powerful mainstream investigative tool.

https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2011.0054

Medical ultrasound: imaging of soft tissue strain and elasticity

Implantable neuroprostheses are engineered systems designed to restore or substitute function for individuals with neurological deficits or disabilities. These systems involve at least one uni- or bidirectional interface between a living neural tissue and a synthetic structure, through which information in the form of electrons, ions or photons flows. Despite a few notable exceptions, the clinical dissemination of implantable neuroprostheses remains limited, because many implants display inconsistent long-term stability and performance, and are ultimately rejected by the body. Intensive research is currently being conducted to untangle the complex interplay of failure mechanisms. In this Review, we emphasize the importance of minimizing the physical and mechanical mismatch between neural tissues and implantable interfaces. We explore possible materials solutions to design and manufacture neurointegrated prostheses, and outline their immense therapeutic potential. Implantable neuroprostheses communicate with the nervous system to provide diagnosis or therapy to the injured body. In this review, we discuss materials-based approaches to overcome the physical and mechanical mismatch at the tissue–implant interface and to design long-term neurointegrated prostheses.

/pdf/materials-and-technologies-for-soft-implantable-36oxplq3az.pdf

Materials and technologies for soft implantable neuroprostheses

A new 3 dimensional finite element representation of the human head complex has been constructed for simulating the transient occurrences of simple pedestrian accidents. This paper describes the development, features and validation of that model. When constructing the model, emphasis was placed on element quality and ease of mesh generation. As such, a number of variations of the model were created. The model was validated against a series of cadaveric impact tests. A parametric study (a High/Low study) was performed to investigate the effect of the bulk and shear modulus of the brain and cerebrospinal fluid (CSF). The influence of different mesh densities on the models and the use of different element formulations for the skull were also investigated. It was found that the short-term shear modulus of the neural tissue had the predominant effect on intracranial frontal pressure, and on the predicted Von-Mises response. The bulk modulus of the fluid had a significant effect on the contre-coup pressure when the CSF was modelled using a coupled node definition. Differences of intracranial pressure were reported that show the sensitivity of the method by which the skull is modelled. By simulating an identical impact scenario with a range of different finite element models it has been possible to investigate the influence of model topologies. We can conclude that careful modelling of the CSF (depth/volume) and skull thickness (including cortical/ trabecular ratio) is necessary if the correct intracranial pressure distribution is to be predicted, and so further forms of validation are required to improve the finite element models' injury prediction capabilities.

The creation of three-dimensional finite element models for simulating head impact biomechanics

Fifty years of brain tissue mechanical testing: From in vitro to in vivo investigations

Head injury prediction capability of the HIC, HIP, SIMon and ULP criteria.

The impact response of a three-dimensional human head model has been determined by simulating two cadaver tests. The objective of this study was to validate a finite-element human head model under different impact conditions by considering intracranial compressibility. The current University Louis Pasteur model was subjected initially to a direct head impact, of short (6 ms) duration, and the simulation results were compared with published experimental cadaver tests. The model response closely matched the experimental data. A long duration pulse was chosen for the second impact and this necessitated careful consideration of the head–neck joint in order to replicate the experimental kinematics. The skull was defined as a rigid body and was subjected to six velocities. Output from the model did not accurately match the experimental results and this clearly indicates that it is important to validate a finite-element head model under various impact conditions to define the range of validity. Lack of agreement for the second impact is attributed to the nonlinearity in the dynamic behavior of intracranial stress, a problem that is not reported in the literature. © 1999 Biomedical Engineering Society.

Three-dimensional human head finite-element model validation against two experimental impacts.

This study presents an original numerical human head model followed by there modal and temporal validation against human head vibration analysis in vivo and cadaver impact tests. The human head FE model developed by ULP presents two particularities : one at the brain-skull interface level were fluid-structure interaction is taken into account, the other at the skull modelling level by integrating the bone fracture simulation. Validation shows that the model correlated well with a number of experimental cadaver tests and predicted intra-cranial pressure accurately. However, for long duration impacts the model reaches its limits. The skull stiffness and fracture force were accurately predicted when compared with experimental values from the literature. This improved numerical human head surrogates has then be used for numerical real world accident reconstruction. Helmet damage from thirteen motorcycle accidents was replicated in drop tests in order to define the head's loading conditions. A total of twenty two well documented American football head trauma have been reconstructed as well as twenty eight pedestrian head impacts. By correlating head injury type and location with intra-cerebral mechanical field parameters, it was possible to derive new injury risk curves relative to specific injury mechanisms.

Human head tolerance limits to specific injury mechanisms

Head injury remains one of the most frequent and severe injuries sustained by vehicle occupants, motorcyclists, pedestrians and cyclists in road accidents and account for approximately 40% of road fatalities in the European Union (EU). One essential requirement for reducing the incidence of fatal and severe head injuries is to develop head injury assessment methods that can accurately and comprehensively assess the potential head injury risk under a broad range of head impact conditions. At present, the most widely accepted method of assessing head injury risk in road safety research is the Head Injury Criterion (HIC). However, HIC only considers the injury risk to the head resulting from linear head accelerations. In an attempt to develop improved head injury criteria for specific mechanisms, 68 head impact conditions that occurred in motor sport, motorcyclist, American football and pedestrian accidents were re-constructed with a state of the art finite element (FE) human head model (ULP head model). Sta...

Rémy Willinger

Papers

Fifty years of brain tissue mechanical testing: From in vitro to in vivo investigations

Head injury prediction capability of the HIC, HIP, SIMon and ULP criteria.

Three-dimensional human head finite-element model validation against two experimental impacts.

Human head tolerance limits to specific injury mechanisms

Improved head injury criteria based on head FE model