Model parameter estimation of atherosclerotic plaque mechanical properties : calculus-based and heuristic algorithms

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.Includes bibliographical references (p. 123-133).A sufficient understanding of the pathology that leads to cardiovascular disease is currently deficient. Atherosclerosis is a complex disease that is believed to be initiated and promoted by linked biochemical and biomechanical pathways. This thesis focuses on studying plaque biomechanics because (i) there is a dearth of data on the mechanical behavior of soft arterial tissue yet (ii) it is the biomechanics that is able to provide invaluable insight into patient-specific disease evolution and plaque vulnerability. Arterial elasticity reconstruction is a venture that combines imaging, elastography, and computational modeling in an effort to build maps of an artery's material properties, ultimately to identify plaques exhibiting stress concentrations and to pinpoint rupture-prone locales. The inverse elasticity problem was explored extensively and two solution methods are demonstrated. The first is a version of the traditional linear perturbation Gauss-Newton method, which contingent on an appropriate regularization scheme, was able to reconstruct both homogeneous and inhomogeneous distributions including hard and spatially continuous inclusions. The second was an attempt to tackle the inherent and problem-specific limitations associated with such gradient-based searches. With a model reduction of the discrete elasticity parameters into lumped values, such as the plaque components, more robust and adaptive strategies become feasible. A novel combined finite element modeling-genetic algorithm system was implemented that is easily implemented, manages multiple regions of far-reaching modulus, is globally convergent, shows immunity to ill-conditioning, and is expandable to more complex material models(cont.) and geometries. The implementation of both provides flexibility in the endeavor of arterial elasticity reconstruction as well as potential complementary and joint efforts.by Ahmad S. Khalil.S.M

Continuous Versus Discontinuous Elastic Modulus Distribution in Inverse Problems Based on Finite Element Methods

Elasticity imaging, which is also known as Elastography, aims to determine the elastic property distribution of non-homogeneous deformable solids such as soft tissues. This can be done non-destructively using displacement fields measured with medical imaging modalities, such as ultrasound or magnetic resonance imaging. Elasticity imaging can potentially be used to detect tumors based on the stiffness contrast between different materials. This requires the solution of an inverse problem in elasticity. This field has been growing very fast in the past decade. One of the most useful applications of elasticity imaging may be in breast cancer diagnosis, where the tumor could potentially be detected and visualized by its stiffness contrast from its surrounding tissues. In this work the inverse problem will be solved for the shear modulus which is directly related to the Young’s modulus through the Poisson’s ratio. The inverse problem is posed as a constrained optimization problem, where the difference between a computed (predicted) and measured displacement field is minimized. The computed displacement field satisfies the equations of equilibrium. The material is modeled as an isotropic and incompressible material. The present work focuses on assessing the solution of the inverse problem for problem domains defined with a continuous and discontinuous shear modulus distribution. In particular, two problem domains will be considered: 1) a stiff inclusion in a homogeneous background representing a stiff tumor surrounded by soft tissues, 2) a layered ring model representing an arterial wall cross-section. The hypothetical "measured" displacement field for these problem domains will be created by solving the finite element forward problem. Additionally, noise will be added to the displacement field to simulate noisy measured displacement data. According to the results of my thesis work, the potential of the elasticity imaging in the medical field is emerging. The inclusion in problem domain 1, representing a stiffer tumor in a uniform background, can be found and located in the shear modulus reconstructions. Thus, these reconstructed images can potentially be used to detect tumors in the medical field

Caractérisation des propriétés élastiques de la paroi artérielle par ultrasonographie endovasculaire

