41 research outputs found

    Early Detection of Doxorubicin-Induced Cardiotoxicity Using Combined Biomechanical Modeling and Multi-Parametric Cardiovascular MRI

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    RÉSUMÉ La chimiothérapie à la doxorubicine est efficace et est largement utilisée pour traiter la leucémie lymphoblastique aiguë. Toutefois, son efficacité est entravée par un large spectre de cardiotoxicités incluant des changements affectant à la fois la morphologie et la fonction du myocarde. Ces changements dépendent principalement de la dose cumulée administrée au patient. Actuellement, très peu de techniques sont disponibles pour détecter de telles cardiotoxicités. L'utilisation d’images de fibres musculaires (par exemple, à l’aide de l’imagerie des tenseurs de diffusion par IRM) ou des techniques d'imagerie 3D (par exemple, ciné DENSE IRM) sont des alternatives prometteuses, cependant, leur application en clinique est limitée en raison du temps d'acquisition d’images et les erreurs d'estimation qui en résultent. En revanche, l'utilisation de l'IRM multi-paramétrique ainsi que le ciné IRM sont des alternatives prometteuses, puisque ces techniques sont déjà disponibles au niveau clinique. L’IRM multiparamétrique incluant l’imagerie des temps de relaxation T1 et T2 peut être utile dans la détection des lésions dans le tissu du myocarde alors que l’imagerie ciné IRM peut être plus appropriée pour détecter les changements fonctionnels au sein du myocarde. La combinaison de ces deux techniques peut également permettre une caractérisation complète de la fonction du tissu myocardique. Dans ce projet, l'utilisation des temps de relaxation T1 pré- et post-gadolinium et T2 est d'abord évaluée et proposée pour détecter les dommages myocardiques induits par la chimiothérapie à la doxorubicine. En second lieu, l'utilisation de patrons 2D de déplacements myocardiques est évaluée dans le cadre de la détection des dommages myocardiques et altération fonctionnelle due au traitement à la doxorubicine. Enfin, l'utilisation de la modélisation par éléments finis, incluant les contraintes et déformations mécaniques est proposée pour évaluer les changements dans les propriétés mécaniques au niveau du myocarde, avec l’hypothèse que le traitement à base de doxorubicine induit des changements importants à la fois dans le tissu et au niveau de la fonction myocardique. Dans notre cohorte de survivants de cancer, des changements myocardiques locaux ont été trouvés entre le groupe à risque standard et le groupe à risque élevé lorsque le T1 pré-gadolinium fut utilisé. Ces changements ont été amplifiés avec l’utilisation d’agent de contraste tel que confirmé par le coefficient de partition, ce qui suggère que l’utilisation du T1 post-gadolonium et le coefficient de----------ABSTRACT Doxorubicin chemotherapy is effective and widely used to treat acute lymphoblastic leukemia. However, its effectiveness is hampered by a wide spectrum of dose-dependent cardiotoxicity including both morphological and functional changes affecting the myocardium. Currently, very few techniques are available for detecting such cardiotoxic effect. The use of muscle fibers orientation (e.g., diffusion tensor imaging DT-MRI) or 3D imaging techniques (e.g., cine DENSE MRI) are possible alternatives, however, their clinical application is limited due to the acquisition time and their estimation errors. In contrast, the use of multi-parametric MRI along with cine MRI is a promising alternative, since theses techniques are already available at a clinical level. Multiparametric MRI including T1 and T2 imaging may be helpful in detecting myocardial tissue damage, while cine MRI may be more appropriate to detect functional changes within the myocardium. The combination of these two techniques may further allow an extensive characterization of myocardial tissue function. In this doctoral project, the use of pre- and post-gadolinium T1 and T2 relaxation times is firstly assessed and proposed to detect myocardial damage induced by doxorubicin chemotherapy. Secondly, the use of 2D myocardial displacement patterns is assessed in detecting myocardial damage and functional alteration due to doxorubicin-based treatment. Finally, the use of finite element modeling including mechanical strains and stresses to evaluate mechanical properties changes within the myocardium is alternatively proposed, assuming that doxorubicin-based treatment induces significant changes to both myocardial tissue morphology and function. In our cohort of cancer survivors, local myocardial changes were found between standard risk and high risks group using pre-gadolinium T1 relaxation times. These changes were further amplified with gadolinium enhancement, as confirmed by the use of partition coefficient, suggesting this MRI parameter along with partition coefficient as candidates imaging markers of doxorubicin induced cardiomyopathy. The use of T2 on the other hand showed that the high risk group of cancer survivors had higher T2 relaxation times compared to the standard risk group and similar to reported values. Though, a larger cohort of cancer survivors may be required to assess the use of T1 and T2 relaxation time as possible indices for myocardial tissue damage in the onset of doxorubicin-induced cardiotoxicity

