A Rule-Based Method to Model Myocardial Fiber Orientation for Simulating Ventricular Outflow Tract Arrhythmias

Abstract : Myocardial fiber orientation determines the propagation of electrical waves in the heart and the contraction of cardiac tissue. One common approach for assigning fiber orientation to cardiac anatomical models are Rule-Based Methods (RBM). However, RBM have been developed to assimilate data mostly from the Left Ventricle. In consequence, fiber information from RBM does not match with histological data in other areas of the heart, having a negative impact in cardiac simulations beyond the LV. In this work, we present a RBM where fiber orientation is separately modeled in each ventricle following observations from histology. This allows to create detailed fiber orientation in specific regions such as the right ventricle endocardium, the interventricular septum and the outflow tracts. Electrophysiological simulations including these anatomical structures were then performed, with patient-specific data of outflow tract ventricular arrhythmias (OTVA) cases. A comparison between the obtained simulations and electro-anatomical data of these patients confirm the potential for in silico identification of the site of origin in OTVAs before the intervention.
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Communication dans un congrès
Lecture Notes in Computer Science. Functional imaging and modelling of the heart 2017, Jun 2017, Toronto, Canada. 10263, 2017, Functional imaging and modelling of the heart 2017 Proceedings. 〈10.1007/978-3-319-59448-4_33〉
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https://hal.inria.fr/hal-01533389
Contributeur : Sophie Giffard-Roisin <>
Soumis le : mardi 6 juin 2017 - 13:51:02
Dernière modification le : mercredi 30 mai 2018 - 13:56:03

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Rubén Doste, David Soto-Iglesias, Gabriel Bernardino, Rafael Sebastian, Sophie Giffard-Roisin, et al.. A Rule-Based Method to Model Myocardial Fiber Orientation for Simulating Ventricular Outflow Tract Arrhythmias. Lecture Notes in Computer Science. Functional imaging and modelling of the heart 2017, Jun 2017, Toronto, Canada. 10263, 2017, Functional imaging and modelling of the heart 2017 Proceedings. 〈10.1007/978-3-319-59448-4_33〉. 〈hal-01533389〉

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