Magnetic Resonance Elastography of the Brain: from Phantom to Mouse to Man

The overall objective of this study is to develop magnetic resonance elastography: MRE) imaging to better understand brain deformation, brain tissue mechanical properties, and brain-skull interaction in vivo. The findings of this study provide parameters for numerical models of human head biomechanics, as well as data for validation of these models. Numerical simulations offer enormous potential to the study of traumatic brain injury: TBI) and may also contribute to the development of prophylactic devices for high-risk subjects: e.g., military personnel, first-responders, and athletes). Current numerical models have not been adequately parameterized or validated and their predictions remain controversial. This dissertation describes three kinds of MRE experiments, conducted in phantom: physical model), mouse, and man. Phantom studies provide a means to experimentally confirm the accuracy of MRE estimates of viscoelastic parameters in relatively simple materials and geometries. Studies in the mouse provide insight into the dispersive nature of brain tissue mechanical properties at frequencies beyond those that can be measured in humans. Studies in human subjects provide direct measurements of the human brain\u27s response to dynamic extracranial loads, including skull-brain energy transmission and viscoelastic properties

Characterizing anisotropy in fibrous soft materials by MR elastography of slow and fast shear waves

The general objective of this work was to develop experimental methods based on magnetic resonance elastography (MRE) to characterize fibrous soft materials. Mathematical models of tissue biomechanics capable of predicting injury, such as traumatic brain injury (TBI), are of great interest and potential. However, the accuracy of predictions from such models depends on accuracy of the underlying material parameters. This dissertation describes work toward three aims. First, experimental methods were designed to characterize fibrous materials based on a transversely isotropic material model. Second, these methods are applied to characterize the anisotropic properties of white matter brain tissue ex vivo. Third, a theoretical investigation of the potential application of MRE to probe nonlinear mechanical behavior of soft tissue was performed. These studies provide new methods to characterize anisotropic and nonlinear soft materials as well as contributing significantly to our understanding of the behavior of specific biological soft tissues

Dynamic Deformation and Mechanical Properties of Brain Tissue

Traumatic brain injury is an important medical problem affecting millions of people. Mathematical models of brain biomechanics are being developed to simulate the mechanics of brain injury and to design protective devices. However, because of a lack of quantitative data on brain-skull boundary conditions and deformations, the predictions of mathematical models remain uncertain. The objectives of this dissertation are to develop methods and obtain experimental data that will be used to parameterize and validate models of traumatic brain injury. To that end, this dissertation first addresses the brain-skull boundary conditions by measuring human brain motion using tagged magnetic resonance imaging. Magnetic resonance elastography was performed in the ferret brain to measure its mechanical properties in vivo. Brain tissue is not only heterogeneous, but may also be anisotropic. To characterize tissue anisotropy, an experimental procedure combining both shear testing and indentation was developed and applied to white matter and gray matter. These measurements of brain-skull interactions and mechanical properties of the brain will be valuable in the development and validation of finite element simulations of brain biomechanics

Anisotropic Elastography for Local Passive Properties and Active Contractility of Myocardium from Dynamic Heart Imaging Sequence

Major heart diseases such as ischemia and hypertrophic myocardiopathy are accompanied with significant changes in the passive mechanical properties and active contractility of myocardium. Identification of these changes helps diagnose heart diseases, monitor therapy, and design surgery. A dynamic cardiac elastography (DCE) framework is developed to assess the anisotropic viscoelastic passive properties and active contractility of myocardial tissues, based on the chamber pressure and dynamic displacement measured with cardiac imaging techniques. A dynamic adjoint method is derived to enhance the numerical efficiency and stability of DCE. Model-based simulations are conducted using a numerical left ventricle (LV) phantom with an ischemic region. The passive material parameters of normal and ischemic tissues are identified during LV rapid/reduced filling and artery contraction, and those of active contractility are quantified during isovolumetric contraction and rapid/reduced ejection. It is found that quasistatic simplification in the previous cardiac elastography studies may yield inaccurate material parameters

