Data fusion of left ventricle Electro-Anatomic Mapping and Multislice Computerized Tomography for Cardiac Resynchronisation Therapy optimization

International audienceCardiac Resynchronization Therapy is a treatment for bi-ventricular asynchronism. It can be optimized by the identification of the most effective pacing sites. The aim of this study is to provide a helpful tool to perform this identification by the fusion of electrical and anatomical information resulting from Electro-Anatomic Mapping (EAM) data and Multislice Computerized Tomography (MSCT) imaging. EAM data provide an approximation of the left ventricle (LV) 3D-surface (SEAM). Left cardiac chambers are segmented from MSCT imaging and surfaces are reconstructed (SCT). In order to represent this information in a unified framework, a three steps method is proposed: (1) the LV is separated from the left auricle on SCT providing S'CT; (2) a semi-automatic rigid registration method is applied to SEAM and S'CT; (3) activation time delays are estimated on S'CT from the EAM data. This method results in a graphical interface offering to clinicians means to identify abnormal electrical activity sites

Recalage et fusion d'informations multimodales pour l'optimisation de la thérapie de resynchronisation cardiaque

This work is based on the registration and the fusion of multi-modality data for cardiac resynchronization therapy (CRT) optimization. Local descriptors of the electro-mechanical coupling of the heart are extracted from anatomical, functional and mechanical data acquired from CT-scan volumes (CT), speckle tracking echocardiography (STE) and electro-anatomical mapping (EAM). The proposed approach is based on the registration of multi-modality data on a 3D+t model of the left ventricle (LV) computed from CT segmented surfaces. It consists in two steps : (1) the semi-interactive registration of EAM data and CT images ; (2) the registration of STE data on the dynamic model for which two automatic methods (one static, the other dynamic) have been developed. These step consider a radial based projection and an interpolation (radial basis function) of the electrical data on the proposed model as well as the synchronization and matching (by dynamic time warping) of temporal instants between the EAM and STE data. These methods allow the possibility to compute, under different cardiac stimulation modes, local activation times, voltage maps, mechanical delays and local electro-mechanical delays. The vizualisation (by 3D and 2D maps) of these descriptors gives the means to characterize the intra-segments electro-mechanical coupling of the LV. These methods have been applied on simulated and real data. They show the feasibility of extracting local descriptors of the cardiac function that are significant for the optimization of stimulation probes implantation in CRT.Ces travaux portent sur le recalage et la fusion d'informations multimodales dans le cadre de l'optimisation de la thérapie de resynchronisation cardiaque (CRT). Des descripteurs locaux du couplage électromécanique cardiaque sont extraits à partir d'informations anatomiques, fonctionnelles, électriques et mécaniques issues de volumes scanner (CT), d'échocardiographie par ''speckle tracking'' (US) et de cartographies électroanatomiques (EAM). L'approche proposée repose sur le recalage des données multimodales sur un modèle 3D+t du ventricule gauche (VG) calculé à partir de surfaces segmentées. Cette approche procède en deux temps : (1) un recalage semi-interactif des données EAM et d'images CT ; (2) un recalage de données US avec le modèle dynamique pour lequel les deux méthodes automatiques (statique et dynamique) ont été développées. Ces techniques intègrent un mode de projection radiale et une interpolation de mise en correspondance temporelle (par Dynamic Time Warping) des données EAM et US. Ces méthodes offrent la possibilité de calculer, sous différents modes de simulation cardiaque, les délais d'activation électrique, les cartes de voltage, les délais mécaniques et les délais électromécaniques locaux. La visualisation (cartographies 3D et 2D) de ces descripteurs permet de caractériser le couplage électromécanique intra-segments du VG. Ces méthodes ont été appliquées sur données simulées et réelles. Elles ont montré leur pertinence quant à la possibilité d'extraire des descripteurs locaux de la fonction cardiaque significatifs pour l'optimisation de la pose de stimulateur en CRT

Recalage et fusion d'informations multimodales pour l'optimisation de la thérapie de resynchronisation cardiaque

