Intracranial biomechanics following cortical contusion in live rats

The Networking Brain: How Extracellular Matrix, Cellular Networks, and Vasculature Shape the In Vivo Mechanical Properties of the Brain

Mechanically, the brain is characterized by both solid and fluid properties. The resulting unique material behavior fosters proliferation, differentiation, and repair of cellular and vascular networks, and optimally protects them from damaging shear forces. Magnetic resonance elastography (MRE) is a noninvasive imaging technique that maps the mechanical properties of the brain in vivo. MRE studies have shown that abnormal processes such as neuronal degeneration, demyelination, inflammation, and vascular leakage lead to tissue softening. In contrast, neuronal proliferation, cellular network formation, and higher vascular pressure result in brain stiffening. In addition, brain viscosity has been reported to change with normal blood perfusion variability and brain maturation as well as disease conditions such as tumor invasion. In this article, the contributions of the neuronal, glial, extracellular, and vascular networks are discussed to the coarse-grained parameters determined by MRE. This reductionist multi-network model of brain mechanics helps to explain many MRE observations in terms of microanatomical changes and suggests that cerebral viscoelasticity is a suitable imaging marker for brain disease.

Advanced Neuroimaging Role in Traumatic Brain Injury: A Narrative Review

Traumatic brain injury (TBI) is a common source of morbidity and mortality among civilians and military personnel. Initial routine neuroimaging plays an essential role in rapidly assessing intracranial injury that may require intervention. However, in the context of TBI, limitations of routine neuroimaging include poor visualization of more subtle changes of brain parenchymal after injury, poor prognostic ability and inability to analyze cerebral perfusion, metabolite and mechanical properties. With the development of modern neuroimaging techniques, advanced neuroimaging techniques have greatly boosted the studies in the diagnosis, prognostication, and eventually impacting treatment of TBI. Advances in neuroimaging techniques have shown potential, including (1) Ultrasound (US) based techniques (contrast-enhanced US, intravascular US, and US elastography), (2) Magnetic resonance imaging (MRI) based techniques (diffusion tensor imaging, magnetic resonance spectroscopy, perfusion weighted imaging, magnetic resonance elastography and functional MRI), and (3) molecular imaging based techniques (positron emission tomography and single photon emission computed tomography). Therefore, in this review, we aim to summarize the role of these advanced neuroimaging techniques in the evaluation and management of TBI. This review is the first to combine the role of the US, MRI and molecular imaging based techniques in TBI. Advanced neuroimaging techniques have great potential; still, there is much to improve. With more clinical validation and larger studies, these techniques will be likely applied for routine clinical use from the initial research.

Traumatic brain injury-induced cerebral microbleeds in the elderly

Traumatic brain injury (TBI) was shown to lead to the development of cerebral microbleeds (CMBs), which are associated with long term cognitive decline and gait disturbances in patients. The elderly is one of the most vulnerable parts of the population to suffer TBI. Importantly, ageing is known to exacerbate microvascular fragility and to promote the formation of CMBs. In this overview, the effect of ageing is discussed on the development and characteristics of TBI-related CMBs, with special emphasis on CMBs associated with mild TBI. Four cases of TBI-related CMBs are described to illustrate the concept that ageing exacerbates the deleterious microvascular effects of TBI and that similar brain trauma may induce more CMBs in old patients than in young ones. Recommendations are made for future prospective studies to establish the mechanistic effects of ageing on the formation of CMBs after TBI, and to determine long-term consequences of CMBs on clinically relevant outcome measures including cognitive performance, gait and balance function.

Mind the gap: A mechanobiological hypothesis for the role of gap junctions in the mechanical properties of injured brain tissue

Despite more than half a century of work on the brain biomechanics, there are still significant unknowns about this tissue. Since the brain is highly susceptible to injury, damage biomechanics has been one of the main areas of interest to the researchers in the field of brain biomechanics. In many previous studies, mechanical properties of brain tissue under sub-injury and injury level loading conditions have been addressed; however, to the best of our knowledge, the role of cell-cell interactions in the mechanical behavior of brain tissue has not been well examined yet. This note introduces the hypothesis that gap junctions as the major type of cell-cell junctions in the brain tissue play a pivotal role in the mechanical properties of the tissue and their failure during injury leads to changes in brain's material properties. According to this hypothesis, during an injury, the gap junctions are damaged, leading to a decrease in tissue stiffness, whereas following the injury, new junction proteins are expressed, leading to an increase in tissue stiffness. We suggest that considering the mechanobiological effect of gap junctions in the material properties of brain tissue may help better understand the brain injury mechanism.

