Local Conduction Velocity Mapping for Electrocardiographic Imaging

International audienceSlow conduction is a well-known pro-arrhythmic feature for tachycardia and fibrillation. Cardiac conduction velocity (CV) mapping can be extremely helpful for investigating unusual activation patterns. Although methods have been developed to estimate velocity vector field, from ex-vivo preparations (e.g. from optical mapping recordings), the estimation from in-vivo electrograms (EGMs) remains challenging. This paper presents a new method specifically designed for EGMs reconstructed non-invasively from body surface potentials using electrocardiographic imaging (ECGi). The algorithm is based on cardiac activation maps and assumes either a linear or quadratic wavefront shape. The proposed methodology was performed on computed and experimental data for epicardial pacing on healthy tissue. The results were compared with reference velocity vector fields and evaluated by analyzing the errors of direction and speed. The outcomes indicate that a linear wavefront is the most suited for cardiac propagation in healthy tissue

Local characterization of cardiac activation wavefront propagation to aid diagnosis of atrial and ventricular tachycardias : application for non-invasive electrocardiographic imaging

Les tachycardies ventriculaires (TV) et atriales (TA) sont les arythmies les plus fréquemment diagnostiquées en clinique. En vue d’ablater les tissus pathologiques, deux techniques de diagnostic sont utilisées : la cartographie électro-anatomique pour un diagnostic précis à l’aide d’électrogrammes (EGM) mesurés par cathéters intracardiaques et repérés sur la géométrie tridimensionnelle (3-D) de la cavité étudiée ; et l’imagerie électrocardiographique non-invasive (ECGi) pour une vision globale de l’arythmie, avec des EGM reconstruits mathématiquement à partir des électrocardiogrammes et des géométries cardio-thoraciques 3-D obtenues par CT-Scan. Les TV et TA sont alors diagnostiquées en étudiant les cartes d’activation qui sont des représentations des temps de passage locaux de l’onde d’activation sur la géométrie 3-D cardiaque. Cependant, les zones de ralentissement favorisant les TV et TA, et leurs motifs de propagation spécifiques n’y sont pas facilement identifiables. Ainsi, la caractérisation locale de la propagation de l’onde d’activation peut être utile pour améliorer le diagnostic. L’objet de cette thèse est le développement d’une méthode de caractérisation locale de la propagation de l’onde d’activation. Pour cela, un champ vectoriel de vitesse est estimé et analysé. La méthode a en premier lieu été validée sur des données simulées issues de modélisation, puis appliquée 1) à des données cliniques issues de l’ECGi pour la localisation des cicatrices d’infarctus et pour améliorer le diagnostic des TA; et 2) sur des données obtenues par cartographie électro-anatomique pour caractériser les zones pathogènes.Ventricular (VT) and atrial (AT) tachycardias are some of the most common clinical cardiac arrhythmias. For ablation of tachycardia substrates, two clinical diagnosis methods are used : electro-anatomical mapping for an accurate diagnosis using electrograms (EGMs) acquired with intracardiac catheters and localized on the three-dimensional (3-D) mesh of the studied cavities ; and non-invasive electrocardiographic imaging (ECGi) for a global view of the arrhythmia, with EGMs mathematically reconstructed from body surface electrocardiograms and the 3-D cardio-thoracic meshes obtained with CT-scan. VT and AT are diagnosed studying activation time maps ; that are 3-D representations of the transit time of the activation wavefront on the cardiac mesh. Nevertheless, slow conduction areas, a well-known pro-arrhythmic feature for tachycardias, and the tachycardias specific propagation patterns are not easily identifiable with these maps. Hence, local characterization of the activation wavefront propagation can be helpful for improving VT and AT diagnosis. The purpose of this thesis is to develop a method to locally characterize the activation wavefront propagation. For that, a conduction velocity vector field is estimated and analyzed. The method was first validated on a simulated database from computer models, then applied to 1) a clinical database obtained from ECGi to localize infarct tissues and improve AT diagnosis ; and 2) a clinical database acquired with electro-anatomical mapping systems to define pathological areas

Caractérisation locale de la propagation de l’onde d’activation cardiaque pour l’aide au diagnostic des tachycardies atriales et ventriculaires : application à l’imagerie électrocardiographique non-invasive

