Robust Cardiac Motion Estimation using Ultrafast Ultrasound Data: A Low-Rank-Topology-Preserving Approach

Cardiac motion estimation is an important diagnostic tool to detect heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of the complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate the cardiac motion using ultrafast ultrasound data. -- Our solution is based on a variational formulation characterized by the L2-regularized class. The displacement is represented by a lattice of b-splines and we ensure robustness by applying a maximum likelihood type estimator. While this is an important part of our solution, the main highlight of this paper is to combine a low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati Matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. While maintaining the accuracy of the solution, the low-rank preprocessing is shown to speed up the convergence of the variational problem. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that experience motion.Comment: 15 pages, 10 figures, Physics in Medicine and Biology, 201

Ultrafast Ultrasound Imaging

Among medical imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), ultrasound imaging stands out due to its temporal resolution. Owing to the nature of medical ultrasound imaging, it has been used for not only observation of the morphology of living organs but also functional imaging, such as blood flow imaging and evaluation of the cardiac function. Ultrafast ultrasound imaging, which has recently become widely available, significantly increases the opportunities for medical functional imaging. Ultrafast ultrasound imaging typically enables imaging frame-rates of up to ten thousand frames per second (fps). Due to the extremely high temporal resolution, this enables visualization of rapid dynamic responses of biological tissues, which cannot be observed and analyzed by conventional ultrasound imaging. This Special Issue includes various studies of improvements to the performance of ultrafast ultrasoun

A biomechanical analysis of shear wave elastography in pediatric heart models

Early detection of cardiac disease in children is essential to optimize treatment and follow-up, but also to reduce its associated mortality and morbidity. Various cardiac imaging modalities are available for the cardiologist, mainly providing information on tissue morphology and structure with high temporal and/or spatial resolution. However, none of these imaging methods is able to directly measure stresses or intrinsic mechanical properties of the heart, which are potential key diagnostic markers to distinguish between normal and abnormal physiology. This thesis investigates the potential of a relatively new ultrasound-based technique, called shear wave elastography (SWE), to non-invasively measure myocardial stiffness. The technique generates an internal perturbation inside the tissue of interest, and consequently measures the propagation of the acoustically excited shear wave, of which the propagation speed is directly related to tissue stiffness. This allows SWE to identify regions with higher stiffness, which is associated with pathology. SWE has shown to be successful in detecting tumors in breast tissue and fibrosis in liver tissue, however application of SWE to the heart is more challenging due to the complex mechanical and structural properties of the heart. This thesis provides insights into the acoustically excited shear wave physics in the myocardium by using computer simulations in combination with experiments. Furthermore, these models also allow to assess the performance of currently used SWE-based material characterization algorithms

