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Estimation of purkinje activation from ECG: An intermittent left bundle branch block study

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Sophie Giffard-Roisin, Lauren Fovargue, Jessica Webb, Roch Molléro, Jack Lee, Hervé Delingette, Nicholas Ayache, Reza Razavi, Maxime Sermesant

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer‐Verlag Berlin Heidelberg
Pages135-142
Number of pages8
Volume10124 LNCS
ISBN (Print)9783319527178
DOIs
Published24 Jan 2017
Event7th International Workshop on Statistical Atlases and Computational Models of the Heart Imaging and Modelling Challenges, STACOM 2016 Held in Conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece
Duration: 17 Oct 201621 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10124 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference7th International Workshop on Statistical Atlases and Computational Models of the Heart Imaging and Modelling Challenges, STACOM 2016 Held in Conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country/TerritoryGreece
CityAthens
Period17/10/201621/10/2016

Documents

King's Authors

Abstract

Modelling the cardiac electrophysiology (EP) can help understand pathologies and predict the response to therapies such as cardiac resynchronization. To this end, estimating patient-specific model parameters is crucial. In the case of patients with bundle branch blocks (BBB), part of the Purkinje system is often affected. The aim of this work is to estimate the activation of the right and left Purkinje systems from standard non-invasive techniques: magnetic resonance imaging (MRI) and 12-lead electrocardiogram (ECG). As it is difficult to differentiate the contribution of the Purkinje system, this work relies on a particular intermittent left BBB (LBBB) case where both LBBB and absence of LBBB (ALBBB) were recorded on different 12-lead ECGs. First, an efficient forward EP model is proposed by coupling a Mitchell-Schaeffer cardiac model with a current dipole formulation that simulates the ECG. We used the Covariance Matrix Adaptation Evolution Strategy (CMAES) algorithm to optimize the 3 parameters by minimizing the error with the real ECG. The estimation of conduction velocity (CV) parameters for LBBB and ALBBB shows a good agreement on the myocardial CV (0.39 m/s for ABBB, 0.40 m/s for LBBB), while the estimation of the left Purkinje CV seems to identify the pathology (1.32 m/s for ALBBB, 0.49 m/s for LBBB). Finally, the plots of the simulated 12-lead ECGs together with the ground truth ECGs indicate similar shapes.

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