Session S42.2

Grid Computing Simulations of Ion Channel Block Effects on the ECG Using 3D Anatomically-Based Models

MO Bernabeu*, A Corrias, J Pitt-Francis, B Rodriguez, B Bethwaite, C Enticott,
S Garic, T Peachey, J Tan, D Abramson, D Gavaghan

Oxford University
Oxford, UK

In this work, Grid computing technology is combined with state-of-the-art cardiac simulation software and 3D ventricular models to provide the computational framework required to investigate changes in the electrocardiogram (ECG) caused by ion channel block. The technological challenges addressed through this work are highly interdisciplinary including numerical, computational, modelling and electrophysiological aspects.
The forward problem of electrocardiography in complex cardiac geometries is challenging in terms of biological complexity and computational tractability. Here we employ a multi-scale modelling approach to the problem, which includes representation from the ion channel to the ECG level. The Chaste software was used to simulate propagation of the AP throughout the ventricles using the bidomain model. Chaste was coupled to the Nimrod toolkit in order to (1) identify the computational resources available in the Grid, (2) set up a parameter sweep experiment and (3) schedule them appropriately according to the resources available.
Our application is to enable the investigation of the impact of the block of the HERG current on the ECG waveform using a 3D ventricular model of the heart immersed in a control volume. The software pipeline developed enables (1) automated parameter sweep using multiscale models (from ion channel to ECG) and (2) reduced execution time of the simulations performed. Our results show how the QT interval in the ECG signal recorded at a node in the medium surrounding the heart increases as the K+ current is gradually blocked.
In this work we have successfully integrated a cardiac simulator with a Grid toolkit, and we have applied the newly created software pipeline for the simulation of multiscale processes in cardiac electrophysiology. We believe this work will set the path for future high computing-demand studies on how cellular processes affect the overall cardiac mechanism.

(Abstract Control Number: 12)