Estimation and Validation of Cardiac Conduction Velocity and Wavefront Reconstruction Using Epicardial and Volumetric Data

Diffuse functional and structural abnormalities in fibrosis: Potential structural basis for sustaining atrial fibrillation

BACKGROUND

Structural remodeling has been associated with increased incidence of atrial fibrillation, but how fibrotic regions allow atrial fibrillation to be sustained remains unclear.

OBJECTIVE

With a novel transgenic goat model, we evaluated structural and functional differences between structurally remodeled and healthy regions of the atria.

METHODS

A novel transgenic goat model with cardiac-specific overexpression of transforming growth factor β1 was used. Ex vivo cardiac magnetic resonance imaging and histology were used to evaluate differences in fibrosis, fiber disarray, and structural anisotropy. Functional analysis examined conduction speeds and direction heterogeneity. By use of underlying fiber orientation obtained with diffusion tensor imaging, conduction anisotropy was calculated.

RESULTS

The transgenic goats had on average 21% of the left atria labeled fibrotic, determined from ex vivo cardiac magnetic resonance imaging. The histology samples within the labeled fibrotic regions showed an increase in fibrosis percentage. Fractional anisotropy, a measurement of structural anisotropy, was lower, whereas fiber direction heterogeneity, a measurement of the angle difference of the fiber from its neighbors, was greater, indicating increased fiber disarray in fibrotic regions. The fibrotic regions had slower conduction speeds and more aligned conduction directions, potentially allowing unidirectional conduction block to develop. Conduction anisotropy, measured on the underlying fiber directions, was found to be lower in the fibrotic regions.

CONCLUSION

Fibrotic regions had slower conduction, and propagation tended to flow more unidirectionally. The direction of propagation differs from the underlying fiber direction, leading to lower conduction anisotropy. Functional and structural abnormalities of the fibrotic tissue may allow fibrotic regions to serve as a substrate for an arrhythmia to develop and to be sustained.

Functional and Structural Remodeling as Atrial Fibrillation Progresses in a Persistent Atrial Fibrillation Canine Model

BACKGROUND

Contractile, electrical, and structural remodeling has been associated with atrial fibrillation (AF), but the progression of functional and structural changes as AF sustains has not been previously evaluated serially.

OBJECTIVES

Using a rapid-paced persistent AF canine model, the authors aimed to evaluate the structural and functional changes serially as AF progresses.

METHODS

Serial electrophysiological studies in a chronic rapid-paced canine model (n = 19) prior to AF sustaining and repeated at 1, 3, and 6 months of sustained AF were conducted to measure changes in atrial conduction speed and direction. Cardiac late gadolinium enhancement magnetic resonance imaging was performed prior to and following sustained AF to evaluate structural remodeling.

RESULTS

As AF progressed, the overall area of the left atrium with fibrosis increased. Over time, conduction speeds slowed, with speeds decreasing by 0.15 m/s after 3 months and 0.26 m/s after 6 months of sustained AF. Regions that developed fibrosis experienced greater slowing compared with healthy regions (0.32 ± 0.01 m/s decrease vs 0.21 ± 0.01 m/s decrease; P < 0.001). Conduction directions became more aligned (conduction direction heterogeneity decreased from 19.7 ± 0.1° to 17.5 ± 0.1° after 6 months of sustained AF; P < 0.001). Fibrotic regions had a greater decrease in conduction direction heterogeneity (2.7 ± 0.3° vs 2.0 ± 0.2°; P = 0.008).

CONCLUSIONS

As AF progressed, functional changes occurred globally throughout the left atrium. Conduction speed slowed, and conduction directions became more aligned over time, with the greatest changes occurring within regions that developed fibrosis.

A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data

Computational models of cardiac electrophysiology have gradually matured during the past few decades and are now being personalised to provide patient-specific therapy guidance for improving suboptimal treatment outcomes. The predictive features of these personalised electrophysiology models hold the promise of providing optimal treatment planning, which is currently limited in the clinic owing to reliance on a population-based or average patient approach. The generation of a personalised electrophysiology model entails a sequence of steps for which a range of activation mapping, calibration methods and therapy simulation pipelines have been suggested. However, the optimal methods that can potentially constitute a clinically relevant in silico treatment are still being investigated and face limitations, such as uncertainty of electroanatomical data recordings, generation and calibration of models within clinical timelines and requirements to validate or benchmark the recovered tissue parameters. This paper is aimed at reporting techniques on the personalisation of cardiac computational models, with a focus on calibrating cardiac tissue conductivity based on electroanatomical mapping data.

Capturing the Influence of Conduction Velocity on Epicardial Activation Patterns Using Uncertainty Quantification

Individual variability in parameter settings, due to either user selection or disease states, can impact accuracy when simulating the electrical behavior of the heart. Here, we aim to test the impact of inevitable uncertainty in conduction velocities (CVs) on the output of simulations of cardiac propagation, given three stimulus locations on the left ventricular (LV) free wall. To understand the role of physiological variability in CV in simulations of cardiac activation, we generated detailed maps of the variability in propagation simulations by implementing bi-ventricular activation simulations and quantified the effects by deploying robust uncertainty quantification techniques based on polynomial chaos expansion (PCE). PCE allows efficient stochastic exploration with reduced computational demand by utilizing an emulator for the underlying forward model. Our results suggest that CV within healthy physiological ranges plays a small role in the activation times across all stimulation locations. However, we noticed differences in variation coefficients depending on the stimulation site, i.e., LV endocardium, midmyocardium, and epicardium. We observed low levels of variation in activation times near the earliest activation sites, whereas there was higher variation toward the termination sites. These results suggest that CV variability can play a role when simulating healthy and diseased states.

