Bruce Hopenfeld

Magnetic Resonance–Based Anatomical Analysis of Scar-Related Ventricular Tachycardia. Implications for Catheter Ablation

In catheter ablation of scar-related monomorphic ventricular tachycardia (VT), substrate voltage mapping is used to electrically define the scar during sinus rhythm. However, the electrically defined scar may not accurately reflect the anatomical scar. Magnetic resonance–based visualization of the scar may elucidate the 3D anatomical correlation between the fine structural details of the scar and scar-related VT circuits. We registered VT activation sequence with the 3D scar anatomy derived from high-resolution contrast-enhanced MRI in a swine model of chronic myocardial infarction using epicardial sock electrodes (n=6, epicardial group), which have direct contact with the myocardium where the electrical signal is recorded. In a separate group of animals (n=5, endocardial group), we also assessed the incidence of endocardial reentry in this model using endocardial basket catheters. Ten to 12 weeks after myocardial infarction, sustained monomorphic VT was reproducibly induced in all animals (n=11). In the epicardial group, 21 VT morphologies were induced, of which 4 (19.0%) showed epicardial reentry. The reentry isthmus was characterized by a relatively small volume of viable myocardium bound by the scar tissue at the infarct border zone or over the infarct. In the endocardial group (n=5), 6 VT morphologies were induced, of which 4 (66.7%) showed endocardial reentry. In conclusion, MRI revealed a scar with spatially complex structures, particularly at the isthmus, with substrate for multiple VT morphologies after a single ischemic episode. Magnetic resonance–based visualization of scar morphology would potentially contribute to preprocedural planning for catheter ablation of scar-related, unmappable VT.

Mechanism for ST Depression Associated with Contiguous Subendocardial Ischemia

Introduction: A mechanism for ST depression arising on the epicardial surface over the border between normal and ischemic tissue is proposed. Depression is caused by current flowing in a transmural loop that begins and ends at the lateral boundary between healthy and ischemic tissue and passes through the transmural boundary between healthy and ischemic tissue. The result is ST depression at the epicardium over the lateral boundary. The size and direction of current flow are dictated by differences in the magnitude and orientation of anisotropic conductivity between those boundaries.

On the Passive Cardiac Conductivity

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 controled 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 bidomain conductivities for healthy tissue resulted in an effective intracellular conductivity of 0.16S/m (longitudinal) and 0.005S/m (transverse) and an effective extracellular conductivity of 0.21S/m (longitudinal) and 0.06S/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.

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

We quantify and provide biophysical explanations for some aspects of the relationship between the bidomain conductivities and ST-segment epicardial potentials that result from subendocardial ischemia. We performed computer simulations of ischemia with a realistic whole heart model. The model included a patch of subendocardial ischemic tissue of variable transmural thickness with reduced action potential amplitude. We also varied both intracellular and extracellular conductivities of the heart and the conductivity of ventricular blood in the simulations. At medium or high thicknesses of transmural ischemia (i.e., at least 40% thickness through the heart wall), a consistent pattern of two minima of the epicardial potential over opposite sides of the boundary between healthy and ischemic tissue appeared on the epicardium over a wide range of conductivity values. The magnitude of the net epicardial potential difference, the epicardial maximum minus the epicardial minimum, was strongly correlated to the intracellular to extracellular conductivity ratios both along and across fibers. Anisotropy of the ischemic source region was critical in predicting epicardial potentials, whereas anisotropy of the heart away from the ischemic region had a less significant impact on epicardial potentials. Subendocardial ischemia that extends through at least 40% of the heart wall is manifest on the epicardium by at least one area of ST-segment depression located over a boundary between ischemic and healthy tissue. The magnitude of the depression is a function of the bidomain conductivity values.

Modelling passive cardiac conductivity during ischaemia.

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.

Model of Bipolar Electrogram Fractionation and Conduction Block Associated With Activation Wavefront Direction at Infarct Border Zone Lateral Isthmus Boundaries

