Modulating OPG and TGF-ß1 mRNA expression via bioelectrical stimulation.

BACKGROUND: Bone remodeling is a lifelong process that ranges from orthodontic tooth movement/alignment to bone damage/healing, to overall bone health. Osteoprotegerin (OPG) and transforming growth factor ß1 (TGF-ß1) are secreted by osteoblasts and participate in bone remodeling. OPG promotes bone remineralization and stabilization prominent in post-mechanical repositioning of the teeth in the dental alveolus. TGF-ß1 participates in regulatory processes to promote osteoblast and osteoclast equilibrium. In the context of orthodontic tooth movement, post-treatment fixation requires additional, exogenous, stabilization support. Recent research showcases supplementary solutions, in conjunction to standard tooth fixation techniques, such as OPG injections into gum and periodontal tissues to accelerate tooth anchorage; however, injections are prone to post-procedure complications and discomfort. This study utilizes noninvasive bioelectric stimulation (BES) to modulate OPG and TGF-ß1 as a novel solution to regulate bone remineralization specifically in the context of post-orthodontic tooth movement. PURPOSE: The aim of this study was to investigate a spectrum of BES parameters that would modulate OPG and TGF-ß1 expression in osteoblasts. METHODS: Osteoblasts were cultured and stimulated using frequencies from 25 Hz to 3 MHz. RT-qPCR was used to quantify changes in OPG and TGFb-1 mRNA expression. RESULTS: OPG mRNA expression was significantly increased at frequencies above 10,000 Hz with a maximum expression increase of 332 ± 8% at 100 kHz. Conversely, OPG mRNA expression was downregulated at frequencies lower than 1000 Hz. TGF-ß1 mRNA expression increased throughout all stimulation frequencies with a peak of 332 ± 72% at 250 kHz. Alizarin Red tests for calcium, indicated that mineralization of stimulated osteoblasts in vitro increased 28% after 6 weeks in culture. DISCUSSION: Results support the working hypothesis that OPG and TGF-ß1 mRNA expression can be modulated through BES. Noninvasive BES approaches have the potential to accelerate bone remineralization by providing a novel tool to supplement the anchorage process, reduce complications, and promote patient compliance and reduce post-treatment relapse. Noninvasive BES may be applicable to other clinical applications as a novel therapeutic tool to modulate bone remodeling.

Validating defibrillation simulation in a human-shaped phantom.

BACKGROUND: We previously developed a computational model to aid clinicians in positioning implantable cardioverter-defibrillators (ICDs), especially in the case of abnormal anatomies that commonly arise in pediatric cases. We have validated the model clinically on the body surface; however, validation within the volume of the heart is required to establish complete confidence in the model and improve its use in clinical settings. OBJECTIVE: The goal of this study was to use an animal model and thoracic phantom to record the ICD potential field within the heart and on the torso to validate our defibrillation simulation system. METHODS: We recorded defibrillator shock potentials from an ICD suspended together with an animal heart in a human-shaped torso tank and compared them with simulated values. We also compared the scaled distribution threshold, an analog to the defibrillation threshold, calculated from the measured and simulated electric fields within the myocardium. RESULTS: ICD potentials recorded on the tank and cardiac surface and within the myocardium agreed well with those predicted by the simulation. A quantitative comparison of the recorded and simulated potentials yielded a mean correlation of 0.94 and a relative error of 19.1%. The simulation can also predict scaled distribution thresholds similar to those calculated from the measured potential fields. CONCLUSION: We found that our simulation could predict potential fields with high correlation with the measured values within the heart and on the torso surface. These results support the use of this model for the optimization of ICD placements.

Novel experimental model for studying the spatiotemporal electrical signature of acute myocardial ischemia: a translational platform.

Myocardial ischemia is one of the most common cardiovascular pathologies and can indicate many severe and life threatening diseases. Despite these risks, current electrocardiographic detection techniques for ischemia are mediocre at best, with reported sensitivity and specificity ranging from 50%-70% and 70%-90%, respectively. OBJECTIVE: To improve this performance, we set out to develop an experimental preparation to induce, detect, and analyze bioelectric sources of myocardial ischemia and determine how these sources reflect changes in body-surface potential measurements. APPROACH: We designed the experimental preparation with three important characteristics: (1) enable comprehensive and simultaneous high-resolution electrical recordings within the myocardial wall, on the heart surface, and on the torso surface; (2) develop techniques to visualize these recorded electrical signals in time and space; and (3) accurately and controllably simulate ischemic stress within the heart by modulating the supply of blood, the demand for perfusion, or a combination of both. MAIN RESULTS: To achieve these goals we designed comprehensive system that includes (1) custom electrode arrays (2) signal acquisition and multiplexing units, (3) a surgical technique to place electrical recording and myocardial ischemic control equipment, and (4) an image based modeling pipeline to acquire, process, and visualize the results. With this setup, we are uniquely able to capture simultaneously and continuously the electrical signatures of acute myocardial ischemia within the heart, on the heart surface, and on the body surface. SIGNIFICANCE: This novel experimental preparation enables investigation of the complex and dynamic nature of acute myocardial ischemia that should lead to new, clinically translatable results.