Ces travaux portent sur le recalage et la fusion d'informations multimodales dans le cadre de l'optimisation de la thérapie de resynchronisation cardiaque (CRT). Des descripteurs locaux du couplage électromécanique cardiaque sont extraits à partir d'informations anatomiques, fonctionnelles, électriques et mécaniques issues de volumes scanner (CT), d'échocardiographie par ''speckle tracking'' (US) et de cartographies électroanatomiques (EAM). L'approche proposée repose sur le recalage des données multimodales sur un modèle 3D+t du ventricule gauche (VG) calculé à partir de surfaces segmentées. Cette approche procède en deux temps : (1) un recalage semi-interactif des données EAM et d'images CT ; (2) un recalage de données US avec le modèle dynamique pour lequel les deux méthodes automatiques (statique et dynamique) ont été développées. Ces techniques intègrent un mode de projection radiale et une interpolation de mise en correspondance temporelle (par Dynamic Time Warping) des données EAM et US. Ces méthodes offrent la possibilité de calculer, sous différents modes de simulation cardiaque, les délais d'activation électrique, les cartes de voltage, les délais mécaniques et les délais électromécaniques locaux. La visualisation (cartographies 3D et 2D) de ces descripteurs permet de caractériser le couplage électromécanique intra-segments du VG. Ces méthodes ont été appliquées sur données simulées et réelles. Elles ont montré leur pertinence quant à la possibilité d'extraire des descripteurs locaux de la fonction cardiaque significatifs pour l'optimisation de la pose de stimulateur en CRT.This work is based on the registration and the fusion of multi-modality data for cardiac resynchronization therapy (CRT) optimization. Local descriptors of the electro-mechanical coupling of the heart are extracted from anatomical, functional and mechanical data acquired from CT-scan volumes (CT), speckle tracking echocardiography (STE) and electro-anatomical mapping (EAM). The proposed approach is based on the registration of multi-modality data on a 3D+t model of the left ventricle (LV) computed from CT segmented surfaces. It consists in two steps : (1) the semi-interactive registration of EAM data and CT images ; (2) the registration of STE data on the dynamic model for which two automatic methods (one static, the other dynamic) have been developed. These step consider a radial based projection and an interpolation (radial basis function) of the electrical data on the proposed model as well as the synchronization and matching (by dynamic time warping) of temporal instants between the EAM and STE data. These methods allow the possibility to compute, under different cardiac stimulation modes, local activation times, voltage maps, mechanical delays and local electro-mechanical delays. The vizualisation (by 3D and 2D maps) of these descriptors gives the means to characterize the intra-segments electro-mechanical coupling of the LV. These methods have been applied on simulated and real data. They show the feasibility of extracting local descriptors of the cardiac function that are significant for the optimization of stimulation probes implantation in CRT.RENNES1-BU Sciences Philo (352382102) / SudocSudocFranceF

Fusion of MSCT imaging, Electro-Anatomical Mapping and Speckle Tracking Echocardiography for the characterization of local electro-mechanical delays in CRT optimization.

International audienceIn this work, we sought to assist the optimization of Cardiac Resynchronization Therapy (CRT) through the characterization of electro-mechanical delays for each region of the Left Ventricle. This characterization is based on the fusion of electrical, mechanical and anatomical data acquired from Electro-Anatomical Mapping (EAM), Speckle Tracking Echocardiography (STE) and Multislice CT (MSCT) imaging, respectively. Using MSCT as a reference, the first step is the registration of EAM 3D maps and STE 2D Contours on extracted MSCT LV-surfaces. After this registration step, local electrical and mechanical activation times can be displayed in the same space through 2D quantitative maps, therefore allowing the computation of local electro-mechanical delays. Local and global electro-mechanical delays from septal and lateral walls were calculated for three patients. The complementary information obtained may be useful for a better patient selection for CRT

Multimodal Registration and Data Fusion for Cardiac Resynchronization Therapy Optimization

International audienceCardiac Resynchronization Therapy (CRT) has been shown to improve cardiovascular function in specific patients suffering from heart failure. This procedure still needs to be optimized to overcome the high rate of implanted patients that do not respond to this therapy. We propose in this work a better characterization of the electro-mechanical (EM) coupling of each region of the left ventricle (LV) that could be useful to precise the best implantation site. A new descriptor is proposed with the extraction of local electro-mechanical delays. Their measurement is based on the fusion of anatomical, functional and electrical data acquired using computed tomography (CT), speckle tracking echocardiography (STE) and electro-anatomical mappings (EAM). We propose a workflow to place multimodal data in the same geometrical referential system and to extract local electro-mechanical descriptors. It implies the fusion of electrical and mechanical data on a 3D+t anatomical model of the left ventricle (LV). It mainly consists in four steps: (1) the modeling of the endocardium using a dynamic surface estimated from CT images; (2) the semi-interactive registration of EAM data and CT images; (3) the automatic registration of STE data on the dynamic model, using a metric based on Fourier descriptors and Dynamic Time Warping (DTW); (4) the temporal alignment between EAM and STE and the estimation of local electro-mechanical delays. The proposed process has been applied to real data corresponding to five patients undergoing CRT. Results show that local electro-mechanical delays provide meaningful information on the local characterization of the LV and may be useful for the optimal pacing site selection in CRT

Segmentation-free MRI to CT 3D registration for Cardiac Resynchronization Therapy optimization.