Optical Mapping of Cardiomyocytes in Monolayer Derived from Induced Pluripotent Stem Cells

Optical mapping is a powerful imaging technique widely adopted to measure membrane potential changes and intracellular Ca2+ variations in excitable tissues using voltage-sensitive dyes and Ca2+ indicators, respectively. This powerful tool has rapidly become indispensable in the field of cardiac electrophysiology for studying depolarization wave propagation, estimating the conduction velocity of electrical impulses, and measuring Ca2+ dynamics in cardiac cells and tissues. In addition, mapping these electrophysiological parameters is important for understanding cardiac arrhythmia mechanisms. In this review, we delve into the fundamentals of cardiac optical mapping technology and its applications when applied to hiPSC-derived cardiomyocytes and discuss related advantages and challenges. We also provide a detailed description of the processing and analysis of optical mapping data, which is a crucial step in the study of cardiac diseases and arrhythmia mechanisms for extracting and comparing relevant electrophysiological parameters.

Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models

The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.

Atrial conduction velocity mapping: clinical tools, algorithms and approaches for understanding the arrhythmogenic substrate

Characterizing patient-specific atrial conduction properties is important for understanding arrhythmia drivers, for predicting potential arrhythmia pathways, and for personalising treatment approaches. One metric that characterizes the health of the myocardial substrate is atrial conduction velocity, which describes the speed and direction of propagation of the electrical wavefront through the myocardium. Atrial conduction velocity mapping algorithms are under continuous development in research laboratories and in industry. In this review article, we give a broad overview of different categories of currently published methods for calculating CV, and give insight into their different advantages and disadvantages overall. We classify techniques into local, global, and inverse methods, and discuss these techniques with respect to their faithfulness to the biophysics, incorporation of uncertainty quantification, and their ability to take account of the atrial manifold.

Combining endocardial mapping and electrocardiographic imaging (ECGI) for improving PVC localization: A feasibility study

INTRODUCTION

Accurate reconstruction of cardiac activation wavefronts is crucial for clinical diagnosis, management, and treatment of cardiac arrhythmias. Furthermore, reconstruction of activation profiles within the intramural myocardium has long been impossible because electrical mapping was only performed on the endocardial surface. Recent advancements in electrocardiographic imaging (ECGI) have made endocardial and epicardial activation mapping possible. We propose a novel approach to use both endocardial and epicardial mapping in a combined approach to reconstruct intramural activation times.

OBJECTIVE

To implement and validate a combined epicardial/endocardial intramural activation time reconstruction technique.

METHODS

We used 11 simulations of ventricular activation paced from sites throughout myocardial wall and extracted endocardial and epicardial activation maps at approximate clinical resolution. From these maps, we interpolated the activation times through the myocardium using thin-plate-spline radial basis functions. We evaluated activation time reconstruction accuracy using root-mean-squared error (RMSE) of activation times and the percent of nodes within 1 ms of the ground truth.

RESULTS

Reconstructed intramural activation times showed an RMSE and percentage of nodes within 1 ms of the ground truth simulations of 3 ms and 70%, respectively. In the worst case, the RMSE and percentage of nodes were 4 ms and 60%, respectively.

CONCLUSION

We showed that a simple, yet effective combination of clinical endocardial and epicardial activation maps can accurately reconstruct intramural wavefronts. Furthermore, we showed that this approach provided robust reconstructions across multiple intramural stimulation sites.

A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation

In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is played, in this respect, by a new way of setting a parametrization of electrophysiological mathematical models based on conduction velocities; these latter are estimated from high-density mapping data, which provide a detailed characterization of patients' electrophysiological substrate during sinus rhythm. We integrate numerically approximated conduction velocities into a mathematical model consisting of a coupled system of partial and ordinary differential equations, formed by the monodomain equation and the Courtemanche-Ramirez-Nattel model. Our new model parametrization is then adopted to predict the formation and self-sustainment of localized reentries characterizing atrial fibrillation, by numerically simulating the onset of ectopic beats from the pulmonary veins. We investigate the paroxysmal and the persistent form of AF starting from electro-anatomical maps of two patients. The model's response to stimulation shows how substrate characteristics play a key role in inducing and sustaining these arrhythmias. Localized reentries are less frequent and less stable in case of paroxysmal AF, while they tend to anchor themselves in areas affected by severe slow conduction in case of persistent AF.

Quantifying the Spatiotemporal Influence of Acute Myocardial Ischemia on Volumetric Conduction Speeds

Acute myocardial ischemia compromises the ordered electrical activation of the heart, however, because of sampling limitations, volumetric changes in activation have not been measured. We used a large-animal experimental model and high-resolution volumetric mapping to study the effects of ischemia on conduction speeds (CS) throughout the myocardium. We estimated CS and electrocardiographic changes (ST segments) and evaluated the spatial and temporal correlations between them across 11 controlled episodes. We found that ischemia induces significant conduction slowing, reducing the global median speed by 25 cm/s. Furthermore, there was a high temporal correlation between the development of ischemic severity and CS (corr. = 0.93) through each episode. The spatial correlations between ST-segment changes and CS slowing were more spatially complex than expected with substantial slowing at the periphery of the zones that showed ST-segment changes. This is the first study that has documented in an experimental model volumetric changes of CS during acute myocardial ischemia and explored the relationships between ischemia development in space and time. We showed that conduction speed changes are spatiotemporally correlated to ischemic severity and illustrated the biphasic response long proposed from cellular studies.