    Détection précoce de la cardiotoxicité due à la doxorubicine chez le miniporc par imagerie par résonance magnétique

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    RÉSUMÉ Objectif : La chimiothérapie est une méthode qui a fait ses preuves quant à l’élimination de différents types de cancers. Cependant la cardiotoxicité associée reste sa plus grande barrière à la bonne santé à long terme des patients. Les jeunes patients recevant un haut dosage sont les plus touchés par cette cardiotoxicité, précoce ou retardée selon les cas. Cette étude vise à examiner la réaction précoce du myocarde à l’injection intraveineuse d’une haute dose de médicament anti-cancéreux chez un large modèle animal par IRM multiparamétrique (mpMRI). Matériel et méthodes : Cinq miniporcs Yucatan femelles prépubères ont reçu 5 doses de doxorubicine (75mg/m2) à trois semaines d’intervalles (dose cumulative totale de 375mg/m2) formant le groupe expérimental appelé groupe Doxo. Deux miniporcs ont reçu de la saline selon le même protocole, formant le groupe contrôle. Trois acquisitions d’images IRM et échocardiographiques ont été réalisées au cours du projet : la première avant la première injection (A1), la deuxième après la quatrième injection (A2, dose cumulative de 300mg/m2) et la troisième trois semaines après la dernière injection (A3). Des tests d’hématologie ont été réalisés pour vérifier la déficience de l’immunité due au traitement de chimiothérapie. Les données d’IRM ont été comparées entre les acquisitions et les groupes grâce à des ANOVA à une voie sur les rangs et incluaient le déplacement cumulatif de chaque point du contour myocardique, les aires ventriculaires, la longueur des ventricules, l’épaisseur des parois, la torsion du ventricule gauche, les valeurs cumulatives de contrainte et déformations selon von Mises, les temps de relaxation T1 (avant, T1pre, et après, T1post, l’injection d’un agent de contraste) et T2. Résultats : Les miniporcs recevant la chimiothérapie ont souffert d’alopécie et de diarrhée pendant quelques jours après chaque injection. Les taux de globules blancs et de plaquettes ont chuté dans le groupe Doxo restant stable chez les miniporcs sains. Les fractions d’éjection et de raccourcissement ainsi que le flux aortique ont chuté lors de la dernière acquisition dans le groupe Doxo, ce qui n’a pas été noté chez les porcs sains. Les mesures d’aires, de longueurs, d’épaisseurs et de torsions calculées par IRM présentaient des courbes similaires mais dont l’amplitude changeait selon les groupes et les acquisitions. Les valeurs de contraintes et déformations ont diminué lors de la dernière acquisition en systole et fin de diastole.----------ABSTRACT Purpose: Chemotherapy has been proven to be the best way to eliminate several types of cancer. However, the associated cardiotoxicity is an important drawback to the long-term well-being of patients. Young patients receiving a high dosage are the most prone to develop this cardiotoxicity, which can occur either early or late after treatment. This study aims to investigate the early myocardial response to an intravenous injection of a high dosage of anticancer agent, using multiparametric MRI (mpMRI), in a large animal model. Material & Methods: Five young female Yucatan minipigs received five doses of doxorubicine (75mg/m2), one every three weeks (total cumulative dose of 375mg/m2), constituting the experimental group called Doxo group. Two minipigs received saline under the same protocol, constituting the control group. Three MRI and echocardiographic images acquisitions were performed: the first before the first injection (A1), the second after the fourth injection (A2, cumulative dose of 300mg/m2) and the third three weeks after the last injection (A3). Hematologic tests were performed to verify the immune deficiency due to chemotherapy. MRI data were compared between groups and acquisitions using one way ANOVA on ranks and included cumulative displacement of each point on the myocardial contour, ventricular areas, ventricular lengths, wall thicknesses, left ventricle torsion, cumulative values of von Mises stress and strain, relaxation times T1 (before, T1pre, and after, T1post, a contrast agent injection) and T2. Results: Minipigs receiving chemotherapy suffered from alopecia and diarrhoea for some days after each injection. White blood cells and platelets rates decreased in the Doxo group while staying stable in the control group. The ejection fraction, the shortening fraction and the aortic blood flow decreased at A3 in the Doxo group but not in the control group. Similar curves were shown for MRI measurements of areas, lengths, thicknesses and LV torsion but their amplitude was different according to groups and acquisitions. Stress and strain values decreased at A3 in systole and end-diastole. T1 pre-gadolinium values decreased with time in the control group. T1 post-gadolinium values decreased in both groups with time. T2 values decreased in the Doxo group