RÉSUMÉ Dans le cadre de ce projet, on présente une nouvelle technique d'imagerie ultrasonore de l'élasticité du tissu artériel: l'élastographie endovasculaire (EEV). Le changement de la rigidité du tissu artériel est souvent un indice d'état pathologique. Il en est ainsi de l'athérosclérose qui est une pathologie au cours de laquelle la paroi artérielle s'épaissit et perd graduellement son élasticité. Cette pathologie se caractérise par la formation de plaques d'athéromes constituées de dépôts de nature variée (lipidiques, fibreux ou calcifiés) qui induisent des changements localisés des propriétés élastiques du tissu artériel et un rétrécissement de la lumière artérielle. L'objectif de ce projet de recherche est de développer un outil capable de caractériser et de quantifier les propriétés élastiques de la paroi artérielle afin de permettre le diagnostic de pathologies artérielles comme l'athérosclérose. Il existe diverses techniques d'exploration vasculaire. L'ultrasonographie intravasculaire (USIV), par exemple, fournit une visualisation tomographique de la paroi artérielle qui permet l'étude de son comportement. Les estimations de déplacement et de déformation, issues de l'USIV, sont utilisées pour la caractérisation des propriétés élastiques de la paroi artérielle. Dans l'élastographie endovasculaire (EEV), les mesures de déplacements internes issus de l'USIV sont utilisées pour obtenir l'information relative aux propriétés élastiques de la paroi artérielle. L'EEV permettrait une visualisation précise de l'étendue de la pathologie et du niveau de son infiltration dans la paroi. De plus, certaines plaques sont plus instables que d'autres et, grâce à l'EEV, il serait possible de prédire les sites qui sont propices à la rupture. Ces sites correspondraient aux points de concentration de contraintes. Généralement, c'est à ces endroits que les plaques se disloquent et conduisent à la formation de thromboses qui provoquent le plus souvent l'arrêt de la circulation sanguine. L'EEV, par sa capacité de différencier les types de plaques et de caractériser leur rigidité, pourrait servir à raffiner le diagnostic ainsi que les interventions thérapeutiques. En utilisant le modèle théorique de l'EEV, il serait possible de prédire la réponse du tissu à une intervention comme l'angioplastie. Ceci permettrait d'anticiper toute complication, comme la déchirure intimale, et ainsi de choisir une autre modalité d'intervention plus appropriée. Nous verrons, au chapitre 3, la formulation du problème direct (PD) en EEV. La résolution du PD est basée sur l'utilisation d'un modèle théorique qui décrit l'équilibre mécanique du tissu artériel suite à l'application d'un faible échelon de pression intraluminale. La pression intraluminale est appliquée au moyen d'un dispositif composé d'un ballonnet et d'un transducteur ultrasonore. Ce dispositif, en plus de fournir les images échographiques de l'opération de compression, stabilise le système d'imagerie, offrant ainsi des conditions quasi statiques. Le tissu artériel est modélisé comme un milieu élastique, linéaire, isotopique et quasi incompressible (v = 0.497). Dans ces conditions, seul le module de Young est requis pour une caractérisation complète du comportement du tissu artériel. D'autre part, puisque seules les composantes du déplacement qui sont dans le plan de propagation des ultrasons sont mesurables, le modèle est considéré comme en état plan de déformation. Cette hypothèse ne représente pas une limitation excessive, puisque l'artère est dans un état d'étirement longitudinal qui minimise sa déformation dans cette orientation. L'image de la distribution de déformation interne, dérivée du champ de déplacement induit par la compression du tissu artériel, est appelée «élastogramme endovasculaire». Sous l'hypothèse de l'uniformité du champ de contrainte issu de cette compression, la distribution de déformation est interprétée comme la distribution du module d'élasticité du tissu artériel. Le champ de contrainte est fonction des conditions aux frontières et de la distribution d'élasticité. Puisque cette distribution d'élasticité n'est pas uniforme, la distribution de contrainte ne l'est pas non plus. Cette inhomogénéité du champ de contrainte se traduit par une manifestation artefactuelle. Cette manifestation est directement liée à la complexité structurale