Ventricular (VT) and atrial (AT) tachycardias are some of the most common clinical cardiac arrhythmias. For ablation of tachycardia substrates, two clinical diagnosis methods are used : electro-anatomical mapping for an accurate diagnosis using electrograms (EGMs) acquired with intracardiac catheters and localized on the three-dimensional (3-D) mesh of the studied cavities ; and non-invasive electrocardiographic imaging (ECGi) for a global view of the arrhythmia, with EGMs mathematically reconstructed from body surface electrocardiograms and the 3-D cardio-thoracic meshes obtained with CT-scan. VT and AT are diagnosed studying activation time maps ; that are 3-D representations of the transit time of the activation wavefront on the cardiac mesh. Nevertheless, slow conduction areas, a well-known pro-arrhythmic feature for tachycardias, and the tachycardias specific propagation patterns are not easily identifiable with these maps. Hence, local characterization of the activation wavefront propagation can be helpful for improving VT and AT diagnosis. The purpose of this thesis is to develop a method to locally characterize the activation wavefront propagation. For that, a conduction velocity vector field is estimated and analyzed. The method was first validated on a simulated database from computer models, then applied to 1) a clinical database obtained from ECGi to localize infarct tissues and improve AT diagnosis ; and 2) a clinical database acquired with electro-anatomical mapping systems to define pathological areas.Les tachycardies ventriculaires (TV) et atriales (TA) sont les arythmies les plus fréquemment diagnostiquées en clinique. En vue d’ablater les tissus pathologiques, deux techniques de diagnostic sont utilisées : la cartographie électro-anatomique pour un diagnostic précis à l’aide d’électrogrammes (EGM) mesurés par cathéters intracardiaques et repérés sur la géométrie tridimensionnelle (3-D) de la cavité étudiée ; et l’imagerie électrocardiographique non-invasive (ECGi) pour une vision globale de l’arythmie, avec des EGM reconstruits mathématiquement à partir des électrocardiogrammes et des géométries cardio-thoraciques 3-D obtenues par CT-Scan. Les TV et TA sont alors diagnostiquées en étudiant les cartes d’activation qui sont des représentations des temps de passage locaux de l’onde d’activation sur la géométrie 3-D cardiaque. Cependant, les zones de ralentissement favorisant les TV et TA, et leurs motifs de propagation spécifiques n’y sont pas facilement identifiables. Ainsi, la caractérisation locale de la propagation de l’onde d’activation peut être utile pour améliorer le diagnostic. L’objet de cette thèse est le développement d’une méthode de caractérisation locale de la propagation de l’onde d’activation. Pour cela, un champ vectoriel de vitesse est estimé et analysé. La méthode a en premier lieu été validée sur des données simulées issues de modélisation, puis appliquée 1) à des données cliniques issues de l’ECGi pour la localisation des cicatrices d’infarctus et pour améliorer le diagnostic des TA; et 2) sur des données obtenues par cartographie électro-anatomique pour caractériser les zones pathogènes

Adaptive placement of the pseudo-boundaries improves the conditioning of the inverse problem

Meshing the heart and measurement surfaces can be time consuming, especially when dealing with complicated geometries or cardiac motion. To overcome this, a meshless method based on the method of fundamental solutions (MFS) has been adapted to non-invasive electrocardiographic imaging (ECGI). In the MFS, potentials are expressed as a summation over a discrete set of virtual point sources placed outside of the domain of interest (named 'pseudo-boundary'). It is well-known that optimal placement of the pseudo-boundary can improve the efficacy of the MFS. Despite this, there have been no attempts to optimize their placement in the ECGI problem as far as we are aware. In the standard MFS, the sources are placed in two pseudo-boundaries constructed by inflating and deflating the heart and torso surfaces with respect to the geometric center of the heart. However, for some heart-torso geometries, this geometric center is a poor reference. We here show that adaptive placement of the pseudo-boundaries (depending on the distance between the torso electrodes and the nearest heart locations) improves the conditioning of the inverse problem, making it less sensitive to the regularization process.L'Institut de Rythmologie et modélisation Cardiaqu

Adaptive placement of the pseudo-boundaries improves the conditioning of the inverse problem

Meshing the heart and measurement surfaces can be time consuming, especially when dealing with complicated geometries or cardiac motion. To overcome this, a meshless method based on the method of fundamental solutions (MFS) has been adapted to non-invasive electrocardiographic imaging (ECGI). In the MFS, potentials are expressed as a summation over a discrete set of virtual point sources placed outside of the domain of interest (named ‘pseudo-boundary’). It is well-known that optimal placement of the pseudoboundary can improve the efficacy of the MFS. Despite this, there have been no attempts to optimize their placement in the ECGI problem as far as we are aware. In the standard MFS, the sources are placed in two pseudo-boundaries constructed by inflating and deflating the heart and torso surfaces with respect to the geometric center of the heart. However, for some heart-torso geometries, this geometric center is a poor reference. We here show that adaptive placement of the pseudoboundaries (depending on the distance between the torso electrodes and the nearest heart locations) improves the conditioning of the inverse problem, making it less sensitive to the regularization process.This study received financial support from the French Government as part of the “Investments of the Future” program managed by the National Research Agency (ANR), Grant reference ANR-10-IAHU-04 and from the Conseil Régional Aquitaine as part of the project “Assimilation de données en cancérologie et cardiologie”