COMPUTATIONAL ULTRASOUND ELASTOGRAPHY: A FEASIBILITY STUDY

Ultrasound Elastography (UE) is an emerging set of imaging modalities used to assess the biomechanical properties of soft tissues. UE has been applied to numerous clinical applications. Particularly, results from clinical trials of UE in breast lesion differentiation and staging liver fibrosis indicated that there was a lack of confidence in UE measurements or image interpretation. Confidence on UE measurements interpretation is critically important for improving the clinical utility of UE. The primary objective of my thesis is to develop a computational simulation platform based on open-source software packages including Field II, VTK, FEBio and Tetgen. The proposed virtual simulation platform can be used to simulate SE and acoustic radiation force based SWE simulations, including pSWE, SSI and ARFI. To demonstrate its usefulness, in this thesis, examples for breast cancer detections were provided. The simulated results can reproduce what has been reported in the literature. To statistically analyze the intrinsic variations of shear wave speed (SWS) in the fibrotic liver tissues, a probability density function (PDF) of the SWS distribution in conjunction with a lossless stochastic tissue model was derived using the principle of Maximum Entropy (ME). The performance of the proposed PDF was evaluated using Monte-Carlo (MC) simulated shear wave data and against three other commonly used PDFs. We theoretically demonstrated that SWS measurements follow a non-Gaussian distribution for the first time. One advantage of the proposed PDF is its physically meaningful parameters. Also, we conducted a case study of the relationship between shear wave measurements and the microstructure of fibrotic liver tissues. Three different virtual tissue models were used to represent underlying microstructures of fibrotic liver tissues. Furthermore, another innovation of this thesis is the inclusion of “biologically-relevant” fibrotic liver tissue models for simulation of shear wave elastography. To link tissue structure, composition and architecture to the ultrasound measurements directly, a “biologically relevant” tissue model was established using Systems Biology. Our initial results demonstrated that the simulated virtual liver tissues qualitatively could reproduce histological results and wave speed measurements. In conclusions, these computational tools and theoretical analysis can improve the confidence on UE image/measurements interpretation

Heterogeneous Material Characterization Using Incomplete and Complete Data with Application to Soft Solids

This dissertation proposes and develops novel features into the existing inverse algorithms for characterizing nonhomogeneous material properties of soft solids. Firstly, a new feature that material properties are defined as a piece-wise constant in each element has been implemented in the inverse program. Secondly, to reduce boundary sensitivity of the solution to the inverse problem in elasticity, we modify the objective function using a spatially weighted displacement correlation term. Compared to the conventional objective function, the new formulation performs well in preserving stiffness contrast between the inclusion and background. Then, we present an approach to estimate the nonhomogeneous elastic property distribution using only boundary displacement datasets. We further improve this approach by using force indentation measurements to quantitatively map the elastic properties and analyze the sensitivity of this approach to a variety of factors, e.g., the location and size of the inclusion. Furthermore, we present a method to quantitatively determine the shear modulus distribution using full-field displacements with partially known material properties on the boundary and without any traction or force information. We test its performance using two different types of regularization: total variation diminishing (TVD) and total contrast diminishing (TCD) regularizations. We observe that TCD regularization is capable of mapping the absolute shear modulus distribution, while TVD regularization fails to achieve this. Furthermore, we investigate the feasibility of using the linear elastic inverse solver to solve inverse problems for nonlinear elasticity for large deformations. We conclude that the linear elastic approximation will overestimate the stiffness contrast between the inclusion and background. We also extend the inverse strategy to map the orthotropic linear elastic parameter distributions. The reconstructions reveal that this method performs well in the presence of low displacement noise levels, while performing poorly with 3% noise. Finally, a feature that maps the viscoelastic behavior of solids using harmonic displacement data has been implemented and tested. In summary, these new features not only strengthen our understanding in solving the inverse problem for inhomogeneous material property characterization, but also provide a potential technique to characterize nonhomogeneous material properties of soft tissues nondestructively that could be useful in clinical practice

Novel Ultrasound Elastography Imaging System for Breast Cancer Assessment

Abstract Most conventional methods of breast cancer screening such as X-ray, Ultrasound (US) and MRI have some issues ranging from weaknesses associated with tumour detection or classification to high cost or excessive time of image acquisition and reconstruction. Elastography is a non- invasive technique to visualize suspicious areas in soft tissues such as the breast, prostate and myocardium using tissue stiffness as image contrast mechanism. In this study, a breast Elastography system based on US imaging is proposed. This technique is fast, expected to be cost effective and more sensitive and specific compared to conventional US imaging. Unlike current Elastography techniques that image relative elastic modulus, this technique is capable of imaging absolute Young\u27s modulus (YM). In this technique, tissue displacements and surface forces used to mechanically stimulate the tissue are acquired and used as input to reconstruct the tissue YM distribution. For displacements acquisition, two techniques were used in this research: 1) a modified optical flow technique, which estimates the displacement of each node from US pre- and post-compression images and 2) Radio Frequency (RF) signal cross-correlation technique. In the former, displacements are calculated in 2 dimensions whereas in the latter, displacements are calculated in the US axial direction only. For improving the quality of elastography images, surface force data was used to calculate the stress distribution throughout the organ of interest by using an analytical model and a statistical numerical model. For force data acquisition, a system was developed in which load cells are used to measure forces on the surface of the breast. These forces are input into the stress distribution models to estimate the tissue stress distribution. By combining the stress field with the strain field calculated from the acquired displacements using Hooke\u27s law, the YM can be reconstructed efficiently. To validate the proposed technique, numerical and tissue mimicking phantom studies were conducted. For the numerical phantom study, a 3D breast-shape phantom was created with synthetic US pre- and post-compression images where the results showed the feasibility of reconstructing the absolute value of YM of tumour and background. In the tissue mimicking study, a block shape gelatine- agar phantom was constructed with a cylindrical inclusion. Results obtained from this study also indicated reasonably accurate reconstruction of the YM. The quality of the obtained elasticity images shows that image quality is improved by incorporating the adapted stress calculation techniques. Furthermore, the proposed elastography system is reasonably fast and can be potentially used in real-time clinical applications