Estimating and understanding motion : from diagnostic to robotic surgery

Estimating and understanding motion from an image sequence is a central topic in computer vision. The high interest in this topic is because we are living in a world where many events that occur in the environment are dynamic. This makes motion estimation and understanding a natural component and a key factor in a widespread of applications including object recognition , 3D shape reconstruction, autonomous navigation and medica! diagnosis. Particularly, we focus on the medical domain in which understanding the human body for clinical purposes requires retrieving the organs' complex motion patterns, which is in general a hard problem when using only image data. In this thesis, we cope with this problem by posing the question - How to achieve a realistic motion estimation to offer a better clinical understanding? We focus this thesis on answering this question by using a variational formulation as a basis to understand one of the most complex motions in the human's body, the heart motion, through three different applications: (i) cardiac motion estimation for diagnostic, (ii) force estimation and (iii) motion prediction, both for robotic surgery. Firstly, we focus on a central topic in cardiac imaging that is the estimation of the cardiac motion. The main aim is to offer objective and understandable measures to physicians for helping them in the diagnostic of cardiovascular diseases. We employ ultrafast ultrasound data and tools for imaging motion drawn from diverse areas such as low-rank analysis and variational deformation to perform a realistic cardiac motion estimation. The significance is that by taking low-rank data with carefully chosen penalization, synergies in this complex variational problem can be created. We demonstrate how our proposed solution deals with complex deformations through careful numerical experiments using realistic and simulated data. We then move from diagnostic to robotic surgeries where surgeons perform delicate procedures remotely through robotic manipulators without directly interacting with the patients. As a result, they lack force feedback, which is an important primary sense for increasing surgeon-patient transparency and avoiding injuries and high mental workload. To solve this problem, we follow the conservation principies of continuum mechanics in which it is clear that the change in shape of an elastic object is directly proportional to the force applied. Thus, we create a variational framework to acquire the deformation that the tissues undergo due to an applied force. Then, this information is used in a learning system to find the nonlinear relationship between the given data and the applied force. We carried out experiments with in-vivo and ex-vivo data and combined statistical, graphical and perceptual analyses to demonstrate the strength of our solution. Finally, we explore robotic cardiac surgery, which allows carrying out complex procedures including Off-Pump Coronary Artery Bypass Grafting (OPCABG). This procedure avoids the associated complications of using Cardiopulmonary Bypass (CPB) since the heart is not arrested while performing the surgery on a beating heart. Thus, surgeons have to deal with a dynamic target that compromisetheir dexterity and the surgery's precision. To compensate the heart motion, we propase a solution composed of three elements: an energy function to estimate the 3D heart motion, a specular highlight detection strategy and a prediction approach for increasing the robustness of the solution. We conduct evaluation of our solution using phantom and realistic datasets. We conclude the thesis by reporting our findings on these three applications and highlight the dependency between motion estimation and motion understanding at any dynamic event, particularly in clinical scenarios.L’estimació i comprensió del moviment dins d’una seqüència d’imatges és un tema central en la visió per ordinador, el que genera un gran interès perquè vivim en un entorn ple d’esdeveniments