Experimental Validation of Image-Based Modeling of Torso Surface Potentials During Acute Myocardial Ischemia.

INTRODUCTION: Myocardial ischemia is an early clinical indicator of several underlying cardiac pathologies, including coronary artery disease, Takatsobu cardiomyopathy, and coronary artery dissection. Significant progress has been made in computing body-surface potentials from cardiac sources by solving the forward problem of electrocardiography. However, the lack of in vivo studies to validate such computations from ischemic sources has limited the translational potential of such models. METHODS: To resolve this need, we have developed a large-animal experimental model that includes simultaneous recordings within the myocardium, on the epicardial surface, and on the torso surface during episodes of acute, controlled ischemia. Following each experiment, magnetic resonance images were obtained of the anatomy and electrode locations to create a subject-specific model for each animal. From the electrical recordings of the heart, we identified ischemic sources and used the finite element method to solve a static bidomain equation on a geometric model to compute torso surface potentials. RESULTS: Across 33 individual heartbeats, the forward computed torso potentials showed only moderate agreement in both pattern and amplitude with the measured values on the torso surface. Qualitative analysis showed a more encouraging pattern of elevations and depressions shared by computed and measured torso potentials. Pearson's correlation coefficient, root mean squared error, and absolute error varied significantly by heartbeat (0.1642 ± 0.223, 0.10 ± 0.03mV, and 0.08 ± 0.03mV, respectively). DISCUSSION: We speculate several sources of error in our computation including noise within torso surface recordings, registration of electrode and anatomical locations, assuming a homogeneous torso conductivities, and imposing a uniform "transition zone" between ischemic and non-ischemic tissues. Further studies will focus on characterizing these sources of error and understanding how they effect the study results.

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.

Analyzing Source Sampling to Reduce Error in ECG Forward Simulations.

A continuing challenge in validating ECG Imaging is the persistent error in the associated forward problem observed in experimental studies. One possible cause of error is insufficient representation of the cardiac sources, which is often measured from only the ventricular epicardium, ignoring the endocardium and the atria. We hypothesize that measurements that completely cover the heart are required for accurate forward solutions. In this study, we used simulated and measured cardiac potentials to test the effect of different levels of sampling on the forward simulation. We found that omitting source samples on the atria increases the peak RMS error by a mean of 464 µV when compared the the fully sampled cardiac surface. Increasing the sampling on the atria in stages reduced the average error of the forward simulation proportionally to the number of additional samples and revealed some strategies may reduce error with fewer samples, such as adding samples to the AV plane and the atrial roof. Based on these results, we can design a sampling strategy to use in future validation studies.

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.

The Role of Reduced Left Ventricular, Systolic Blood Volumes in ST Segment Potentials Overlying Diseased Tissue of the Ischemic Heart.

Myocardial ischemia is the response of the heart to reduced coronary blood flow, leading to changes in ST segment potentials. ST segment depression is regarded as an indicator of nontransmural myocardial ischemia; however, not all nontransmural ischemia results in ST depression. This apparent discrepancy may be the result of many complex factors in cardiac response mechanisms to reduced blood flow. As a result, sophisticated computer models have emerged that have provided key insights into this complex phenomenon and the circumstances surrounding ST depression. Though these models have been able to produce ST depressions, many have neglected the effect of intracavitary blood volume, associated with different phases of the cardiac cycle. To explore the influence of the cardiac blood volume variability on epicardial potentials during nontransmural ischemia, we incorporated a thin, subendocardial ischemic zone geometry into an anatomically realistic, image-based ventricular model, and generated a finite element, static bidomain solution to determine the resulting epicardial surface potentials. It was first determined that, under baseline conditions (i.e., expanded left ventricular volumes corresponding to diastole), a predictable ST depression developed over the ischemic region. Left ventricular volume was then incrementally reduced, while maintaining the size and general shape of the ischemic region, in order to reflect the systolic phase of the cardiac cycle. As blood volume geometries decreased, epicardial ST depression overlying the ischemic region first increased in surface area as blood volume was reduced and before dramatically reducing near 30% blood volume reduction - accentuating the role and importance of blood volume variation in computational models of ischemia.