Localized characterization of brain tissue mechanical properties by needle induced cavitation rheology and volume controlled cavity expansion

Changes in the elastic properties of brain tissue have been correlated with injury, cancers, and neurodegenerative diseases. However, discrepancies in the reported elastic moduli of brain tissue are persistent, and spatial inhomogeneities complicate the interpretation of macroscale measurements such as rheology. Here we introduce needle induced cavitation rheology (NICR) and volume-controlled cavity expansion (VCCE) as facile methods to measure the apparent Young's modulus E of minimally manipulated brain tissue, at specific tissue locations and with sub-millimeter spatial resolution. For different porcine brain regions and sections analyzed by NICR, we found E to be 3.7 ± 0.7 kPa and 4.8 ± 1.0 kPa for gray matter, and white matter, respectively. For different porcine brain regions and sections analyzed by VCCE, we found E was 0.76 ± 0.02 kPa for gray matter and 0.92 ± 0.01 kPa for white matter. Measurements from VCCE were more similar to those obtained from macroscale shear rheology (0.75 ± 0.06 kPa) and from instrumented microindentation of white matter (0.97 ± 0.40 kPa) and gray matter (0.86 ± 0.20 kPa). We attributed the higher stiffness reported from NICR to that method's assumption of a cavitation instability due to a neo-Hookean constitutive response, which does not capture the strain-stiffening behavior of brain tissue under large strains, and therefore did not provide appropriate measurements. We demonstrate via both analytical modeling of a spherical cavity and finite element modeling of a needle geometry, that this strain stiffening may prevent a cavitation instability. VCCE measurements take this stiffening behavior into account by employing an incompressible one-term Ogden model to find the nonlinear elastic properties of the tissue. Overall, VCCE afforded rapid and facile measurement of nonlinear mechanical properties of intact, healthy mammalian brain tissue, enabling quantitative comparison among brain tissue regions and also between species. Finally, accurate estimation of elastic properties for this strain stiffening tissue requires methods that include appropriate constitutive models of the brain tissue response, which here are represented by inclusion of the Ogden model in VCCE.

Structural Anisotropy vs. Mechanical Anisotropy: The Contribution of Axonal Fibers to the Material Properties of Brain White Matter

Brain's micro-structure plays a critical role in its macro-structure material properties. Since the structural anisotropy in the brain white matter has been introduced due to axonal fibers, considering the direction of axons in the continuum models has been mediated to improve the results of computational simulations. The aim of the current study was to investigate the role of fiber direction in the material properties of brain white matter and compare the mechanical behavior of the anisotropic white matter and the isotropic gray matter. Diffusion tensor imaging (DTI) was employed to detect the direction of axons in white matter samples, and tensile stress-relaxation loads up to 20% strains were applied on bovine gray and white matter samples. In order to calculate the nonlinear and time-dependent properties of white matter and gray matter, a visco-hyperelastic model was used. The results indicated that the mechanical behavior of white matter in two orthogonal directions, parallel and perpendicular to axonal fibers, are significantly different. This difference indicates that brain white matter could be assumed as an anisotropic material and axons have contribution in the mechanical properties. Also, up to 15% strain, white matter samples with axons parallel to the force direction are significantly stiffer than both the gray matter samples and white matter samples with axons perpendicular to the force direction. Moreover, the elastic moduli of white matter samples with axons both parallel and perpendicular to the loading direction and gray matter samples at 15-20% strain are not significantly different. According to these observations, it is suggested that axons have negligible roles in the material properties of white matter when it is loaded in the direction perpendicular to the axon direction. Finally, this observation showed that the anisotropy of brain tissue not only has effects on the elastic behavior, but also has effects on the viscoelastic behavior.

A knowledge map analysis of brain biomechanics: Current evidence and future directions

Although brain, one of the most complex organs in the mammalian body, has been subjected to many studies from physiological and pathological points of view, there remain significant gaps in the available knowledge regarding its biomechanics. This article reviews the research trends in brain biomechanics with a focus on injury. We used published scientific articles indexed by Web of Science database over the past 40 years and tried to address the gaps that still exist in this field. We analyzed the data using VOSviewer, which is a software tool designed for scientometric studies. The results of this study showed that the response of brain tissue to external forces has been one of the significant research topics among biomechanicians. These studies have addressed the effects of mechanical forces on the brain and mechanisms of traumatic brain injury, as well as characterized changes in tissue behavior under trauma and other neurological diseases to provide new diagnostic and monitoring methods. In this study, some challenges in the field of brain injury biomechanics have been identified and new directions toward understanding the gaps in this field are suggested.