dinàmics. Per aquest motiu és considerat com un component natural i factor clau dins d’un ampli ventall d’aplicacions, el qual inclou el reconeixement d’objectes, la reconstrucció de formes tridimensionals, la navegació autònoma i el diagnòstic de malalties. En particular, ens situem en l’àmbit mèdic en el qual la comprensió del cos humà, amb finalitats clíniques, requereix l’obtenció de patrons complexos de moviment dels òrgans. Aquesta és, en general, una tasca difícil quan s’utilitzen només dades de tipus visual. En aquesta tesi afrontem el problema plantejant-nos la pregunta - Com es pot aconseguir una estimació realista del moviment amb l’objectiu d’oferir una millor comprensió clínica? La tesi se centra en la resposta mitjançant l’ús d’una formulació variacional com a base per entendre un dels moviments més complexos del cos humà, el del cor, a través de tres aplicacions: (i) estimació del moviment cardíac per al diagnòstic, (ii) estimació de forces i (iii) predicció del moviment, orientant-se les dues últimes en cirurgia robòtica. En primer lloc, ens centrem en un tema principal en la imatge cardíaca, que és l’estimació del moviment cardíac. L’objectiu principal és oferir als metges mesures objectives i comprensibles per ajudar-los en el diagnòstic de les malalties cardiovasculars. Fem servir dades d’ultrasons ultraràpids i eines per al moviment d’imatges procedents de diverses àrees, com ara l’anàlisi de baix rang i la deformació variacional, per fer una estimació realista del moviment cardíac. La importància rau en que, en prendre les dades de baix rang amb una penalització acurada, es poden crear sinergies en aquest problema variacional complex. Mitjançant acurats experiments numèrics, amb dades realístiques i simulades, hem demostrat com les nostres propostes solucionen deformacions complexes. Després passem del diagnòstic a la cirurgia robòtica, on els cirurgians realitzen procediments delicats remotament, a través de manipuladors robòtics, sense interactuar directament amb els pacients. Com a conseqüència, no tenen la percepció de la força com a resposta, que és un sentit primari important per augmentar la transparència entre el cirurgià i el pacient, per evitar lesions i per reduir la càrrega de treball mental. Resolem aquest problema seguint els principis de conservació de la mecànica del medi continu, en els quals està clar que el canvi en la forma d’un objecte elàstic és directament proporcional a la força aplicada. Per això hem creat un marc variacional que adquireix la deformació que pateixen els teixits per l’aplicació d’una força. Aquesta informació s’utilitza en un sistema d’aprenentatge, per trobar la relació no lineal entre les dades donades i la força aplicada. Hem dut a terme experiments amb dades in-vivo i ex-vivo i hem combinat l’anàlisi estadístic, gràfic i de percepció que demostren la robustesa de la nostra solució. Finalment, explorem la cirurgia cardíaca robòtica, la qual cosa permet realitzar procediments complexos, incloent la cirurgia coronària sense bomba (off-pump coronary artery bypass grafting o OPCAB). Aquest procediment evita les complicacions associades a l’ús de circulació extracorpòria (Cardiopulmonary Bypass o CPB), ja que el cor no s’atura mentre es realitza la cirurgia. Això comporta que els cirurgians han de tractar amb un objectiu dinàmic que compromet la seva destresa i la precisió de la cirurgia. Per compensar el moviment del cor, proposem una solució composta de tres elements: un funcional d’energia per estimar el moviment tridimensional del cor, una estratègia de detecció de les reflexions especulars i una aproximació basada en mètodes de predicció, per tal d’augmentar la robustesa de la solució. L’avaluació de la nostra solució s’ha dut a terme mitjançant conjunts de dades sintètiques i realistes. La tesi conclou informant dels nostres resultats en aquestes tres aplicacions i posant de relleu la dependència entre l’estimació i la comprensió del moviment en qualsevol esdeveniment dinàmic, especialment en escenaris clínics.Postprint (published version

