Biomedical subjects

M Sermesant

Publications and source records attributed to M Sermesant.

6 recordsLinked to original sources

PubMed2006

Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties.

In this paper, we present a framework to estimate local ventricular myocardium contractility using clinical MRI, a heart model and data assimilation. First, we build a generic anatomical model of the ventricles including muscle fibre orientations and anatomical subdivisions. Then, this model is deformed to fit a clinical MRI, using a semi-automatic fuzzy segmentation, an affine registration method and a local deformable biomechanical model. An electromechanical model of the heart is then presented and simulated. Finally, a data assimilation procedure is described, and applied to this model. Data assimilation makes it possible to estimate local contractility from given displacements. Presented results on fitting to patient-specific anatomy and assimilation with simulated data are very promising. Current work on model calibration and estimation of patient parameters opens up possibilities to apply this framework in a clinical environment.

Adult↗

PubMed2006

An electromechanical model of the heart for image analysis and simulation.

This paper presents a new three-dimensional electromechanical model of the two cardiac ventricles designed both for the simulation of their electrical and mechanical activity, and for the segmentation of time series of medical images. First, we present the volumetric biomechanical models built. Then the transmembrane potential propagation is simulated, based on FitzHugh-Nagumo reaction-diffusion equations. The myocardium contraction is modeled through a constitutive law including an electromechanical coupling. Simulation of a cardiac cycle, with boundary conditions representing blood pressure and volume constraints, leads to the correct estimation of global and local parameters of the cardiac function. This model enables the introduction of pathologies and the simulation of electrophysiology interventions. Moreover, it can be used for cardiac image analysis. A new proactive deformable model of the heart is introduced to segment the two ventricles in time series of cardiac images. Preliminary results indicate that this proactive model, which integrates a priori knowledge on the cardiac anatomy and on its dynamical behavior, can improve the accuracy and robustness of the extraction of functional parameters from cardiac images even in the presence of noisy or sparse data. Such a model also allows the simulation of cardiovascular pathologies in order to test therapy strategies and to plan interventions.

Body Surface Potential Mapping↗

PubMed2005

Localization of abnormal conduction pathways for tachyarrhythmia treatment using tagged MRI.

Tachyarrhythmias are pathological fast heart rhythms often caused by abnormally conducting myocardial areas (foci). Treatment by radio-frequency (RF) ablation uses electrode-catheters to monitor and destroy foci. The procedure is normally guided with x-rays (2D), and thus prone to errors in location and excessive radiation exposure. Our main goal is to provide pre- and intra-operative 3D MR guidance in XMR systems by locating the abnormal conduction pathways. We address the inverse electro-mechanical relation by using motion in order to infer electrical propagation. For this purpose we define a probabilistic measure of the onset of regional myocardial activation, derived from 3D motion fields obtained by tracking tagged MR sequences with non-rigid registration. Activation isochrones are then derived to determine activation onset. We also compare regional motion between two different image acquisitions, thus assisting in diagnosing arrhythmia, in follow up of treatment, and in determining whether the ablation was successful. Difference maps of isochrones and other motion descriptors are computed to determine abnormal patterns. Validation was carried out using an electromechanical model of the heart, synthetic data, a cardiac MRI atlas of motion and geometry, MRI data from 6 healthy volunteers (one of them subjected to stress), and an MRI study on a patient with tachyarrhythmia, before and after RF ablation. A pre-operative MRI study on a second patient with tachyarrhythmia was used to test the methodology in a clinical scenario, predicting the abnormally conducting region.

Adult↗

PubMed2005

A fast-marching approach to cardiac electrophysiology simulation for XMR interventional imaging.

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 solve Eikonal-based models on triangular meshes. These models can be used to extract hidden parameters of the cardiac function from clinical data in a very short time, thus could be used during interventions. We propose a first approach to estimate these parameters, and have tested it on synthetic and real data derived using XMR imaging. We demonstrated a qualitative matching between the estimated parameter and XMR data. This novel approach opens up possibilities to directly integrate modelling in the interventional room.

Action Potentials↗

PubMed2005

Simulation of cardiac pathologies using an electromechanical biventricular model and XMR interventional imaging.

Simulating cardiac electromechanical activity is of great interest for a better understanding of pathologies and for therapy planning. Design and validation of such models is difficult due to the lack of clinical data. XMR systems are a new type of interventional facility in which patients can be rapidly transferred between X-ray and MR systems. Our goal is to design and validate an electromechanical model of the myocardium using XMR imaging. The proposed model is computationally fast and uses clinically observable parameters. We present the integration of anatomy, electrophysiology, and motion from patient data. Pathologies are introduced in the model and simulations are compared to measured data. Initial qualitative comparison on the two clinical cases presented is encouraging. Once fully validated, these models will make it possible to simulate different interventional strategies.

Algorithms↗

PubMed2003

Deformable biomechanical models: application to 4D cardiac image analysis.

This article describes a methodology for creating a generic volumetric biomechanical model from different image modalities and segmenting time series of medical images using this model. The construction of such a generic model consists of three stages: geometric meshing, non-rigid deformation of the mesh in images of various modalities, and image-to-mesh information mapping through rasterization. The non-rigid deformation stage, which relies on a combination of global and local deformations, can then be used to segment time series of images, e.g. cine MRI or gated SPECT cardiac images. We believe that this type of deformable biomechanical model can play an important role in the extraction of useful quantitative local parameters of cardiac function. The biomechanical model of the heart will be coupled with an electrical model of another collaborative project in order to simulate and analyze a larger class of pathologies.

Algorithms↗