64 research outputs found

    Model-based indices of early-stage cardiovascular failure and its therapeutic management in Fontan patients

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    International audienceInvestigating the causes of failure of Fontan circulation in individual patients remains challenging despite detailed combined inva-sive cardiac catheterisation and magnetic resonance (XMR) exams at rest and during stress. In this work, we use a biomechanical model of the heart and Fontan circulation with the components of systemic and pulmonary beds to augment the diagnostic assessment of the patients undergoing the XMR stress exam. We apply our model in 3 Fontan patients and one biventricular "control" case. In all subjects, we obtained important biophysical factors of cardiovascular physiology-contractil-ity, contractile reserve and changes in systemic and pulmonary vascular resistance-which contribute to explaining the mechanism of failure in individual patients. Finally, we used the patient-specific model of one Fontan patient to investigate the impact of changes in pulmonary vas-cular resistance, aiming at in silico testing of pulmonary vasodilation treatments

    Estimation of tissue contractility from cardiac cine-MRI using a biomechanical heart model

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    International audienceThe objective of this paper is to propose and assess an estimation procedure - based on data assimilation principles - well-suited to obtain some regional values of key biophysical parameters in a beating heart model, using actual Cine-MR images. The motivation is twofold: (1) to provide an automatic tool for personalizing the characteristics of a cardiac model in order to achieve predictivity in patient-specific modeling, and (2) to obtain some useful information for diagnosis purposes in the estimated quantities themselves. In order to assess the global methodology we specifically devised an animal experiment in which a controlled infarct was produced and data acquired before and after infarction, with an estimation of regional tissue contractility - a key parameter directly affected by the pathology - performed for every measured stage. After performing a preliminary assessment of our proposed methodology using synthetic data, we then demonstrate a full-scale application by first estimating contractility values associated with 6 regions based on the AHA subdivision, before running a more detailed estimation using the actual AHA segments. The estimation results are assessed by comparison with the medical knowledge of the specific infarct, and with late enhancement MR images. We discuss their accuracy at the various subdivision levels, in the light of the inherent modeling limitations and of the intrinsic information contents featured in the data

    Age-related changes in intraventricular kinetic energy:a physiological or pathological adaptation?

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    International audienceAging has important deleterious effects on the cardiovascular system. We sought to compare intraventricular kinetic energy (KE) in healthy subjects of varying ages with subjects with ventricular dysfunction to understand if changes in energetic momentum may predispose individuals to heart failure. Four-dimensional flow MRI was acquired in 35 healthy subjects (age: 1– 67 yr) and 10 patients with left ventricular (LV) dysfunction (age: 28 –79 yr). Healthy subjects were divided into age quartiles (1st quartile: 16 yr, 2nd quartile: 17–32 yr, 3rd quartile: 33– 48 yr, and 4th quartile: 49 – 64 yr). KE was measured in the LV throughout the cardiac cycle and indexed to ventricular volume. In healthy subjects, two large peaks corresponding to systole and early diastole occurred during the cardiac cycle. A third smaller peak was seen during late diastole in eight adults. Systolic KE (P 0.182) and ejection fraction (P 0.921) were preserved through all age groups. Older adults showed a lower early peak diastolic KE compared with children (P 0.0001) and young adults (P 0.025). Subjects with LV dysfunction had reduced ejection fraction (P 0.001) and compared with older healthy adults exhibited a similar early peak diastolic KE (P 0.142) but with the addition of an elevated KE in diastasis (P 0.029). In healthy individuals, peak diastolic KE progressively decreases with age, whereas systolic peaks remain constant. Peak diastolic KE in the oldest subjects is comparable to those with LV dysfunction. Unique age-related changes in ventric-ular diastolic energetics might be physiological or herald subclin-ical pathology

    Cardiac displacement tracking with data assimilation combining a biomechanical model and an automatic contour detection

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    International audienceData assimilation in computational models represents an essential step in building patient-specific simulations. This work aims at circumventing one major bottleneck in the practical use of data assimilation strategies in cardiac applications, namely, the difficulty of formulating and effectively computing adequate data-fitting term for cardiac imaging such as cine MRI. We here provide a proof-of-concept study of data assimilation based on automatic contour detection. The tissue motion simulated by the data assimilation framework is then assessed with displacements extracted from tagged MRI in six subjects, and the results illustrate the performance of the proposed method, including for circumferential displacements, which are not well extracted from cine MRI alone

    Estimation of passive and active properties in the human heart using 3D tagged MRI

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    Advances in medical imaging and image processing are paving the way for personalised cardiac biomechanical modelling. Models provide the capacity to relate kinematics to dynamics and-through patient-specific modelling-derived material parameters to underlying cardiac muscle pathologies. However, for clinical utility to be achieved, model-based analyses mandate robust model selection and parameterisation. In this paper, we introduce a patient-specific biomechanical model for the left ventricle aiming to balance model fidelity with parameter identifiability. Using non-invasive data and common clinical surrogates, we illustrate unique identifiability of passive and active parameters over the full cardiac cycle. Identifiability and accuracy of the estimates in the presence of controlled noise are verified with a number of in silico datasets. Unique parametrisation is then obtained for three datasets acquired in vivo. The model predictions show good agreement with the data extracted from the images providing a pipeline for personalised biomechanical analysis.</p

