Exploring susceptibility to atrial and ventricular arrhythmias resulting from remodeling of the passive electrical properties in the heart: a simulation approach

Abstract

Under diseased conditions, remodeling of the cardiac tissue properties ("passive properties") takes place; these are aspects of electrophysiological behavior that are not associated with active ion transport across cell membranes. Remodeling of the passive electrophysiological properties most often results from structural remodeling, such as gap junction down-regulation and lateralization, fibrotic growth infiltrating the myocardium, or the development of an infarct scar. Such structural remodeling renders atrial or ventricular tissue as a major substrate for arrhythmias. The current review focuses on these aspects of cardiac arrhythmogenesis. Due to the inherent complexity of cardiac arrhythmias, computer simulations have provided means to elucidate interactions pertinent to this spatial scale. Here we review the current state-of-the-art in modeling atrial and ventricular arrhythmogenesis as arising from the disease-induced changes in the passive tissue properties, as well as the contributions these modeling studies have made to our understanding of the mechanisms of arrhythmias in the heart. Because of the rapid advance of structural imaging methodologies in cardiac electrophysiology, we chose to present studies that have used such imaging methodologies to construct geometrically realistic models of cardiac tissue, or the organ itself, where the regional remodeling properties of the myocardium can be represented in a realistic way. We emphasize how the acquired knowledge can be used to pave the way for clinical applications of cardiac organ modeling under the conditions of structural remodeling.

Keywords: arrhythmia; computer modeling; fibrosis; infarct; structural remodeling.

Figure 1

Overall approach to image-based modeling of cardiac electrophysiology. (A) The multiscale aspect of cardiac electrophysiological models. Passive electrical coupling of cardiac cells mediates the tissue-scale propagation of bioelectric impulses that originate at the membrane level (action potentials). ^*indicates representative points in ventricular and atrial tissue models. 3D geometrical models are reconstructed from images of a canine heart (left), as in Arevalo et al. (2013), and human patient atria (right), as in Krueger et al. (2011). (B) Schematics showing the orientation of myocardial fibers in the ventricular and atrial models. Left panel modified with permission from Arevalo et al. (2013).

Figure 2

Constructing image-based models of the ventricles from an infarcted canine heart (A,B) and the fibrotic atria of a human patient with AF. (A) Reconstruction from an ex-vivo MRI scan of an infarcted canine heart. Fractional anisotropy (FA) maps as calculated from the DT-MRI, brighter color corresponds with higher FA value. The images are segmented into healthy myocardium, gray zone (GZ), and scar, to reconstruct an image-based model of the infracted canine heart (right-most panel). Modified with permission from Arevalo et al. (2013). (B) Construction of a patient-specific ventricular model of arrhythmia from a clinical MR scan. Shown are images of an infarcted patient heart before ablation (treatment) and the corresponding segmentation: healthy (red), GZ (green), or scar (yellow). An image of the three-dimensional geometric model of the patient heart rendered with the epicardium and the infarct border zone semitransparent is shown in the third panel. The right-most panel presents in silico activation map of arrhythmia, revealing reentry on the left ventricular endocardium. The color code in the bottom right shows electrical activation time. Modified with permission from Winslow et al. (2012). (C) A model of the fibrotic human atria generated from a patient LGE-MRI scan (top left) following segmentation (top right) into normal and fibrotic tissue (fibrotic lesions in red). With permission from McDowell et al. (2012).

Figure 3

Modeling fibrosis as regions of collagen presence. Collagen is represented as an insulator. (A) Simulations of propagation in models of 2D tissue sections of canine atrium (control, left, and fibrosis, right). With permission from Burstein et al. (2009). (B) Simulations in models of a transmural slice of canine posterior LA under HF conditions; the top of the slice (red dashed lines) corresponds to the epicardial surface. Snapshots at several timeframes for cross-field stimulation (left), and pacing at a frequency of 6 Hz (right), as well as endocardial time-space plots. Colors indicate transmembrane voltage from low (blue) to high (red). The site of unidirectional block (ub). is indicated by a black arrow. White circles on the upper voltage maps indicate sites of wavebreak. With permission from Tanaka et al. (2007).