Background—Improved understanding of the mechanisms underlying infarct border zone electrogram fractionation may be helpful to identify arrhythmogenic regions in the postinfarction heart. We describe the generation of electrogram fractionation from changes in activation wavefront curvature in experimental canine infarction. Methods and Results—A model was developed to estimate the extracellular signal shape that would be generated by wavefront propagation parallel to versus perpendicular to the lateral boundary (LB) of the reentrant ventricular tachycardia (VT) isthmus or diastolic pathway. LBs are defined as locations where functional block forms during VT, and elsewhere they have been shown to coincide with sharp thin-to-thick transitions in infarct border zone thickness. To test the model, bipolar electrograms were acquired from infarct border zone sites in 10 canine heart experiments 3 to 5 days after experimental infarction. Activation maps were constructed during sinus rhythm and during VT. The characteristics of model-generated versus actual electrograms were compared. Quantitatively expressed VT fractionation (7.6±1.2 deflections; 16.3±8.9-ms intervals) was similar to model-generated values with wavefront propagation perpendicular to the LB (9.4±2.4 deflections; 14.4±5.2-ms intervals). Fractionation during sinus rhythm (5.9±1.8 deflections; 9.2±4.4-ms intervals) was similar to model-generated fractionation with wavefront propagation parallel to the LB (6.7±3.1 deflections; 7.1±3.8-ms intervals). VT and sinus rhythm fractionation sites were adjacent to LBs ≈80% of the time. Conclusions—The results suggest that in a subacute canine infarct model, the LBs are a source of activation wavefront discontinuity and electrogram fractionation, with the degree of fractionation being dependent on activation rate and wavefront orientation with respect to the LB.

The Guardian: an implantable system for chronic ambulatory monitoring of acute myocardial infarction

The AngelMed Guardian is an implantable medical device that records cardiac data and detects ischemic events using a standard pacemaker intracardiac lead positioned in the right ventricular apex. The Guardian has been implanted in 55 people in the United States and Brazil and is currently undergoing a Food and Drug Administration phase 2 pivotal trial in the United States. The Guardian detects acute ischemic events by analyzing ST-segment shifts. The ST-segment shifts are calculated as the difference between the ST deviation of a current 10-second electrogram window and a baseline ST deviation value. If the ST-segment shift is greater than a heart rate-dependent programmable threshold, then the device generates an emergency alert signal. Results thus far have demonstrated that (i) the intracardiac electrogram is relatively noise-free and (ii) the ST-shift technique used by the Guardian is effective for detecting acute ischemic events.

Spherical harmonic-based finite element meshing scheme for modelling current flow within the heart.

The paper describes a spherical harmonic-based finite element scheme for solving Poisson-type equations throughout volumes characterised by irregularly shaped inner and outer surfaces. The inner and outer surfaces are defined by spherical harmonics, and the volume in between these surfaces is divided into nested shells that are weighted averages of the inner and outer surfaces. The resulting mesh comprises hexahedral elements, wherein each hexahedral element is defined by inner and outer shells in the radial direction and divisions in the polar and azimuthal directions. The spacing between shells can be set to any desired value. Similarly, the size of the polar and azimuthal divisions can be specified. A test of the scheme on an anisotropic sphere, meshed with 720 nodes, yielded a relative error of 0.78% on the spheres surface. As a comparison, a previously published combined finite element/boundary element scheme with a 946-node mesh produced a corresponding error of 3.57%.

Origin of the Electrocardiographic U Wave: Effects of M Cells and Dynamic Gap Junction Coupling

The electrophysiological basis underlying the genesis of the U wave remains uncertain. Previous U wave modeling studies have generally been restricted to 1-D or 2-D geometries, and it is not clear whether the U waves generated by these models would match clinically observed U wave body surface potential distributions (BSPDs). We investigated the role of M cells and transmural dispersion of repolarization (TDR) in a 2-D, fully ionic heart tissue slice model and a realistic 3-D heart/torso model. In the 2-D model, while a U wave was present in the ECG with dynamic gap junction conductivity, the ECG with static gap junctions did not exhibit a U wave. In the 3-D model, TDR was necessary to account for the clinically observed potential minimum in the right shoulder area during the U wave peak. Peak T wave simulations were also run. Consistent with at least some clinical findings, the U wave body surface maximum was shifted to the right compared to the T wave maximum. We conclude that TDR can account for the clinically observed U wave BSPD, and that dynamic gap junction conductivity can result in realistic U waves generated by M cells.

Using models of the passive cardiac conductivity and full heart anisotropic bidomain to study the epicardial potentials in ischemia

In this paper we present a multi-scale approach for cardiac modeling. Based on the histology of cardiac tissue we created a geometrical model at a cellular scale to compute the effective conductivity of a piece of cardiac tissue. In turn, the conductivity values obtained from this cellular scale model were used in a whole heart model in which we simulated regional, subendocardial ischemia. Histological changes at a cellular level led to changes in the effective conductivity tensor of the tissue, which in turn resulted in changes in the epicardial potential patterns during the ST-interval. Two effects were studied using this multi-scale approach: (1) the influence of a dynamically growing ischemic region on the epicardial potentials, and (2) the influence of a dynamically changing conductivity in the ischemic zone due to changes in the underlying pathology. One specific finding was the presence of epicardial patterns consisting of a central elevation and two opposite depressions at the edges of the ischemic zone which rotated as the ischemia became more transmural. In addition, the epicardial potentials decreased in magnitude with the duration of the ischemia due to changes in the effective conductivity of the ischemic tissue predicted by the cellular level model.