    Modélisation biomécanique personnalisée du cœur et applications cliniques

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    The objective of this thesis is the assessment of a biomechanical heart model using experimental data, and the investigation of clinical applications with patient-specific modeling. At the 1D level we aimed at reproducing physiological experiments with myocardial fiber contraction. For the 3D validation we performed in cooperation with a clinical partner an experiment with animals (pigs) in order to obtain data in the healthy stage and after creating a myocardial infarct. We showed that our model can reproduce the pressures and motion of a healthy heart and that the infarct can be represented by changing only the parameters directly related to the pathology. The objective of the first clinical application was to predict the short-term effect of the Cardiac Resynchronization Therapy (CRT) by means of an increase of 'max LV dp/dt'. The model personalization was performed using patients MRI and pressure data in the baseline condition - prior to CRT. Then we fixed the values of all parameters and applied electrical activation patterns according to the pacing modes considered. We obtained a very good prediction of max LV dp/dt using various pacing patterns in 3 clinical cases. This preliminary clinical validation shows that the modeling of CRT is a very promising approach as an assistance to therapy planning. The second application is based on the adaptation of data assimilation methods developed in the MACS team at INRIA. We performed joint state-parameter estimation with real image data. We showed the effectiveness of these algorithms in automatic model personalization and that the estimated contractility values can serve as an indicator of the local heart function.L'objectif de cette thèse porte sur la validation d'un modèle biomécanique du cœur à base de mesures expérimentales, et sur des investigations concernant des applications cliniques en modélisation personnalisée. Dans le cadre 1D, nous avons reproduit des expériences physiologiques de contraction d'une fibre cardiaque. Concernant la validation 3D, nous avons effectué dans une collaboration clinique une expérience avec des animaux (cochons), afin d'obtenir des données saines et après création d'infarctus. Nous avons démontré que notre modèle est capable de représenter le cœur sain, et que l'infarctus peut être correctement modélisé en modifiant uniquement les paramètres directement concernés par la pathologie. Dans la première application clinique nous avons démontré que le modèle est prédictif sur l'effet immédiat d'une "Cardiac Resynchronization Therapy" (CRT), sur le critère du "max LV dp/dt". La personnalisation du modèle a été réalisée au moyen des données d'IRM et de pressions au stade 'baseline' (avant la CRT). Puis, tous les paramètres du modèle étant figés, nous avons appliqué les schémas d'activation électrique correspondant aux modes de CRT. Nous avons obtenu une prédiction très proche des indicateurs mesurés sur 3 patients avec plusieurs schémas d'activation. Cette étude clinique préliminaire montre que la modélisation de CRT est très prometteuse comme assistance à la planification thérapeutique. Dans une deuxième application nous avons adapté des méthodes d'assimilation de données développées dans l'Equipe-Projet MACS à l'INRIA, à des fins d'aide au diagnostic. Nous avons ainsi réalisé une estimation conjointe état-paramètres en utilisant des données réelles (IRM). Nous avons démontré l'efficacité de ces méthodes, et l'intérêt des paramètres de contractilité estimés comme indicateurs de la fonction du myocarde

    Signed-distance function based non-rigid registration of image series with varying image intensity

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    International audienceIn this paper we propose a method for locally adjusted optical flow-based registration of multimodal images, which uses the segmentation of the object of interest and its representation by the signed-distance function (OF dist method). We deal with non-rigid registration of the image series acquired by the Modiffied Look-Locker Inversion Recovery (MOLLI) magnetic resonance imaging sequence, which is used for a pixel-wise estimation of T 1 relaxation time. The spatial registration of the images within the series is necessary to compensate the patient's imperfect breath-holding. The evolution of intensities and a large variation of image contrast within the MOLLI image series, together with the myocardium of left ventricle (the object of interest) typically not being the most distinct object in the scene, makes the registration challenging. The paper describes all components of the proposed OF dist method and their implementation. The method is then compared to the performance of a standard mutual information maximization-based registration method, applied either to the original image (MIM) or to the signed-distance function (MIM dist). Several experiments with synthetic and real MOLLI images are carried out. On synthetic image with a single object, MIM performed the best, while OF dist and MIM dist provided better results on synthetic images with more than one object and on real images. When applied to signed-distance function of two objects of interest, MIM dist provided a larger registration error (but more homogeneously distributed) compared to OF dist. For the real MOLLI image series with left ventricle pre-segmented using a level-set method, the proposed OF dist registration performed the best, as is demonstrated visually and by measuring the increase of mutual information in the object of interest and its neighborhood

    Assessment of atrioventricular valve regurgitation using biomechanical cardiac modeling

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    International audienceIn this work we introduce the modeling of atrioventricular valve regurgitation in a spatially reduced order biomechanical heart model. The model can be fast calibrated using non-invasive data of cardiac magnetic resonance imaging and provides an objective measure of contractile properties of the myocardium in the volume overloaded ven-tricle, for which the real systolic function may be masked by the significant level of the atrioventricular valve regurgitation. After demonstrating such diagnostic capabilities, we show the potential of modeling to address some clinical questions concerning possible therapeutic interventions for specific patients. The fast running of the model allows targeting specific questions of referring clinicians in a clinically acceptable time
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