des plaques, et la structure des plaques influence considérablement le patron de déformation. Comme les mesures de déplacement sont estimées à partir des sonogrammes intravasculaires, un modèle de formation d'images échographiques endovasculaires est proposé pour permettre une éventuelle étude qui se penchera sur les artefacts reliés à ce type d'imagerie échographique de révolution. Dans le but de réduire l'effet des artefacts et d'obtenir une représentation quantitative de la vraie distribution d'élasticité et, donc, de pouvoir déterminer la distribution de contraintes, on considère l'EEV dans le cadre de résolution d'un problème inverse (PI). La solution du PI est celle qui minimise l'erreur quadratique, au sens des moindres carrés, entre le champ de déplacement axial mesuré et celui prédit. Le champ de déplacement prédit est calculé, en utilisant la méthode des éléments finis, à partir des équations d'élasticité pour une distribution d'élasticité et des conditions aux frontières données. La résolution du PI en EEV est étudiée au chapitre 4. Dans un premier temps, les composantes axiale et latérale du champ de déplacement sont utilisées pour la reconstruction de la distribution d'élasticité. Utilisant la méthode de Gauss-Newton dans des conditions idéales, la distribution d'élasticité injectée est récupérée exempte de toute manifestation artefactuelle, comme celle vue dans l'image de déformation. Dans un deuxième temps, seule la composante axiale est utilisée, puisque la variance dans l'estimation de la composante latérale du champ de déplacement est plus grande que celle de la composante axiale. Pour stabiliser la solution du PI et accéder à une solution unique, la méthode de Levenberg-Marquardt est utilisée. Le problème étant mal posé, une étape essentielle pour la convergence vers la solution est celle de la détermination du paramètre d'amortissement (régularisation) optimal qui sert à adoucir les rebondissements de la solution. Pour le choix de ce facteur d'amortissement, une méthode utilisant la décomposition en valeurs singulières est utilisée. La résolution du PI nous permet de récupérer la distribution d'élasticité même dans le cas où une composante de bruit est ajoutée à l'information de déplacement. Toutefois, lorsque le rapport signal sur bruit est supérieur à 30 dB, la reconstruction est acceptable. En dessous de ce seuil, les artefacts prédominent.--------------------ABSTRACT This thesis deals with the endovascular elastography (EVE) which is a new ultrasonic imaging technique to characterize the elastic properties of the arterial wall tissue. These arterial wall elastic properties are derived from ultrasonically estimated displacements induced by an intraluminal pressure push. The pathological state of arterial tissue is generally correlated with a local change in its mechanical perperties. The objective of this research is to develop a method able to characterize and quantify the arterial elastic properties, allowing the diagnosis of arterial pathologies. Atherosclerosis is this arterial pathology characterized by arterial wall thickening and loss of elasticity. It begins with the accumulation of atheroma (plaque) leading to the narrowing of the arterial lumen. These plaques are often structurally complex, with varying amounts of lipid, fibrous tissue, and calcium deposits. These changes lead to a localized modification of the elastic distribution of the arterial wall tissue. Intravascular ultrasound (IVUS) is this catheter based modality with the ability to provide a tomographic image of the vascular allowing the study of its behavior. The IVUS estimate of the displacement filed is used to characterize the elastic properties of the arterial wall. EVE would allow an accurate visualization of the spread out of the pathology and the depth of its infiltration into the arterial wall. Also, since some plaques are more unstable than others, it would be possible to predict the locations of plaque rupture through the points of stress concentration. Generally, if failure is expected to occur it will be at these points of stress concentration. EVE, by its capacity to distinguish between plaque types and characterize their hardness, would refine the diagnosis and the remedial interventions. It would be possible, with the theoretical model of EVE, to predict the response of