Blaine Hoshizaki

Clinical Risk Score for Persistent Postconcussion Symptoms Among Children With Acute Concussion in the ED

IMPORTANCE Approximately one-third of children experiencing acute concussion experience ongoing somatic, cognitive, and psychological or behavioral symptoms, referred to as persistent postconcussion symptoms (PPCS). However, validated and pragmatic tools enabling clinicians to identify patients at risk for PPCS do not exist. OBJECTIVE To derive and validate a clinical risk score for PPCS among children presenting to the emergency department. DESIGN, SETTING, AND PARTICIPANTS Prospective, multicenter cohort study (Predicting and Preventing Postconcussive Problems in Pediatrics [5P]) enrolled young patients (aged 5-<18 years) who presented within 48 hours of an acute head injury at 1 of 9 pediatric emergency departments within the Pediatric Emergency Research Canada (PERC) network from August 2013 through September 2014 (derivation cohort) and from October 2014 through June 2015 (validation cohort). Participants completed follow-up 28 days after the injury. EXPOSURES All eligible patients had concussions consistent with the Zurich consensus diagnostic criteria. MAIN OUTCOMES AND MEASURES The primary outcome was PPCS risk score at 28 days, which was defined as 3 or more new or worsening symptoms using the patient-reported Postconcussion Symptom Inventory compared with recalled state of being prior to the injury. RESULTS In total, 3063 patients (median age, 12.0 years [interquartile range, 9.2-14.6 years]; 1205 [39.3%] girls) were enrolled (n = 2006 in the derivation cohort; n = 1057 in the validation cohort) and 2584 of whom (n = 1701 [85%] in the derivation cohort; n = 883 [84%] in the validation cohort) completed follow-up at 28 days after the injury. Persistent postconcussion symptoms were present in 801 patients (31.0%) (n = 510 [30.0%] in the derivation cohort and n = 291 [33.0%] in the validation cohort). The 12-point PPCS risk score model for the derivation cohort included the variables of female sex, age of 13 years or older, physician-diagnosed migraine history, prior concussion with symptoms lasting longer than 1 week, headache, sensitivity to noise, fatigue, answering questions slowly, and 4 or more errors on the Balance Error Scoring System tandem stance. The area under the curve was 0.71 (95% CI, 0.69-0.74) for the derivation cohort and 0.68 (95% CI, 0.65-0.72) for the validation cohort. CONCLUSIONS AND RELEVANCE A clinical risk score developed among children presenting to the emergency department with concussion and head injury within the previous 48 hours had modest discrimination to stratify PPCS risk at 28 days. Before this score is adopted in clinical practice, further research is needed for external validation, assessment of accuracy in an office setting, and determination of clinical utility.

Finite element analysis of the effect of loading curve shape on brain injury predictors.

Prediction of traumatic and mild traumatic brain injury is an important factor in managing their prevention. Currently, the prediction of these injuries is limited to peak linear and angular acceleration loading curves derived from laboratory reconstructions. However it remains unclear as to what aspect of these loading curves contributes to brain tissue damage. This research uses the University College Dublin Brain Trauma Model (UCDBTM) to analyse three distinct loading curve shapes meant to represent different helmet loading scenarios. The loading curves were applied independently in each axis of linear and angular acceleration and their effect on currently used predictors of TBI and mTBI was examined. Loading curve shape A had a late time to peak, B an early time to peak and C had a consistent plateau. The areas under the curve for all three loading curve shapes were identical. The results indicate that loading curve A produced consistently higher maximum principal strains and Von Mises stress than the other two loading curve types. Loading curve C consistently produced the lowest values of maximum principal strain and Von Mises stress, with loading curve B being lowest in only 2 cases. The areas of peak Von Mises stress and Principal strain also varied depending on loading curve shape and acceleration input.