Characterization of carotid artery plaques using noninvasive vascular ultrasound elastography

L'athérosclérose est une maladie vasculaire complexe qui affecte la paroi des artères (par l'épaississement) et les lumières (par la formation de plaques). La rupture d'une plaque de l'artère carotide peut également provoquer un accident vasculaire cérébral ischémique et des complications. Bien que plusieurs modalités d'imagerie médicale soient actuellement utilisées pour évaluer la stabilité d'une plaque, elles présentent des limitations telles que l'irradiation, les propriétés invasives, une faible disponibilité clinique et un coût élevé. L'échographie est une méthode d'imagerie sûre qui permet une analyse en temps réel pour l'évaluation des tissus biologiques. Il est intéressant et prometteur d’appliquer une échographie vasculaire pour le dépistage et le diagnostic précoces des plaques d’artère carotide. Cependant, les ultrasons vasculaires actuels identifient uniquement la morphologie d'une plaque en termes de luminosité d'écho ou l’impact de cette plaque sur les caractéristiques de l’écoulement sanguin, ce qui peut ne pas être suffisant pour diagnostiquer l’importance de la plaque. La technique d’élastographie vasculaire non-intrusive (« noninvasive vascular elastography (NIVE) ») a montré le potentiel de détermination de la stabilité d'une plaque. NIVE peut déterminer le champ de déformation de la paroi vasculaire en mouvement d’une artère carotide provoqué par la pulsation cardiaque naturelle. En raison des différences de module de Young entre les différents tissus des vaisseaux, différents composants d’une plaque devraient présenter différentes déformations, caractérisant ainsi la stabilité de la plaque. Actuellement, les performances et l’efficacité numérique sous-optimales limitent l’acceptation clinique de NIVE en tant que méthode rapide et efficace pour le diagnostic précoce des plaques vulnérables. Par conséquent, il est nécessaire de développer NIVE en tant qu’outil d’imagerie non invasif, rapide et économique afin de mieux caractériser la vulnérabilité liée à la plaque. La procédure à suivre pour effectuer l’analyse NIVE consiste en des étapes de formation et de post-traitement d’images. Cette thèse vise à améliorer systématiquement la précision de ces deux aspects de NIVE afin de faciliter la prédiction de la vulnérabilité de la plaque carotidienne. Le premier effort de cette thèse a été dédié à la formation d'images (Chapitre 5). L'imagerie par oscillations transversales a été introduite dans NIVE. Les performances de l’imagerie par oscillations transversales couplées à deux estimateurs de contrainte fondés sur un modèle de déformation fine, soit l’ « affine phase-based estimator (APBE) » et le « Lagrangian speckle model estimator (LSME) », ont été évaluées. Pour toutes les études de simulation et in vitro de ce travail, le LSME sans imagerie par oscillation transversale a surperformé par rapport à l'APBE avec imagerie par oscillations transversales. Néanmoins, des estimations de contrainte principales comparables ou meilleures pourraient être obtenues avec le LSME en utilisant une imagerie par oscillations transversales dans le cas de structures tissulaires complexes et hétérogènes. Lors de l'acquisition de signaux ultrasonores pour la formation d'images, des mouvements hors du plan perpendiculaire au plan de balayage bidimensionnel (2-D) existent. Le deuxième objectif de cette thèse était d'évaluer l'influence des mouvements hors plan sur les performances du NIVE 2-D (Chapitre 6). À cette fin, nous avons conçu un dispositif expérimental in vitro permettant de simuler des mouvements hors plan de 1 mm, 2 mm et 3 mm. Les résultats in vitro ont montré plus d'artefacts d'estimation de contrainte pour le LSME avec des amplitudes croissantes de mouvements hors du plan principal de l’image. Malgré tout, nous avons néanmoins obtenu des estimations de déformations robustes avec un mouvement hors plan de 2.0 mm (coefficients de corrélation supérieurs à 0.85). Pour un jeu de données cliniques de 18 participants présentant une sténose de l'artère carotide, nous avons proposé d'utiliser deux jeux de données d'analyses sur la même plaque carotidienne, soit des images transversales et longitudinales, afin de déduire les mouvements hors plan (qui se sont avérés de 0.25 mm à 1.04 mm). Les résultats cliniques ont montré que les estimations de déformations restaient reproductibles pour toutes les amplitudes de mouvement, puisque les coefficients de corrélation inter-images étaient supérieurs à 0.70 et que les corrélations croisées normalisées entre les images radiofréquences étaient supérieures à 0.93, ce qui a permis de démontrer une plus grande confiance lors de l'analyse de jeu de données cliniques de plaques carotides à l'aide du LSME. Enfin, en ce qui concerne le post-traitement des images, les algorithmes NIVE doivent estimer les déformations des parois des vaisseaux à partir d’images reconstituées dans le but d’identifier les tissus mous et durs. Ainsi, le dernier objectif de cette thèse était de développer un algorithme d'estimation de contrainte avec une résolution de la taille d’un pixel ainsi qu'une efficacité de calcul élevée pour l'amélioration de la précision de NIVE (Chapitre 7). Nous avons proposé un estimateur de déformation de modèle fragmenté (SMSE) avec lequel le champ de déformation dense est paramétré avec des descriptions de transformées