From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury

Neurodegeneration in the cortical sulcus is a feature of chronic traumatic encephalopathy and associated with repetitive head impacts

Neurodegeneration is a seminal feature of many neurological disorders. Chronic traumatic encephalopathy (CTE) is caused by repetitive head impacts (RHI) and is characterized by sulcal tau pathology. However, quantitative assessments of regional neurodegeneration in CTE have not been described. In this study, we quantified three key neurodegenerative measures, including cortical thickness, neuronal density, and synaptic proteins, in contact sport athletes (n = 185) and non-athlete controls (n = 52) within the sulcal depth, middle, and gyral crest of the dorsolateral frontal cortex. Cortical thickness and neuronal density were decreased within the sulcus in CTE compared to controls (p's < 0.05). Measurements of synaptic proteins within the gyral crest showed a reduction of α-synuclein with CTE stage (p = 0.002) and variable changes in PSD-95 density. After adjusting for age, multiple linear regression models demonstrated a strong association between the duration of contact sports play and cortical thinning (p = 0.001) and neuronal loss (p = 0.032) within the sulcus. Additional regression models, adjusted for tau pathology, suggest that within the sulcus, the duration of play was associated with neuronal loss predominantly through tau pathology. In contrast, the association of duration of play with cortical thinning was minimally impacted by tau pathology. Overall, CTE is associated with cortical atrophy and a predominant sulcal neurodegeneration. Furthermore, the duration of contact sports play is associated with measures of neurodegeneration that are more severe in the cortical sulcus and may occur through tau-dependent and independent mechanisms.

How Well Do Popular Bicycle Helmets Protect from Different Types of Head Injury?

Bicycle helmets are designed to protect against skull fractures and associated focal brain injuries, driven by helmet standards. Another type of head injury seen in injured cyclists is diffuse brain injuries, but little is known about the protection provided by bicycle helmets against these injuries. Here, we examine the performance of modern bicycle helmets in preventing diffuse injuries and skull fractures under impact conditions that represent a range of real-world incidents. We also investigate the effects of helmet technology, price, and mass on protection against these pathologies. 30 most popular helmets among UK cyclists were purchased within 9.99-135.00 GBP price range. Helmets were tested under oblique impacts onto a 45° anvil at 6.5 m/s impact speed and four locations, front, rear, side, and front-side. A new headform, which better represents the average human head's mass, moments of inertia and coefficient of friction than any other available headforms, was used. We determined peak linear acceleration (PLA), peak rotational acceleration (PRA), peak rotational velocity (PRV), and BrIC. We also determined the risk of skull fractures based on PLA (linear risk), risk of diffuse brain injuries based on BrIC (rotational risk), and their mean (overall risk). Our results show large variation in head kinematics: PLA (80-213 g), PRV (8.5-29.9 rad/s), PRA (1.6-9.7 krad/s2), and BrIC (0.17-0.65). The overall risk varied considerably with a 2.25 ratio between the least and most protective helmet. This ratio was 1.76 for the linear and 4.21 for the rotational risk. Nine best performing helmets were equipped with the rotation management technology MIPS, but not all helmets equipped with MIPS were among the best performing helmets. Our comparison of three tested helmets which have MIPS and no-MIPS versions showed that MIPS reduced rotational kinematics, but not linear kinematics. We found no significant effect of helmet price on exposure-adjusted injury risks. We found that larger helmet mass was associated with higher linear risk. This study highlights the need for a holistic approach, including both rotational and linear head injury metrics and risks, in helmet design and testing. It also highlights the need for providing information about helmet safety to consumers to help them make an informed choice.

EEG hyperexcitability and hyperconnectivity linked to GABAergic inhibitory interneuron loss following traumatic brain injury

Traumatic brain injury represents a significant global health burden and has the highest prevalence among neurological disorders. Even mild traumatic brain injury can induce subtle, long-lasting changes that increase the risk of future neurodegeneration. Importantly, this can be challenging to detect through conventional neurological assessment. This underscores the need for more sensitive diagnostic tools, such as electroencephalography, to uncover opportunities for therapeutic intervention. Progress in the field has been hindered by a lack of studies linking mechanistic insights at the microscopic level from animal models to the macroscale phenotypes observed in clinical imaging. Our study addresses this gap by investigating a rat model of mild blast traumatic brain injury using both immunohistochemical staining of inhibitory interneurons and translationally relevant electroencephalography recordings. Although we observed no pronounced effects immediately post-injury, chronic time points revealed broadband hyperexcitability and increased connectivity, accompanied by decreased density of inhibitory interneurons. This pattern suggests a disruption in the balance between excitation and inhibition, providing a crucial link between cellular mechanisms and clinical hallmarks of injury. Our findings have significant implications for the diagnosis, monitoring, and treatment of traumatic brain injury. The emergence of electroencephalography abnormalities at chronic time points, despite the absence of immediate effects, highlights the importance of long-term monitoring in traumatic brain injury patients. The observed decrease in inhibitory interneuron density offers a potential cellular mechanism underlying the electroencephalography changes and may represent a target for therapeutic intervention. This study demonstrates the value of combining cellular-level analysis with macroscale neurophysiological recordings in animal models to elucidate the pathophysiology of traumatic brain injury. Future research should focus on translating these findings to human studies and exploring potential therapeutic strategies targeting the excitation-inhibition imbalance in traumatic brain injury.

Assessing Mild Traumatic Brain Injury-Associated Blood-Brain Barrier (BBB) Damage and Restoration Using Late-Phase Perfusion Analysis by 3D ASL MRI: Implications for Predicting Progressive Brain Injury in a Focused Review

Mild traumatic brain injury (mTBI) is a common occurrence around the world, associated with a variety of blunt force and torsion injuries affecting all age groups. Most never reach medical attention, and the identification of acute injury and later clearance to return to usual activities is relegated to clinical evaluation-particularly in sports injuries. Advanced structural imaging is rarely performed due to the usual absence of associated acute anatomic/hemorrhagic changes. This review targets physiologic imaging techniques available to identify subtle blood-brain barrier dysfunction and white matter tract shear injury and their association with chronic traumatic encephalopathy. These techniques provide needed objective measures to assure recovery from injury in those patients with persistent cognitive/emotional symptoms and in the face of repetitive mTBI.

Repeated intrathecal injections of peripheral nerve-derived stem cell spheroids improve outcomes in a rat model of traumatic brain injury

BACKGROUND

Traumatic brain injury (TBI) is a major cause of disability and mortality worldwide. However, existing treatments still face numerous clinical challenges. Building on our prior research showing peripheral nerve-derived stem cell (PNSC) spheroids with Schwann cell-like phenotypes can secrete neurotrophic factors to aid in neural tissue regeneration, we hypothesized that repeated intrathecal injections of PNSC spheroids would improve the delivery of neurotrophic factors, thereby facilitating the restoration of neurological function and brain tissue repair post-TBI.

METHODS

We generated PNSC spheroids from human peripheral nerve tissue using suspension culture techniques. These spheroids were characterized using flow cytometry, immunofluorescence, and reverse-transcription polymerase chain reaction. The conditioned media were evaluated in SH-SY5Y and RAW264.7 cell lines to assess their effects on neurogenesis and inflammation. To simulate TBI, we established a controlled cortical impact (CCI) model in rats. The animals were administered intrathecal injections of PNSC spheroids on three occasions, with each injection spaced at a 3-day interval. Recovery of sensory and motor function was assessed using the modified neurological severity score (mNSS) and rotarod tests, while histological (hematoxylin and eosin, Luxol fast blue staining) and T2-weighted magnetic resonance imaging analyses, alongside immunofluorescence, were conducted to evaluate the recovery of neural structures and pathophysiology.

