Mechanism for ST Depression Associated with Contiguous Subendocardial Ischemia

Hopenfeld, Bruce; Stinstra, J.G.; MacLeod, Rob S.

doi:10.1046/j.1540-8167.2004.04072.x

Cited by 86 publications

(89 citation statements)

References 16 publications

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“…Cell swelling and the decoupling of gap junctions alter the microscopic structure of tissue and, hence, its passive electrical conductivity, and this change in conductivity will alter the volume conductor and thus the epicaxdial potentials. A recent modelling study by HOPENFELD et al (2004; showed that the electrical anisotropy ratio of cardiac tissue and changes in its electrical conductivity influence the distribution of epicardial potentials.…”

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confidence: 99%

Modelling passive cardiac conductivity during ischaemia

Stinstra

Shome

Hopenfeld

et al. 2005

Med. Biol. Eng. Comput.

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The results of a geometric model of cardiac tissue, used to compute the bidomain conductivity tensors during three phases of ischaemia, are described. Ischaemic conditions were simulated by model parameters being changed to match the morphological and electrical changes of three phases of ischaemia reported in literature. The simulated changes included collapse of the interstitial space, cell swelling and the closure of gap junctions. The model contained 64 myocytes described by 2 million tetrahedral elements, to which an external electric field was applied, and then the finite element method was used to compute the associated current density. In the first case, a reduction in the amount of interstitial space led to a reduction in extracellular longitudinal conductivity by about 20%, which is in the range of reported literature values. Moderate cell swelling in the order of 10-20% did not affect extracellular conductivity considerably. To match the reported drop in total tissue conductance reported in experimental studies during the third phase of ischaemia, a ten fold increase in the gap junction resistance was simulated. This ten-fold increase correlates well with the reported changes in gap junction densities in the literature.

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confidence: 99%

Modelling passive cardiac conductivity during ischaemia

Stinstra

Shome

Hopenfeld

et al. 2005

Med. Biol. Eng. Comput.

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“…We let ∆φ p = −30 mV [1,7], and then initially set λ t = 0.01 ∀t, to give a narrow border zone between the normal and ischaemic tissue. We use the same boundary conditions as in previous work [1]; that is, we assume no current flux at the boundary of the intra-and extracellular domains at the air-tissue interfaces and at the blood-air interface.…”

Section: Half-ellipsoidal Modelmentioning

confidence: 99%

Using Generalised Polynomial Chaos to Examine Various Parameters in a Half-ellipsoidal Ventricular Model of Partial Thickness Ischaemia

Johnston

2017

Computing in Cardiology Conference (CinC)

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Elevation and depression in the ST segment of the electrocardiogram is commonly used as part of a diagnosis of myocardial ischaemia, although there is not yet a clear correlation between these observations and partial thickness ischaemia. In this work, we use a half-ellipsoid bidomain model of subendocardial ischaemia in a ventricle to study the effect of changes in model parameters on ST segment epicardial potential distributions (EPDs). We use generalised polynomial chaos techniques to produce mean EPDs, where the six bidomain conductivity values are varied, as well as blood conductivity and fibre rotation, for a number of different representations of the ischaemic region.We find that, as the thickness of the ischaemic region (i.e. the ischaemic depth) increases, the character of the mean EPD first changes from a single minimum approximately above the ischaemic region, to a maximum over the ischaemic region, with the minimum moving to a border of the ischaemic region. Next a second minimum develops, in addition to the previous maximum and minimum. In contrast, the strength of the maximum and the minima is only affected in a minor way by changes in the width of the ischaemic border and the position of the ischaemic region, provided it is not near the apex or base of the ventricle. When the size of the ischaemic region is increased, the magnitudes of both the maximum and the minima increase, but their character does not change.In summary, the qualitative progression of the mean EPD with increasing ischaemic depth, from single minimum through to a maximum surrounded by two minima, is the same, regardless of the size and position of the ischaemic region. IntroductionSimulation studies are an important tool for studying the effects of myocardial ischaemia on the electrocardiogram, and, in particular, the effects of subendocardial ischaemia, since it is less well-understood than transmural ischaemia.If these studies are to be clinically useful, it is important that modellers are able to quantify, in some fashion, the effects of the various modelling assumptions and parameter choices they make in their models.Some previous work in this area has used simplified model geometries for the left ventricle (e.g. slabs, cylinders, half-ellipsoids [1]), while other work uses more realistic geometries [2,3]. Another study [4] has looked at the effect of the shape of the ischaemic region on the epicardial potential distributions (EPDs) that are produced.The majority of recent work represents the cardiac tissue as consisting of interpenetrating bi-domains, intracellular (i) and extracellular (e). In these the current is assumed to flow in three mutually orthogonal directions, longitudinal (l), transverse (t) and normal (n), that is along, across and between the sheets of cardiac fibres, respectively. This leads to six bidomain conductivity parameters (g pq , p = i, e, q = l, t, n) in the model, in addition to other parameters, such as the blood conductivity g b and the angle (ROT) that represents the overall rotation of ...