en cosinus discret, générant ainsi des composantes de déformations affines (déformations axiales et latérales et en cisaillement) sans opération mathématique de dérivées. En comparant avec le LSME, le SMSE a réduit les erreurs d'estimation lors des tests de simulations, ainsi que pour les mesures in vitro et in vivo. De plus, la faible mise en oeuvre de la méthode SMSE réduit de 4 à 25 fois le temps de traitement par rapport à la méthode LSME pour les simulations, les études in vitro et in vivo, ce qui pourrait permettre une implémentation possible de NIVE en temps réel.Atherosclerosis is a complex vascular disease that affects artery walls (by thickening) and lumens (by plaque formation). The rupture of a carotid artery plaque may also induce ischemic stroke and complications. Despite the use of several medical imaging modalities to evaluate the stability of a plaque, they present limitations such as irradiation, invasive property, low clinical availability and high cost. Ultrasound is a safe imaging method with a real time capability for assessment of biological tissues. It is clinically used for early screening and diagnosis of carotid artery plaques. However, current vascular ultrasound technologies only identify the morphology of a plaque in terms of echo brightness or the impact of the vessel narrowing on flow properties, which may not be sufficient for optimum diagnosis. Noninvasive vascular elastography (NIVE) has been shown of interest for determining the stability of a plaque. Specifically, NIVE can determine the strain field of the moving vessel wall of a carotid artery caused by the natural cardiac pulsation. Due to Young’s modulus differences among different vessel tissues, different components of a plaque can be detected as they present different strains thereby potentially helping in characterizing the plaque stability. Currently, sub-optimum performance and computational efficiency limit the clinical acceptance of NIVE as a fast and efficient method for the early diagnosis of vulnerable plaques. Therefore, there is a need to further develop NIVE as a non-invasive, fast and low computational cost imaging tool to better characterize the plaque vulnerability. The procedure to perform NIVE analysis consists in image formation and image post-processing steps. This thesis aimed to systematically improve the accuracy of these two aspects of NIVE to facilitate predicting carotid plaque vulnerability. The first effort of this thesis has been targeted on improving the image formation (Chapter 5). Transverse oscillation beamforming was introduced into NIVE. The performance of transverse oscillation imaging coupled with two model-based strain estimators, the affine phase-based estimator (APBE) and the Lagrangian speckle model estimator (LSME), were evaluated. For all simulations and in vitro studies, the LSME without transverse oscillation imaging outperformed the APBE with transverse oscillation imaging. Nonetheless, comparable or better principal strain estimates could be obtained with the LSME using transverse oscillation imaging in the case of complex and heterogeneous tissue structures. During the acquisition of ultrasound signals for image formation, out-of-plane motions which are perpendicular to the two-dimensional (2-D) scan plane are existing. The second objective of this thesis was to evaluate the influence of out-of-plane motions on the performance of 2-D NIVE (Chapter 6). For this purpose, we designed an in vitro experimental setup to simulate out-of-plane motions of 1 mm, 2 mm and 3 mm. The in vitro results showed more strain estimation artifacts for the LSME with increasing magnitudes of out-of-plane motions. Even so, robust strain estimations were nevertheless obtained with 2.0 mm out-of-plane motion (correlation coefficients higher than 0.85). For a clinical dataset of 18 participants with carotid artery stenosis, we proposed to use two datasets of scans on the same carotid plaque, one cross-sectional and the other in a longitudinal view, to deduce the out-of-plane motions (estimated to be ranging from 0.25 mm to 1.04 mm). Clinical results showed that strain estimations remained reproducible for all motion magnitudes since inter-frame correlation coefficients were higher than 0.70, and normalized cross-correlations between radiofrequency images were above 0.93, which indicated that confident motion estimations can be obtained when analyzing clinical dataset of carotid plaques using the LSME. Finally, regarding the image post-processing component of NIVE algorithms to estimate strains of vessel walls from reconstructed images with the objective of identifying soft and hard tissues, we developed a strain estimation method with a pixel-wise resolution as well as a high computation efficiency for improving NIVE (Chapter 7). We proposed a sparse model strain estimator (SMSE) for which the dense strain field is parameterized with Discrete Cosine Transform descriptions, thereby deriving affine strain components (axial and lateral strains and shears) without mathematical derivative operations. Compared with the LSME, the SMSE reduced estimation errors in simulations, in vitro and in vivo tests. Moreover, the sparse implementation of the SMSE reduced the processing time by a factor of 4 to 25 compared with the LSME based on simulations, in vitro and in vivo results, which is suggesting a possible implementation of NIVE in real time