RESULTS

PNSC spheroids expressed high levels of Schwann cell markers and neurotrophic factors, such as neurotrophin-3 and Ephrin B3. Their conditioned medium was found to promote neurite outgrowth, reduce reactive oxygen species-mediated cell death and inflammation, and influence M1-M2 macrophage polarization. In the CCI rat model, rats receiving repeated triple intrathecal injections of PNSC spheroids showed significant improvements in sensory and motor function, with considerable neural tissue recovery in damaged areas. Notably, this treatment promoted nerve regeneration, axon regrowth, and remyelination. It also reduced glial scar formation and inflammation, while encouraging angiogenesis.

CONCLUSION

Our findings suggest that repeated intrathecal injections of PNSC spheroids can significantly enhance neural recovery after TBI. This effect is mediated by the diverse neurotrophic factors secreted by PNSC spheroids. Thus, the strategy of combining therapeutic cell delivery with multiple intrathecal injections holds promise as a novel clinical treatment for TBI recovery.

An Objective Injury Threshold for the Maximum Principal Strain Criterion for Brain Tissue in the Finite Element Head Model and Its Application

Although the finite element head model (FEHM) has been widely utilized to analyze injury locations and patterns in traumatic brain injury, significant controversy persists regarding the selection of a mechanical injury variable and its corresponding threshold. This paper aims to determine an objective injury threshold for maximum principal strain (MPS) through a novel data-driven method, and to validate and apply it. We extract the peak responses from all elements across 100 head impact simulations to form a dataset, and then determine the objective injury threshold by analyzing the relationship between the combined injury degree and the threshold according to the stationary value principle. Using an occipital impact case from a clinical report as an example, we evaluate the accuracy of the injury prediction based on the new threshold. The results show that the injury area predicted by finite element analysis closely matches the main injury area observed in CT images, without the issue of over- or underestimating the injury due to an unreasonable threshold. Furthermore, by applying this threshold to the finite element analysis of designed occipital impacts, we observe, for the first time, supra-tentorium cerebelli injury, which is related to visual memory impairment. This discovery may indicate the biomechanical mechanism of visual memory impairment after occipital impacts reported in clinical cases.

Traumatic axonal injury: Clinic, forensic and biomechanics perspectives

Identification of Traumatic axonal injury (TAI) is critical in clinical practice, particularly in terms of long-term prognosis, but also for medico-legal issues, to verify whether the death or the after-effects were attributable to trauma. Multidisciplinary approaches are an undeniable asset when it comes to solving these problems. The aim of this work is therefore to list the different techniques needed to identify axonal lesions and to understand the lesion mechanisms involved in their formation. Imaging can be used to assess the consequences of trauma, to identify indirect signs of TAI, to explain the patient's initial symptoms and even to assess the patient's prognosis. Three-dimensional reconstructions of the skull can highlight fractures suggestive of trauma. Microscopic and immunohistochemical techniques are currently considered as the most reliable tools for the early identification of TAI following trauma. Finite element models use mechanical equations to predict biomechanical parameters, such as tissue stresses and strains in the brain, when subjected to external forces, such as violent impacts to the head. These parameters, which are difficult to measure experimentally, are then used to predict the risk of injury. The integration of imaging data with finite element models allows researchers to create realistic and personalized computational models by incorporating actual geometry and properties obtained from imaging techniques. The personalization of these models makes their forensic approach particularly interesting.

Effect of Human Head Shape on the Risk of Traumatic Brain Injury: A Gaussian Process Regression-Based Machine Learning Approach

INTRODUCTION

Computational head injury models are promising tools for understanding and predicting traumatic brain injuries. However, most available head injury models are "average" models that employ a single set of head geometry (e.g., 50th-percentile U.S. male) without considering variability in these parameters across the human population. A significant variability of head shapes exists in U.S. Army soldiers, evident from the Anthropometric Survey of U.S. Army Personnel (ANSUR II). The objective of this study is to elucidate the effects of head shape on the predicted risk of traumatic brain injury from computational head injury models.

MATERIALS AND METHODS

Magnetic resonance imaging scans of 25 human subjects are collected. These images are registered to the standard MNI152 brain atlas, and the resulting transformation matrix components (called head shape parameters) are used to quantify head shapes of the subjects. A generative machine learning model is used to generate 25 additional head shape parameter datasets to augment our database. Head injury models are developed for these head shapes, and a rapid injurious head rotation event is simulated to obtain several brain injury predictor variables (BIPVs): Peak cumulative maximum principal strain (CMPS), average CMPS, and the volume fraction of brain exceeding an injurious CMPS threshold. A Gaussian process regression model is trained between head shape parameters and BIPVs, which is then used to study the relative sensitivity of the various BIPVs on individual head shape parameters. We distinguish head shape parameters into 2 types: Scaling components ${T_{xx}}$, ${T_{yy}}$, and ${T_{zz}}$ that capture the breadth, length, and height of the head, respectively, and shearing components (${T_{xy}},{T_{xz}},{T_{yx}},{T_{yz}},{T_{zx}}$, and ${T_{zy}}$) that capture the relative skewness of the head shape.

RESULTS

An overall positive correlation is evident between scaling components and BIPVs. Notably, a very high, positive correlation is seen between the BIPVs and the head volume. As an example, a 57% increase in peak CMPS was noted between the smallest and the largest investigated head volume parameters. The variation in shearing components ${T_{xy}},{T_{xz}},{T_{yx}},{T_{yz}},{T_{zx}}$, and ${T_{zy}}$ on average does not cause notable changes in the BIPVs. From the Gaussian process regression model, all 3 BIPVs showed an increasing trend with each of the 3 scaling components, but the BIPVs are found to be most sensitive to the height dimension of the head. From the Sobol sensitivity analysis, the ${T_{zz}}$ scaling parameter contributes nearly 60% to the total variance in peak and average CMPS; ${T_{yy}}$ contributes approximately 20%, whereas ${T_{xx}}$ contributes less than 5%. The remaining contribution is from the 6 shearing components. Unlike peak and average CMPS, the VF-CMPS BIPV is associated with relatively evenly distributed Sobol indices across the 3 scaling parameters. Furthermore, the contribution of shearing components on the total variance in this case is negligible.

CONCLUSIONS

Head shape has a considerable influence on the injury predictions of computational head injury models. Available "average" head injury models based on a 50th-percentile U.S. male are likely associated with considerable uncertainty. In general, larger head sizes correspond to greater BIPV magnitudes, which point to potentially a greater injury risk under rapid neck rotation for people with larger heads.

White matter and cortical gray matter microstructural abnormalities in new daily persistent headache: a NODDI study

BACKGROUND

New daily persistent headache (NDPH) is a rare primary headache with unclear pathogenesis. Neuroimaging studies of NDPH are limited, and controversy still exists. Diffusion tensor imaging (DTI) is commonly used to study the white matter. However, lacking specificity, the potential pathological mechanisms of white matter microstructural changes remain poorly understood. In addition, the intricacy of gray matter structures impedes the application of the DTI model. Here, we applied an advanced diffusion model of neurite orientation dispersion and density imaging (NODDI) to study the white matter and cortical gray matter microstructure in patients with NDPH.

METHODS

This study assessed brain microstructure, including 27 patients with NDPH, and matched 28 healthy controls (HCs) by NODDI. The differences between the two groups were assessed by tract-based spatial statistics (TBSS) and surface-based analysis (SBA), focusing on the NODDI metrics (neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)). Furthermore, we performed Pearson's correlation analysis between the NODDI indicators and clinical characteristics.

RESULTS

Compared to HCs, patients with NDPH had a reduction of density and complexity in several fiber tracts. For robust results, the fiber tracts were defined as comprising more than 100 voxels, including bilateral inferior fronto-occipital fasciculus (IFOF), left superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF), as well as right corticospinal tract (CST). Moreover, the reduction of neurite density was uncovered in the left superior and middle frontal cortex, left precentral cortex, and right lateral orbitofrontal cortex and insula. There was no correlation between the NODDI metrics of these brain regions and clinical variables or scales of relevance after the Bonferroni correction.

CONCLUSIONS

Our research indicated that neurite loss was detected in both white matter and cortical gray matter of patients with NDPH.