    From medical images to individualized cardiac mechanics: A Physiome approach

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    Cardiac mechanics is a branch of science that deals with forces, kinematics, and material properties of the heart, which is valuable for clinical applications and physiological studies. Although anatomical and biomechanical experiments are necessary to provide the fundamental knowledge of cardiac mechanics, the invasive nature of the procedures limits their further applicability. In consequence, noninvasive alternatives are required, and cardiac images provide an excellent source of subject-specific and in vivo information. Noninvasive and individualized cardiac mechanical studies can be achieved through coupling general physiological models derived from invasive experiments with subject-specific information extracted from medical images. Nevertheless, as data extracted from images are gross, sparse, or noisy, and do not directly provide the information of interest in general, the couplings between models and measurements are complicated inverse problems with numerous issues need to be carefully considered. The goal of this research is to develop a noninvasive framework for studying individualized cardiac mechanics through systematic coupling between cardiac physiological models and medical images according to their respective merits. More specifically, nonlinear state-space filtering frameworks for recovering individualized cardiac deformation and local material parameters of realistic nonlinear constitutive laws have been proposed. To ensure the physiological meaningfulness, clinical relevance, and computational feasibility of the frameworks, five key issues have to be properly addressed, including the cardiac physiological model, the heart representation in the computational environment, the information extraction from cardiac images, the coupling between models and image information, and also the computational complexity. For the cardiac physiological model, a cardiac physiome model tailored for cardiac image analysis has been proposed to provide a macroscopic physiological foundation for the study. For the heart representation, a meshfree method has been adopted to facilitate implementations and spatial accuracy refinements. For the information extraction from cardiac images, a registration method based on free-form deformation has been adopted for robust motion tracking. For the coupling between models and images, state-space filtering has been applied to systematically couple the models with the measurements. For the computational complexity, a mode superposition approach has been adopted to project the system into an equivalent mathematical space with much fewer dimensions for computationally feasible filtering. Experiments were performed on both synthetic and clinical data to verify the proposed frameworks

    Three-dimensional model-based analysis of vascular and cardiac images

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    This thesis is concerned with the geometrical modeling of organs to perform medical image analysis tasks. The thesis is divided in two main parts devoted to model linear vessel segments and the left ventricle of the heart, respectively. Chapters 2 to 4 present different aspects of a model-based technique for semi-automated quantification of linear vessel segments from 3-D Magnetic Resonance Angiography (MRA). Chapter 2 is concerned with a multiscale filter for the enhancement of vessels in 2-D and 3-D angiograms. Chapter 3 applies the filter developed in Chapter 2 to determine the central vessel axis in 3-D MRA images. This procedure is initialized using an efficient user interaction technique that naturally incorporates the knowledge of the operator about the vessel of interest. Also in this chapter, a linear vessel model is used to recover the position of the vessel wall in order to carry out an accurate quantitative analysis of vascular morphology. Prior knowledge is provided in two main forms: a cylindrical model introduces a shape prior while prior knowledge on the image acquisition (type of MRA technique) is used to define an appropriate vessel boundary criterion. In Chapter 4 an extensive in vitro and in vivo evaluation of the algorithm introduced in Chapter 3 is described. Chapters 5 to 7 change the focus to 3D cardiac image analysis from Magnetic Resonance Imaging. Chapter 5 presents an extensive survey, a categorization and a critical review of the field of cardiac modeling. Chapter 6 and Chapter 7 present successive refinements of a method for building statistical models of shape variability with particular emphasis on cardiac modeling. The method is based on an elastic registration method using hierarchical free-form deformations. A 3D shape model of the left and right ventricles of the heart was constructed. This model contains both the average shape of these organs as well as their shape variability. The methodology presented in the last two chapters could also be applied to other anatomical structures. This has been illustrated in Chapter 6 with examples of geometrical models of the nucleus caudate and the radius

    On motion in dynamic magnetic resonance imaging: Applications in cardiac function and abdominal diffusion

