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[EN] Optimization of lead placement and interventricular delay settings in patients under cardiac resynchronization therapy is a complex task that might benefit from prior information based on models. Biophysical models can be used to predict the sequence of electrical heart activation in a patient given a set of parameters which should be personalized to the patient. In this paper, we use electroanatomical maps to personalize the endocardial activation of the right ventricle, and the different tissue conductivities in a pig model with left bundle branch block, to reproduce personalized biventricular activations. Following, we tested the personalized heart model by virtually simulating cardiac resynchronization therapy ; This work was supported by the "Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2013-2016" from the Ministerio de Economia, Industria y Competitividad of Spain and Fondo Europeo de Desarrollo Regional (FEDER) DPI2016-75799-R (AEI/FEDER, UE), and by the Direccion General de Politica Cientifica de la Generalitat Valenciana (PROMETEU 2016/088) ; Gómez García, JF.; Trenor Gomis, BA.; Sebastián Aguilar, R. (2020). Prediction of CRT Activation Sequence by Personalization of Biventricular Models from Electroanatomical Maps. Lecture Notes in Computer Science. 12009:342-351. https://doi.org/10.1007/978-3-030-39074-7_36 ; S ; 342 ; 351 ; 12009 ; Auricchio, A., et al.: Characterization of left ventricular activation in patients with heart failure and left bundle-branch block. Circulation 109(9), 1133–9 (2004). https://doi.org/10.1161/01.CIR.0000118502.91105.F6 ; Bristow, M.R., et al.: Comparison of medical therapy, pacing, and defibrillation in heart failure (COMPANION) investigators: cardiac-resynchronization therapy with or without an implantable defibrillator in advanced chronic heart failure. N. Engl. J. Med. 350(21), 2140–50 (2004). https://doi.org/10.1056/NEJMoa032423 ; Carpio, E.F., et al.: Optimization of lead placement in the right ventricle during cardiac resynchronization ...

Rule-based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule-based methods often does not match histological data in other areas of the heart such as the right ventricle, having a negative impact in cardiac simulations beyond the left ventricle. In this work, we present a rule-based method 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 endocardium of the right ventricle, the interventricular septum and the outflow tracts. We also carried out electrophysiological simulations involving these structures and with different fiber configurations. In particular, we built a modelling pipeline for creating patient-specific volumetric meshes of biventricular geometries, including the outflow tracts, and subsequently simulate the electrical wavefront propagation in outflow tract ventricular arrhythmias with different origins for the ectopic focus. The resulting simulations with the proposed rule-based method showed a very good agreement with clinical parameters such as the 10 ms isochrone ratio in a cohort of nine patients suffering from this type of arrhythmia. The developed modelling pipeline confirms its potential for an in silico identification of the site of origin in outflow tract ventricular arrhythmias before clinical intervention. ; This work was partially funded by the European Union under the Horizon 2020 Programme for Research, Innovation (grant agreement No. 642676 CardioFunXion).

Comunicació presentada a: FIMH 2017 9th International Conference, celebrada a Toronto, Canadà, de l'11 al 13 de juny de 2017. ; 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 anatomi- cal models are Rule-Based Methods (RBM). However, RBM have been developed to assimilate data mostly from the Left Ventricle. In conse- quence, 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 sep- tum and the outow tracts. Electrophysiological simulations including these anatomical structures were then performed, with patient-specific data of outow tract ventricular arrhythmias (OTVA) cases. A compar- ison 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. ; This work was partially funded by the European Union under the Horizon 2020 Programme for Research, Innovation (grant agreement No. 642676 CardioFunX- ion)