Brett Burton

A toolkit for forward/inverse problems in electrocardiography within the SCIRun problem solving environment

Computational modeling in electrocardiography often requires the examination of cardiac forward and inverse problems in order to non-invasively analyze physiological events that are otherwise inaccessible or unethical to explore. The study of these models can be performed in the open-source SCIRun problem solving environment developed at the Center for Integrative Biomedical Computing (CIBC). A new toolkit within SCIRun provides researchers with essential frameworks for constructing and manipulating electrocardiographic forward and inverse models in a highly efficient and interactive way. The toolkit contains sample networks, tutorials and documentation which direct users through SCIRun-specific approaches in the assembly and execution of these specific problems.

Spatial organization of acute myocardial ischemia

INTRODUCTION Myocardial ischemia is a pathological condition initiated by supply and demand imbalance of the blood to the heart. Previous studies suggest that ischemia originates in the subendocardium, i.e., that nontransmural ischemia is limited to the subendocardium. By contrast, we hypothesized that acute myocardial ischemia is not limited to the subendocardium and sought to document its spatial distribution in an animal preparation. The goal of these experiments was to investigate the spatial organization of ischemia and its relationship to the resulting shifts in ST segment potentials during short episodes of acute ischemia. METHODS We conducted acute ischemia studies in open-chest canines (N=19) and swines (N=10), which entailed creating carefully controlled ischemia using demand, supply or complete occlusion ischemia protocols and recording intramyocardial and epicardial potentials. Elevation of the potentials at 40% of the ST segment between the J-point and the peak of the T-wave (ST40%) provided the metric for local ischemia. The threshold for ischemic ST segment elevations was defined as two standard deviations away from the baseline values. RESULTS The relative frequency of occurrence of acute ischemia was higher in the subendocardium (78% for canines and 94% for swines) and the mid-wall (87% for canines and 97% for swines) in comparison with the subepicardium (30% for canines and 22% for swines). In addition, acute ischemia was seen arising throughout the myocardium (distributed pattern) in 87% of the canine and 94% of the swine episodes. Alternately, acute ischemia was seen originating only in the subendocardium (subendocardial pattern) in 13% of the canine episodes and 6% of the swine episodes (p<0.05). CONCLUSIONS Our findings suggest that the spatial distribution of acute ischemia is a complex phenomenon arising throughout the myocardial wall and is not limited to the subendocardium.

Evaluating the effects of border zone approximations with subject specific ischemia models

Current computational models of acute ischemia are deficient because of their inability to be validated against experimental data and their lack of geometric realism. Past models of ischemia have been based on geometric primitives or hearts for which no electrical measurements exist. One consequence is that it is necessary to make modeling assumptions that are not supported by measurements or direct validation with experiments. Based on our subject specific simulations and measurements, we hypothesize that assumptions about the nature and scale of the border zone play a significant role in determining the cardiac potential distributions from ischemic sources of injury current. Geometrically accurate models were created from Magnetic Resonance Imaging (MRI) and Diffuser Tensor Imaging (DTI) after an in situ canine ischemia experiment. The ischemic zone was defined based on transmural electrode readings and was used in a static bidomain simulation representing a time point during the ST segment. Varying the width of the border zone in the simulations changed the magnitude and distribution of epicardial depressions and elevations. We also found that a border zone with linear variation of potential from healthy to ischemic regions was not adequate to simulate measured potentials. A more sophisticated border zone that included an explicit region of partial ischemia was necessary to simulate the field gradients seen in experimental data.

Sensitivity of epicardial electrical markers to acute ischemia detection

INTRODUCTION We hypothesize that electrocardiographic measurements from the intramyocardial space contain more sensitive markers of ischemia than those detectable on the epicardium. The goal of this study was to evaluate different electrical markers for their potential to detect the earliest phases of acute myocardial ischemia. METHODS We conducted acute ischemia studies in open chest animal, by creating finely controlled demand or supply ischemic episodes and recording intramyocardial and epicardial potentials. RESULTS Under the conditions of mild perfusion deficit, acute ischemia induced changes in the T wave that were larger and could be detected earlier on the epicardial surface than ST-segment changes. CONCLUSIONS Our findings indicate that in the setting of very acute ischemia, epicardial T waves have higher sensitivity to mild degrees of acute ischemia than epicardial ST potentials. These results suggest that changes in the T wave shape may augment shifts in ST segments to improve ECG based localization of ischemia.

Visualization for Understanding Uncertainty in the Simulation of Myocardial Ischemia

We have created the Myocardial Uncertainty Viewer (muView or μView) tool for exploring data stemming from the forward simulation of cardiac ischemia. The simulation uses a collection of conductivity values to understand how ischemic regions effect the undamaged anisotropic heart tissue. The data resulting from the simulation is multivalued and volumetric and thus, for every data point, we have a collection of samples describing cardiac electrical properties. μView combines a suite of visual analysis methods to explore the area surrounding the ischemic zone and identify how perturbations of variables changes the propagation of their effects.

