Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Desenvolvimento de um modelo computacional do crânio humano

The leading cause of mortality for both children and adults, between the ages of 5 and 29 years old, is road traffic accidents. To better understand the mechanisms that cause them or to develop prevention and detection mechanisms, several finite element models of the human head have been developed, with the YEAHM developed by members of the university of Aveiro. For this reason, the purpose of this dissertation is to improve the YEAHM, in particular the skull, with differentiation between different types of bone tissues, based on the original external geometry, but segmenting it with sutures, diploë and cortical bone, and validating it as a tool to predict cranial fractures. Several validations are performed, comparing the results of the simulation with the experimental results available in the literature at three levels: i) local validation of the material; ii) Isolated skull blunt trauma; iii) Coupled cranio-intracranial structures subjected to three impacts at different speeds, simulating falls. Accelerations, impact forces and fracture patterns are used to validate the skull model.A principal causa de mortalidade de crianças e adultos, entre 5 e 29 anos, são os acidentes de trânsito. Para melhor compreender os mecanismos que os causam ou desenvolver mecanismos de prevenção e deteção, foram desenvolvidos vários modelos de elementos finitos da cabeça humana, como o YEAHM desenvolvido por membros da Universidade de Aveiro. Por esse motivo, o objetivo desta dissertação é a melhoria do YEAHM, em particular o crânio, com diferenciação entre diferentes tipos de tecidos ósseos, com base na geometria externa original, mas segmentando-a com suturas, diploë e osso cortical, e validá-lo como ferramenta para prever fraturas cranianas. Diversas validações são realizadas, comparando os resultados da simulação com os resultados experimentais disponíveis na literatura em três níveis: i) validação local do material; ii) Lesão contusa isolada do crânio; iii) Estruturas crânio-intracranianas acopladas submetidas a três impactos em diferentes velocidades, simulando quedas. Acelerações, forças de impacto e padrões de fratura são usados para validar o modelo do crânio.Mestrado em Engenharia Mecânic

An animal-to-human scaling law for blast-induced traumatic brain injury risk assessment

Despite recent efforts to understand blast effects on the human brain, there are still no widely accepted injury criteria for humans. Recent animal studies have resulted in important advances in the understanding of brain injury due to intense dynamic loads. However, the applicability of animal brain injury results to humans remains uncertain. Here, we use advanced computational models to derive a scaling law relating blast wave intensity to the mechanical response of brain tissue across species. Detailed simulations of blast effects on the brain are conducted for different mammals using image-based biofidelic models. The intensity of the stress waves computed for different external blast conditions is compared across species. It is found that mass scaling, which successfully estimates blast tolerance of the thorax, fails to capture the brain mechanical response to blast across mammals. Instead, we show that an appropriate scaling variable must account for the mass of protective tissues relative to the brain, as well as their acoustic impedance. Peak stresses transmitted to the brain tissue by the blast are then shown to be a power function of the scaling parameter for a range of blast conditions relevant to TBI. In particular, it is found that human brain vulnerability to blast is higher than for any other mammalian species, which is in distinct contrast to previously proposed scaling laws based on body or brain mass. An application of the scaling law to recent experiments on rabbits furnishes the first physics-based injury estimate for blast-induced TBI in humans.United States. Army Research Office. Institute for Soldier Nanotechnologies (Contract DAAD-19-02-D-0002

Brain networks under attack : robustness properties and the impact of lesions

A growing number of studies approach the brain as a complex network, the so-called ‘connectome’. Adopting this framework, we examine what types or extent of damage the brain can withstand—referred to as network ‘robustness’—and conversely, which kind of distortions can be expected after brain lesions. To this end, we review computational lesion studies and empirical studies investigating network alterations in brain tumour, stroke and traumatic brain injury patients. Common to these three types of focal injury is that there is no unequivocal relationship between the anatomical lesion site and its topological characteristics within the brain network. Furthermore, large-scale network effects of these focal lesions are compared to those of a widely studied multifocal neurodegenerative disorder, Alzheimer’s disease, in which central parts of the connectome are preferentially affected. Results indicate that human brain networks are remarkably resilient to different types of lesions, compared to other types of complex networks such as random or scale-free networks. However, lesion effects have been found to depend critically on the topological position of the lesion. In particular, damage to network hub regions—and especially those connecting different subnetworks—was found to cause the largest disturbances in network organization. Regardless of lesion location, evidence from empirical and computational lesion studies shows that lesions cause significant alterations in global network topology. The direction of these changes though remains to be elucidated. Encouragingly, both empirical and modelling studies have indicated that after focal damage, the connectome carries the potential to recover at least to some extent, with normalization of graph metrics being related to improved behavioural and cognitive functioning. To conclude, we highlight possible clinical implications of these findings, point out several methodological limitations that pertain to the study of brain diseases adopting a network approach, and provide suggestions for future research