Parasternal versus apical view in cardiac natural mechanical wave speed measurements

Shear wave speed measurements can potentially be used to noninvasively measure myocardial stiffness to assess the myocardial function. Several studies showed the feasibility of tracking naturalmechanical waves induced by aortic valve closure in the interventricular septum, but different echocardiographic views have been used. This article systematically studied the wave propagation speedsmeasured in a parasternal long-axis and in an apical four-chamber view in ten healthy volunteers. The apical and parasternal views are predominantly sensitive to longitudinal or transversal tissue motion, respectively, and could, therefore, theoreticallymeasure the speed of different wave modes. We found higher propagation speeds in apical than in the parasternal view (median of 5.1 m/s versus 3.8 m/s, p < 0.01, n = 9). The results in the different views were not correlated (r = 0.26, p = 0.49) and an unexpectedly large variability among healthy volunteers was found in apical view compared with the parasternal view (3.5-8.7 versus 3.2-4.3 m/s, respectively). Complementary finite element simulations of Lamb waves in an elastic plate showed that different propagation speeds can be measured for different particlemotion componentswhen differentwavemodes are induced simultaneously. The in vivo results cannot be fully explained with the theory of Lamb wave modes. Nonetheless, the results suggest that the parasternal long-axis view is amore suitable candidate for clinical diagnosis due to the lower variability in wave speeds

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

2-D and 3-D high frame-rate Pulse Wave Imaging for the characterization of focal vascular disease

Cardiovascular diseases are major causes of morbidity and mortality in Western-style populations. Atherosclerosis and Abdominal Aortic Aneurysms (AAAs) are two prevalent vascular diseases that may progress without symptoms and contribute to acute cardiovascular events such as stroke and AAA rupture, which are consistently among the leading causes of death worldwide. The imaging methods used in the diagnosis of these diseases, have been reported to present several limitations. Given that both are associated with mechanical changes in the arterial wall, imaging of the arterial mechanical properties may improve early disease detection and patient care. Pulse wave velocity (PWV) refers to the velocity at which arterial waves generated by ventricular ejection travel along the arterial tree. PWV is a surrogate marker of arterial stiffness linked to cardiovascular mortality. The foot-to-foot method that is typically used to calculate PWV suffers from errors of distance measurements and time-delay measurements. Additionally, a single PWV estimate is provided over a relatively long distance, thus inherently lacking the capability to provide regional arterial stiffness measurements. Pulse Wave Imaging (PWI) is a noninvasive, ultrasound-based technique for imaging the propagation of pulse waves along the wall of major arteries and providing a regional PWV value for the imaged artery. The aim of this work was to enable PWI to provide more localized PWV and stiffness measurements within the imaged arterial segment and to further extend it into a 2-D and 3-D technique for the detection and monitoring of focal vascular disease at high temporal and spatial resolution. The improved modality was integrated with blood flow imaging modalities aiming to render PWI a comprehensive methodology for the study of arterial biomechanics in vivo. Spatial information was increased with the introduction of piecewise PWI. This novel technique was used to measure PWV within small sub-regions of the imaged vessel in murine aneurysmal (n = 8) and atherosclerotic aortas (n = 11) in vivo. It provided PWV and stiffness maps while capturing the progressive arterial stiffening caused by atherosclerosis. PWI was further augmented with a sophisticated adaptive algorithm, enabling it to optimally partition the imaged artery into relatively homogeneous segments, automatically isolating arterial stiffness inhomogeneities. Adaptive PWI was validated in silicone phantoms consisting of segments of varying stiffness and then tested in murine aortas in vivo. Subsequently, the conventional tradeoff between spatial and temporal resolution was addressed with a plane wave compounding implementation of PWI, allowing the acquisition of full field of view frames at over 2000 Hz. A GPU-accelerated PWI post-processing framework was developed for the processing of the big bulk of generated data. The parameters of coherent compounding were optimized in vivo. The optimized sequences were then used in the clinic to assess the mechanical properties of atherosclerotic carotids (n=10) and carotids of patients after endarterectomy (n=7), a procedure to remove the plaque and restore blood flow to the brain. In the case of atherosclerotic patients undergoing carotid endarterectomy, the results were compared against the histology of the excised plaques. Investigation of the mechanical properties of plaques was also conducted for the first time with a high-frequency transducer (18.5 MHz). Additionally, 4-D PWI was introduced, utilizing high frame rate 3-D plane wave acquisitions with a 2-D matrix array transducer (16x16 elements, 2.5 MHz). A novel methodology for PWV estimation along the direction of pulse wave propagation was implemented and validated in silicone phantoms. 4-D PWI provided comprehensive views of the pulse wave propagation in a plaque phantom and the results were compared against conventional PWI. Finally, its feasibility was tested in the carotid arteries of healthy human subjects (n=6). PWVs derived in 3-D were within the physiological range and showed good agreement with the results of conventional PWI. Finally, PWI was integrated with flow imaging modalities (Color and Vector Doppler). Thus, full field-of-view, high frame-rate, simultaneous and co-localized imaging of the arterial wall dynamics and color flow as well as 2-D vector flow was implemented. The feasibility of both techniques was tested in healthy subjects (n=6) in vivo. The relationship between the timings of the flow and wall velocities was investigated at multiple locations of the imaged artery. Vector flow velocities were found to be aligned with the vessel’s centerline during peak systole in the common carotid artery and interesting flow patterns were revealed in the case of the carotid bifurcation Consequently, with the aforementioned improvements and the inclusion of 3-D imaging, PWI is expected to provide comprehensive information on the mechanical properties of pathological arteries, providing clinicians with a powerful tool for the early detection of vascular abnormalities undetectable on the B-mode, while also enabling the monitoring of fully developed vascular pathology and of the recovery of post-operated vessels