the tissue to a procedure such as angioplasty. This would allow to predict any complication, as intimale tearing, assisting in the choice of an other more appropriate modality. In chapter 3, we will see the formulation of the forward problem (FP) in EVE. Its resolution is based on a theoretical model that describes the mechanical balance of the arterial tissue when excited by a small step of intraluminal pressure. This intraluminal pressure is induced by a combined angioplasty balloon and an ultrasound catheter system. In addition to image the inflation procedure, the combined system stabilizes the artery and the imaging system, and the applied pressure imposes a quasi-static condition. As a first approximation, the arterial wall tissue, including plaques, is modeled as isotropic, incompressible and linearly elastic material. In these circumstances, only Young's modulus is needed to fully characterize the behavior of the arterial tissue. Furthermore, since only the component of the displacement in the acoustical scanning plane is assessable, the model is considered in a plane strain state. This assumption does not represent an extreme restriction, considering the artery is in a state of longitudinal stretching that minimizes its deformation in this direction. The strain image, derived from the displacement field obtained after compressing the arterial tissue, is called the endovascular elastogram. With the assumption of constant stress field at the inner wall boundary, the strain field is considered as a relative measure of the elasticity distribution of the arterial wall. The stress distribution is dependent on the boundary conditions and the elasticity distribution. The non-uniformity of the elasticity distribution implies the non-uniformity of the stress distribution. This inhomogeneity of the stress field conveys to an artifactual exhibition. This artifactual exhibition is directly associated with the structural complexity of plaques. The composition of plaques affects greatly the deformation pattern. While the displacement measures are estimated from intravascular sonograms, an echographic endovascular image formation model is proposed to study the artifact surrounding this kind of imaging system. To reduce the consequence of these artifacts and to obtain a quantitative representation of the elasticity distribution, we consider the EVE in the framework of an inverse problem (IP) solution. The solution of the IP is the one that minimizes the least squares error between the observed and predicted displacement field. The predicted displacement field is computed using the finite element method, to numerically solve the elasticity equations, for a given set of elasticity distribution and boundary conditions. The IP is first solved using both the axial and lateral component of the displacement field. Using the Gauss-Newton method, in an ideal condition, the reconstruction of the elasticity distribution was successful. This elasticity distribution was clear of any artifactual presence as in the strain image. Subsequently, since in practice only the component of the displacement in the acoustical scanning plane can be measured, we use only the axial component of the displacement field to solve the IP. To solve the IP and single out a stable solution, Levenberg-Marquardt method is used. The IP being ill-posed, a fundamental step to get the solution is to regularize the problem and to estimate the optimal damping factor used to damp the solution oscillations. This damping factor is obtained using the singular value decomposition. In this IP solving, we were able to retrieve an acceptable solution even in the case where we add a noise in the displacement data. When the signal to noise ratio (SNR) is greater than 30 dB the solution is admissible. Beyond this threshold the artifacts dominate.-----------CONTENU Physiologie vasculaire -- Athérosclérose et thrombose -- Traitement de l'athérosclérose -- Modalités d'imagerie vasculaire -- Étude de l'élasticité artérielle -- USIV dans la caractérisation du tissu vasculaire -- Estimation du mouvement -- Elastographie endovasculaire -- Endovascular elastography : the forward problem -- The forward problem formulation -- Polar image formation model -- Endovascular elastography : the inverse problem -- The Inverse problem in endovascular elastography

