RHODE , Kawal

International audience

Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010

Computer models of cardiac electrophysiology (EP) can help to better understand the mechanisms of arrhythmias and to guide interventions. However, model adjustment to patient data (personalization) is a required step that is still challenging from clinical data. The progress in the fusion of multimodal data opens up new possibilities in...

Cardiac ablation procedures are becoming more routine to treat arrhythmias. The development of electrophysiological models will allow investigation of treatment strategies. However, current models are computationally expensive and often too complex to be adjusted with current clinical data. In this paper, we have proposed a fast algorithm to...

no abstract

no abstract

Despite recent efforts in cardiac electrophysiology modelling, there is still a strong need to make macroscopic models usable in planning and assistance of the clinical procedures. This requires model personalisation i.e. estimation of patient-specific model parameters and computations compatible with clinical constraints. Fast macroscopic...

Despite recent efforts in cardiac electrophysiology modelling [1], there is still a strong need to make macroscopic models usable in planning and assistance of the clinical procedures. This requires model personalisation i.e. estimation of patient-specific model parameters and computations compatible with clinical constraints. Fast macroscopic...

no abstract

no abstract

Patient-speci c cardiac modelling can help in understanding pathophysiology and predict therapy planning. However it requires to personalize the model geometry, kinematics, electrophysiology and me- chanics. Calibration aims at providing global values (space invariant) of parameters before performing the personalization stage which involves...

In order to translate the important progress in cardiac electrophysiology modelling of the last decades into clinical applications, there is a requirement to make macroscopic models that can be used for the planning and performance of the clinical procedures. This requires model personalization, i.e. estimation of patient-specific model...

Model personalization is a key aspect for biophysical models to impact clinical practice, and cardiac contractility personalization from medical images is a major step in this direction. Existing gradient-based optimization approaches show promising results of identifying the maximum contractility from images, but the contraction and relaxation...

This article presents a framework for building patient-specific models of the myocardium, to help diagnosis, therapy planning, and procedure guidance. The aim is to be able to introduce such models in clinical applications. Thus, there is a need to design models that can be adjusted from clinical data, images, or signals, which are sparse and...

Personalization is a key aspect of biophysical models in order to impact clinical practice. In this paper, we propose a personalization method of electromechanical models of the heart from cine-MR images based on the adjoint method. After estimation of electrophysiological parameters, the cardiac motion is estimated based on a proactive...

Patient-specific cardiac modelling can help in understanding pathophysiology and predict therapy effects. This requires the personalization of the geometry, kinematics, electrophysiology and mechanics. We use the Bestel-Clément-Sorine (BCS) electromechanical model of the heart, which provides reasonable accuracy with a reduced parameter number...

While abnormal patterns of cardiac electrophysiological activation are at the origin of important cardiovascular diseases (e.g. arrhythmia, asynchrony), the only clinically available method to observe detailed left ventricular endocardial surface activation pattern is through invasive catheter mapping. However this electrophysiological...

no abstract