Advanced neuroimaging in traumatic brain injury: an overview

Traumatic brain injury (TBI) is a common condition with many potential acute and chronic neurological consequences. Standard initial radiographic evaluation includes noncontrast head CT scanning to rapidly evaluate for pathology that might require intervention. The availability of fast, relatively inexpensive CT imaging has fundamentally changed the clinician's ability to noninvasively visualize neuroanatomy. However, in the context of TBI, limitations of head CT without contrast include poor prognostic ability, inability to analyze cerebral perfusion status, and poor visualization of underlying posttraumatic changes to brain parenchyma. Here, the authors review emerging advanced imaging for evaluation of both acute and chronic TBI and include QuickBrain MRI as an initial imaging modality. Dynamic susceptibility-weighted contrast-enhanced perfusion MRI, MR arterial spin labeling, and perfusion CT are reviewed as methods for examining cerebral blood flow following TBI. The authors evaluate MR-based diffusion tensor imaging and functional MRI for prognostication of recovery post-TBI. Finally, MR elastography, MR spectroscopy, and convolutional neural networks are examined as future tools in TBI management. Many imaging technologies are being developed and studied in TBI, and some of these may hold promise in improving the understanding and management of TBI. ABBREVIATIONS ASL = arterial spin labeling; CNN = convolutional neural network; CTP = perfusion CT; DAI = diffuse axonal injury; DMN = default mode network; DOC = disorders of consciousness; DTI = diffusion tensor imaging; FA = fractional anisotropy; fMRI = functional MRI; GCS = Glasgow Coma Scale; MD = mean diffusivity; MRE = MR elastography; MRS = MR spectroscopy; mTBI = mild TBI; NAA = N-acetylaspartate; SWI = susceptibility-weighted imaging; TBI = traumatic brain injury; UHF = ultra-high field.

Biomechanical simulation of traumatic brain injury in the rat

BACKGROUND

Traumatic brain injury poses an enormous clinical challenge. Rats are the animals most widely used in pre-clinical experiments. Biomechanical simulations of these experiments predict the distribution of mechanical stress and strain across key tissues. It is in theory possible to dramatically increase our understanding of traumatic brain injury pathophysiology by correlating stress and strain with histological and functional injury outcomes. This review summarizes the state of the art in biomechanical simulation of traumatic brain injury in the rat. It also places this body of knowledge in the context of the wider effort to understand traumatic brain injury in rats and in humans.

METHODS

Peer-reviewed research articles on biomechanical simulation of traumatic brain injury in the rat were reviewed and summarized.

FINDINGS

When mathematical models of traumatic brain injury in the rat first emerged, they relied on scant data regarding biomechanical properties. The data on relevant biomechanical properties has increased recently. However, experimental models of traumatic brain injury in the rat have also become less homogeneous. New and modified models have emerged that are biomechanically distinct from traditional models.

INTERPRETATION

Important progress in mathematical modeling and measurement of biomechanical properties has led to credible, predictive simulations of traditional, experimental models of traumatic brain injury in the rat, such as controlled cortical impact. However, recent trends such as the increasing popularity of closed head models and blast models create new biomechanical challenges. Investigators studying rat brain biomechanics must continue to innovate to keep pace with these developments.

Dual-porosity poroviscoelasticity and quantitative hydromechanical characterization of the brain tissue with experimental hydrocephalus data

Hydromechanical brain models often involve constitutive relations which must account for soft tissue deformation and creep, together with the interstitial fluid movement and exchange through capillaries. The interaction of rather unknown mechanisms which produce, absorb, and circulate the cerebrospinal fluid within the central nervous system can further add to their complexity. Once proper models for these phenomena or processes are selected, estimation of the associated parameters could be even more challenging. This paper presents the results of a consistent, coupled poroviscoelastic modeling and characterization of the brain tissue as a dual-porosity system. The model draws from Biot's theory of poroviscoelasticity, and adopts the generalized Kelvin's rheological description of the viscoelastic tissue behavior. While the interstitial space serves as the primary porosity through which the bulk flow of the interstitial fluid occurs, a secondary porosity network comprising the capillaries and venous system allows for its partial absorption into the blood. The correspondence principle is used in deriving a time-dependent analytical solution to the proposed model. It allows for identical poroelastic formulation of the original poroviscoelastic problem in the Laplace transform space. Hydrocephalus generally refers to a class of medical conditions which share the ventricles enlargement as a common feature. A set of published data from induced hydrocephalus and follow-up perfusion of cats' brains is used for quantitative characterization of the proposed model. A selected portion of these data including the ventricular volume and rate of fluid absorption from the perfused brain, together with the forward model solution, is utilized via an inverse problem technique to find proper estimations of the model parameters. Results show significant improvement in model predictions of the experimental data. The convoluted and coupled solution results are presented through the time-dependent plots of the ventricular volume undergoing the perfusion experiment. The plots demonstrate the intricate interplay of viscous and poroelastic diffusive time scales, and their competition in reaching the steady state response of the system.