Anisotropic Modeling of Fibrous White Matter

2008 ◽  
Author(s):  
Rika M. Wright ◽  
K. T. Ramesh
Keyword(s):  
White Matter ◽  
Experimental Studies ◽  
Diffuse Axonal Injury ◽  
Strain Energy Function ◽  
Brain Structures ◽  
The United States ◽  
Cellular Level ◽  
Brain Deformation ◽  
Injury Mechanisms ◽  
The Brain

Traumatic brain injury (TBI) is a debilitating injury that affects more than 1.4 million people in the United States each year. Of the incidences of TBI, diffuse axonal injury (DAI) accounts for the second largest percentage of deaths. DAI is caused by inertial loads to the head, and it is characterized by damage to neurons. Despite the extensive research on DAI, the injury mechanisms associated with the pathology are still poorly understood. The crucial link between the inertial forces to the head at the macroscale and the resulting damage at the cellular level has yet to be explained. An integral step to understanding this coupling between mechanical forces and the functional damage of neurons is the development of an analytical model that accurately represents the mechanics of brain deformation under inertial loads. It has been noted in clinical and experimental studies that the most common injury location of DAI is within the deep white matter of the brain. Structures such as the splenium of the corpus callosum are cited as being highly susceptible to damage [1]. Although numerous brain tissue models have been proposed, few models account for the anisotropic nature of white matter in the brain. As a first step in developing an anisotropic model for white matter, the effect of the invariant terms in a strain energy function for white matter is analyzed.

A Finite Element Model for Estimating Axonal Damage in Traumatic Brain Injury

2012 ◽  
Author(s):  
Rika M. Wright ◽  
K. T. Ramesh
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
White Matter ◽  
Finite Element Model ◽  
Axonal Injury ◽  
Diffuse Axonal Injury ◽  
Element Model ◽  
Cellular Level ◽  
The Brain

There has been an ongoing effort to reduce the occurrence of sports-related traumatic brain injury. These injuries are caused by an impact to the head and often lead to the damage of neural axons in the brain. This type of damage is classified as diffuse axonal injury (DAI) or traumatic axonal injury (TAI) [1]. One of the difficulties in studying the progression of axonal injury is that the structural signature of DAI cannot be readily visualized with conventional medical imaging modalities since the damage occurs at the cellular level [2]. This also makes the injury difficult to diagnose. Many researchers have turned to finite element (FE) models to study the development of diffuse axonal injury. FE models provide a means for observing the mechanical process of injury development from the loads to the head at the macroscale to the damage that results at the cellular level. However, for a finite element model to be a viable tool for studying DAI, the model must be able to accurately represent the behavior of the brain tissue, and it must be able to accurately predict injury. In this work, we address both of these issues in an effort to improve the material models and injury criteria used in current FE models of TBI. We represent the white matter with an anisotropic, hyper-viscoelastic constitutive model, incorporate the microstructure of the white matter through the use of diffusion tensor imaging (DTI), and estimate injury using an axonal strain injury (ASI) criterion (Figure 1). We also develop a novel method to quantify the degree of axonal damage in the fiber tracts of the brain.

The Use of a Cellular Strain Injury Criterion and Diffusion Tensor Imaging in a Computational Model of Traumatic Brain Injury

2010 ◽  
Author(s):  
Rika M. Wright ◽  
K. T. Ramesh
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mechanical Loading ◽  
Computational Models ◽  
Diffusion Tensor ◽  
Diffuse Axonal Injury ◽  
Element Model ◽  
Cellular Level ◽  
Cellular Injury ◽  
Injury Mechanisms

With the increase in the number of soldiers sustaining traumatic brain injury from military incidents and the recent attention on sports related traumatic brain injury, there has been a focused effort to develop preventative and treatment methods for traumatic brain injury (TBI). Traumatic brain injury is caused by mechanical loading to the head, such as from impacts, sudden accelerations, or blast loading, and the pathology can range from focal damage in the brain to widespread diffuse injury [1]. In this study, we investigate the injury mechanisms of diffuse axonal injury (DAI), which accounts for the second largest percentage of deaths due to brain trauma [2]. DAI is caused by sudden inertial loads to the head, and it is characterized by damage to neural axons. Despite the extensive research on DAI, the coupling between the mechanical loading to the head and the damage at the cellular level is still poorly understood. Unlike previous computational models that use macroscopic stress and strain measures to determine injury, a cellular injury criterion is used in this work as numerous studies have shown that cellular strain can be related to the functional damage of neurons. The effectiveness of using this cellular injury criterion to predict damage in a finite element model of DAI is investigated.

