Adaptive step ODE algorithms for the 3D simulation of electric heart activity with graphics processing units

Garcia-Mollá, Víctor M.; Liberos, Alejandro; Vidal, Antonio M.; Guillem, María S.; Millet, José; González, Alberto; Martínez-Zaldívar, Francisco-Jose; Climent, Andreu Μ.

doi:10.1016/j.compbiomed.2013.10.023

Cited by 34 publications

(16 citation statements)

References 24 publications

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“…This variability may explain the contradictory responses to pharmacologic treatments reported in the literature. New cardiac simulation platforms such as those used in this work 14 allow performance of simulations of populations of models, accounting for the variability observed across subjects. Furthermore, this is the first study in which a population of models has been used to determine the ionic currents linked to arrhythmia perpetuation in a 3D model of AF.…”

Section: Discussionmentioning

confidence: 99%

Balance between sodium and calcium currents underlying chronic atrial fibrillation termination: An in silico intersubject variability study

et al. 2016

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BackgroundAtrial remodeling as a result of long-standing persistent atrial fibrillation (AF) induces substrate modifications that lead to different perpetuation mechanisms than in paroxysmal AF and a reduction in the efficacy of antiarrhythmic treatments.ObjectiveThe purpose of this study was to identify the ionic current modifications that could destabilize reentries during chronic AF and serve to personalize antiarrhythmic strategies.MethodsA population of 173 mathematical models of remodeled human atrial tissue with realistic intersubject variability was developed based on action potential recordings of 149 patients diagnosed with AF. The relationship of each ionic current with AF maintenance and the dynamics of functional reentries (rotor meandering, dominant frequency) were evaluated by means of 3-dimensional simulations.ResultsSelf-sustained reentries were maintained in 126 (73%) of the simulations. AF perpetuation was associated with higher expressions of INa and ICaL (P <.01), with no significant differences in the remaining currents. ICaL blockade promoted AF extinction in 30% of these 126 models. The mechanism of AF termination was related with collisions between rotors because of an increase in rotor meandering (1.71 ± 2.01cm2) and presented an increased efficacy in models with a depressed INa (P <.01).ConclusionMathematical simulations based on a population of models representing intersubject variability allow the identification of ionic mechanisms underlying rotor dynamics and the definition of new personalized pharmacologic strategies. Our results suggest that the underlying mechanism of the diverging success of ICaL block as an antiarrhythmic strategy is dependent on the basal availability of sodium and calcium ion channel conductivities.

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Section: Discussionmentioning

confidence: 99%

Balance between sodium and calcium currents underlying chronic atrial fibrillation termination: An in silico intersubject variability study

et al. 2016

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“…Atrial fibrillation in the in‐silico realistic model was induced by an S1–S2 stimulation protocol. Mathematical computations were performed using an adaptive time‐step solver on a Graphical Processing Unit (NVIDIA Tesla C2075 6G) . Transmembrane potentials were computed for a simulation time of 4 seconds after stabilization of the model and were resampled to 1 kHz.…”

Section: Methodsmentioning

confidence: 99%

Noninvasive Estimation of Epicardial Dominant High‐Frequency Regions During Atrial Fibrillation

Pedron-Torrecilla

Rodrigo

Climent

et al. 2016

Cardiovasc electrophysiol

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Introduction Ablation of high dominant frequency (DF) sources in patients with atrial fibrillation (AF) is an effective treatment option for paroxysmal AF. The aim of this study was to evaluate the accuracy of noninvasive estimation of DF and electrical patterns determination by solving the inverse problem of the electrocardiography. Methods Four representative AF patients with left-to-right and right-to-left atrial DF patterns were included in the study. For each patient, intracardiac electrograms from both atria were recorded simultaneously together with 67-lead body surface recordings. In addition to clinical recordings, realistic mathematical models of atria and torso anatomy with different DF patterns of AF were used. For both mathematical models and clinical recordings, inverse-computed electrograms were compared to intracardiac electrograms in terms of voltage, phase, and frequency spectrum relative errors. Results Comparison between intracardiac and inverse computed electrograms for AF patients showed 8.8 ± 4.4% errors for DF, 32 ± 4% for voltage, and 65 ± 4% for phase determination. These results were corroborated by mathematical simulations showing that the inverse problem solution was able to reconstruct the frequency spectrum and the DF maps with relative errors of 5.5 ± 4.1%, whereas the reconstruction of the electrograms or the instantaneous phase presented larger relative errors (i.e., 38 ± 15% and 48 ± 14 % respectively, P < 0.01). Conclusions Noninvasive reconstruction of atrial frequency maps can be achieved by solving the inverse problem of electrocardiography with a higher accuracy than temporal distribution patterns.

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“…The use of adaptive spatial or time discretization in cardiac simulations can be found in several publications. In Garcia‐Molla et al, time adaptation accelerated by GPUs is used to solve only the ODEs associated to the simulation. The authors of Cherry et al present a space‐time adaptive mesh refinement algorithm to simulate 3D anisotropic media.…”

Section: Discussionmentioning

confidence: 99%

Performance evaluation of GPU parallelization, space‐time adaptive algorithms, and their combination for simulating cardiac electrophysiology

Oliveira

Rocha

Burgarelli

et al. 2017

Numer Methods Biomed Eng

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The use of computer models as a tool for the study and understanding of the complex phenomena of cardiac electrophysiology has attained increased importance nowadays. At the same time, the increased complexity of the biophysical processes translates into complex computational and mathematical models. To speed up cardiac simulations and to allow more precise and realistic uses, 2 different techniques have been traditionally exploited: parallel computing and sophisticated numerical methods. In this work, we combine a modern parallel computing technique based on multicore and graphics processing units (GPUs) and a sophisticated numerical method based on a new space-time adaptive algorithm. We evaluate each technique alone and in different combinations: multicore and GPU, multicore and GPU and space adaptivity, multicore and GPU and space adaptivity and time adaptivity. All the techniques and combinations were evaluated under different scenarios: 3D simulations on slabs, 3D simulations on a ventricular mouse mesh, ie, complex geometry, sinus-rhythm, and arrhythmic conditions. Our results suggest that multicore and GPU accelerate the simulations by an approximate factor of 33×, whereas the speedups attained by the space-time adaptive algorithms were approximately 48. Nevertheless, by combining all the techniques, we obtained speedups that ranged between 165 and 498. The tested methods were able to reduce the execution time of a simulation by more than 498× for a complex cellular model in a slab geometry and by 165× in a realistic heart geometry simulating spiral waves. The proposed methods will allow faster and more realistic simulations in a feasible time with no significant loss of accuracy.

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Adaptive step ODE algorithms for the 3D simulation of electric heart activity with graphics processing units

Cited by 34 publications

References 24 publications

Balance between sodium and calcium currents underlying chronic atrial fibrillation termination: An in silico intersubject variability study

Balance between sodium and calcium currents underlying chronic atrial fibrillation termination: An in silico intersubject variability study

Noninvasive Estimation of Epicardial Dominant High‐Frequency Regions During Atrial Fibrillation

Performance evaluation of GPU parallelization, space‐time adaptive algorithms, and their combination for simulating cardiac electrophysiology

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