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Estimation de la pression aortique à l'aide de l'imagerie par résonance magnétique : développement d'un modèle biomécanique d'écoulement

Abstract : Cardiovascular (CV) diseases remain the most common cause of death worldwide. Hypertension and left ventricle hypertrophy are two major risk factors associated to such diseases. In this context, aortic blood pressure is considered as a biomarker of increased CV risk and, more generally, a CV health indicator. In fact, it encodes information about biomechanical properties of central elastic arteries and represents left ventricle afterload. Assessment of this hemodynamic parameter is thus crucial for CV disease diagnosis and for evaluating therapeutic benefits. The aim of this work is to non-invasively assess the aortic blood pressure by coupling CV Magnetic Resonance Imaging (CV-MRI) to blood flow modeling. We thus developed a reduced one-dimensional (1D) flow model taking into account the fluid-structure interaction. A Windkessel (or zero-dimensional (0D)) model describing the arterial tree downstream of the aorta was coupled to the 1D segment. Both 1D model parameters and boundary conditions (inlet condition and 0D model parameters) were non-invasively determined using CV-MRI data. This gives the opportunity of deriving subject- or patient-specific blood flow models. To validate our approach, we applied our model to both healthy and pathologic aorta phantoms. Each phantom was mounted in an experimental setup reproducing as well as possible in vivo aortic flow and compatible with the MRI environment. Invasive pressure recording was compared to predicted pressure waves. We also performed a sensitivity analysis of our reduced 1D model.
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https://tel.archives-ouvertes.fr/tel-01892053
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Submitted on : Wednesday, October 10, 2018 - 11:52:07 AM
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Khalil Rachid. Estimation de la pression aortique à l'aide de l'imagerie par résonance magnétique : développement d'un modèle biomécanique d'écoulement. Physique Médicale [physics.med-ph]. Université Paris Saclay (COmUE), 2018. Français. ⟨NNT : 2018SACLS251⟩. ⟨tel-01892053⟩

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