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Evaluation of a Rapid Anisotropic Model for ECG Simulation.

ABSTRACT: State-of-the-art cardiac electrophysiology models that are able to deliver physiologically motivated activation maps and electrocardiograms (ECGs) can only be solved on high-performance computing architectures. This makes it nearly impossible to adopt such models in clinical practice. ECG imaging tools typically rely on simplified models, but these neglect the anisotropic electric conductivity of the tissue in the forward problem. Moreover, their results are often confined to the heart-torso interface. We propose a forward model that fully accounts for the anisotropic tissue conductivity and produces the standard 12-lead ECG in a few seconds. The activation sequence is approximated with an eikonal model in the 3d myocardium, while the ECG is computed with the lead-field approach. Both solvers were implemented on graphics processing units and massively parallelized. We studied the numerical convergence and scalability of the approach. We also compared the method to the bidomain model in terms of ECGs and activation maps, using a simplified but physiologically motivated geometry and 6 patient-specific anatomies. The proposed methods provided a good approximation of activation maps and ECGs computed with a bidomain model, in only a few seconds. Both solvers scaled very well to high-end hardware. These methods are suitable for use in ECG imaging methods, and may soon become fast enough for use in interactive simulation tools.

SUBMITTER: Pezzuto S

PROVIDER: S-EPMC5411438 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Evaluation of a Rapid Anisotropic Model for ECG Simulation.

Pezzuto Simone S Kal'avský Peter P Potse Mark M Prinzen Frits W FW Auricchio Angelo A Krause Rolf R

Frontiers in physiology 20170502

State-of-the-art cardiac electrophysiology models that are able to deliver physiologically motivated activation maps and electrocardiograms (ECGs) can only be solved on high-performance computing architectures. This makes it nearly impossible to adopt such models in clinical practice. ECG imaging tools typically rely on simplified models, but these neglect the anisotropic electric conductivity of the tissue in the forward problem. Moreover, their results are often confined to the heart-torso int ...[more]

PMID: 28512434

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Project description:Background The rate of sudden cardiac death (SCD) in Brugada syndrome (BrS) is ≈1%/y. Noninvasive electrocardiographic imaging is a noninvasive mapping system that has a role in assessing BrS depolarization and repolarization abnormalities. This study aimed to analyze electrocardiographic imaging parameters during ajmaline test (AJT). Methods and Results All consecutive epicardial maps of the right ventricle outflow tract (RVOT-EPI) in BrS with CardioInsight were retrospectively analyzed. (1) RVOT-EPI activation time (RVOT-AT); (2) RVOT-EPI recovery time, and (3) RVOT-EPI activation-recovery interval (RVOT-ARI) were calculated. ∆RVOT-AT, ∆RVOT-EPI recovery time, and ∆RVOT-ARI were defined as the difference in parameters before and after AJT. SCD-BrS patients were defined as individuals presenting a history of aborted SCD. Thirty-nine patients with BrS were retrospectively analyzed and 12 patients (30.8%) were SCD-BrS. After AJT, an increase in both RVOT-AT [105.9 milliseconds versus 65.8 milliseconds, P<0.001] and RVOT-EPI recovery time [403.4 milliseconds versus 365.7 milliseconds, P<0.001] was observed. No changes occurred in RVOT-ARI [297.5 milliseconds versus 299.9 milliseconds, P=0.7]. Before AJT no differences were observed between SCD-BrS and non SCD-BrS in RVOT-AT, RVOT-EPI recovery time, and RVOT-ARI (P=0.9, P=0.91, P=0.86, respectively). Following AJT, SCD-BrS patients showed higher RVOT-AT, higher ∆RVOT-AT, lower RVOT-ARI, and lower ∆RVOT-ARI (P<0.001, P<0.001, P=0.007, P=0.002, respectively). At the univariate logistic regression, predictors of SCD-BrS were the following: RVOT-AT after AJT (specificity: 0.74, sensitivity 1.00, area under the curve 0.92); ∆RVOT-AT (specificity: 0.74, sensitivity 0.92, area under the curve 0.86); RVOT-ARI after AJT (specificity 0.96, sensitivity 0.58, area under the curve 0.79), and ∆RVOT-ARI (specificity 0.85, sensitivity 0.67, area under the curve 0.76). Conclusions Noninvasive electrocardiographic imaging can be useful in evaluating the results of AJT in BrS.

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Evaluation of a Rapid Anisotropic Model for ECG Simulation.

Publications

Evaluation of a Rapid Anisotropic Model for ECG Simulation.

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