T. Blaine Hoshizaki

Mechanisms of brain impact injuries and their prediction: A review

Brain injuries are a significant contributor to morbidity and mortality. Currently a great deal of controversy exists concerning the mechanism of these injuries and concussion in particular. The following review discusses the anatomical mechanisms which are known to cause brain injuries and the variables currently used to predict their incidence. This review examines how current engineering techniques and measurements are being used to research brain injury mechanisms. The text examines the past and current measurement techniques and their benefits and drawbacks when it comes to predicting brain injuries and understanding brain injury research. Finally, future methods of quantifying brain injury are discussed with concluding remarks concerning the efficacy of current measurement techniques to predict brain injuries.

Rotational Acceleration, Brain Tissue Strain, and the Relationship to Concussion

The mechanisms of concussion have been investigated by many researchers using a variety of methods. However, there remains much debate over the relationships between head kinematics from an impact and concussion. This review presents the links between research conducted in different disciplines to better understand the relationship between linear and rotational acceleration and brain strains that have been postulated as the root cause of concussion. These concepts are important when assigning performance variables for helmet development, car design, and protective innovation research.

Current and future concepts in helmet and sports injury prevention

Since the introduction of head protection, a decrease in sports-related traumatic brain injuries has been reported. The incidence of concussive injury, however, has remained the same or on the rise. These trends suggest that current helmets and helmet standards are not effective in protecting against concussive injuries. This article presents a literature review that describes the discrepancy between how helmets are designed and tested and how concussions occur. Most helmet standards typically use a linear drop system and measure criterion such as head Injury criteria, Gadd Severity Index, and peak linear acceleration based on research involving severe traumatic brain injuries. Concussions in sports occur in a number of different ways that can be categorized into collision, falls, punches, and projectiles. Concussive injuries are linked to strains induced by rotational acceleration. Because helmet standards use a linear drop system simulating fall-type injury events, the majority of injury mechanisms are neglected. In response to the need for protection against concussion, helmet manufacturers have begun to innovate and design helmets using other injury criteria such as rotational acceleration and brain tissue distortion measures via finite-element analysis. In addition to these initiatives, research has been conducted to develop impact protocols that more closely reflect how concussions occur in sports. Future research involves a better understanding of how sports-related concussions occur and identifying variables that best describe them. These variables can be used to guide helmet innovation and helmet standards to improve the quality of helmet protection for concussive injury.Since the introduction of head protection, a decrease in sports-related traumatic brain injuries has been reported. The incidence of concussive injury, however, has remained the same or on the rise. These trends suggest that current helmets and helmet standards are not effective in protecting against concussive injuries. This article presents a literature review that describes the discrepancy between how helmets are designed and tested and how concussions occur. Most helmet standards typically use a linear drop system and measure criterion such as head Injury criteria, Gadd Severity Index, and peak linear acceleration based on research involving severe traumatic brain injuries. Concussions in sports occur in a number of different ways that can be categorized into collision, falls, punches, and projectiles. Concussive injuries are linked to strains induced by rotational acceleration. Because helmet standards use a linear drop system simulating fall-type injury events, the majority of injury mechanisms are neglected. In response to the need for protection against concussion, helmet manufacturers have begun to innovate and design helmets using other injury criteria such as rotational acceleration and brain tissue distortion measures via finite-element analysis. In addition to these initiatives, research has been conducted to develop impact protocols that more closely reflect how concussions occur in sports. Future research involves a better understanding of how sports-related concussions occur and identifying variables that best describe them. These variables can be used to guide helmet innovation and helmet standards to improve the quality of helmet protection for concussive injury.