Ultrafast Echocardiography

Grâce à son accessibilité, sa polyvalence et sa sécurité, l'échocardiographie est devenue la technique d'imagerie la plus utilisée pour évaluer la fonction cardiaque. Au vu du succès de l'échographie ultrarapide par ondes planes des techniques similaires pour augmenter la résolution temporelle en échocardiographie ont été mise en oeuvre. L’augmentation de la résolution temporelle de l’échographie cardiaque au-delà des valeurs actuellement atteignables (~ 60 à 80 images par secondes), pourrait être utilisé pour améliorer d’autres caractéristiques de l'échocardiographie, comme par exemple élargir la plage de vitesses détectables en imagerie Doppler couleur limitées par la valeur de Nyquist. Nous avons étudié l'échocardiographie ultrarapide en utilisant des fronts d’ondes ultrasonores divergentes. La résolution temporelle atteinte par la méthode d'ondes divergentes a permis d’améliorer les capacités des modes d’échocardiographie en mode B et en Doppler couleur. La résolution temporelle de la méthode mode B a été augmentée jusqu'à 633 images par secondes, tout en gardant une qualité d'image comparable à celle de la méthode d’échocardiographie conventionnelle. La vitesse de Nyquist de la méthode Doppler couleur a été multipliée jusqu'à 6 fois au delà de la limite conventionnelle en utilisant une technique inspirée de l’imagerie radar; l’implémentation de cette méthode n’aurait pas été possible sans l’utilisation de fronts d’ondes divergentes. Les performances avantageuses de la méthode d'échocardiographie ultrarapide sont supportées par plusieurs résultats in vitro et in vivo inclus dans ce manuscrit.Because of its low cost, versatility and safety, echocardiography has become the most common imaging technique to assess the cardiac function. The recent success of ultrafast ultrasound plane wave imaging has prompted the implementation of similar approaches to enhance the echocardiography temporal resolution. The ability to enhance the echocardiography frame rate beyond conventional values (~60 to 80 fps) would positively impact other echocardiography features, e.g. broaden the color Doppler unambiguous velocity range. We investigated the ultrafast echocardiography imaging approach using ultrasound diverging waves. The high frame rate offered by the diverging wave method was used to enhance the capabilities of both B-mode and color Doppler echocardiography. The B-mode temporal resolution was increased to 633 fps whilst the image quality was kept almost unchanged with reference to the conventional echocardiography technique. The color Doppler Nyquist velocity range was extended to up to 6 times the conventional limit using a weather radar imaging approach; such an approach could not have been implemented without using the ultrafast diverging wave imaging technique. The advantageous performance of the ultrafast diverging wave echocardiography approach is supported by multiple in vitro and in vivo results included in this manuscript