Elastography of soft materials and tissues by holographic imaging of surface acoustic waves

We use optical interferometry to capture coherent surface acoustic waves for elastographic imaging. An inverse method is employed to convert multi-frequency data into an elastic depth profile. Using this methodwe image elastic properties over a 55 mm range with <5 mm resolution. For relevance to breast cancer detectionwe employ a tissue phantom with a tumor-like inclusion. Holographic elastography is also shown to be well-behaved in ex vivo tissuerevealing the subsurface position of a bone. Because digital holography can assess waves over a wide surface areathis constitutes a flexible new platform for large volume and non-invasive elastography

Biomechanical Modeling and Inverse Problem Based Elasticity Imaging for Prostate Cancer Diagnosis

Early detection of prostate cancer plays an important role in successful prostate cancer treatment. This requires screening the prostate periodically after the age of 50. If screening tests lead to prostate cancer suspicion, prostate needle biopsy is administered which is still considered as the clinical gold standard for prostate cancer diagnosis. Given that needle biopsy is invasive and is associated with issues including discomfort and infection, it is desirable to develop a prostate cancer diagnosis system that has high sensitivity and specificity for early detection with a potential to improve needle biopsy outcome. Given the complexity and variability of prostate cancer pathologies, many research groups have been pursuing multi-parametric imaging approach as no single modality imaging technique has proven to be adequate. While imaging additional tissue properties increases the chance of reliable prostate cancer detection and diagnosis, selecting an additional property needs to be done carefully by considering clinical acceptability and cost. Clinical acceptability entails ease with respect to both operating by the radiologist and patient comfort. In this work, effective tissue biomechanics based diagnostic techniques are proposed for prostate cancer assessment with the aim of early detection and minimizing the numbers of prostate biopsies. The techniques take advantage of the low cost, widely available and well established TRUS imaging method. The proposed techniques include novel elastography methods which were formulated based on an inverse finite element frame work. Conventional finite element analysis is known to have high computational complexity, hence computation time demanding. This renders the proposed elastography methods not suitable for real-time applications. To address this issue, an accelerated finite element method was proposed which proved to be suitable for prostate elasticity reconstruction. In this method, accurate finite element analysis of a large number of prostates undergoing TRUS probe loadings was performed. Geometry input and displacement and stress fields output obtained from the analysis were used to train a neural network mapping function to be used for elastopgraphy imaging of prostate cancer patients. The last part of the research presented in this thesis tackles an issue with the current 3D TRUS prostate needle biopsy. Current 3D TRUS prostate needle biopsy systems require registering preoperative 3D TRUS to intra-operative 2D TRUS images. Such image registration is time-consuming while its real-time implementation is yet to be developed. To bypass this registration step, concept of a robotic system was proposed which can reliably determine the preoperative TRUS probe position relative to the prostate to place at the same position relative to the prostate intra-operatively. For this purpose, a contact pressure feedback system is proposed to ensure similar prostate deformation during 3D and 2D image acquisition in order to bypass the registration step

Inverse-Consistent Determination of Young\u27s Modulus of Human Lung

Human lung undergoes respiration-induced deformation due to sequential inhalation and exhalation. Accurate determination of lung deformation is crucial for tumor localization and targeted radiotherapy in patients with lung cancer. Numerical modeling of human lung dynamics based on underlying physics and physiology enables simulation and virtual visualization of lung deformation. Dynamical modeling is numerically complicated by the lack of information on lung elastic behavior, structural heterogeneity as well as boundary constrains. This study integrates physics-based modeling and image-based data acquisition to develop the patient-specific biomechanical model and consequently establish the first consistent Young\u27s modulus (YM) of human lung. This dissertation has four major components: (i) develop biomechanical model for computation of the flow and deformation characteristics that can utilize subject-specific, spatially-dependent lung material property; (ii) develop a fusion algorithm to integrate deformation results from a deformable image registration (DIR) and physics-based modeling using the theory of Tikhonov regularization; (iii) utilize fusion algorithm to establish unique and consistent patient specific Young\u27s modulus and; (iv) validate biomechanical model utilizing established patient-specific elastic property with imaging data. The simulation is performed on three dimensional lung geometry reconstructed from four-dimensional computed tomography (4DCT) dataset of human subjects. The heterogeneous Young\u27s modulus is estimated from a linear elastic deformation model with the same lung geometry and 4D lung DIR. The biomechanical model adequately predicts the spatio-temporal lung deformation, consistent with data obtained from imaging. The accuracy of the numerical solution is enhanced through fusion with the imaging data beyond the classical comparison of the two sets of data. Finally, the fused displacement results are used to establish unique and consistent patient-specific elastic property of the lung