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“…In order to simulate both the effects of fiber orientation and changes in the effective conductivity, we developed a multi-scale modeling approach [1]- [3] . At a cellular level, the model simulates a piece of cardiac tissue and includes details such as cell geometry, gap junctions, and the specific conductivities of various electrolytes.…”

Section: A Simulation Setupmentioning

confidence: 99%

“…The model of the whole heart simulates epicardial potentials from ischemic sources and is based on the bidomain equations. The anatomical and fiber structure data underlying this model originated in the Auckland canine heart [4] and the ischemic source was a difference in the transmembrane potential between healthy and ischemic tissue of 30 mV [1]. …”

Section: A Simulation Setupmentioning

confidence: 99%

“…INTRODUCTION A recent modeling study using a full anisotropic model of the heart during ischemia suggests that epicardial potential distributions depend on the underlying fiber structure of the myocardium [1], [2]. Not only do the epicardial potentials depend on macroscopic structures like fiber orientation, studies of changes in the cardiac conductivity suggest that dynamic changes at a cellular level affect this conductivity and thence the electrical properties of the myocardium as a whole [3].…”

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confidence: 99%

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A Study of the Dynamics of Cardiac Ischemia using Experimental and Modeling Approaches

Shome

Stinstra

Hopenfeld

et al.

The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-The dynamics of cardiac ischemia was investigated using experimental studies and computer simulations. An experimental model consisting of an isolated and perfused canine heart with full control over blood flow rate to a targeted coronary artery was used in the experimental study and a realistically shaped computer model of a canine heart, incorporating anisotropic conductivity and realistic fiber orientation, was used in the simulation study. The phenomena investigated were: (1) the influence of fiber rotation on the epicardial potentials during ischemia and (2) the effect of conductivity changes during a period of sustained ischemia. Comparison of preliminary experimental and computer simulation results suggest that as the ischemic region grows from the endocardium towards the epicardium, the epicardial potential patterns follow the rotating fiber orientation in the myocardium. Secondly, in the experimental studies it was observed that prolonged ischemia caused a subsequent reduction in the magnitude of epicardial potentials. Similar results were obtained from the computer model when the conductivity of the tissue in the ischemic region was reduced.

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Mechanism for ST Depression Associated with Contiguous Subendocardial Ischemia

Abstract: ST depression at the epicardium appears over a lateral boundary between healthy and ischemic tissue.

Cited by 86 publications

References 16 publications

Modelling passive cardiac conductivity during ischaemia

Modelling passive cardiac conductivity during ischaemia

Using Generalised Polynomial Chaos to Examine Various Parameters in a Half-ellipsoidal Ventricular Model of Partial Thickness Ischaemia

A Study of the Dynamics of Cardiac Ischemia using Experimental and Modeling Approaches

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