Prediction of electrical activation patterns in porcine hearts with a meshless model Smoothed Particle Hydrodynamics: an silico study

Albors Lucas, Carlos

Prediction of electrical activation patterns in porcine hearts with a meshless model Smoothed Particle Hydrodynamics: an silico study

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Albors Lucas, C. Prediction of electrical activation patterns in porcine hearts with a meshless model Smoothed Particle Hydrodynamics: an silico study. 2020. handle: http://hdl.handle.net/10230/46324

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Abstract

Computational models can be a valuable tool for optimizing electrode placement and reducing non-responders rates in those patients requiring cardiac resynchronization therapy (CRT). Most of these computer models are mesh-based, mostly relying on the Finite Element Method (FEM). In this project, the Smoothed Particle Hydrodynamics (SPH) meshless model is proposed as an interesting alternative due to its adaptability to the easy acquisition technique for difficult geometries and the independence of the quality of the extracted mesh to determine the reliability of the results. Although it is difficult to compare both methods qualitatively and quantitatively, some benchmarks are available through the emergence of challenges as the CRT-EPiggy19. This study is part of the challenge participation in which the SPH solver had to be adapted and personalized for the dataset available in order to predict the electrical response of CRT and propose the optimal device configuration in swines models with a left bundle branch block (LBBB). By using optimization algorithms for parameter tuning, an average Local Activation Time (LAT) error in the LBBB cases of 6.75±1.59 ms and an overall prediction with an average error of 10.38 ± 3.80 ms in the CRT cases is acquired. Similar results have been obtained by other participants using FEM models. Taking in mind these results, more studies should be done considering an improvement in the definition of velocity conductivities, the number of different regions established in the model and the optimization method used to obtain the optimum values.