GIFFARD-ROISIN , Sophie

The objective of this thesis is to use non-invasive data (body surface potentialmapping, BSPM) to personalise the main parameters of a cardiac electrophysiological(EP) model for predicting the response to cardiac resynchronization therapy(CRT). CRT is a clinically proven treatment option for some heart failures.However, these therapies are...

Although myocardial deformation imaging is often used in clinical practice, to date, the spatial resolution of any speckle tracking algorithm has not been tested. The minimum size of the resolvable dysfunctional areas with these techniques remains unknown while this is relevant for reliable clinical diagnosis. The current study therefore aimed...

Finite element methods (FEM) are generally used in cardiac 3D-electromechanical modeling. For FEM modeling, a step of a suitable mesh construction is required, which is non-trivial and time consuming for complex geometries. A meshless method is proposed to avoid meshing. The smoothed particle hydrodynamics (SPH) method was used to solve an...

In the scope of modelling cardiac electrophysiology (EP) for understanding pathologies and predicting the response to therapies, patient-specific model parameters need to be estimated. Although per-sonalisation from non-invasive data (body surface potential mapping, BSPM) has been investigated on simple cases mostly with a single pacing site,...

Goal: Non-invasive cardiac electrophysiology (EP) model personalisation has raised interest for instance in the scope of predicting EP cardiac resynchronization therapy (CRT) response. However, the restricted clinical applicability of current methods is due in particular to the limitation to simple situations and the important computational...

The use of synthetic sequences is one of the most promising tools for advanced in silico evaluation of the quantification of cardiac deformation and strain through 3D ultrasound (US) and magnetic resonance (MR) imaging. In this paper, we propose the first simulation framework which allows the generation of realistic 3D synthetic cardiac US and...

Rule-based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule-based methods often does not match histological data in other areas of the heart such as the right...

Myocardial fiber orientation determines the propagation of electrical waves in the heart and the contraction of cardiac tissue. One common approach for assigning fiber orientation to cardiac anatomical models are Rule-Based Methods (RBM). However, RBM have been developed to assimilate data mostly from the Left Ventricle. In consequence, fiber...