Simulation of ST Segment Changes During Subendocardial Ischemia Using a Realistic 3-D Cardiac Geometry

Abstract

The mechanisms underlying the ST segment shifts associated with subendocardial ischemia remain unclear. The aim of this paper is to shed further light on the subject through numerical simulations of these shifts. A realistic three-dimensional model of the ventricles, including fiber rotation and anisotropy, is embedded in a nonhomogeneous torso model. A simplification of the bidomain model is used to calculate only the ST segment shift, assuming known values of the transmembrane potential during the plateau and rest phases. A similar simulation is performed in two dimensions. The simulation results suggest that subendocardial ischemia can be located by ST segment shift on the epicardial and torso surfaces. It is shown that ST elevation is associated with the transmural ischemic boundary, while ST depression is associated with the lateral ischemic boundaries.

Design of a multi-electrode array to measure cardiac conductivities

“…Later work (not presented) also shows that this is possible for the other available six conductivity dataset, that of MacLachlan et al [18]. An additional study (not presented) indicates that, for both of these datasets, particularly sensitive electrodes are those with the lowest values of φ e .…”

“…This led to the inclusion of three distinct propagation directions in a number of recent studies [8,30,15,32] and some of these showed that simulations that include three, rather than two, distinct propagation directions much more closely match experimental results. Despite C274 the use of some six bidomain conductivity datasets [9,8,18], none of these are fully determined by experiments.…”

The Effect of Conductivity Values on Activation Times and Defibrillation Thresholds

“…However, these are not significant limitations as the purpose of this study is to compare the effect of the input conductivities. The effect is particularly noticeable for the four-conductivity datasets (Table 1, rows 1-3), as well as that of MacLachlan et al [6]. Hence, it is suggested that researchers should use one of the six-conductivity datasets from Table 1 (rows 5-8) in cardiac electrophysiological simulations that use the bidomain model.…”

“…For both types of activation time there is approximately a 50% difference between the quickest and slowest times: 30 and 46 ms for surface breakthrough and 126 and 197 ms for total depolarisation. In this case MacLachlan [6] and Roberts and Scher [14] are equally quick and Clerc [12] is the slowest. The remaining results vary by less than 20%.…”

“…These values vary considerably, and to be used in modelling studies the assumption must be made that the normal conductivities are equal to the transverse conductivities. It has been shown that, in simulation studies modelling partial thickness ischaemia, these sets produce very different results from one another [3,4] and from the two (non-experimental) sixconductivity datasets [5,6] given in the literature (Table 1, rows 4 and 5) [7].…”