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    La imagen por resonancia magnética (MRI), hoy en día, representa una potente herramienta para el diagnóstico clínico debido a su flexibilidad y sensibilidad a un amplio rango de propiedades del tejido. Sus principales ventajas son su sobresaliente versatilidad y su capacidad para proporcionar alto contraste entre tejidos blandos. Gracias a esa versatilidad, la MRI se puede emplear para observar diferentes fenómenos físicos dentro del cuerpo humano combinando distintos tipos de pulsos dentro de la secuencia. Esto ha permitido crear distintas modalidades con múltiples aplicaciones tanto biológicas como clínicas. La adquisición de MR es, sin embargo, un proceso lento, lo que conlleva una solución de compromiso entre resolución y tiempo de adquisición (Lima da Cruz, 2016; Royuela-del Val, 2017). Debido a esto, la presencia de movimiento fisiológico durante la adquisición puede conllevar una grave degradación de la calidad de imagen, así como un incremento del tiempo de adquisición, aumentando así tambien la incomodidad del paciente. Esta limitación práctica representa un gran obstáculo para la viabilidad clínica de la MRI. En esta Tesis Doctoral se abordan dos problemas de interés en el campo de la MRI en los que el movimiento fisiológico tiene un papel protagonista. Éstos son, por un lado, la estimación robusta de parámetros de rotación y esfuerzo miocárdico a partir de imágenes de MR-Tagging dinámica para el diagnóstico y clasificación de cardiomiopatías y, por otro, la reconstrucción de mapas del coeficiente de difusión aparente (ADC) a alta resolución y con alta relación señal a ruido (SNR) a partir de adquisiciones de imagen ponderada en difusión (DWI) multiparamétrica en el hígado.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

    Impact of uncertainties in cardiac mechanics simulations

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    Modeling the mechanics of the heart have led to considerable insights, but it still representes a complex and demanding computational problem, especially in a strongly coupled electromechanical setting. Passive cardiac tissue is commonly modeled as a hyperelastic, near-incompressible and orthotropic material, which are properties very challenging for the numerical solution of the model. In particular, near-incompressibility is known to cause numerical issues. In this work, some improvements were done in a cardiac mechanics simulator in order to be more efficient in the treatment of these numerical issues. With the improved solver for cardiac mechanics, it was possible to run problems with higher computational cost, such as sensitivity and uncertainty quantification analyses. This type of analysis has been a topic of scientific interest to assess the possibility of translating patient-specific simulations to clinical applications. However, personalized simulations are still challenging problems, because of the wide biological variability among patients, the uncertainties in experimental measurements and in the geometric representation of the heart. Due to these uncertainties in model inputs, it is difficult to define a reliable model that can be translated to clinical applications. Recent studies have focused on quantifying uncertainties for cardiac models in order to investigate how they can influence simulation results and, consequently, how we can make the models more reliable. Then, the present work also quantifies how uncertainties in the geometry can impact in quantities of interest from cardiac mechanics. The polynomial chaos approach was used to quantify uncertainties in geometries of the left ventricle during cardiac mechanics simulations. Initially, we performed some studies using simplified geometries during ventricular filling phase simulations and, after, we quantify uncertainties in more realistic geometries during the full cardiac cycle.A modelagem da mecânica cardíaca tem levado a descobertas interessantes, porém este continua sendo um problema complexo e de alta demanda computacional, especialmente em modelos eletromecânicos fortemente acoplados. O tecido cardíaco é geralmente considerado como um material hiperelástico, quase incompressível e ortotrópico, fatores que dificultam a solução numérica do modelo. Neste trabalho, melhorias foram realizadas em um simulador da mecânica cardíaca para tratar tais problemas numéricos de forma mais eficiente. Com este simulador mais eficiente foi possível tratar problemas que demandam de um maior esfoço computacional, como as análises de sensibilidade e quantificação de incertezas, onde várias simulações precisam ser realizadas. Este tipo de análise tem sido tópico de interesse científico para avaliar a possibilidade de usar simulações personalizadas por paciente em aplicações clínicas. Porém, estas simulações ainda são problemas desafiadores, por causa da grande variabilidade biológica entre pacientes e das incertezas em medidas experimentais e em representações geométricas do coração. Devido a estas incertezas em entradas do modelo, é difícil definir um modelo confiável que possa ser usado em aplicações clínicas. Estudos recentes têm se voltado à investigação de como estas incertezas podem influenciar no resultado de simulações e, consequentemente, descobrir como tornar os modelos mais confiáveis. Então, o presente trabalho quantifica incertezas nas geometrias usadas nas simulações para investigar como quantidades de interesse da mecânica cardíaca podem ser afetadas. A abordagem do polinômio caos é utilizada para a quantificação de incertezas em geometrias do ventrículo esquerdo submetidas a simulações da mecânica cardíaca. Inicialmente, as análises foram realizadas usando geometrias simplificadas em simulações da fase de preenchimento ventricular e, posteriormente, análises de quantificação de incertezas em geometrias mais realísticas submetidas a simulações do ciclo cardíaco completo são realizadas.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superio
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