Evaluation of cerebral cortex viscoelastic property estimation with nonlinear inversion magnetic resonance elastography

Objective. Magnetic resonance elastography (MRE) of the brain has shown promise as a sensitive neuroimaging biomarker for neurodegenerative disorders; however, the accuracy of performing MRE of the cerebral cortex warrants investigation due to the unique challenges of studying thinner and more complex geometries. Approach. A series of realistic, whole-brain simulation experiments are performed to examine the accuracy of MRE to measure the viscoelasticity (shear stiffness, μ, and damping ratio, ξ) of cortical structures predominantly effected in aging and neurodegeneration. Variations to MRE spatial resolution and the regularization of a nonlinear inversion (NLI) approach are examined. Main results. Higher-resolution MRE displacement data (1.25 mm isotropic resolution) and NLI with a low soft prior regularization weighting provided minimal measurement error compared to other studied protocols. With the optimized protocol, an average error in μ and ξ was 3% and 11%, respectively, when compared with the known ground truth. Mid-line structures, as opposed to those on the cortical surface, generally display greater error. Varying model boundary conditions and reducing the thickness of the cortex by up to 0.67 mm (which is a realistic portrayal of neurodegenerative pathology) results in no loss in reconstruction accuracy. Significance. These experiments establish quantitative guidelines for the accuracy expected of in vivo MRE of the cortex, with the proposed method providing valid MRE measures for future investigations into cortical viscoelasticity and relationships with health, cognition, and behavior

