The Effect of Conductivity on ST-Segment Epicardial Potentials Arising from Subendocardial Ischemia

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

doi:10.1007/s10439-005-3236-2

Cited by 41 publications

(77 citation statements)

References 10 publications

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“…Our results are consistent with previous modelling studies in realistic hearts [2,3] that found that the EPD assumes a different character for low, medium and high thicknesses of the ischaemic region. However, systematic studies into the effect of different fibre rotation angles and also into the effect of varying the six bidomain conductivity values in realistic geometries have not yet been performed.…”

Section: Resultssupporting

confidence: 93%

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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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Section: Resultssupporting

confidence: 93%

“…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.…”

Section: Introductionmentioning

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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“…Two studies have used whole-heart models to explore the effects of model parameters on epicardial potentials. Hopenfeld et al [20] studied the effect of anisotropy values and transmural extent on epicardial potential patterns. Our previous study concentrated on the value of ST deviation on the epicardium directly overlying the ischemic zone [41], considering anisotropy values, transmural extent, and radius of the zone.…”

Section: Effect On Simulated Action Potentialsmentioning

confidence: 99%

“…Thus, these studies explain why ST depression could not be reproduced in animal models. They also suggest alternatives: ST depression can result if the subendocardial ischemic zone is sufficiently thin and covers a large part of the subendocardium [20,41]. This may well correspond (1) with the clinical observation of ST depression in left-main or multivessel disease, which involves ischemic zones that occupy nearly the entire left ventricular subendocardium, as witnessed by autopsy results [5,28,38]; and (2) with the typical pattern of ST depression that can be observed during a stress test and is thought to be caused by global subendocardial ischemia [12].…”

Section: Introductionmentioning

confidence: 98%

The role of extracellular potassium transport in computer models of the ischemic zone

et al. 2007

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Ischemic heart disease is associated with large mortality and morbidity. Understanding of the relations between coronary artery occlusion, geometry of the ischemic region, physiology of ischemia, and the resulting changes in electrocardiogram (ECG) leads and catheter signals is important to support diagnosis and treatment. Computer models play an important role in understanding ischemia, by linking experimental to clinical results. In this paper we argue that the observed transport of extracellular potassium should be represented in such models. We used a diffusion equation to describe the transport mechanism. This model reproduced the measured spatial distribution of potassium, and its temporal development. We discuss the role of potassium transport next to other aspects of ischemia: the mechanism of changes in action potential and ECG, cellular coupling, anisotropic bidomain tissue conductivity, and the geometry of the ischemic zone.

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“…14,15 For such simulations we used the bidomain approach, 12 which requires intracellular and extracellular anisotropic conductivity tensors under normal conditions and under the varied influences of acute ischemia (e.g. differences in cell and capillary volumes due to accumulation of metabolic waste products and changes in the osmotic/hydrostatic pressure, as well as changes in gap junction conductivity and the rise in extracellular potassium), conditions for which there is very sparse experimental literature.…”

Section: Introductionmentioning

confidence: 99%

On the Passive Cardiac Conductivity

2005

Self Cite

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In order to relate the structure of cardiac tissue to its passive electrical conductivity, we created a geometrical model of cardiac tissue on a cellular scale that encompassed myocytes, capillaries, and the interstitial space that surrounds them. A special mesh generator was developed for this model to create realistically shaped myocytes and interstitial space with a controlled degree of variation included in each model. In order to derive the effective conductivities, we used a finite element model to compute the currents flowing through the intracellular and extracellular space due to an externally applied electrical field. The product of these computations were the effective conductivity tensors for the intracellular and extracellular spaces. The simulations of bi-domain conductivities for healthy tissue resulted in an effective intracellular conductivity of 0.16S/m (longitudinal) and 0.005 S/m (transverse) and an effective extracellular conductivity of 0.21S/m (longitudinal) and 0.06 S/m (transverse). The latter values are within the range of measured values reported in literature. Furthermore, we anticipate that this method can be used to simulate pathological conditions for which measured data is far more sparse.

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The Effect of Conductivity on ST-Segment Epicardial Potentials Arising from Subendocardial Ischemia

Cited by 41 publications

References 10 publications

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

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

The role of extracellular potassium transport in computer models of the ischemic zone

On the Passive Cardiac Conductivity

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