Figure 4

Modeling fibroblast proliferation in the regions of fibrosis. (A) Effect of myocyte-fibroblast coupling (modeled as in Maleckar et al., 2009a) on spiral wave behavior in a human atrial cell monolayer model of size 4.5 × 4.5 cm. Top, control case without fibroblasts. Middle and bottom, models of low-density and high-density fibroblast proliferation (LD-Fbs and HD-Fbs) in a central circular region of the sheet. In the LD-Fbs, and HD-Fbs models, atrial myocytes (100 pF), each connecting to 4 fibroblasts (6.3 pF) within the Fb-Area, account for 12.5% and 50.0% of that area, respectively. With permission from Ashihara et al. (2012). (B) Maps of action potential duration (APD) in four human atrial models (same atrial geometry). Fibrotic lesions are modeled with (bottom row), and without (top row) myofibroblast infiltration (and coupling to myocytes), as well as with (right column), and without (left column) diffuse collagen deposition for both sets of maps. Myofibroblasts in the fibrotic regions were coupled to atrial myocytes as described in Maleckar et al. (2009a) and Maleckar et al. (2009b). Anatomical landmarks in upper-left sub-panel: right inferior, right superior, left inferior, and left superior pulmonary veins (RIPV, RSPV, LIPV, LSPV, respectively); left atrial appendage (LAA). With permission from McDowell et al. (2013).

Figure 5

Reentry morphologies during post-infarction ventricular tachycardia (VT) in a canine cardiac model. (A) VT morphology 1: Activation maps on the epicardium and in a long-axis cross-section of the ventricles, revealing figure-of-eight reentries on the epicardium, and on the right ventricular (RV) endocardium. VT is sustained by two I-type filaments (pink lines) located within the GZ with endpoints on the epicardium and RV endocardium. (Red: endocardial and epicardial surfaces, Yellow: scar surface, semi-transparent green: GZ) (B) VT morphology 2: Activation maps on the epicardium and in a short-axis cross-section of the ventricles, revealing figure-of-eight reentry on the epicardium, and two breakthroughs on endocardium (white dots). Reentry was organized around two I-type filaments with endpoints on the epicardium and scar (pink lines). (C) Activation map showing an apparent reentry around a scar distal from filaments. The overall VT morphology is similar to VT morphology 2 in Panel B. With permission from Arevalo et al. (2013).

Figure 6

(A) Proposed simulation-guided approach for determining the ablation targets of infarct-related ventricular tachycardia. The patients referred for ventricular tachycardia (VT) ablation undergo pre-ablation MRI, which was processed to provide the heart and infarct geometry (scar: red; GZ: yellow). These geometrical data were incorporated into a model of VT to estimate potential target regions. This method is alternative to an invasive electrophysiology study (EPS), and ablation [“Standard Approach”; by using biplane X-ray fluoroscopy and electroanatomical mapping (CARTO)]. LAO—left anterior oblique; RAO—right anterior oblique. (B) Comparison between simulation-guided and standard electrophysiological approaches for identifying endocardial ablation targets in two patients with infarct-related ventricular tachycardias (VTs). Left column: propagation pathways (green) and lines of conduction block (blue) are overlaid over VT activation maps simulated in image-based patient heart models. Middle column: preablation infarct geometry (infarct scar: orange, border zone: yellow, and non-infarcted: gray) along with ablation lesions delivered by the standard approach (red circles), and conduction block lines as calculated from ventricular simulations. Right column: optimal ablation zones (green shading) predicted by simulations, with narrowest isthmuses indicated (cyan); in both cases, only a fraction of the ablation sites from the standard approach were within the predicted optimal LV endocardial ablation zone (yellow circles). Modified with permission from Ashikaga et al. (2013).