A Multiscale Computational Approach to Estimating Axonal Damage under Inertial Loading of the Head

A computational modeling framework is developed to estimate the location and degree of diffuse axonal injury (DAI) under inertial loading of the head. DAI is one of the most common pathological features of traumatic brain injury and is characterized by damage to the neural axons in the white matter regions of the brain. We incorporate the microstructure of the white matter (i.e., the fiber orientations and fiber dispersion) through the use of diffusion tensor imaging (DTI), and model the white matter with an anisotropic, hyper-viscoelastic constitutive model. The extent of DAI is estimated using an axonal strain injury criterion. A novel injury analysis method is developed to quantify the degree of axonal damage in the fiber tracts of the brain and identify the tracts that are at the greatest risk for functional failure. Our modeling framework is applied to analyze DAI in a real-life ice hockey incident that resulted in concussive injury. To simulate the impact, two-dimensional finite element (FE) models of the head were constructed from detailed MRI and DTI data and validated using available human head experimental data. Acceleration loading curves from accident reconstruction data were then applied to the FE models. The rotational (rather than translational) accelerations were shown to dominate the injury response, which is consistent with previous studies. Through this accident reconstruction, we demonstrate a conceptual framework to estimate the degree of axonal injury in the fiber tracts of the human brain, enabling the future development of relationships between computational simulation and neurocognitive impairment.

Examination of the relationship between peak linear and angular accelerations to brain deformation metrics in hockey helmet impacts

Ice hockey is a contact sport which has a high incidence of brain injury. The current methods of evaluating protective devices use peak resultant linear acceleration as their pass/fail criteria, which are not fully representative of brain injuries as a whole. The purpose of this study was to examine how the linear and angular acceleration loading curves from a helmeted impact influence currently used brain deformation injury metrics. A helmeted Hybrid III headform was impacted in five centric and non-centric impact sites to elicit linear and angular acceleration responses. These responses were examined through the use of a brain model. The results indicated that when the helmet is examined using peak resultant linear acceleration alone, they are similar and protective, but when a 3D brain deformation response is used to examine the helmets, there are risks of brain injury with lower linear accelerations which would pass standard certifications for safety.

A centric/non-centric impact protocol and finite element model methodology for the evaluation of American football helmets to evaluate risk of concussion

American football reports high incidences of head injuries, in particular, concussion. Research has described concussion as primarily a rotation dominant injury affecting the diffuse areas of brain tissue. Current standards do not measure how helmets manage rotational acceleration or how acceleration loading curves influence brain deformation from an impact and thus are missing important information in terms of how concussions occur. The purpose of this study was to investigate a proposed three-dimensional impact protocol for use in evaluating football helmets. The dynamic responses resulting from centric and non-centric impact conditions were examined to ascertain the influence they have on brain deformations in different functional regions of the brain that are linked to concussive symptoms. A centric and non-centric protocol was used to impact an American football helmet; the resulting dynamic response data was used in conjunction with a three-dimensional finite element analysis of the human brain to calculate brain tissue deformation. The direction of impact created unique loading conditions, resulting in peaks in different regions of the brain associated with concussive symptoms. The linear and rotational accelerations were not predictive of the brain deformation metrics used in this study. In conclusion, the test protocol used in this study revealed that impact conditions influences the region of loading in functional regions of brain tissue that are associated with the symptoms of concussion. The protocol also demonstrated that using brain deformation metrics may be more appropriate when evaluating risk of concussion than using dynamic response data alone.

Proprioception of foot and ankle complex in young regular practitioners of ice hockey, ballet dancing and running.

This study examined the proprioception of the foot and ankle complex in regular ice hockey practitioners, runners, and ballet dancers. A total of 45 young people with different exercise habits formed four groups: the ice hockey, ballet dancing, running, and sedentary groups. Kinesthesia of the foot and ankle complex was measured in plantarflexion (PF), dorsiflexion (DF), inversion (IV), and eversion (EV) at 0.4°/s using a custom-made device. The results showed the following: (1) significantly better perceived passive motion sense in PF/DF was found as compared with the measurements in IV/EV within each group (P < .01); (2) ice hockey and ballet groups perceived significantly better passive motion sense in IV/EV than the running (P < .05) and the sedentary (P < .01) groups; and (3) no significant difference in the all measurements was found between running and sedentary groups. The benefits of ice hockey and ballet dancing on proprioception may be associated with their movement characteristics.