Investigating apparent differences between standard DKI and axisymmetric DKI and its consequences for biophysical parameter estimates

PURPOSE

The purpose of the study is to identify differences between axisymmetric diffusion kurtosis imaging (DKI) and standard DKI, their consequences for biophysical parameter estimates, and the protocol choice influence on parameter estimation.

METHODS

Noise-free and noisy, synthetic diffusion MRI human brain data is simulated using standard DKI for a standard and the fast "199" acquisition protocol. First the noise-free "baseline" difference between both DKI models is estimated and the influence of fiber complexity is investigated. Noisy data is used to establish the signal-to-noise ratio at which the baseline difference exceeds noise variability. The influence of protocol choices and denoising is investigated. The five axisymmetric DKI tensor metrics (AxTM), the parallel and perpendicular diffusivity and kurtosis and mean of the kurtosis tensor are used to compare both DKI models. Additionally, the baseline difference is also estimated for the five parameters of the WMTI-Watson model.

RESULTS

The parallel and perpendicular kurtosis and all of the WMTI-Watson parameters had large baseline differences. Using a Westin or FA mask reduced the number of voxels with large baseline difference, that is, by selecting voxels with less complex fibers. For the noisy data, precision was worsened by the fast "199" protocol but adaptive denoising can help counteract these effects.

CONCLUSION

For the diffusivities and mean of the kurtosis tensor, axisymmetric DKI with a standard protocol delivers similar results as standard DKI. Fiber complexity is one main driver of the baseline differences. Using the "199" protocol worsens precision in noisy data but adaptive denoising mitigates these effects.

Mechanobiological insight into brain diseases based on mechanosensitive channels: Common mechanisms and clinical potential

BACKGROUND

As physical signals, mechanical cues regulate the neural cells in the brain. The mechanosensitive channels (MSCs) perceive the mechanical cues and transduce them by permeating specific ions or molecules across the plasma membrane, and finally trigger a series of intracellular bioelectrical and biochemical signals. Emerging evidence supports that wide-distributed, high-expressed MSCs like Piezo1 play important roles in several neurophysiological processes and neurological disorders.

AIMS

To systematically conclude the functions of MSCs in the brain and provide a novel mechanobiological perspective for brain diseases.

METHOD

We summarized the mechanical cues and MSCs detected in the brain and the research progress on the functional roles of MSCs in physiological conditions. We then concluded the pathological activation and downstream pathways triggered by MSCs in two categories of brain diseases, neurodegenerative diseases and place-occupying damages. Finally, we outlined the methods for manipulating MSCs and discussed their medical potential with some crucial outstanding issues.

RESULTS

The MSCs present underlying common mechanisms in different brain diseases by acting as the "transportation hubs" to transduce the distinct signal patterns: the upstream mechanical cues and the downstream intracellular pathways. Manipulating the MSCs is feasible to alter the complicated downstream processes, providing them promising targets for clinical treatment.

CONCLUSIONS

Recent research on MSCs provides a novel insight into brain diseases. The common mechanisms mediated by MSCs inspire a wide range of therapeutic potentials targeted on MSCs in different brain diseases.

Brain Deformation Estimation With Transfer Learning for Head Impact Datasets Across Impact Types

OBJECTIVE

The machine-learning head model (MLHM) to accelerate the calculation of brain strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model accuracy was found to decrease sharply when the training/test datasets were from different head impacts types (i.e., car crash, college football), which limits the applicability of MLHMs to different types of head impacts and sports. Particularly, small sizes of target dataset for specific impact types with tens of impacts may not be enough to train an accurate impact-type-specific MLHM.

METHODS

To overcome this, we propose data fusion and transfer learning to develop a series of MLHMs to predict the maximum principal strain (MPS) and maximum principal strain rate (MPSR).

RESULTS

The strategies were tested on American football (338), mixed martial arts (457), reconstructed car crash (48) and reconstructed American football (36) and we found that the MLHMs developed with transfer learning are significantly more accurate in estimating MPS and MPSR than other models, with a mean absolute error (MAE) smaller than 0.03 in predicting MPS and smaller than [Formula: see text] in predicting MPSR on all target impact datasets. High performance in concussion detection was observed based on the MPS and MPSR estimated by the transfer-learning-based models.

CONCLUSION

The MLHMs can be applied to various head impact types for rapidly and accurately calculating brain strain and strain rate.

SIGNIFICANCE

This study enables developing MLHMs for the head impact type with limited availability of data, and will accelerate the applications of MLHMs.

Insights and improvements in correspondence between axonal volume fraction measured with diffusion-weighted MRI and electron microscopy

Biophysical diffusion-weighted imaging (DWI) models are increasingly used in neuroscience to estimate the axonal water fraction (f AW ), which in turn is key for noninvasive estimation of the axonal volume fraction (f A ). These models require thorough validation by comparison with a reference method, for example, electron microscopy (EM). While EM studies often neglect the unmyelinated axons and solely report the fraction of myelinated axons, in DWI both myelinated and unmyelinated axons contribute to the DWI signal. However, DWI models often include simplifications, for example, the neglect of differences in the compartmental relaxation times or fixed diffusivities, which in turn might affect the estimation off AW . We investigate whether linear calibration parameters (scaling and offset) can improve the comparability between EM- and DWI-based metrics off A . To this end, we (a) used six DWI models based on the so-called standard model of white matter (WM), including two models with fixed compartmental diffusivities (e.g., neurite orientation dispersion and density imaging, NODDI) and four models that fitted the compartmental diffusivities (e.g., white matter tract integrity, WMTI), and (b) used a multimodal data set including ex vivo diffusion DWI and EM data in mice with a broad dynamic range of fibre volume metrics. We demonstrated that the offset is associated with the volume fraction of unmyelinated axons and the scaling factor is associated with different compartmentalT 2 and can substantially enhance the comparability between EM- and DWI-based metrics off A . We found that DWI models that fitted compartmental diffusivities provided the most accurate estimates of the EM-basedf A . Finally, we introduced a more efficient hybrid calibration approach, where only the offset is estimated but the scaling is fixed to a theoretically predicted value. Using this approach, a similar one-to-one correspondence to EM was achieved for WMTI. The method presented can pave the way for use of validated DWI-based models in clinical research and neuroscience.

Custom-engineered hydrogels for delivery of human iPSC-derived neurons into the injured cervical spinal cord

Cervical damage is the most prevalent type of spinal cord injury clinically, although few preclinical research studies focus on this anatomical region of injury. Here we present a combinatorial therapy composed of a custom-engineered, injectable hydrogel and human induced pluripotent stem cell (iPSC)-derived deep cortical neurons. The biomimetic hydrogel has a modular design that includes a protein-engineered component to allow customization of the cell-adhesive peptide sequence and a synthetic polymer component to allow customization of the gel mechanical properties. In vitro studies with encapsulated iPSC-neurons were used to select a bespoke hydrogel formulation that maintains cell viability and promotes neurite extension. Following injection into the injured cervical spinal cord in a rat contusion model, the hydrogel biodegraded over six weeks without causing any adverse reaction. Compared to cell delivery using saline, the hydrogel significantly improved the reproducibility of cell transplantation and integration into the host tissue. Across three metrics of animal behavior, this combinatorial therapy significantly improved sensorimotor function by six weeks post transplantation. Taken together, these findings demonstrate that design of a combinatorial therapy that includes a gel customized for a specific fate-restricted cell type can induce regeneration in the injured cervical spinal cord.

p17/C18-ceramide-mediated mitophagy is an endogenous neuroprotective response in preclinical and clinical brain injury

