Novel strain analysis informs about injury susceptibility of the corpus callosum to repeated impacts

Champagne, Allen A.; Peponoulas, Emile; Terem, Itamar; Ross, Andrew; Tayebi, Maryam; Coverdale, Nicole S.; Nielsen, Poul M. F.; Wang, Alan; Shim, Vickie; Holdsworth, Samantha J.; Cook, Douglas J.

doi:10.1093/braincomms/fcz021

Cited by 23 publications

(39 citation statements)

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“…The median linear and rotational head accelerations for striking and struck players reported in this study are lower than measurements in other similar studies. 8,11,12,30,31 Four other studies have measured head impact magnitudes in Canadian university football players using the GFT head impact sensor. 8,11,12,31 However, only one of them used a location-dependent algorithm to calculate centre of mass impact magnitudes from the helmet shell measurements 8 which reduces the mean absolute percent error of peak linear and rotational accelerations measurements from 50% to less than 10%.…”

Section: Discussionmentioning

confidence: 99%

The Hammer and the Nail: Biomechanics of Striking and Struck Canadian University Football Players

et al. 2021

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This study sought to evaluate head accelerations in both players involved in a football collision. Players on two opposing Canadian university teams were equipped with helmet mounted sensors during one game per season, for two consecutive seasons. A total of 276 collisions between 58 instrumented players were identified via video and cross-referenced with sensor timestamps. Player involvement (striking and struck), impact type (block or tackle), head impact location (front, back, left and right), and play type were recorded from video footage. While struck players did not experience significantly different linear or rotational accelerations between any play types, striking players had the highest linear and rotational head accelerations during kickoff plays (p ≤ .03). Striking players also experienced greater linear and rotational head accelerations than struck players during kickoff plays (p = .001). However, struck players experienced greater linear and rotational accelerations than striking players during kick return plays (p ≤ .008). Other studies have established that the more severe the head impact, the greater risk for injury to the brain. This paper’s results highlight that kickoff play rule changes, as implemented in American college football, would decrease head impact exposure of Canadian university football athletes and make the game safer.

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Section: Discussionmentioning

confidence: 99%

The Hammer and the Nail: Biomechanics of Striking and Struck Canadian University Football Players

et al. 2021

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“…We have developed a subject-specific FE model of the human brain using their MR images. 11,31 However, the material properties for this model came from the literature, limiting its subject-specificity to the geometry and white matter fiber tracts only. Therefore, the location-specific material properties obtained from our study along with the MRI scans taken both pre and post-impact are being used to create a completely subject-specific finite element model (both geometry and material propertywise), which will be the first fully subject-specific brain FE model.…”

Section: Discussionmentioning

confidence: 99%

Analyzing the changes in the brain material properties after a mild traumatic brain injury—A pilot study

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Holdsworth

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et al. 2020

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Traumatic brain injury (TBI) is a major health challenge, is very difficult to diagnose, and currently has no accepted treatment options. The difficulty in diagnosis is due to the complex pathophysiology of TBI, where the damage mechanisms span multiple spatial and temporal scales and ultimately manifest as diverse cognitive impairments in brain function. The speed and dynamic nature with which the mechanical insults occur in TBI means that computational models are the best candidate to mimic the in vivo event and to investigate the injury progression in detail. A current weakness in TBI computational models is the poor understanding of how material properties within different regions of the brain change after damage. Here, we developed an animal experiment pipeline where a controlled and reproducible mechanical insult can be applied to a sheep brain in vivo followed by ex vivo compression mechanical testing. For each brain, the compression mechanical testing was conducted across the length of the brain to assess baseline regional variations in material properties and how these properties changed after mechanical impact. Using this pipeline, we have characterized locational variations in the brain material properties both pre and post-TBI. Our preliminary results confirm that there exist locational variations in the brain material properties across all regions of cerebrum. The analysis of post-TBI tissues showed that compressive strength was reduced in the area nearest the direct impact.

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“…A subject-specific finite element model of the human brain was generated from magnetic resonance imaging (MRI) data of our previous research [19] where a longitudinal study with male Canadian football players was performed to measure the changes in brain structure measured with MRI. Briefly, MRI data (T1 high resolution anatomical image and diffusion tensor imaging (DTI)) from football players (all male, average age = 20.3 1.4) was acquired longitudinally over the course of the season at three time points -1) prior to the pre-season training camp within 2 months before the first contact practice ("PRE"); 2) post training following 14day training camp and the first two games of the season ("PTC"); 3) post season ("POST").…”

Section: A Subject-specific Fe Analysis Of the Brain With Embedded Wmentioning

confidence: 99%

“…The parameter values 1,~4, were obtained from Chatelin et al [19] and given below (Table 1). Other major tissues in the brain were modelled separately, which included the dura matter, falx and scalp.…”

Section: Figure 3 Embedding the White Matter Fibre Orientation To Thmentioning

confidence: 99%

“…The material values used for these tissues were obtained from the literature as shown in Table 2. Regarding the boundary condition, we used the dynamic contact mechanics algorithm developed by Fan et al [19], which allowed us to model TBI by impacting the head with an impactor as described in Zhang et al [7]. We simulated both frontal and occipital impacts.…”

Section: Figure 3 Embedding the White Matter Fibre Orientation To Thmentioning

confidence: 99%

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Rapid Prediction of Brain Injury Pattern in mTBI by Combining FE Analysis With a Machine-Learning Based Approach

et al. 2020

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Mild traumatic brain injury (mTBI) is a significant issue worldwide. Public awareness of the dangers of mTBI has increased sharply in recent years, yet there is no easy-to-use tool available for early detection and post injury management. Computational models of the head impact, usually in the form of finite element analysis, are a method of choice for characterizing how mechanical impacts lead to brain damage by causing high strains in certain regions of the brain. However, those models require a prohibitively large amount of computational power as well as pre and post processing expertise, making them unrealistic to be used in clinical settings. In this study, we propose a framework that combines finite element analysis with a machine learning based approach where a large number of pre-computed FE results are used to train a statistical model. We analyzed a number of different head impact scenarios in which a football player would sustain a minor brain injury and computed brain internal strain patterns. These pre-computed strain patterns were then used to train a partial least squares regression model to be able to predict the general strain pattern and the location and magnitude of peak strains. Our models were able to predict the overall distribution pattern, including the location of the peak strain, with an average error of 3%. The peak strain magnitudes were also predicted accurately with the average error of 9% at almost real time speed (less than 10 seconds). This model may play an important role in developing a diagnostic tool for mTBI that can predict the severity of head impacts. INDEX TERMS diffusion tensor imaging, finite element analysis, magnetic resonance imaging, mild traumatic brain injury, partial least squares regression

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Novel strain analysis informs about injury susceptibility of the corpus callosum to repeated impacts

Cited by 23 publications

References 63 publications

The Hammer and the Nail: Biomechanics of Striking and Struck Canadian University Football Players

The Hammer and the Nail: Biomechanics of Striking and Struck Canadian University Football Players

Analyzing the changes in the brain material properties after a mild traumatic brain injury—A pilot study

Rapid Prediction of Brain Injury Pattern in mTBI by Combining FE Analysis With a Machine-Learning Based Approach

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