PFEIFER: Preprocessing Framework for Electrograms Intermittently Fiducialized from Experimental Recordings

PFEIFER was specifically designed to process electrocardiographic recordings from electrodes placed on or around the heart or on the body surface. Specific steps included in PFEIFER allow the user to remove some forms of noise, correct for signal drift, and mark specific instants or intervals in time (fiducialize) within all of the time sampled channels. PFEIFER includes many unique features that allow the user to process electrical signals in a consistent and time efficient manner, with additional options for advanced user configurations and input. PFEIFER is structured as a consolidated framework that provides many standard processing pipelines but also has flexibility to allow the user to customize many of the steps. PFEIFER allows the user to import time aligned cardiac electrical signals, semi-automatically determine fiducial markings from those signals, and perform computational tasks that prepare the signals for subsequent display and analysis.

muView: A Visual Analysis System for Exploring Uncertainty in Myocardial Ischemia Simulations

In this paper we describe the Myocardial Uncertainty Viewer (muView or μView) system for exploring data stemming from the simulation of cardiac ischemia. The simulation uses a collection of conductivity values to understand how ischemic regions effect the undamaged anisotropic heart tissue. The data resulting from the simulation is multi-valued and volumetric, and thus, for every data point, we have a collection of samples describing cardiac electrical properties. μView combines a suite of visual analysis methods to explore the area surrounding the ischemic zone and identify how perturbations of variables change the propagation of their effects. In addition to presenting a collection of visualization techniques, which individually highlight different aspects of the data, the coordinated view system forms a cohesive environment for exploring the simulations. We also discuss the findings of our study, which are helping to steer further development of the simulation and strengthening our collaboration with the biomedical engineers attempting to understand the phenomenon.

Image-based modeling of acute myocardial ischemia using experimentally derived ischemic zone source representations

BACKGROUND Computational models of myocardial ischemia often use oversimplified ischemic source representations to simulate epicardial potentials. The purpose of this study was to explore the influence of biophysically justified, subject-specific ischemic zone representations on epicardial potentials. METHODS We developed and implemented an image-based simulation pipeline, using intramural recordings from a canine experimental model to define subject-specific ischemic regions within the heart. Static epicardial potential distributions, reflective of ST segment deviations, were simulated and validated against measured epicardial recordings. RESULTS Simulated epicardial potential distributions showed strong statistical correlation and visual agreement with measured epicardial potentials. Additionally, we identified and described in what way border zone parameters influence epicardial potential distributions during the ST segment. CONCLUSION From image-based simulations of myocardial ischemia, we generated subject-specific ischemic sources that accurately replicated epicardial potential distributions. Such models are essential in understanding the underlying mechanisms of the bioelectric fields that arise during ischemia and are the basis for more sophisticated simulations of body surface ECGs.

Reducing Error in ECG Forward Simulations With Improved Source Sampling

A continuing challenge in validating electrocardiographic imaging (ECGI) is the persistent error in the associated forward problem observed in experimental studies. One possible cause of this error is insufficient representation of the cardiac sources; cardiac source measurements often sample only the ventricular epicardium, ignoring the endocardium and the atria. We hypothesize that measurements that completely cover the pericardial surface are required for accurate forward solutions. In this study, we used simulated and measured cardiac potentials to test the effect of different levels of spatial source sampling on the forward simulation. Not surprisingly, increasing the source sampling over the atria reduced the average error of the forward simulations, but some sampling strategies were more effective than others. Uniform and random distributions of samples across the atrial surface were the most efficient strategies in terms of lowest error with the fewest sampling locations, whereas “single direction” strategies, i.e., adding to the atrioventricular (AV) plane or atrial roof only, were the least efficient. Complete sampling of the atria is needed to eliminate errors from missing cardiac sources, but while high density sampling that covers the entire atria yields the best results, adding as few as 11 electrodes on the atria can significantly reduce these errors. Future validation studies of the ECG forward simulations should use a cardiac source sampling that takes these considerations into account, which will, in turn, improve validation and understanding of ECGI.

A Framework for Image-Based Modeling of Acute Myocardial Ischemia Using Intramurally Recorded Extracellular Potentials

The biophysical basis for electrocardiographic evaluation of myocardial ischemia stems from the notion that ischemic tissues develop, with relative uniformity, along the endocardial aspects of the heart. These injured regions of subendocardial tissue give rise to intramural currents that lead to ST segment deflections within electrocardiogram (ECG) recordings. The concept of subendocardial ischemic regions is often used in clinical practice, providing a simple and intuitive description of ischemic injury; however, such a model grossly oversimplifies the presentation of ischemic disease—inadvertently leading to errors in ECG-based diagnoses. Furthermore, recent experimental studies have brought into question the subendocardial ischemia paradigm suggesting instead a more distributed pattern of tissue injury. These findings come from experiments and so have both the impact and the limitations of measurements from living organisms. Computer models have often been employed to overcome the constraints of experimental approaches and have a robust history in cardiac simulation. To this end, we have developed a computational simulation framework aimed at elucidating the effects of ischemia on measurable cardiac potentials. To validate our framework, we simulated, visualized, and analyzed 226 experimentally derived acute myocardial ischemic events. Simulation outcomes agreed both qualitatively (feature comparison) and quantitatively (correlation, average error, and significance) with experimentally obtained epicardial measurements, particularly under conditions of elevated ischemic stress. Our simulation framework introduces a novel approach to incorporating subject-specific, geometric models and experimental results that are highly resolved in space and time into computational models. We propose this framework as a means to advance the understanding of the underlying mechanisms of ischemic disease while simultaneously putting in place the computational infrastructure necessary to study and improve ischemia models aimed at reducing diagnostic errors in the clinic.