International audienceThe purpose of this work is to include tissue and dynamic information from cardiac magnetic resonance (CMR) sequences in a previously proposed fusion framework aiming to optimize Cardiac Resynchronization Therapy (CRT). To do so, the 3D iconic registration between 3D+t cardiac MR and 3D+t cardiac computed tomography (CT) sequences is explored. Two rigid registration approaches have been evaluated: end-diastole (ED) images registration and dynamical time warping (DTW) based registration. DTW is used to align both sequences in time. They are tested on five patients that underwent for CRT. Quantitative evaluation has been performed using the dice score between ED delineations of left ventricle (LV). An average error of 4.71% (std 4.58%) is obtained for ED registration. For DTW registration, an average error of 2.68% (std 2.76%) is obtained using the normalized correlation curves of MR and CT sequences. These results demonstrate the feasibility to perform a 3D registration of MR and CT sequences without the need of temporal interpolation

Fusion De Données De Cartographie Électro-Anatomique Et D'imagerie Scanner Multibarette Pour La Resynchronisation Cardiaque.

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Dynamic registration of cardiac US and CT data using Fourier descriptors and Dynamic Time Warping.

International audienceCardiac Resynchronization Therapy (CRT) can be optimized by the fusion of anatomical, functional and electrical information in a unified framework in order to identify the most effective pacing sites. The aim of this work is to perform a registration between dynamic CT and ultrasound (US) images (2D speckle tracking mode). The proposed registration approach is based on a contour to surface scheme, decomposed in four steps: (1) the temporal synchronization of data; (2) the segmentation of the left ventricle endocardial surface from the 3D+t CT data; (3) the segmentation and tracking of the myocardium from the 2D+t US data; (4) the registration of US contour with the CT surface. The originality of the method relies on the use of Fourier descriptors and Dynamic Time Warping (DTW) to handle different spatial and temporal resolutions as well as dissimilar cardiac rhythms between CT and US data. An evaluation on simulated data is described as well as results obtained on three patient databases

Data Fusion of Left Ventricle Electro-Anatomic Mapping and Multislice Computerized Tomography.

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Registration of dynamic multiview 2D ultrasound and late gadolinium enhanced images of the heart: Application to hypertrophic cardiomyopathy characterization

International audienceDescribing and analyzing heart multiphysics requires the acquisition and fusion of multisensor cardiac images. Multisensor image fusion enables a combined analysis of these heterogeneous modalities. We propose to register intra-patient multiview 2D+t ultrasound (US) images with multiview late gadolinium-enhanced (LGE) images acquired during cardiac magnetic resonance imaging (MRI), in order to fuse mechanical and tissue state information. The proposed procedure registers both US and LGE to cine MRI. The correction of slice misalignment and the rigid registration of multiview LGE and cine MRI are studied, to select the most appropriate similarity measure. It showed that mutual information performs the best for LGE slice misalignment correction and for LGE and cine registration. Concerning US registration, dynamic endocardial contours resulting from speckle tracking echocardiography were exploited in a geometry-based dynamic registration. We propose the use of an adapted dynamic time warping procedure to synchronize cardiac dynamics in multiview US and cine MRI. The registration of US and LGE MRI was evaluated on a dataset of patients with hypertrophic cardiomyopathy. A visual assessment of 330 left ventricular regions from US images of 28 patients resulted in 92.7% of regions successfully aligned with cardiac structures in LGE. Successfully-aligned regions were then used to evaluate the abilities of strain indicators to predict the presence of fibrosis. Longitudinal peak-strain and peak-delay of aligned left ventricular regions were computed from corresponding regional strain curves from US. The Mann-Withney test proved that the expected values of these indicators change between the populations of regions with and without fibrosis (p \textless 0.01). ROC curves otherwise proved that the presence of fibrosis is one factor amongst others which modifies longitudinal peak-strain and peak-dela