Towards the in vivo mechanical characterization of abdominal wall in animal model: application to hernia repair

El trabajo presentado en esta tesis se centra en el diseño e implementación de una metodología que permita caracterizar in vivo el comportamiento mecánico pasivo de la pared abdominal. Esta metodología permitiría a los cirujanos disponer de información mecánica relevante sobre un paciente especí co, lo que podría contribuir a mejorar el tratamiento quirúrgico de hernias mediante malla protésica. El tratamiento quirúrgico de hernias consiste en cerrar la debilidad creada en el músculo, ya sea directamente con puntos de sutura o mediante la implantación de una malla protésica. En el caso de la malla, ésta es la responsable de absorber las tensiones a las que el músculo se ve sometido durante el tiempo en el que se produce la regeneración de tejido. Para reducir el riego de aparición de dolor postoperatorio, rotura o rasgadura de tejido o incluso una recidiva, la malla debe mimetizar la respuesta mecánica de la zona de la pared donde vaya a ser colocada, que a su vez puede variar de un paciente a otro en función de su edad, género, índice de masa corporal u otras características físicas. Un mejor conocimiento de las propiedades mecánicas del abdomen en paciente especí co ayudaría al cirujano a determinar qué malla protésica se puede considerar la ideal, mecánicamente hablando. Por todo ello, el trabajo que aquí se presenta plantea una aproximación in vivo para caracterizar la pared abdominal sobre un modelo animal y su posterior implementación en casos de patologías herniarias. En un primer paso, se ha realizado un estudio biomecánico del cierre en línea alba, que ayudase a entender los aspectos mecánicos y biológicos que tienen lugar durante la curación de la herida a corto y largo plazo. A continuación, se han llevado a cabo ensayos mecánicos de in ado sobre la pared, que combinados con el uso de cámaras y técnicas de adquisición de imagen han permitido extraer la respuesta del tejido de una manera no invasiva. Este estudio experimental, se ha llevado a cabo sobre especímenes sanos y otro herniados y reparados con distintas mallas quirúrgicas, lo que ha permitido extrapolar el efecto in vivo que provocan estas mallas. A partir de los datos experimentales también se ha desarrollado un análisis numérico que permitiese caracterizar la respuesta mecánica especí ca de cada espécimen. A este efecto, dicha caracterización se ha tratado como un problema inverso y resuelto primeramente mediante un análisis de super cies de respuesta y después con un algoritmo propio aplicado a modelos hiperelásticos. Finalmente, también se ha reconstruido un modelo de elementos nitos de la cavidad abdominal que permite simular el efecto producido por distintas mallas protésicas así como su alteración respecto al tejido sano

Évaluation de la biomécanique cardiovasculaire par élastographie ultrasonore non-invasive