Repeat concussions (or repetitive mild traumatic brain injury [rmTBI]) are complex pathological processes consisting of a primary insult and long-term secondary complications and are also a prerequisite for chronic traumatic encephalopathy (CTE). Recent evidence implies a significant role of autophagy-mediated dysfunctional mitochondrial clearance, mitophagy, in the cascade of secondary deleterious events resulting from TBI. C18-ceramide, a bioactive sphingolipid produced in response to cell stress and damage, and its synthesizing enzyme (CerS1) are precursors to selective stress-mediated mitophagy. A transporter, p17, mediates the trafficking of CerS1, induces C18-ceramide synthesis in the mitochondrial membrane, and acts as an elimination signal in cell survival. Whether p17-mediated mitophagy occurs in the brain and plays a causal role in mitochondrial quality control in secondary disease development after rmTBI are unknown. Using a novel repetitive less-than-mild TBI (rlmTBI) injury paradigm, ablation of mitochondrial p17/C18-ceramide trafficking in p17 knockout (KO) mice results in a loss of C18-ceramide-induced mitophagy, which contributes to susceptibility and recovery from long-term secondary complications associated with rlmTBI. Using a ceramide analog with lipid-selenium conjugate drug, LCL768 restored mitophagy and reduced long-term secondary complications, improving cognitive deficits in rlmTBI-induced p17KO mice. We obtained a significant reduction of p17 expression and a considerable decrease of CerS1 and C18-ceramide levels in cortical mitochondria of CTE human brains compared with age-matched control brains. These data demonstrated that p17/C18-ceramide trafficking is an endogenous neuroprotective mitochondrial stress response following rlmTBI, thus suggesting a novel prospective strategy to interrupt the CTE consequences of concussive TBI.

Adverse Outcome Following Mild Traumatic Brain Injury Is Associated with Microstructure Alterations at the Gray and White Matter Boundary

The gray matter/white matter (GM/WM) boundary of the brain is vulnerable to shear strain associated with mild traumatic brain injury (mTBI). It is, however, unknown whether GM/WM microstructure is associated with long-term outcomes following mTBI. The diffusion and structural MRI data of 278 participants between 18 and 65 years of age with and without military background from the Department of Defense INTRuST study were analyzed. Fractional anisotropy (FA) was extracted at the GM/WM boundary across the brain and for each lobe. Additionally, two conventional analytic approaches were used: whole-brain deep WM FA (TBSS) and whole-brain cortical thickness (FreeSurfer). ANCOVAs were applied to assess differences between the mTBI cohort (n = 147) and the comparison cohort (n = 131). Associations between imaging features and post-concussive symptom severity, and functional and cognitive impairment were investigated using partial correlations while controlling for mental health comorbidities that are particularly common among military cohorts and were present in both the mTBI and comparison group. Findings revealed significantly lower whole-brain and lobe-specific GM/WM boundary FA (p < 0.011), and deep WM FA (p = 0.001) in the mTBI cohort. Whole-brain and lobe-specific GM/WM boundary FA was significantly negatively correlated with post-concussive symptoms (p < 0.039), functional (p < 0.016), and cognitive impairment (p < 0.049). Deep WM FA was associated with functional impairment (p = 0.002). Finally, no significant difference was observed in cortical thickness, nor between cortical thickness and outcome (p > 0.05). Findings from this study suggest that microstructural alterations at the GM/WM boundary may be sensitive markers of adverse long-term outcomes following mTBI.

An Instrumented Mouthguard for Real-Time Measurement of Head Kinematics under a Large Range of Sport Specific Accelerations

BACKGROUND

Head impacts in sports can produce brain injuries. The accurate quantification of head kinematics through instrumented mouthguards (iMG) can help identify underlying brain motion during injurious impacts. The aim of the current study is to assess the validity of an iMG across a large range of linear and rotational accelerations to allow for on-field head impact monitoring.

METHODS

Drop tests of an instrumented helmeted anthropometric testing device (ATD) were performed across a range of impact magnitudes and locations, with iMG measures collected concurrently. ATD and iMG kinematics were also fed forward to high-fidelity brain models to predict maximal principal strain.

RESULTS

The impacts produced a wide range of head kinematics (16-171 g, 1330-10,164 rad/s2 and 11.3-41.5 rad/s) and durations (6-18 ms), representing impacts in rugby and boxing. Comparison of the peak values across ATD and iMG indicated high levels of agreement, with a total concordance correlation coefficient of 0.97 for peak impact kinematics and 0.97 for predicted brain strain. We also found good agreement between iMG and ATD measured time-series kinematic data, with the highest normalized root mean squared error for rotational velocity (5.47 ± 2.61%) and the lowest for rotational acceleration (1.24 ± 0.86%). Our results confirm that the iMG can reliably measure laboratory-based head kinematics under a large range of accelerations and is suitable for future on-field validity assessments.

The biomechanical signature of loss of consciousness: computational modelling of elite athlete head injuries

Sports related head injuries can cause transient neurological events including loss of consciousness and dystonic posturing. However, it is unknown why head impacts that appear similar produce distinct neurological effects. The biomechanical effect of impacts can be estimated using computational models of strain within the brain. Here, we investigate the strain and strain rates produced by professional American football impacts that led to loss of consciousness, posturing or no neurological signs. We reviewed 1280 National Football League American football games and selected cases where the team's medical personnel made a diagnosis of concussion. Videos were then analysed for signs of neurological events. We identified 20 head impacts that showed clear video signs of loss of consciousness and 21 showing clear abnormal posturing. Forty-one control impacts were selected where there was no observable evidence of neurological signs, resulting in 82 videos of impacts for analysis. Video analysis was used to guide physical reconstructions of these impacts, allowing us to estimate the impact kinematics. These were then used as input to a detailed 3D high-fidelity finite element model of brain injury biomechanics to estimate strain and strain rate within the brain. We tested the hypotheses that impacts producing loss of consciousness would be associated with the highest biomechanical forces, that loss of consciousness would be associated with high forces in brainstem nuclei involved in arousal and that dystonic posturing would be associated with high forces in motor regions. Impacts leading to loss of consciousness compared to controls produced higher head acceleration (linear acceleration; 81.5 g ± 39.8 versus 47.9 ± 21.4; P = 0.004, rotational acceleration; 5.9 krad/s2 ± 2.4 versus 3.5 ± 1.6; P < 0.001) and in voxel-wise analysis produced larger brain deformation in many brain regions, including parts of the brainstem and cerebellum. Dystonic posturing was also associated with higher deformation compared to controls, with brain deformation observed in cortical regions that included the motor cortex. Loss of consciousness was specifically associated with higher strain rates in brainstem regions implicated in maintenance of consciousness, including following correction for the overall severity of impact. These included brainstem nuclei including the locus coeruleus, dorsal raphé and parabrachial complex. The results show that in head impacts producing loss of consciousness, brain deformation is disproportionately seen in brainstem regions containing nuclei involved in arousal, suggesting that head impacts produce loss of consciousness through a biomechanical effect on key brainstem nuclei involved in the maintenance of consciousness.

Distinct patterns of neurodegeneration after TBI and in Alzheimer's disease

INTRODUCTION

Traumatic brain injury (TBI) is a dementia risk factor, with Alzheimer's disease (AD) more common following injury. Patterns of neurodegeneration produced by TBI can be compared to AD and aging using volumetric MRI.

METHODS

A total of 55 patients after moderate to severe TBI (median age 40), 45 with AD (median age 69), and 61 healthy volunteers underwent magnetic resonance imaging over 2 years. Atrophy patterns were compared.

RESULTS

AD patients had markedly lower baseline volumes. TBI was associated with increased white matter (WM) atrophy, particularly involving corticospinal tracts and callosum, whereas AD rates were increased across white and gray matter (GM). Subcortical WM loss was shared in AD/TBI, but deep WM atrophy was TBI-specific and cortical atrophy AD-specific. Post-TBI atrophy patterns were distinct from aging, which resembled AD.

DISCUSSION

Post-traumatic neurodegeneration 1.9-4.0 years (median) following moderate-severe TBI is distinct from aging/AD, predominantly involving central WM. This likely reflects distributions of axonal injury, a neurodegeneration trigger.