Microstructural Hyperelastic Characterization of Brain White Matter in Tension

2019 ◽  
Author(s):  
Mohammadreza Ramzanpour ◽  
Mohammad Hosseini-Farid ◽  
Mariusz Ziejewski ◽  
Ghodrat Karami
Keyword(s):  
Finite Element ◽  
White Matter ◽  
Human Brain ◽  
Volume Fraction ◽  
Fibrous Composite ◽  
Diffuse Axonal Injury ◽  
Stiffness Ratio ◽  
Fibrous Composite Material ◽  
Brain White Matter ◽  
The Brain

Abstract Axons as microstructural constituent elements of brain white matter are highly oriented in extracellular matrix (ECM) in one direction. Therefore, it is possible to model the human brain white matter as a unidirectional fibrous composite material. A micromechanical finite element model of the brain white matter is developed to indirectly measure the brain white matter constituents’ properties including axon and ECM under tensile loading. Experimental tension test on corona radiata conducted by Budday et al. 2017 [1] is used in this study and one-term Ogden hyperelastic constitutive model is applied to characterize its behavior. By the application of genetic algorithm (GA) as a black box optimization method, the Ogden hyperelastic parameters of axon and ECM minimizing the error between numerical finite element simulation and experimental results are measured. Inverse analysis is conducted on the resultant optimized parameters shows high correlation of coefficient (>99%) between the numerical and experimental data which verifies the accuracy of the optimization procedure. The volume fraction of axons in porcine brain white matter is taken to be 52.7% and the stiffness ratio of axon to ECM is perceived to be 3.0. As these values are not accurately known for human brain white matter, we study the material properties of axon and ECM for different stiffness ratio and axon volume fraction values. The results of this study helps to better understand the micromechanical structure of the brain and micro-level injuries such as diffuse axonal injury.

Anisotropic Behavior of White Matter in Shear and Implications for Transversely Isotropic Models

2013 ◽  
Author(s):  
Ruth J. Okamoto ◽  
Yuan Feng ◽  
Guy M. Genin ◽  
Philip V. Bayly
Keyword(s):  
White Matter ◽  
Strain Tensor ◽  
Experimental Studies ◽  
Transversely Isotropic ◽  
Stretch Ratio ◽  
Fiber Axis ◽  
Fiber Direction ◽  
Material Models ◽  
Green Strain ◽  
The Brain

Experimental studies [1] have shown that white matter (WM) in the brain is mechanically anisotropic. Based on its fibrous structure, transversely isotropic (TI) material models have been suggested to capture WM behavior. TI hyperelastic material models involve strain energy density functions that depend on the I4 and I5 pseudo-invariants of the Cauchy-Green strain tensor to account for the effects of stiff fibers. The pseudo-invariant I4 is the square of the stretch ratio in the fiber direction; I5 contains contributions of shear strain in planes parallel to the fiber axis. Most, if not all, published models of WM depend on I4 but not on I5.

Simulating Axonal Stretch During Traumatic Brain Injury Events

2010 ◽  
Author(s):  
Jean-Pierre Dollé ◽  
Jeffrey Barminko ◽  
Rene Schloss ◽  
Martin L. Yarmush
Keyword(s):  
Brain Injuries ◽  
Motor Vehicle ◽  
Axonal Injury ◽  
Diffuse Axonal Injury ◽  
The United States ◽  
Motor Vehicle Accidents ◽  
Inertial Forces ◽  
Vehicle Accidents ◽  
Rapid Deceleration ◽  
The Brain

Traumatic Brain Injuries (TBI) affect up to 1.5 million people annually within the United States with as many as 250,000 being hospitalized and 50,000 dying [1]. TBI events occur when the brain experiences a sudden trauma such as a rapid deceleration of the brain that typically occurs during motor vehicle accidents. During rapid deceleration events, the brain is subjected to high inertial forces that can result in a shearing or elongation of axons that is commonly known as Diffuse Axonal Injury (DAI) [2,3].

scholarly journals Can exercise make our children smarter?

