Quantifying the effects of ischaemia on electrophysiology and the ST segment of the ECG in human virtual ventricular cells and tissues

Abstract

We have developed human virtual cell and tissue models of ischaemia, and used these models to quantify electrophysiological and ECG ST segment changes during subendocardial and global ischaemia. Our investigation has highlighted key differences with previous computational studies based on animal models: (i) propagation failure in the human model occurs with a smaller degree of hyperkalaemia compared to previously used animal models, due to differences in sodium channels kinetics; (ii) the human model is more sensitive to repolarising potassium currents during phase 3 repolarisation than the previously used animal models, and therefore the magnitude of the ATPsensitive potassium current must be smaller in the human model to produce similar changes in action potential duration during ischaemia; and (iii) unlike in animal models where hyperkalaemia was identified as the major component of ST segment depression, we find in the human model that both anoxia and hyperkalaemia are responsible.

Construction and validation of anisotropic and orthotropic ventricular geometries for quantitative predictive cardiac electrophysiology

“…Ischaemic areas of ventricular tissue appear as underperfused and thus relatively dark tissue, as in figure 11a. For computational reconstruction, the poorly perfused tissue can be segmented as in figure 11b, and the ischaemic volume reconstructed: this gives a size, shape and location of the ischaemic tissue, within which the parameters of the cell electrophysiology model can be modified, as in Aslanidi et al [84] and Benson et al [85]. Myocardial perfusion CMR data (figure 11c) allow the estimation of local perfusion with a high temporal and spatial resolution.…”

Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model

“…Ischemia is characterized by increase in resting membrane potential and shortening of APD. ECG is computed from the model and shown that ST elevation corresponds to transmural ischemia and ST depression corresponds to endocardial ischemia which correlates with clinical findings (Benson et al, 2008 ; Lu et al, 2010 ). Simplified 2D and 3D bidomain models of lesser computational complexity are proposed by defining seven sub regions corresponding to cardiac regions with characteristic cell properties (SAN, atria, AVN, His bundle, bundle branches, Purkinje fibers, and ventricles) and tissue conductivities (Sovilj et al, 2013 , 2014 ).…”