The Relationship between Head Impact Characteristics and Brain Trauma

Brain injury is complex in nature and extraordinarily challenging when attempting to describe the relationship between the event and the resulting injury. In an effort to reduce its severity and incidence a great deal of research investigating mechanisms of brain injury has involved the areas of anatomical, reconstructive, and finite elements modeling. The anatomical research primarily examines functional and mechanical failure thresholds for different types of brain tissue [1-3]. Approximate strain levels are described for the different tissues that are then used to represent human responses [4]. Anatomical research examines individual brain tissues while reconstructive research simulates how injured individuals were impacted in order to discover relationships between engineering variables such as acceleration, stress, and strain and the resulting brain injury [5-7]. Currently, much of this research has focused on sporting concussions as they are frequent and often documented providing information for accurate reconstructions [5,6]. Finite element modeling provides a tool to obtain brain tissue response values resulting from an impact. Within the term traumatic brain injury (TBI) there are several different types of brain injury lesions, each with their own respective mechanisms and possibly predictive variables [8]. The multiple types of injuries described within TBI may also expound concussion, which has been described to have different levels of severity: sub concussive, transient, and persistent. In addition to examining the nature of the continuum of brain injury associated with the severity of impact, the mechanisms of injury contributing to these outcomes are also examined. The most common mechanisms of brain injury include: falls, collisions, projectiles, and punches. These mechanisms are examined and a synthesis of how they contribute to the outcome of the injury within the continuum of TBI and concussion is discussed. This provides information on how accelerations, resulting from an impact, affect brain tissue response and the location of the highest magnitudes of stress and strain. This review examines the nature of traumatic and concussive brain injury within the context of a continuum based upon impact severity using anatomical, reconstructive and finite element methodologies.

Performance analysis of winter activity protection headgear for young children

OBJECT The purpose of this study was to evaluate how currently used helmets would perform for winter play activities, such as tobogganing. In Canada and northern parts of the US, the advent of winter is followed by an increase in visits to hospital emergency departments by young children presenting with head injuries resulting from winter activities. Sliding, skating, skiing, and snowboarding all involve risks of head injury from situations such as falling on ice or sliding into stationary objects. This study compared the protective characteristics of helmets used by young children (< 7 years of age) participating in winter recreational activities. METHODS Ice hockey, alpine ski, and bicycling helmets were impacted at 2.0, 4.0, 6.0, and 8.0 m/second at the front and side impact location by using a monorail drop rig. RESULTS The results for the front impact showed that the ice hockey helmet protected the child significantly better at 2 and 4 m/second when considering both linear and angular peak acceleration. The bicycle helmet performed significantly better than the other 2 helmets at 8 m/second for the front location and only angularly for the side impacts. CONCLUSIONS Depending on the impact velocity of the hazard, the type of helmet significantly affected the risk of brain injury.

The ability of American football helmets to manage linear acceleration with repeated high-energy impacts

CONTEXT Football players can receive up to 1400 head impacts per season, averaging 6.3 impacts per practice and 14.3 impacts per game. A decrease in the capacity of a helmet to manage linear acceleration with multiple impacts could increase the risk of traumatic brain injury. OBJECTIVE To investigate the ability of football helmets to manage linear acceleration with multiple high-energy impacts. DESIGN Descriptive laboratory study. SETTING Laboratory. MAIN OUTCOME MEASURE(S) We collected linear-acceleration data for 100 impacts at 6 locations on 4 helmets of different models currently used in football. Impacts 11 to 20 were compared with impacts 91 to 100 for each of the 6 locations. RESULTS Linear acceleration was greater after multiple impacts (91-100) than after the first few impacts (11-20) for the front, front-boss, rear, and top locations. However, these differences are not clinically relevant as they do not affect the risk for head injury. CONCLUSIONS American football helmet performance deteriorated with multiple impacts, but this is unlikely to be a factor in head-injury causation during a game or over a season.