2020 ◽  
Vol 10 (2) ◽  
Author(s):  
Nenad Stojiljković ◽  
Petar Mitić ◽  
Goran Sporiš
Keyword(s):  
White Matter ◽  
Brain Structure ◽  
Methodological Approach ◽  
Brain Structures ◽  
Structure And Function ◽  
Healthy Children ◽  
Cross Sectional ◽  
Brain Structure And Function ◽  
And Function ◽  
The Brain

Purpose. The aim of this study is to reveal the effects of exercise on the brain structure and function in children, and to analyze methodological approach applied in the researches of this topic. Methods. This literature review provides an overview of important findings in this fast growing research domain. Results from cross-sectional, longitudinal, and interventional studies of the influence of exercise on the brain structure and function of healthy children are reviewed and discussed. Results. The majority of researches are done as cross sectional studies based on the exploring correlation between the level of physical activity and characteristics of brain structure and function. Results of the studies indicate that exercise has positive correlation with improved cognition and beneficial changes to brain function in children. Physically active children have greater white matter integrity in several white matter tracts (corpus callosum, corona radiata, and superior longitudinal fasciculus), have greater volume of gray matter in the hippocampus and basal ganglia than their physically inactive counterparts. The longitudinal/interventional studies also showed that exercise (mainly aerobic) improve cognitive performance of children and causes changes observed on functional magnetic resonance imaging scans (fMRI) located in prefrontal and parietal regions. Conclusion. Previous researches undoubtable proved that exercise can make positive changes of the brain structures in children, specifically the volume of the hippocampus which is the center of learning and memory. Finally the researchers agree that the most influential type of exercise on changes of brain structure and functions are the aerobic exercises. 

In Situ Deformations in the Immature Brain During Rapid Rotations

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Nicole G. Ibrahim ◽  
Rahul Natesh ◽  
Spencer E. Szczesny ◽  
Karen Ryall ◽  
Stephanie A. Eucker ◽  
...  
Keyword(s):  
Computational Models ◽  
Axonal Injury ◽  
Head Rotation ◽  
Lower Velocity ◽  
Brain Deformation ◽  
Injury Mechanisms ◽  
Viscoelastic Modulus ◽  
Lubricated Plate ◽  
The Brain

Head trauma is the leading cause of death and debilitating injury in children. Computational models are important tools used to understand head injury mechanisms but they must be validated with experimental data. In this communication we present in situ measurements of brain deformation during rapid, nonimpact head rotation in juvenile pigs of different ages. These data will be used to validate computational models identifying age-dependent thresholds of axonal injury. Fresh 5 days (n=3) and 4 weeks (n=2) old piglet heads were transected horizontally and secured in a container. The cut surface of each brain was marked and covered with a transparent, lubricated plate that allowed the brain to move freely in the plane of rotation. For each brain, a rapid (20–28 ms) 65 deg rotation was applied sequentially at 50 rad/s, 75 rad/s, and 75 rad/s. Each rotation was digitally captured at 2500 frames/s (480×320 pixels) and mark locations were tracked and used to compute strain using an in-house program in MATLAB. Peak values of principal strain (Epeak) were significantly larger during deceleration than during acceleration of the head rotation (p<0.05), and doubled with a 50% increase in velocity. Epeak was also significantly higher during the second 75 rad/s rotation than during the first 75 rad/s rotation (p<0.0001), suggesting structural alteration at 75 rad/s and the possibility that similar changes may have occurred at 50 rad/s. Analyzing only lower velocity (50 rad/s) rotations, Epeak significantly increased with age (16.5% versus 12.4%, p<0.003), which was likely due to the larger brain mass and smaller viscoelastic modulus of the 4 weeks old pig brain compared with those of the 5 days old. Strain measurement error for the overall methodology was estimated to be 1%. Brain tissue strain during rapid, nonimpact head rotation in the juvenile pig varies significantly with age. The empirical data presented will be used to validate computational model predictions of brain motion under similar loading conditions and to assist in the development of age-specific thresholds for axonal injury. Future studies will examine the brain-skull displacement and will be used to validate brain-skull interactions in computational models.

Application of Diffusion Tensor Imaging in Modeling Diffuse Axonal Injury

2009 ◽  
Author(s):  
Rika M. Wright ◽  
K. T. Ramesh
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Fiber Orientation ◽  
Structural Damage ◽  
Diffusion Tensor ◽  
Axonal Injury ◽  
Diffuse Axonal Injury ◽  
Material Model ◽  
Orientation Data ◽  
The Brain

