Principles and Applications of Computer Modeling in Patients With Devices

Introduction

Computer modeling of heart function has emerged as a powerful tool in the study of heart rhythm and pump disorders. Biophysically detailed cardiac simulations can explain experimental observations and help reveal how organ-scale arrhythmogenic phenomena (ectopic heartbeats, conduction failure, electrical turbulence, etc.) and contractile dysfunction emerge from pathologic effects at the tissue, cell, and protein levels. This extensive “virtual heart” methodology has been built upon a strong foundation of experimentally constrained model developments. Advancements in single cell action potential modeling have produced the contemporary building blocks for constructing models of the atria and the ventricles with unprecedented levels of biophysical detail and accuracy. Similarly, cell mechanics (myofilament) models (reviewed by Trayanova and Rice ) have enabled the assembly of coupled electromechanical models of the heart. Such developments have helped to fuel the exciting progress made in simulating cardiac electrical and mechanical behavior at the organ level. Importantly, the emergent, integrative behaviors in the heart uncovered by these modeling studies have demonstrated how they result from complex interactions not only within a specific level but also from feedforward and feedback interactions that connect a broad range of hierarchical levels of biological organization, further underscoring the importance of integrative research in heart (dys)function. Several recent reviews have been written on our current understanding of atrial and ventricular mechanisms from an integrative interactions perspective, often derived from computer simulations.

Recent developments in modeling of heart rhythm and pump disorders have begun to adopt the patient-specific approach, where the geometry and structure of the heart (including structural remodeling such as infarction or fibrosis ), and in some cases the torso geom­etry, is reconstructed from clinical imaging modalities. Patient-specific electrophysiologic or mechanical information has also begun to be incorporated in simulation studies. This new level of heart function modeling has rendered heart models capable of representing the responses of the heart to inputs from devices, such as pacemakers and defibrillators (particularly implantable cardioverter-defibrillators [ICDs]), including those for cardiac resynchronization therapy (CRT). In this chapter, we review the current state-of-the-art in using computer modeling as applied to patients with devices. Specifically, we focus on simulations that have used human heart models to model antiarrhythmia treatments such as pacing for termination of atrial fibrillation (AF) and ventricular defibrillation, as well as the use of biophysically detailed computer models of the heart for risk stratification of arrhythmias to assess the need of ICD deployment better. We present the basic principles of how such models are developed, along with how simulations of arrhythmias and pump dysfunction as well as patient heart-device interactions can be used to improve treatment of patients with heart disease.

Overview of Modeling Principles and Methodology

Computer modeling of electrophysiology and electromechanics has made enormous progress over the last decade. This section reviews briefly the methodologic basis and advancements in biophysically based models of heart function. A schematic of the current state-of-the-art general approach to 3D multiscale (from the molecule to the organ) electrophysiology modeling (atrial or ventricular) is shown in Figure 22-1 . Modeling the electrophysiology of the heart, even in its most simple mathematical representation, involves propagation of an electrical impulse (cell action potential) in a three-dimensional network of cells. In the vast majority, these models involve biophysically detailed cell membrane kinetics, that is, ionic currents, pumps, and exchangers, the mathematical description of which is based on the formalism introduced by Hodgkin and Huxley. The ionic exchanges across cell membranes, represented by the action potential ionic model comprising numerous ordinary differential and algebraic equations, drive current flow in the tissue.

In tissue, atrial myocytes are electrically connected via low-resistance gap junctions. Ionic current can flow from cell to cell via this pathway, in addition to the current exchange between intracellular and extracellular spaces through cell membrane proteins. Propagation of the action potential is typically modeled using spatially continuous models that are viewed as resulting from a local spatial homogenization of behavior in tissue compartments (membrane, intracellular and extracellular spaces). Current flow in the tissue structure is typically governed by the monodomain reaction-diffusion partial differential equation (PDE) over the tissue or organ volume, with the use of conductivity tensor fields. Simultaneous solution of the PDE(s) with the set of ionic model equations represents simulation of electrical wave propagation in the heart. The conductivity tensor fields used in these continuous models integrate all the information about the distribution of gap junctions over the cell membranes as well as the fiber, sheet, and other microstructure organization in the atria. Cardiac tissue has orthotropic passive electrical conductivities that arise from the cellular organization of the myocardium into fibers and laminar sheets. Global conductivity values in the atrial or ventricular model are obtained by combining fiber and sheet organization with myocyte-specific local conductivity values.

Multiscale models of human heart electrophysiology are typically modular, allowing the use of a variety of cellular ionic models, with different levels of biophysical detail. Solutions are executed on user-specified organ geometries, typically the geometry of individual hearts (atria and/or ventricles), and structure, most often obtained from clinical magnetic resonance imaging (MRI). Clinical MRI scans with a contrast agent (late gadolinum enhancement [LGE]) can also be used to visualize the structural remodeling in atria and ventricles. Figure 22-2A presents ventricular model generation from clinical LGE-MRI images, as described by Prakosa et al in 2014. Figure 22-2A (far right panel) demonstrates how the images can be used to model a reentrant arrhythmia in the patient ventricles. Atrial geometries used in electrophysiologic simulations were acquired using MRI data, as well as computed tomography (CT). Figure 22-2B illustrates the construction of a geometric model of the patient atria from clinical LGE-MRI scans, as described by McDowell et al in 2012, 2013 ; in this case the patient atria show a significant amount of fibrotic remodeling. Because the atria are much thinner than the ventricles, image-based models of at least one of the human atrial chambers can further be subclassified into surface and volumetric models. Surface models represent atrial geometry in three dimensions but neglect wall thickness ; the latter is not true for volumetric models.

Local fiber directions in ventricular or atrial models have traditionally been mapped based on ex vivo histologic sectioning information or on diffusion tensor MRI; however, a different approach, which had to be envisioned for the human studies, is reviewed in this chapter. A novel approach was developed in 2012 using an atlas human heart ; the methodology is shown schematically in Figure 22-3A , with the reconstructed ventricular fiber orientation in a patient heart shown in Figure 22-3B . Rule-based approaches have been used to assign fiber orientation consistent with measurements, either manually or using a semiautomatic rule-based approach. This particularly applies to atrial fiber orientation.

Finally, numeric approaches for simulating the electrical behavior of the heart have been described in detail in previous publications, some of which offer comprehensive reviews on the subject.