HIGHLIGHTS

We compared patterns of brain atrophy longitudinally after moderate to severe TBI in late-onset AD and healthy aging. Patients after TBI had abnormal brain atrophy involving the corpus callosum and other WM tracts, including corticospinal tracts, in a pattern that was specific and distinct from AD and aging. This pattern is reminiscent of axonal injury following TBI, and atrophy rates were predicted by the extent of axonal injury on diffusion tensor imaging, supporting a relationship between early axonal damage and chronic neurodegeneration.

Mechanisms of mechanical load transfer through brain tissue

Brain injuries are often characterized by diffusely distributed axonal and vascular damage invisible to medical imaging techniques. The spatial distribution of mechanical stresses and strains plays an important role, but is not sufficient to explain the diffuse distribution of brain lesions. It remains unclear how forces are transferred from the organ to the cell scale and why some cells are damaged while neighboring cells remain unaffected. To address this knowledge gap, we subjected histologically stained fresh human and porcine brain tissue specimens to compressive loading and simultaneously tracked cell and blood vessel displacements. Our experiments reveal different mechanisms of load transfer from the organ or tissue scale to single cells, axons, and blood vessels. Our results show that cell displacement fields are inhomogeneous at the interface between gray and white matter and in the vicinity of blood vessels-locally inducing significant deformations of individual cells. These insights have important implications to better understand injury mechanisms and highlight the importance of blood vessels for the local deformation of the brain's cellular structure during loading.

Acute Blood Levels of Neurofilament Light Indicate One-Year White Matter Pathology and Functional Impairment in Repetitive Mild Traumatic Brain Injured Mice

Mild traumatic brain injury (mTBI) mostly causes transient symptoms, but repeated (r)mTBI can lead to neurodegenerative processes. Diagnostic tools to evaluate the presence of ongoing occult neuropathology are lacking. In a mouse model of rmTBI, we investigated MRI and plasma biomarkers of brain damage before chronic functional impairment arose. Anesthetized adult male and female C57BL/6J mice were subjected to rmTBI or a sham procedure. Sensorimotor deficits were evaluated up to 12 months post-injury in SNAP and Neuroscore tests. Cognitive function was assessed in the novel object recognition test at six and 12 months. Diffusion tensor imaging (DTI) and structural magnetic resonance imaging (MRI) were performed at six and 12 months to examine white matter and structural damage. Plasma levels of neurofilament light (NfL) were assessed longitudinally up to 12 months. Brain histopathology was performed at 12 months. Independent groups of mice were used to examine the effects of 2-, 7- and 14-days inter-injury intervals on acute plasma NfL levels and on hyperactivity. Twelve months after an acute transient impairment, sensorimotor functions declined again in rmTBI mice (p < 0.001 vs sham), but not earlier. Similarly, rmTBI mice showed memory impairment at 12 (p < 0.01 vs sham) but not at 6 months. White matter damage examined by DTI was evident in rmTBI mice at both six and 12 months (p < 0.001 vs sham). This was associated with callosal atrophy (p < 0.001 vs sham) evaluated by structural MRI. Plasma NfL at one week was elevated in rmTBI (p < 0.001 vs sham), and its level correlated with callosal atrophy at 12 months (Pearson r = 0.72, p < 0.01). Histopathology showed thinning of the corpus callosum and marked astrogliosis in rmTBI mice. The NfL levels were higher in mice subjected to short (2 days) compared with longer (7 and 14 days) inter-injury intervals (p < 0.05), and this correlated with hyperactivity in mice (Pearson r = 0.50; p < 0.05). These findings show that rmTBI causes white matter pathology detectable by MRI before chronic functional impairment. Early quantification of plasma NfL correlates with the degree of white matter atrophy one year after rmTBI and can serve to monitor the brain's susceptibility to a second mTBI, supporting its potential clinical application to guide the return to practice in sport-related TBI.

In-Depth Bicycle Collision Reconstruction: From a Crash Helmet to Brain Injury Evaluation

Traumatic brain injury (TBI) is a prevalent injury among cyclists experiencing head collisions. In legal cases, reliable brain injury evaluation can be difficult and controversial as mild injuries cannot be diagnosed with conventional brain imaging methods. In such cases, accident reconstruction may be used to predict the risk of TBI. However, lack of collision details can render accident reconstruction nearly impossible. Here, we introduce a reconstruction method to evaluate the brain injury in a bicycle–vehicle collision using the crash helmet alone. Following a thorough inspection of the cyclist’s helmet, we identified a severe impact, a moderate impact and several scrapes, which helped us to determine the impact conditions. We used our helmet test rig and intact helmets identical to the cyclist’s helmet to replicate the damage seen on the cyclist’s helmet involved in the real-world collision. We performed both linear and oblique impacts, measured the translational and rotational kinematics of the head and predicted the strain and the strain rate across the brain using a computational head model. Our results proved the hypothesis that the cyclist sustained a severe impact followed by a moderate impact on the road surface. The estimated head accelerations and velocity (167 g, 40.7 rad/s and 13.2 krad/s2) and the brain strain and strain rate (0.541 and 415/s) confirmed that the severe impact was large enough to produce mild to moderate TBI. The method introduced in this study can guide future accident reconstructions, allowing for the evaluation of TBI using the crash helmet only.

Axisymmetric diffusion kurtosis imaging with Rician bias correction: A simulation study

PURPOSE

To compare the estimation accuracy of axisymmetric diffusion kurtosis imaging (DKI) and standard DKI in combination with Rician bias correction (RBC).

METHODS

Axisymmetric DKI is more robust against noise-induced variation in the measured signal than standard DKI because of its reduced parameter space. However, its susceptibility to Rician noise bias at low signal-to-noise ratios (SNR) is unknown. Here, we investigate two main questions: first, does RBC improve estimation accuracy of axisymmetric DKI?; second, is estimation accuracy of axisymmetric DKI increased compared to standard DKI? Estimation accuracy was investigated on the five axisymmetric DKI tensor metrics (AxTM): the parallel and perpendicular diffusivity and kurtosis and mean of the kurtosis tensor, using a noise simulation study based on synthetic data of tissues with varying fiber alignment and in-vivo data focusing on white matter.

RESULTS

RBC mainly increased accuracy for the parallel AxTM in tissues with highly to moderately aligned fibers. For the perpendicular AxTM, axisymmetric DKI without RBC performed slightly better than with RBC. However, the combination of axisymmetric DKI with RBC was the overall best performing algorithm across all five AxTM in white matter and axisymmetric DKI itself substantially improved accuracy in axisymmetric tissues with low fiber alignment.

CONCLUSION

Combining axisymmetric DKI with RBC facilitates accurate DKI parameter estimation at unprecedented low SNRs ( ≈ 15 $$ \approx 15 $$ ) in white matter, possibly making it a valuable tool for neuroscience and clinical research studies where scan time is a limited resource. The tools used here are available in the open-source ACID toolbox for SPM.

A multiscale tissue assessment in a rat model of mild traumatic brain injury

Diffusion tensor imaging (DTI) has demonstrated the potential to assess the pathophysiology of mild traumatic brain injury (mTBI) but correlations of DTI findings and pathological changes in mTBI are unclear. We evaluated the potential of ex vivo DTI to detect tissue damage in a mild mTBI rat model by exploiting multiscale imaging methods, histology and scanning micro-X-ray diffraction (SμXRD) 35 days after sham-operation (n = 2) or mTBI (n = 3). There were changes in DTI parameters rostral to the injury site. When examined by histology and SμXRD, there was evidence of axonal damage, reduced myelin density, gliosis, and ultrastructural alterations in myelin that were ongoing at the experimental time point of 35 days postinjury. We assessed the relationship between the 3 imaging modalities by multiple linear regression analysis. In this analysis, DTI and histological parameters were moderately related, whereas SμXRD parameters correlated weakly with DTI and histology. These findings suggest that while DTI appears to distinguish tissue changes at the microstructural level related to the loss of myelinated axons and gliosis, its ability to visualize alterations in myelin ultrastructure is limited. The use of several imaging techniques represents a novel approach to reveal tissue damage and provides new insights into mTBI detection.