Traumatic brain injury (TBI) is a debilitating injury that has received a lot of attention within the past few years partly as a result of the increased number of TBI incidents arising from military conflicts. Of the incidences of TBI, diffuse axonal injury (DAI) accounts for the second largest percentage of deaths [1]. DAI is caused by sudden inertial loads to the head, and it is characterized by damage to neural cells [2]. These inertial loads at the macroscale result in functional and structural damage at the cellular level. To understand the coupling between the mechanical forces and the functional damage of neurons, an analytical model that accurately represents the mechanics of brain deformation under inertial loads must be developed. It has been shown in clinical and experimental studies that the deep white matter of the brain is highly susceptible to injury [2]. Unlike the gray matter of the brain, the white matter structures contain an organized arrangement of neural axons and therefore can be considered anisotropic (Figure 1). To account for the anisotropic nature of the white matter in finite element simulations, the orientation of the neural axons must be incorporated into a material model for brain tissue. In this study, the use of diffusion tensor imaging (DTI) as a tool to provide fiber orientation information to continuum models is investigated. By incorporating fiber orientation data into a material model for white matter, the strains experienced by neural axons in the white matter tracts of the brain are computed, and this strain is related to cellular stretch thresholds of diffuse axonal injury.

scholarly journals Within a Nanometer of your Life

2001 ◽  
Vol 123 (08) ◽  
pp. 54-58 ◽  
Author(s):  
Allen J. Menezes ◽  
Vik J. Kapoor ◽  
Vijay K. Goel ◽  
Brent D. Cameron ◽  
Jian-Yu Lu
Keyword(s):  
Early Stage ◽  
The United States ◽  
Neurosecretory Cells ◽  
Cellular Level ◽  
Orthopaedic Implant ◽  
Macro Scale ◽  
Complex Shapes ◽  
Manufacturing Techniques ◽  
Physical And Chemical ◽  
The Brain

This article reviews advances in semiconductor manufacturing techniques that are bringing medicine closer to cures and treatments that have eluded researchers working on the macro scale. An orthopaedic implant company, Implex Corp. of Allendale, New Jersey, has developed spinal fusion devices for the cervical, thoracic, and lumbar spine using a novel biomaterial called Hedrocel Trabecular Metal. According to Implex, Hedrocel, which has a porous structure and mechanical properties like bone, can be formed or machined into complex shapes. Implex has developed hip and knee reconstruction devices made wholly or in part of Hedrocel. The spinal implants are in commercial use in Europe and are undergoing clinical trials in the United States. By studying fluid samples at the cellular level, the system can diagnose the physical and chemical status of cells to detect disease at an early stage. Nanopore fabrication technology is used to make microcapsules for implanting neurons in the brain. Once the capsules are implanted, the neurons are electrically stimulated to release neurotransmitters. Disorders where basic neurosecretory cells are missing or damaged can be treated using nanopore technology.

scholarly journals Fusion of quantitative susceptibility maps and T1-weighted images improve brain tissue contrast in primates

2021 ◽  
Author(s):  
Rakshit Dadarwal ◽  
Michael Ortiz-Rios ◽  
Susann Boretius
Keyword(s):  
White Matter ◽  
Brain Tissue ◽  
Brain Structures ◽  
Macaque Monkey ◽  
List Type ◽  
Subcortical Structures ◽  
Tissue Segmentation ◽  
Tissue Contrast ◽  
T1 Contrast ◽  
The Brain

AbstractRecent progress in quantitative susceptibility mapping (QSM) has enabled the accurate delineation of submillimeter scale subcortical brain structures in humans. QSM reflects the magnetic susceptibility arising from the spatial distribution of iron, myelin, and calcium in the brain. The simultaneous visualization of cortical, subcortical, and white matter structure remains, however, challenging, utilizing QSM data solely. Here we present TQ-SILiCON, a fusion method that enhances the contrast of cortical and subcortical structures and provides an excellent white matter delineation by combining QSM and conventional T1-weighted (T1w) images. In this study, we first established QSM in the macaque monkey to map iron-rich subcortical structures. Implementing the same QSM acquisition and analyses methods allowed a similar accurate delineation of subcortical structures in humans. Moreover, applying automatic brain tissue segmentation to TQ-SILiCON images of the macaque improved the classification of the brain tissue types as compared to the single T1 contrast. Furthermore, we validate our dual-contrast fusion approach in humans and similarly demonstrate improvements in automated segmentation of cortical and subcortical structures. We believe the proposed contrast will facilitate translational studies in non-human primates to investigate the pathophysiology of neurodegenerative diseases that affect the subcortical structures of the basal ganglia in humans.HighlightsThe subcortical gray matter areas of macaque monkeys are reliably mapped by QSM, much as they are in humans.Combining T1w and QSM images improves the visualization and segmentation of white matter, cortical and subcortical structures in the macaque monkey.The proposed dual contrast TQ-SILiCON provides a similar image quality also in humans.TQ-SILiCON facilitates comparative and translational neuroscience studies investigating subcortical structures.

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