Ultrasound shear wave imaging for diagnosis of nonalcoholic fatty liver disease

Pour le diagnostic et la stratification de la fibrose hépatique, la rigidité du foie est un biomarqueur quantitatif estimé par des méthodes d'élastographie. L'élastographie par ondes de cisaillement (« shear wave », SW) utilise des ultrasons médicaux non invasifs pour évaluer les propriétés mécaniques du foie sur la base des propriétés de propagation des ondes de cisaillement. La vitesse des ondes de cisaillement (« shear wave speed », SWS) et l'atténuation des ondes de cisaillement (« shear wave attenuation », SWA) peuvent fournir une estimation de la viscoélasticité des tissus. Les tissus biologiques sont intrinsèquement viscoélastiques et un modèle mathématique complexe est généralement nécessaire pour calculer la viscoélasticité en imagerie SW. Le calcul précis de l'atténuation est essentiel, en particulier pour une estimation précise du module de perte et de la viscosité. Des études récentes ont tenté d'augmenter la précision de l'estimation du SWA, mais elles présentent encore certaines limites. Comme premier objectif de cette thèse, une méthode de décalage de fréquence revisitée a été développée pour améliorer les estimations fournies par la méthode originale de décalage en fréquence [Bernard et al 2017]. Dans la nouvelle méthode, l'hypothèse d'un paramètre de forme décrivant les caractéristiques spectrales des ondes de cisaillement, et assumé initialement constant pour tous les emplacements latéraux, a été abandonnée permettant un meilleur ajustement de la fonction gamma du spectre d'amplitude. En second lieu, un algorithme de consensus d'échantillons aléatoires adaptatifs (« adaptive random sample consensus », A-RANSAC) a été mis en œuvre pour estimer la pente du paramètre de taux variable de la distribution gamma afin d’améliorer la précision de la méthode. Pour valider ces changements algorithmiques, la méthode proposée a été comparée à trois méthodes récentes permettant d’estimer également l’atténuation des ondes de cisaillements (méthodes de décalage en fréquence, de décalage en fréquence en deux points et une méthode ayant comme acronyme anglophone AMUSE) à l'aide de données de simulations ou fantômes numériques. Également, des fantômes de gels homogènes in vitro et des données in vivo acquises sur le foie de canards ont été traités. Comme deuxième objectif, cette thèse porte également sur le diagnostic précoce de la stéatose hépatique non alcoolique (NAFLD) qui est nécessaire pour prévenir sa progression et réduire la mortalité globale. À cet effet, la méthode de décalage en fréquence revisitée a été testée sur des foies humains in vivo. La performance diagnostique de la nouvelle méthode a été étudiée sur des foies humains sains et atteints de la maladie du foie gras non alcoolique. Pour minimiser les sources de variabilité, une méthode d'analyse automatisée faisant la moyenne des mesures prises sous plusieurs angles a été mise au point. Les résultats de cette méthode ont été comparés à la fraction de graisse à densité de protons obtenue de l'imagerie par résonance magnétique (« magnetic resonance imaging proton density fat fraction », MRI-PDFF) et à la biopsie du foie. En outre, l’imagerie SWA a été utilisée pour classer la stéatose et des seuils de décision ont été établis pour la dichotomisation des différents grades de stéatose. Finalement, le dernier objectif de la thèse consiste en une étude de reproductibilité de six paramètres basés sur la technologie SW (vitesse, atténuation, dispersion, module de Young, viscosité et module de cisaillement). Cette étude a été réalisée chez des volontaires sains et des patients atteints de NAFLD à partir de données acquises lors de deux visites distinctes. En conclusion, une méthode robuste de calcul du SWA du foie a été développée et validée pour fournir une méthode de diagnostic de la NAFLD.For diagnosis and staging of liver fibrosis, liver stiffness is a quantitative biomarker estimated by elastography methods. Ultrasound shear wave (SW) elastography utilizes noninvasive medical ultrasound to assess the mechanical properties of the liver based on the monitoring of the SW propagation. SW speed (SWS) and SW attenuation (SWA) can provide an estimation of tissue viscoelasticity. Biological tissues are inherently viscoelastic in nature and a complex mathematical model is usually required to compute viscoelasticity in SW imaging. Accurate computation of attenuation is critical, especially for accurate loss modulus and viscosity estimation. Recent studies have made attempts to increase the precision of SWA estimation, but they still face some limitations. As a first objective of this thesis, a revisited frequency-shift method was developed to improve the estimates provided by the original implementation of the frequency-shift method [Bernard et al 2017]. In the new method, the assumption of a constant shape parameter of the gamma function describing the SW magnitude spectrum has been dropped for all lateral locations, allowing a better gamma fitting. Secondly, an adaptive random sample consensus algorithm (A-RANSAC) was implemented to estimate the slope of the varying rate parameter of the gamma distribution to improve the accuracy of the method. For the validation of these algorithmic changes, the proposed method was compared with three recent methods proposed to estimate SWA (frequency-shift, two-point frequency-shift and AMUSE methods) using simulation data or numerical phantoms. In addition, in vitro homogenous gel phantoms and in vivo animal (duck) liver data were processed. As a second objective, this thesis also aimed at improving the early diagnosis of nonalcoholic fatty liver disease (NAFLD), which is necessary to prevent its progression and decrease the overall mortality. For this purpose, the revisited frequency-shift method was tested on in vivo human livers. The new method's diagnosis performance was investigated with healthy and NAFLD human livers. To minimize sources of variability, an automated analysis method averaging measurements from several angles has been developed. The results of this method were compared to the magnetic resonance imaging proton density fat fraction (MRI-PDFF) and to liver biopsy. SWA imaging was used for grading steatosis and cut-off decision thresholds were established for dichotomization of different steatosis grades. As a third objective, this thesis is proposing a reproducibility study of six SW-based parameters (speed, attenuation, dispersion, Young’s modulus, viscosity and shear modulus). The assessment was performed in healthy volunteers and NAFLD patients using data acquired at two separate visits. In conclusion, a robust method for computing the liver’s SWA was developed and validated to provide a diagnostic method for NAFLD

Novel applications, model, and methods in magnetic resonance elastography

Magnetic Resonance Elastography (MRE) is a non-invasive imaging technique that maps and quantifies the mechanical properties of soft tissue related to the propagation and attenuation of shear waves. There is considerable interest in whether MRE can bring new insight into pathologies. Brain in particular has been of utmost interest in the recent years. Brain tumors, Alzheimer's disease, and Multiple Sclerosis have all been subjects of MRE studies. This thesis addresses four aspects of MRE, ranging from novel applications in brain MRE, to physiological interpretation of measured mechanical properties, to improvements in MRE technology. First, we present longitudinal measurements of the mechanical properties of glioblastoma tumorigenesis and progression in a mouse model. Second, we present a new finding from our group regarding a localized change in mechanical properties of neural tissue when functionally stimulated. Third, we address contradictory results in the literature regarding the effects of vascular pressure on shear wave speed in soft tissues. To reconcile these observations, a mathematical model based on poro-hyperelasticity is used. Finally, we consider a part of MRE that requires inferring mechanical properties from MR measurements of vibration patterns in tissue. We present improvements to MRE reconstruction methods by developing and using an advanced variational formulation of the forward problem for shear wave propagation