L’élastographie est une technique d’imagerie qui vise à cartographier in vivo les propriétés mécaniques des tissus biologiques dans le but de fournir des informations diagnostiques additionnelles. Depuis son introduction en imagerie ultrasonore dans les années 1990, l’élastographie a trouvé de nombreuses applications. Cette modalité a notamment été utilisée pour l’étude du sein, du foie, de la prostate et des artères par imagerie ultrasonore, par résonance magnétique ou en tomographie par cohérence optique. Dans le contexte des maladies cardiovasculaires, cette modalité a un fort potentiel diagnostique puisque l’athérosclérose modifie la structure des tissus biologiques et leurs propriétés mécaniques bien avant l’apparition de tout symptôme. Quelle que soit la modalité d’imagerie utilisée, l’élastographie repose sur : l’excitation mécanique du tissu (statique ou dynamique), la mesure de déplacements et de déformations induites, et l’inversion qui permet de recouvrir les propriétés mécaniques des tissus sous-jacents. Cette thèse présente un ensemble de travaux d’élastographie dédiés à l’évaluation des tissus de l’appareil cardiovasculaire. Elle est scindée en deux parties. La première partie intitulée « Élastographie vasculaire » s’intéresse aux pathologies affectant les artères périphériques. La seconde, intitulée « Élastographie cardiaque », s’adresse aux pathologies du muscle cardiaque. Dans le contexte vasculaire, l’athérosclérose modifie la physiologie de la paroi artérielle et, de ce fait, ses propriétés biomécaniques. La première partie de cette thèse a pour objectif principal le développement d’un outil de segmentation et de caractérisation mécanique des composantes tissulaires (coeur lipidique, tissus fibreux et inclusions calciques) de la paroi artérielle, en imagerie ultrasonore non invasive, afin de prédire la vulnérabilité des plaques. Dans une première étude (Chapitre 5), nous présentons un nouvel estimateur de déformations, associé à de l’imagerie ultrarapide par ondes planes. Cette nouvelle méthode d’imagerie permet d’augmenter les performances de l’élastographie non invasive. Dans la continuité de cette étude, on propose une nouvelle méthode d’inversion mécanique dédiée à l’identification et à la quantification des propriétés mécaniques des tissus de la paroi (Chapitre 6). Ces deux méthodes sont validées in silico et in vitro sur des fantômes d’artères en polymère. Dans le contexte cardiaque, les ischémies et les infarctus causés par l’athérosclérose altèrent la contractilité du myocarde et, de ce fait, sa capacité à pomper le sang dans le corps (fonction myocardique). En échocardiographie conventionnelle, on évalue généralement la fonction myocardique en analysant la dynamique des mouvements ventriculaires (vitesses et déformations du myocarde). L’abscence de contraintes physiologiques agissant sur le myocarde (contrairement à la pression sanguine qui contraint la paroi vasculaire) ne permet pas de résoudre le problème inverse et de retrouver les propriétés mécaniques du tissu. Le terme d’élastographie fait donc ici référence à l’évaluation de la dynamique des mouvements et des déformations et non à l’évaluation des propriétés mécanique du tissu. La seconde partie de cette thèse a pour principal objectif le développement de nouveaux outils d’imagerie ultrarapide permettant une meilleure évaluation de la dynamique du myocarde. Dans une première étude (Chapitre 7), nous proposons une nouvelle approche d’échocardiographie ultrarapide et de haute résolution, par ondes divergentes, couplée à de l'imagerie Doppler tissulaire. Cette combinaison, validée in vitro et in vivo, permet d’optimiser le contraste des images mode B ainsi que l’estimation des vitesses Doppler tissulaires. Dans la continuité de cette première étude, nous proposons une nouvelle méthode d’imagerie des vecteurs de vitesses tissulaires (Chapitre 8). Cette approche, validée in vitro et in vivo, associe les informations de vitesses Doppler tissulaires et le mode B ultrarapide de l’étude précédente pour estimer l’ensemble du champ des vitesses 2D à l’intérieur du myocarde.Elastography is an imaging technique that aims to map the in vivo mechanical properties of biological tissues in order to provide additional diagnostic information. Since its introduction in ultrasound imaging in the 1990s, elastography has found many applications. This method has been used for the study of the breast, liver, prostate and arteries by ultrasound imaging, magnetic resonance imaging (MRI) or optical coherence tomography (OCT). In the context of cardiovascular diseases (CVD), this modality has a high diagnostic potential as atherosclerosis, a common pathology causing cardiovascular diseases, changes the structure of biological tissues and their mechanical properties well before any symptoms appear. Whatever the imaging modality, elastography is based on: the mechanical excitation of the tissue (static or dynamic), the measurement of induced displacements and strains, and the inverse problem allowing the quantification of the mechanical properties of underlying tissues. This thesis presents a series of works in elastography for the evaluation of cardiovascular tissues. It is divided into two parts. The first part, entitled « Vascular elastography » focuses on diseases affecting peripheral arteries. The second, entitled « Cardiac elastography » targets heart muscle pathologies. In the vascular context, atherosclerosis changes the physiology of the arterial wall and thereby its biomechanical properties. The main objective of the first part of this thesis is to develop a tool that enables the segmentation and the mechanical characterization of tissues (necrotic core, fibrous tissues and calcium inclusions) in the vascular wall of the peripheral arteries, to predict the vulnerability of plaques. In a first study (Chapter 5), we propose a new strain estimator, associated with ultrafast plane wave imaging. This new imaging technique can increase the performance of the noninvasive elastography. Building on this first study, we propose a new inverse problem method dedicated to the identification and quantification of the mechanical properties of the vascular wall tissues (Chapter 6). These two methods are validated in silico and in vitro on polymer phantom mimicking arteries. In the cardiac context, myocardial infarctions and ischemia caused by atherosclerosis alter myocardial contractility. In conventional echocardiography, the myocardial function is generally evaluated by analyzing the dynamics of ventricular motions (myocardial velocities and deformations). The abscence of physiological stress acting on the myocardium (as opposed to the blood pressure which acts the vascular wall) do not allow the solving the inverse problem and to find the mechanical properties of the fabric. Elastography thus here refers to the assessment of motion dynamics and deformations and not to the evaluation of mechanical properties of the tissue. The main objective of the second part of this thesis is to develop new ultrafast imaging tools for a better evaluation of the myocardial dynamics. In a first study (Chapter 7), we propose a new approach for ultrafast and high-resolution echocardiography using diverging waves and tissue Doppler. This combination, validated in vitro and in vivo, optimize the contrast in B-mode images and the estimation of myocardial velocities with tissue Doppler. Building on this study, we propose a new velocity vector imaging method (Chapter 8). This approach combines tissue Doppler and ultrafast B-mode of the previous study to estimate 2D velocity fields within the myocardium. This original method was validated in vitro and in vivo on six healthy volunteers