Experimental Data and Geometric Analysis Repository-EDGAR.

INTRODUCTION: The "Experimental Data and Geometric Analysis Repository", or EDGAR is an Internet-based archive of curated data that are freely distributed to the international research community for the application and validation of electrocardiographic imaging (ECGI) techniques. The EDGAR project is a collaborative effort by the Consortium for ECG Imaging (CEI, ecg-imaging.org), and focused on two specific aims. One aim is to host an online repository that provides access to a wide spectrum of data, and the second aim is to provide a standard information format for the exchange of these diverse datasets. METHODS: The EDGAR system is composed of two interrelated components: 1) a metadata model, which includes a set of descriptive parameters and information, time signals from both the cardiac source and body-surface, and extensive geometric information, including images, geometric models, and measure locations used during the data acquisition/generation; and 2) a web interface. This web interface provides efficient, search, browsing, and retrieval of data from the repository. RESULTS: An aggregation of experimental, clinical and simulation data from various centers is being made available through the EDGAR project including experimental data from animal studies provided by the University of Utah (USA), clinical data from multiple human subjects provided by the Charles University Hospital (Czech Republic), and computer simulation data provided by the Karlsruhe Institute of Technology (Germany). CONCLUSIONS: It is our hope that EDGAR will serve as a communal forum for sharing and distribution of cardiac electrophysiology data and geometric models for use in ECGI research.

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.

Verification of a Defibrillation Simulation Using Internal Electric Fields in a Human Shaped Phantom.

We have developed a computer simulation to evaluate the success of Implantable Cardioverter Defibrillators (ICDs) in a patient specific manner. Though we have verified the simulations by means of surface recordings of shock potentials in humans, recordings of potentials within the heart and torso are needed to further verify the model for use in a clinical setting. We suspended an ex-planted porcine heart in a torso shaped electrolytic tank and recorded potentials on the tank surface, the epicardial surface, and within the myocardium during ICD shocks and compared these recordings to finite element solutions based on the same geometries. Potentials recorded from the surface and within the volume of the torso tank agreed well with the simulated potentials. Quantitative comparison between recorded and simulated potentials showed a mean correlation of 0.90, a mean normalized RMS error of 0.102, and a mean relative error of 26.5%. These results suggest that our simulation model can guide the optimization of ICD design and use.

New Additions to the Toolkit for Forward/Inverse Problems in Electrocardiography within the SCIRun Problem Solving Environment.

Cardiac electrical imaging often requires the examination of different forward and inverse problem formulations based on mathematical and numerical approximations of the underlying source and the intervening volume conductor that can generate the associated voltages on the surface of the body. If the goal is to recover the source on the heart from body surface potentials, the solution strategy must include numerical techniques that can incorporate appropriate constraints and recover useful solutions, even though the problem is badly posed. Creating complete software solutions to such problems is a daunting undertaking. In order to make such tools more accessible to a broad array of researchers, the Center for Integrative Biomedical Computing (CIBC) has made an ECG forward/inverse toolkit available within the open source SCIRun system. Here we report on three new methods added to the inverse suite of the toolkit. These new algorithms, namely a Total Variation method, a non-decreasing TMP inverse and a spline-based inverse, consist of two inverse methods that take advantage of the temporal structure of the heart potentials and one that leverages the spatial characteristics of the transmembrane potentials. These three methods further expand the possibilities of researchers in cardiology to explore and compare solutions to their particular imaging problem.

Uncertainty Visualization in Forward and Inverse Cardiac Models.

Quantification and visualization of uncertainty in cardiac forward and inverse problems with complex geometries is subject to various challenges. Specific to visualization is the observation that occlusion and clutter obscure important regions of interest, making visual assessment difficult. In order to overcome these limitations in uncertainty visualization, we have developed and implemented a collection of novel approaches. To highlight the utility of these techniques, we evaluated the uncertainty associated with two examples of modeling myocardial activity. In one case we studied cardiac potentials during the repolarization phase as a function of variability in tissue conductivities of the ischemic heart (forward case). In a second case, we evaluated uncertainty in reconstructed activation times on the epicardium resulting from variation in the control parameter of Tikhonov regularization (inverse case). To overcome difficulties associated with uncertainty visualization, we implemented linked-view windows and interactive animation to the two respective cases. Through dimensionality reduction and superimposed mean and standard deviation measures over time, we were able to display key features in large ensembles of data and highlight regions of interest where larger uncertainties exist.

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.