The influence of dynamic response and brain deformation metrics on the occurrence of subdural hematoma in different regions of the brain

OBJECT The purpose of this study was to examine how the dynamic response and brain deformation of the head and brain-representing a series of injury reconstructions of which subdural hematoma (SDH) was the outcome-influence the location of the lesion in the lobes of the brain. METHODS Sixteen cases of falls in which SDH was the outcome were reconstructed using a monorail drop rig and Hybrid III headform. The location of the SDH in 1 of the 4 lobes of the brain (frontal, parietal, temporal, and occipital) was confirmed by CT/MR scan examined by a neurosurgeon. RESULTS The results indicated that there were minimal differences between locations of the SDH for linear acceleration. The peak resultant rotational acceleration and x-axis component were larger for the parietal lobe than for other lobes. There were also some differences between the parietal lobe and the other lobes in the z-axis component. Maximum principal strain, von Mises stress, shear strain, and product of strain and strain rate all had differences in magnitude depending on the lobe in which SDH was present. The parietal lobe consistently had the largest-magnitude response, followed by the frontal lobe and the occipital lobe. CONCLUSIONS The results indicated that there are differences in magnitude for rotational acceleration and brain deformation metrics that may identify the location of SDH in the brain.

Characterization of persistent concussive syndrome using injury reconstruction and finite element modelling.

Concussions occur 1.7 million times a year in North America, and account for approximately 75% of all traumatic brain injuries (TBI). Concussions usually cause transient symptoms but 10 to 20% of patients can have symptoms that persist longer than a month. The purpose of this research was to use reconstructions and finite element modeling to determine the brain tissue stresses and strains that occur in impacts that led to persistent post concussive symptoms (PCS) in hospitalized patients. A total of 21 PCS patients had their head impacts reconstructed using computational, physical and finite element methods. The dependent variables measured were maximum principal strain, von Mises stress (VMS), strain rate, and product of strain and strain rate. For maximum principal strain alone there were large regions of brain tissue incurring 30 to 40% strain. This large field of strain was also evident when using strain rate, product of strain and strain rate. In addition, VMS also showed large magnitudes of stress throughout the cerebrum tissues. The distribution of strains throughout the brain tissues indicated peak responses were always present in the grey matter (0.481), with the white matter showing significantly lower strains (0.380) (p<0.05). The impact conditions of the PCS cases were severe in nature, with impacts against non-compliant surfaces (concrete, steel, ice) resulting in higher brain deformation. PCS biomechanical parameters were shown to fit between those that have been shown to cause transient post concussive symptoms and those that lead to actual pathologic damage like contusion, however, values of all metrics were characterized by large variance and high average responses. This data supports the theory that there exists a progressive continuum of impacts that lead to a progressive continuum of related severity of injury from transient symptoms to pathological damage.

Comparison between Hybrid III and Hodgson–WSU headforms by linear and angular dynamic impact response

In brain injury research, linear and angular resultant acceleration data have been considered important mechanisms contributing to various levels of brain injury. The development of biofidelic headforms with similar dimensions and weight to that of a real human head has allowed for researchers to repeatedly collect data related to the effects of different impacts on the human head. Currently, there are different types of headforms available for impact testing, each with varying degrees of biofidelity and repeatability. Two commonly used headforms were tested: the Hybrid III and the Hodgson–WSU (NOCSAE). The two headforms were outfitted with nine single-axis accelerometers positioned orthogonally following a 3–2–2–2 array. Both headforms show good linearity and correlate well throughout the different velocities and are, therefore, reliable tools. Significant differences are observed in peak linear and peak angular accelerations between Hybrid III and Hodgson–WSU headforms. The shapes of the loading curves are visually different and thus may have significant impact on the output from FE modelling of the brain response.

The influence of acceleration loading curve characteristics on traumatic brain injury

To prevent brain trauma, understanding the mechanism of injury is essential. Once the mechanism of brain injury has been identified, prevention technologies could then be developed to aid in their prevention. The incidence of brain injury is linked to how the kinematics of a brain injury event affects the internal structures of the brain. As a result it is essential that an attempt be made to describe how the characteristics of the linear and rotational acceleration influence specific traumatic brain injury lesions. As a result, the purpose of this study was to examine the influence of the characteristics of linear and rotational acceleration pulses and how they account for the variance in predicting the outcome of TBI lesions, namely contusion, subdural hematoma (SDH), subarachnoid hemorrhage (SAH), and epidural hematoma (EDH) using a principal components analysis (PCA). Monorail impacts were conducted which simulated falls which caused the TBI lesions. From these reconstructions, the characteristics of the linear and rotational acceleration were determined and used for a PCA analysis. The results indicated that peak resultant acceleration variables did not account for any of the variance in predicting TBI lesions. The majority of the variance was accounted for by duration of the resultant and component linear and rotational acceleration. In addition, the components of linear and rotational acceleration characteristics on the x, y, and z axes accounted for the majority of the remainder of the variance after duration.