Full Waveform Inversion Guided Wave Tomography Based on Recurrent Neural Network

Corrosion quantitative detection of plate or plate-like structures is a critical and challenging topic in industrial Non-Destructive Testing (NDT) research which determines the remaining life of material. Compared with other methods (X-ray, magnetic powder, eddy current), ultrasonic guided wave tomography has the advantages of non-invasiveness, high efficiency, high precision and low cost. Among various ultrasonic guided wave tomography algorithms, travel time or diffraction algorithms can be used to reconstruct defect or corrosion model, but the accuracy is low and heavily influenced by the noise. Full Waveform Inversion (FWI) can build accurate reconstructions of physical properties in plate structures, however, it requires a relatively accurate initial model, and there is still room for improvement in the convergence speed, imaging resolution and robustness. This thesis starting with the physical principle of ultrasonic guided waves, the dispersion characteristic curve of the guided wave propagating in the plate structure converts the change of the remaining thickness of the plate structure material into the wave velocity variation when the ultrasonic guided wave propagates in it, and provides a physical principle for obtaining the thickness distribution map from the velocity reconstruction. Secondly, a guided wave tomography method based on Recurrent Neural Network Full Waveform Inversion (RNN-FWI) is proposed. Finally, the efficiency of the above method is verified through practical experiments. The main work of the thesis includes: The feasibility of conventional full waveform inversion for guided wave tomography is introduced and verified. An FWI algorithm based on RNN is proposed. In the framework of RNN-FWI, the effects of different optimization algorithms on imaging performance and the effects of different sensor numbers and positions on imaging performance are analyzed. The quadratic Wasserstein distance is used as the objective equation to further reduce the dependence on the initial model. The depth image prior (DIP) based on convolutional neural network (CNN) is used as the regularization method to further improve the conventional FWI algorithm, and the effectiveness of the improved algorithm is verified by simulation and actual experiments