Morphological changes in glial cells arrangement under mechanical loading: A quantitative study

The mechanical properties and microstructure of brain tissue, as its two main physical parameters, could be affected by mechanical stimuli. In previous studies, microstructural alterations due to mechanical loading have received less attention than the mechanical properties of the tissue. Therefore, the current study aimed to investigate the effect of ex-vivo mechanical forces on the micro-architecture of brain tissue including axons and glial cells. A three-step loading protocol (i.e., loading-recovery-loading) including eight strain levels from 5% to 40% was applied to bovine brain samples with axons aligned in one preferred direction (each sample experienced only one level of strain). After either the first or secondary loading step, the samples were fixed, cut in planes parallel and perpendicular to the loading direction, and stained for histology. The histological images were analyzed to measure the end-to-end length of axons and glial cell-cell distances. The results showed that after both loading steps, as the strain increased, the changes in the cell nuclei arrangement in the direction parallel to axons were more significant compared to the other two perpendicular directions. Based on this evidence, we hypothesized that the spatial pattern of glial cells is highly affected by the orientation of axonal fibers. Moreover, the results revealed that in both loading steps, the maximum cell-cell distance occurred at 15% strain, and this distance decreased for higher strains. Since 15% strain is close to the previously reported brain injury threshold, this evidence could suggest that at higher strains, the axons start to rupture, causing a reduction in the displacement of glial cells. Accordingly, it was concluded that more attention to glial cells' architecture during mechanical loading may lead to introduce a new biomarker for brain injury.

Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports

Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.

Traumatic Brain Injury Leads to Alterations in Contusional Cortical miRNAs Involved in Dementia

There is compelling evidence that head injury is a significant environmental risk factor for Alzheimer's disease (AD) and that a history of traumatic brain injury (TBI) accelerates the onset of AD. Amyloid-β plaques and tau aggregates have been observed in the post-mortem brains of TBI patients; however, the mechanisms leading to AD neuropathology in TBI are still unknown. In this study, we hypothesized that focal TBI induces changes in miRNA expression in and around affected areas, resulting in the altered expression of genes involved in neurodegeneration and AD pathology. For this purpose, we performed a miRNA array in extracts from rats subjected to experimental TBI, using the controlled cortical impact (CCI) model. In and around the contusion, we observed alterations of miRNAs associated with dementia/AD, compared to the contralateral side. Specifically, the expression of miR-9 was significantly upregulated, while miR-29b, miR-34a, miR-106b, miR-181a and miR-107 were downregulated. Via qPCR, we confirmed these results in an additional group of injured rats when compared to naïve animals. Interestingly, the changes in those miRNAs were concomitant with alterations in the gene expression of mRNAs involved in amyloid generation and tau pathology, such as β-APP cleaving enzyme (BACE1) and Glycogen synthase-3-β (GSK3β). In addition increased levels of neuroinflammatory markers (TNF-α), glial activation, neuronal loss, and tau phosphorylation were observed in pericontusional areas. Therefore, our results suggest that the secondary injury cascade in TBI affects miRNAs regulating the expression of genes involved in AD dementia.

Finding the Spatial Co-Variation of Brain Deformation With Principal Component Analysis

OBJECTIVE

Strain and strain rate are effective traumatic brain injury metrics. In finite element (FE) head model, thousands of elements were used to represent the spatial distribution of these metrics. Owing that these metrics are resulted from brain inertia, their spatial distribution can be represented in more concise pattern. Since head kinematic features and brain deformation vary largely across head impact types (Zhan et al., 2021), we applied principal component analysis (PCA) to find the spatial co-variation of injury metrics (maximum principal strain (MPS), MPS rate (MPSR) and MPS × MPSR) in four impact types: simulation, football, mixed martial arts and car crashes, and used the PCA to find patterns in these metrics and improve the machine learning head model (MLHM).

METHODS

We applied PCA to decompose the injury metrics for all impacts in each impact type, and investigate the spatial co-variation using the first principal component (PC1). Furthermore, we developed a MLHM to predict PC1 and then inverse-transform to predict for all brain elements. The accuracy, the model complexity and the size of training dataset of PCA-MLHM are compared with previous MLHM (Zhan et al., 2021).

RESULTS

PC1 explained variance on the datasets. Based on PC1 coefficients, the corpus callosum and midbrain exhibit high variance on all datasets. Finally, the PCA-MLHM reduced model parameters by 74% with a similar MPS estimation accuracy.

CONCLUSION

The brain injury metric in a dataset can be decomposed into mean components and PC1 with high explained variance.

SIGNIFICANCE

The spatial co-variation analysis enables better interpretation of the patterns in brain injury metrics. It also improves the efficiency of MLHM.

Oblique impact responses of Hybrid III and a new headform with more biofidelic coefficient of friction and moments of inertia

New oblique impact methods for evaluating head injury mitigation effects of helmets are emerging, which mandate measuring both translational and rotational kinematics of the headform. These methods need headforms with biofidelic mass, moments of inertia (MoIs), and coefficient of friction (CoF). To fulfill this need, working group 11 of the European standardization head protection committee (CEN/TC158) has been working on the development of a new headform with realistic MoIs and CoF, based on recent biomechanics research on the human head. In this study, we used a version of this headform (Cellbond) to test a motorcycle helmet under the oblique impact at 8 m/s at five different locations. We also used the Hybrid III headform, which is commonly used in the helmet oblique impact. We tested whether there is a difference between the predictions of the headforms in terms of injury metrics based on head kinematics, including peak translational and rotational acceleration, peak rotational velocity, and BrIC (brain injury criterion). We also used the Imperial College finite element model of the human head to predict the strain and strain rate across the brain and tested whether there is a difference between the headforms in terms of the predicted strain and strain rate. We found that the Cellbond headform produced similar or higher peak translational accelerations depending on the impact location (−3.2% in the front-side impact to 24.3% in the rear impact). The Cellbond headform, however, produced significantly lower peak rotational acceleration (−41.8% in a rear impact to −62.7% in a side impact), peak rotational velocity (−29.5% in a side impact to −47.6% in a rear impact), and BrIC (−29% in a rear-side impact to −45.3% in a rear impact). The 90th percentile values of the maximum brain strain and strain rate were also significantly lower using this headform. Our results suggest that MoIs and CoF have significant effects on headform rotational kinematics, and consequently brain deformation, during the helmeted oblique impact. Future helmet standards and rating methods should use headforms with realistic MoIs and CoF (e.g., the Cellbond headform) to ensure more accurate representation of the head in laboratory impact tests.

A biomechanical-based approach to scale blast-induced molecular changes in the brain

Animal studies provide valuable insights on how the interaction of blast waves with the head may injure the brain. However, there is no acceptable methodology to scale the findings from animals to humans. Here, we propose an experimental/computational approach to project observed blast-induced molecular changes in the rat brain to the human brain. Using a shock tube, we exposed rats to a range of blast overpressures (BOPs) and used a high-fidelity computational model of a rat head to correlate predicted biomechanical responses with measured changes in glial fibrillary acidic protein (GFAP) in rat brain tissues. Our analyses revealed correlates between model-predicted strain rate and measured GFAP changes in three brain regions. Using these correlates and a high-fidelity computational model of a human head, we determined the equivalent BOPs in rats and in humans that induced similar strain rates across the two species. We used the equivalent BOPs to project the measured GFAP changes in the rat brain to the human. Our results suggest that, relative to the rat, the human requires an exposure to a blast wave of a higher magnitude to elicit similar brain-tissue responses. Our proposed methodology could assist in the development of safety guidelines for blast exposure.