Analysis of the influence of independent variables used for reconstruction of a traumatic brain injury incident

Traumatic brain injuries contribute to a high degree of morbidity and mortality in society. To study traumatic brain injuries researchers reconstruct the event using both physical and FE models. The purpose of these reconstructions is to correlate the brain deformation metric to the type of injury as a measure for prediction. These reconstructions are guided by a series of independent variables which all have influence upon the outcome variables. This research uses a combination of physical and FE modelling to quantify how independent variables such as velocity and impact vector (angle) contribute to the resulting variance in brain deformation metrics. The results indicated that using a Hybrid III neck controls the rotational acceleration response from an impact. Also, it was found that strain rate and product of strain and strain rate were more sensitive to changes in impact angle. Linear acceleration decreased with increasing impact angle, while brain deformations did not follow this trend, which suggests that peak linear acceleration may not be the only factor in the production of larger brain deformations.

A comparison of head dynamic response and brain tissue stress and strain using accident reconstructions for concussion, concussion with persistent postconcussive symptoms, and subdural hematoma

OBJECT Concussions typically resolve within several days, but in a few cases the symptoms last for a month or longer and are termed persistent postconcussive symptoms (PPCS). These persisting symptoms may also be associated with more serious brain trauma similar to subdural hematoma (SDH). The objective of this study was to investigate the head dynamic and brain tissue responses of injury reconstructions resulting in concussion, PPCS, and SDH. METHODS Reconstruction cases were obtained from sports medicine clinics and hospitals. All subjects received a direct blow to the head resulting in symptoms. Those symptoms that resolved in 9 days or fewer were defined as concussions (n = 3). Those with symptoms lasting longer than 18 months were defined as PPCS (n = 3), and 3 patients presented with SDHs (n = 3). A Hybrid III headform was used in reconstruction to obtain linear and rotational accelerations of the head. These dynamic response data were then input into the University College Dublin Brain Trauma Model to calculate maximum principal strain and von Mises stress. A Kruskal-Wallis test followed by Tukey post hoc tests were used to compare head dynamic and brain tissue responses between injury groups. Statistical significance was set at p < 0.05. RESULTS A significant difference was identified for peak resultant linear and rotational acceleration between injury groups. Post hoc analyses revealed the SDH group had higher linear and rotational acceleration responses (316 g and 23,181 rad/sec(2), respectively) than the concussion group (149 g and 8111 rad/sec(2), respectively; p < 0.05). No significant differences were found between groups for either brain tissue measures of maximum principal strain or von Mises stress. CONCLUSIONS The reconstruction of accidents resulting in a concussion with transient symptoms (low severity) and SDHs revealed a positive relationship between an increase in head dynamic response and the risk for more serious brain injury. This type of relationship was not found for brain tissue stress and strain results derived by finite element analysis. Future research should be undertaken using a larger sample size to confirm these initial findings. Understanding the relationship between the head dynamic and brain tissue response and the nature of the injury provides important information for developing strategies for injury prevention.

Analysis of loading curve characteristics on the production of brain deformation metrics

Traumatic and mild traumatic brain injuries are incurred as a result of the complex motions of the head after an impact. These motions can be quantified in terms of linear and rotational accelerations which cause the injurious levels of brain deformation. Currently, it is unclear what aspects of the linear and rotational acceleration loading curves influence injurious brain deformation. This research uses the University College Dublin Brain Trauma Model to analyse the loading curve shapes from a series of centric and non-centric impacts to a Hybrid III headform fitted with different hockey helmets. The results found that peak resultant linear acceleration did not always correlate with brain deformation measures. The results also indicated that, due to the complex nature of the interaction between loading curve characteristic and tissue parameters, there was no commonality in curve shape which produced large magnitudes of brain deformation. However, the discriminant function did show that angular acceleration loading curve characteristics would predict brain deformation more reliably than linear acceleration loading curves.