Adaptive placement of the pseudo-boundaries improves the conditioning of the inverse problem

Meshing the heart and measurement surfaces can be time consuming, especially when dealing with complicated geometries or cardiac motion. To overcome this, a meshless method based on the method of fundamental solutions (MFS) has been adapted to non-invasive electrocardiographic imaging (ECGI). In the MFS, potentials are expressed as a summation over a discrete set of virtual point sources placed outside of the domain of interest (named ‘pseudo-boundary’). It is well-known that optimal placement of the pseudoboundary can improve the efficacy of the MFS. Despite this, there have been no attempts to optimize their placement in the ECGI problem as far as we are aware. In the standard MFS, the sources are placed in two pseudo-boundaries constructed by inflating and deflating the heart and torso surfaces with respect to the geometric center of the heart. However, for some heart-torso geometries, this geometric center is a poor reference. We here show that adaptive placement of the pseudoboundaries (depending on the distance between the torso electrodes and the nearest heart locations) improves the conditioning of the inverse problem, making it less sensitive to the regularization process.This study received financial support from the French Government as part of the “Investments of the Future” program managed by the National Research Agency (ANR), Grant reference ANR-10-IAHU-04 and from the Conseil Régional Aquitaine as part of the project “Assimilation de données en cancérologie et cardiologie”

Local Conduction Velocity Mapping for Electrocardiographic Imaging

Slow conduction is a well-known pro-arrhythmic feature for tachycardia and fibrillation. Cardiac conduction velocity (CV) mapping can be extremely helpful for investigating unusual activation patterns. Although methods have been developed to estimate velocity vector field, from ex-vivo preparations (e.g. from optical mapping recordings), the estimation from in-vivo electrograms (EGMs) remains challenging. This paper presents a new method specifically designed for EGMs reconstructed non-invasively from body surface potentials using electrocardiographic imaging (ECGi). The algorithm is based on cardiac activation maps and assumes either a linear or quadratic wavefront shape. The proposed methodology was performed on computed and experimental data for epicardial pacing on healthy tissue. The results were compared with reference velocity vector fields and evaluated by analyzing the errors of direction and speed. The outcomes indicate that a linear wavefront is the most suited for cardiac propagation in healthy tissue

Effect of the torso conductivity heterogeneities on the ECGI inverse problem solution

The effect of torso conductivity heterogeneities on the electrocardiographic imaging (ECGI) inverse problem solution is still subject of debate. In this study we present a method to assess the effect of these heterogeneities. We use an anatomical model containing the heart the lungs the bones and the torso surfaces. We use the bidomain model and we solve it using finite element methods in order to generate in silico data taking into account the torso heterogeneities. We add different noise levels on the body surface potentials and we solve the inverse problem for both homogenous and heterogeneous torso conductivities. We analyse the reconstructed solution using the relative error and the correlation coefficient

Cardiac Propagation Pattern Mapping With Vector Field for Helping Tachyarrhythmias Diagnosis With Clinical Tridimensional Electro-Anatomical Mapping Tools

Ventricular (VT) and atrial (AT) tachycardias are some of the most common clinical cardiac arrhythmias. For ablation of tachycardia substrates, two clinical diagnosis methods are used: invasive electroanatomical mapping for an accurate diagnosis using electrograms (EGMs) acquired with intracardiac catheters, and localized on the surface mesh of the studied cavities; and noninvasive electrocardiographic imaging (ECGi) for a global view of the arrhythmia, with EGMs mathematically reconstructed from body surface electrocardiograms using 3-D cardio-thoracic surface meshes obtained from CT-scans. In clinics, VT and AT are diagnosed by studying activation time maps that depict the propagation of the activation wavefront on the cardiac mesh. Nevertheless, slow conduction areas-a well-known proarrhythmic feature for tachycardias-and tachycardia specific propagation patterns are not easily identifiable with these maps. Therefore, local characterization of the activation wavefront propagation can be helpful for improving VT and AT diagnoses. The purpose of this study is to develop a method to locally characterize the activation wavefront propagation for clinical data. For this, a conduction velocity vector field is estimated and analyzed using divergence and curl mathematical operators. The workflow was first validated on a simulated database from computer models, and then applied to a clinical database obtained from ECGi to improve AT diagnosis. The results show the relevancy and the efficacy of the proposed method to guide ablation of tachyarrhythmias