Brain architecture-based vulnerability to traumatic injury

The white matter tracts forming the intricate wiring of the brain are subject-specific; this heterogeneity can complicate studies of brain function and disease. Here we collapse tractography data from the Human Connectome Project (HCP) into structural connectivity (SC) matrices and identify groups of similarly wired brains from both sexes. To characterize the significance of these architectural groupings, we examined how similarly wired brains led to distinct groupings of neural activity dynamics estimated with Kuramoto oscillator models (KMs). We then lesioned our networks to simulate traumatic brain injury (TBI) and finally we tested whether these distinct architecture groups’ dynamics exhibited differing responses to simulated TBI. At each of these levels we found that brain structure, simulated dynamics, and injury susceptibility were all related to brain grouping. We found four primary brain architecture groupings (two male and two female), with similar architectures appearing across both sexes. Among these groupings of brain structure, two architecture types were significantly more vulnerable than the remaining two architecture types to lesions. These groups suggest that mesoscale brain architecture types exist, and these architectural differences may contribute to differential risks to TBI and clinical outcomes across the population.

The Protective Performance of Modern Motorcycle Helmets Under Oblique Impacts

Motorcyclists are at high risk of head injuries, including skull fractures, focal brain injuries, intracranial bleeding and diffuse brain injuries. New helmet technologies have been developed to mitigate head injuries in motorcycle collisions, but there is limited information on their performance under commonly occurring oblique impacts. We used an oblique impact method to assess the performance of seven modern motorcycle helmets at five impact locations. Four helmets were fitted with rotational management technologies: a low friction layer (MIPS), three-layer liner system (Flex) and dampers-connected liner system (ODS). Helmets were dropped onto a 45° anvil at 8 m/s at five locations. We determined peak translational and rotational accelerations (PTA and PRA), peak rotational velocity (PRV) and brain injury criteria (BrIC). In addition, we used a human head finite element model to predict strain distribution across the brain and in corpus callosum and sulci. We found that the impact location affected the injury metrics and brain strain, but this effect was not consistent. The rear impact produced lowest PTAs but highest PRAs. This impact produced highest strain in corpus callosum. The front impact produced the highest PRV and BrIC. The side impact produced the lowest PRV, BrIC and strain across the brain, sulci and corpus callosum. Among helmet technologies, MIPS reduced all injury metrics and brain strain compared with conventional helmets. Flex however was effective in reducing PRA only and ODS was not effective in reducing any injury metrics in comparison with conventional helmets. This study shows the importance of using different impact locations and injury metrics when assessing head protection effects of helmets. It also provides new data on the performance of modern motorcycle helmets. These results can help with improving helmet design and standard and rating test methods.

Intravenous infusion of the exosomes derived from human umbilical cord mesenchymal stem cells enhance neurological recovery after traumatic brain injury via suppressing the NF-κB pathway

Traumatic brain injury (TBI) is a predominant cause of death and permanent disability globally. In recent years, much emphasis has been laid on treatments for TBI. Increasing evidence suggests that human umbilical cord mesenchymal stem cells (HUCMSCs) can improve neurological repair after TBI. However, the clinical use of HUCMSCs transplantation in TBI has been limited by immunological rejection, ethical issues, and the risk of tumorigenicity. Many studies have shown that HUCMSCs-derived exosomes may be an alternative approach for HUCMSCs transplantation. We hypothesized that exosomes derived from HUCMSCs could inhibit apoptosis after TBI, reduce neuroinflammation, and promote neurogenesis. A rat model of TBI was established to investigate the efficiency of neurological recovery with exosome therapy. We found that exosomes derived from HUCMSCs significantly ameliorated sensorimotor function and spatial learning in rats after TBI. Moreover, HUCMSCs-derived exosomes significantly reduced proinflammatory cytokine expression by suppressing the NF-κB signaling pathway. Furthermore, we found that HUCMSC-derived exosomes inhibited neuronal apoptosis, reduced inflammation, and promoted neuron regeneration in the injured cortex of rats after TBI. These results indicate that HUCMSCs-derived exosomes may be a promising therapeutic strategy for TBI.

The relationship between road traffic collision dynamics and traumatic brain injury pathology

Road traffic collisions are a major cause of traumatic brain injury. However, the relationship between road traffic collision dynamics and traumatic brain injury risk for different road users is unknown. We investigated 2065 collisions from Great Britain's Road Accident In-depth Studies collision database involving 5374 subjects (2013-20). Five hundred and ninety-five subjects sustained a traumatic brain injury (20.2% of 2940 casualties), including 315 moderate-severe and 133 mild-probable injuries. Key pathologies included skull fracture (179, 31.9%), subarachnoid haemorrhage (171, 30.5%), focal brain injury (168, 29.9%) and subdural haematoma (96, 17.1%). These results were extended nationally using >1 000 000 police-reported collision casualties. Extrapolating from the in-depth data we estimate that there are ∼20 000 traumatic brain injury casualties (∼5000 moderate-severe) annually on Great Britain's roads, accounting for severity differences. Detailed collision investigation allows vehicle collision dynamics to be understood and the change in velocity (known as delta-V) to be estimated for a subset of in-depth collision data. Higher delta-V increased the risk of moderate-severe brain injury for all road users. The four key pathologies were not observed below 8 km/h delta-V for pedestrians/cyclists and 19 km/h delta-V for car occupants (higher delta-V threshold for focal injury in both groups). Traumatic brain injury risk depended on road user type, delta-V and impact direction. Accounting for delta-V, pedestrians/cyclists had a 6-times higher likelihood of moderate-severe brain injury than car occupants. Wearing a cycle helmet during a collision was protective against overall and mild-to-moderate-to-severe brain injury, particularly skull fracture and subdural haematoma. Cycle helmet protection was not due to travel or impact speed differences between helmeted and non-helmeted cyclist groups. We additionally examined the influence of the delta-V direction. Car occupants exposed to a higher lateral delta-V component had a greater prevalence of moderate-severe brain injury, particularly subarachnoid haemorrhage. Multivariate logistic regression models created using total delta-V value and whether lateral delta-V was dominant had the best prediction capabilities (area under the receiver operator curve as high as 0.95). Collision notification systems are routinely fitted in new cars. These record delta-V and automatically alert emergency services to a collision in real-time. These risk relationships could, therefore, inform how routinely fitted automatic collision notification systems alert the emergency services to collisions with a high brain injury risk. Early notification of high-risk scenarios would enable quicker activation of the highest level of emergency service response. Identifying those that require neurosurgical care and ensuring they are transported directly to a centre with neuro-specialist provisions could improve patient outcomes.

Correlation of in-vivo imaging with histopathology: A review

Despite tremendous advancements in in vivo imaging modalities, there remains substantial uncertainty with respect to tumor delineation on in these images. Histopathology remains the gold standard for determining the extent of malignancy, with in vivo imaging to histopathologic correlation enabling spatial comparisons. In this review, the steps necessary for successful imaging to histopathologic correlation are described, including in vivo imaging, resection, fixation, specimen sectioning (sectioning technique, securing technique, orientation matching, slice matching), microtome sectioning and staining, correlation (including image registration) and performance evaluation. The techniques used for each of these steps are also discussed. Hundreds of publications from the past 20 years were surveyed, and 62 selected for detailed analysis. For these 62 publications, each stage of the correlative pathology process (and the sub-steps of specimen sectioning) are listed. A statistical analysis was conducted based on 19 studies that reported target registration error as their performance metric. While some methods promise greater accuracy, they may be expensive. Due to the complexity of the processes involved, correlative pathology studies generally include a small number of subjects, which hinders advanced developments in this field.

Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation

Brain tissue deformation resulting from head impacts is primarily caused by rotation and can lead to traumatic brain injury. To quantify brain injury risk based on measurements of kinematics on the head, finite element (FE) models and various brain injury criteria based on different factors of these kinematics have been developed, but the contribution of different kinematic factors has not been comprehensively analyzed across different types of head impacts in a data-driven manner. To better design brain injury criteria, the predictive power of rotational kinematics factors, which are different in (1) the derivative order (angular velocity, angular acceleration, angular jerk), (2) the direction and (3) the power (e.g., square-rooted, squared, cubic) of the angular velocity, were analyzed based on different datasets including laboratory impacts, American football, mixed martial arts (MMA), NHTSA automobile crashworthiness tests and NASCAR crash events. Ordinary least squares regressions were built from kinematics factors to the 95% maximum principal strain (MPS95), and we compared zero-order correlation coefficients, structure coefficients, commonality analysis, and dominance analysis. The angular acceleration, the magnitude and the first power factors showed the highest predictive power for the majority of impacts including laboratory impacts, American football impacts, with few exceptions (angular velocity for MMA and NASCAR impacts). The predictive power of rotational kinematics about three directions (x: posterior-to-anterior, y: left-to-right, z: superior-to-inferior) of kinematics varied with different sports and types of head impacts.