Computing Brain White and Grey Matter Injury Severity in a Traumatic Fall

In the real world, the severity of traumatic injuries is measured using the Abbreviated Injury Scale (AIS). However, the AIS scale cannot currently be computed by using the output from finite element human computer models, which currently rely on maximum principal strains (MPS) to capture serious and fatal injuries. In order to overcome these limitations, a unique Organ Trauma Model (OTM) able to calculate the threat to the life of a brain model at all AIS levels is introduced. The OTM uses a power method, named Peak Virtual Power (PVP), and defines brain white and grey matter trauma responses as a function of impact location and impact speed. This research has considered ageing in the injury severity computation by including soft tissue material degradation, as well as brain volume changes due to ageing. Further, to account for the limitations of the Lagrangian formulation of the brain model in representing hemorrhage, an approach to include the effects of subdural hematoma is proposed and included as part of the predictions. The OTM model was tested against two real-life falls and has proven to correctly predict the post-mortem outcomes. This paper is a proof of concept, and pending more testing, could support forensic studies

Multi-Scale Visual Analysis of Trauma Injury

We develop a multi-scale high-fidelity biomechanical and physiologically based modeling tools for trauma (ballistic/impact and blast) injury to brain, lung and spinal cord for resuscitation, treatment planning and design of personnel protection. Several approaches have been used to study blast and ballistic/impact injuries. Dummy containing pressure sensors and synthetic phantoms of human organs have been used to study bomb blast and car crashes. Large animals like pigs also have been equipped with pressure sensors exposed to blast waves. But these methods do not provide anatomically and physiologically, full optimization of body protection design and require animal sacrifice. Anatomy and medical image-based high-fidelity computational modeling can be used to analyze injury mechanisms and to optimize the design of body protection. This paper presents novel approach of coupled computational fluid dynamics and computational structures dynamics to simulate fluid (air, cerebrospinal fluid)–solid (cranium, brain tissue) interaction during ballistic/blast impact. We propose a trauma injury simulation pipeline concept staring from anatomy and medical image-based high-fidelity 3D geometric modeling, extraction of tissue morphology, generation of computational grids, multi-scale biomechanical and physiological simulations, and data visualization

POPC Phospholipid Bilayer Failure Under Biaxial Deformations Using Molecular Dynamics

Mechanical injuries to the cell often lead to disruptions of the cell’s phospholipid bilayer membrane and potential detrimental effects including cell death. Understanding the mechanical states required to disrupt the phospholipid bilayer would result in better multiscale constitutive models and further knowledge of cell injury. The objectives of this research were to perform biaxial deformations of the phospholipid bilayer to quantify phospholipid bilayer disruption and to identify potential parameters that can be used in multiscale constitutive equations. We show that the von Mises stress, 26.6-61.1, increases linearly with the von Mises strain rate, 1.7e8-6.7e8, and that the strain at failure is dependent on the stress state with non- and equibiaxial being the most detrimental when failing at \u3c.73 von Mises strain. Understanding the effects of nanoscale mechanical trauma to the cell provides a better understanding of cell injury and may provide insight regarding initiation and progression of cell damage

POPC Phospholipid Bilayer Failure Under Biaxial Deformations Using Molecular Dynamics

Mechanical injuries to the cell often lead to disruptions of the cell’s phospholipid bilayer membrane and potential detrimental effects including cell death. Understanding the mechanical states required to disrupt the phospholipid bilayer would result in better multiscale constitutive models and further knowledge of cell injury. The objectives of this research were to perform biaxial deformations of the phospholipid bilayer to quantify phospholipid bilayer disruption and to identify potential parameters that can be used in multiscale constitutive equations. We show that the von Mises stress, 26.6-61.1, increases linearly with the von Mises strain rate, 1.7e8-6.7e8, and that the strain at failure is dependent on the stress state with non- and equibiaxial being the most detrimental when failing at \u3c.73 von Mises strain. Understanding the effects of nanoscale mechanical trauma to the cell provides a better understanding of cell injury and may provide insight regarding initiation and progression of cell damage