Axonal marker neurofilament light predicts long-term outcomes and progressive neurodegeneration after traumatic brain injury

[Figure: see text].

Dependence of visual and cognitive outcomes on animal holder configuration in a rodent model of blast overpressure exposure

Blast-induced traumatic brain injury is the signature injury of modern military conflicts. To more fully understand the effects of blast exposure, we placed rats in different holder configurations, exposed them to blast overpressure, and assessed the degree of eye and brain injury. Anesthetized Long-Evans rats received blast exposures directed at the head (63 kPa, 195 dB-SPL) in either an "open holder" (head and neck exposed; n = 7), or an "enclosed holder" (window for blast exposure to eye; n = 15) and were compared to non-blast exposed (control) rats (n = 22). Outcomes included optomotor response (OMR), electroretinography (ERG), and spectral domain optical coherence tomography (SD-OCT) at 2, 4, and 6 months post-blast, and cognitive function (Y-maze) at 3 months. Spatial frequency and contrast sensitivity were reduced in ipsilateral blast-exposed eyes in both holders (p < 0.01), while contralateral eyes showed greater deficits with the enclosed holder (p < 0.05). Thinner retinas (p < 0.001) and reduced ERG a- and b- wave amplitudes (p < 0.05) were observed for both ipsilateral and contralateral eyes with the enclosed, but not the open, holder. Rats in the open holder showed cognitive deficits compared to rats in the enclosed holder (p < 0.05). Overall, the animal holder configuration used in blast exposure studies can significantly affect outcomes. Enclosed holders may cause secondary damage to the contralateral eye by concussive injury or blast wave reflection off the holder wall. Open holders may damage the brain via rapid head movement (contrecoup injury). These results highlight additional factors to be considered when evaluating patients with blast exposure or developing models of blast injury.

Multiscale modelling of cerebrovascular injury reveals the role of vascular anatomy and parenchymal shear stresses

Neurovascular injury is often observed in traumatic brain injury (TBI). However, the relationship between mechanical forces and vascular injury is still unclear. A key question is whether the complex anatomy of vasculature plays a role in increasing forces in cerebral vessels and producing damage. We developed a high-fidelity multiscale finite element model of the rat brain featuring a detailed definition of the angioarchitecture. Controlled cortical impacts were performed experimentally and in-silico. The model was able to predict the pattern of blood-brain barrier damage. We found strong correlation between the area of fibrinogen extravasation and the brain area where axial strain in vessels exceeds 0.14. Our results showed that adjacent vessels can sustain profoundly different axial stresses depending on their alignment with the principal direction of stress in parenchyma, with a better alignment leading to larger stresses in vessels. We also found a strong correlation between axial stress in vessels and the shearing component of the stress wave in parenchyma. Our multiscale computational approach explains the unrecognised role of the vascular anatomy and shear stresses in producing distinct distribution of large forces in vasculature. This new understanding can contribute to improving TBI diagnosis and prevention.

Player position in American football influences the magnitude of mechanical strains produced in the location of chronic traumatic encephalopathy pathology: A computational modelling study

American football players are frequently exposed to head impacts, which can cause concussions and may lead to neurodegenerative diseases such as chronic traumatic encephalopathy (CTE). Player position appears to influence the risk of concussion but there is limited work on its effect on the risk of CTE. Computational modelling has shown that large brain deformations during head impacts co-localise with CTE pathology in sulci. Here we test whether player position has an effect on brain deformation within the sulci, a possible biomechanical trigger for CTE. We physically reconstructed 148 head impact events from video footage of American Football games. Players were separated into 3 different position profiles based on the magnitude and frequency of impacts. A detailed finite element model of TBI was then used to predict Green-Lagrange strain and strain rate across the brain and in sulci. Using a one-way ANOVA, we found that in positions where players were exposed to large magnitude and low frequency impacts (e.g. defensive back and wide receiver), strain and strain rate across the brain and in sulci were highest. We also found that rotational head motion is a key determinant in producing large strains and strain rates in the sulci. Our results suggest that player position has a significant effect on impact kinematics, influencing the magnitude of deformations within sulci, which spatially corresponds to where CTE pathology is observed. This work can inform future studies investigating different player-position risks for concussion and CTE and guide design of prevention systems.

Traumatic brain injury: a comparison of diffusion and volumetric magnetic resonance imaging measures

Cognitive impairment after traumatic brain injury remains hard to predict. This is partly because axonal injury, which is of fundamental importance, is difficult to measure clinically. Advances in MRI allow axonal injury to be detected after traumatic brain injury, but the most sensitive approach is unclear. Here, we compare the performance of diffusion tensor imaging, neurite orientation dispersion and density-imaging and volumetric measures of brain atrophy in the identification of white-matter abnormalities after traumatic brain injury. Thirty patients with moderate-severe traumatic brain injury in the chronic phase and 20 age-matched controls had T1-weighted and diffusion MRI. Neuropsychological tests of processing speed, executive functioning and memory were used to detect cognitive impairment. Extensive abnormalities in neurite density index and orientation dispersion index were observed, with distinct spatial patterns. Fractional anisotropy and mean diffusivity also indicated widespread abnormalities of white-matter structure. Neurite density index was significantly correlated with processing speed. Slower processing speed was also related to higher mean diffusivity in the corticospinal tracts. Lower white-matter volumes were seen after brain injury with greater effect sizes compared to diffusion metrics; however, volume was not sensitive to changes in cognitive performance. Volume was the most sensitive at detecting change between groups but was not specific for determining relationships with cognition. Abnormalities in fractional anisotropy and mean diffusivity were the most sensitive diffusion measures; however, neurite density index and orientation dispersion index may be more spatially specific. Lower neurite density index may be a useful metric for examining slower processing speed.

A New Assessment of Bicycle Helmets: The Brain Injury Mitigation Effects of New Technologies in Oblique Impacts

New helmet technologies have been developed to improve the mitigation of traumatic brain injury (TBI) in bicycle accidents. However, their effectiveness under oblique impacts, which produce more strains in the brain in comparison with vertical impacts adopted by helmet standards, is still unclear. Here we used a new method to assess the brain injury prevention effects of 27 bicycle helmets in oblique impacts, including helmets fitted with a friction-reducing layer (MIPS), a shearing pad (SPIN), a wavy cellular liner (WaveCel), an airbag helmet (Hövding) and a number of conventional helmets. We tested whether helmets fitted with the new technologies can provide better brain protection than conventional helmets. Each helmeted headform was dropped onto a 45° inclined anvil at 6.3 m/s at three locations, with each impact location producing a dominant head rotation about one anatomical axes of the head. A detailed computational model of TBI was used to determine strain distribution across the brain and in key anatomical regions, the corpus callosum and sulci. Our results show that, in comparison with conventional helmets, the majority of helmets incorporating new technologies significantly reduced peak rotational acceleration and velocity and maximal strain in corpus callosum and sulci. Only one helmet with MIPS significantly increased strain in the corpus collosum. The helmets fitted with MIPS and WaveCel were more effective in reducing strain in impacts producing sagittal rotations and a helmet fitted with SPIN in coronal rotations. The airbag helmet was effective in reducing brain strain in all impacts, however, peak rotational velocity and brain strain heavily depended on the analysis time. These results suggest that incorporating different impact locations in future oblique impact test methods and designing helmet technologies for the mitigation of head rotation in different planes are key to reducing brain injuries in bicycle accidents.