Spatial organization of acute myocardial ischemia

Aras, Kedar; Burton, Brett; Swenson, Darrell; MacLeod, Rob S.

doi:10.1016/j.jelectrocard.2016.02.014

Cited by 31 publications

(59 citation statements)

References 34 publications

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“…Recent experimental studies, however, have brought the subendocardial ischemia paradigm into question. 2,3 In these studies, intramural extracellular (EC) potentials were measured as an electrical proxy for the metabolic and electrophysiological changes associated with acute ischemia. Spatial distributions of these EC potentials contradicted the accepted dogma of geometrically well-defined, subendocardial ischemic zones.…”

Section: Introductionmentioning

confidence: 99%

“…EC potentials, generated by a variety of different ischemic conditions, were, in general, geometrically complex and intramurally distributed, rather than simple zones located only near the endocardium. 2,3 This discovery of distributed ischemic potentials is a relatively new finding, and has, therefore, seen little application in the computational modeling community. 26 Computational models have historically adopted the schematic ischemic zone paradigm wherein singular, subendocardial ischemic zones, defined by simple geometric primitives, are embedded within a cardiac volume conductor and used as sources from which resulting extracellular potentials throughout the heart can be determined.…”

Section: Introductionmentioning

confidence: 99%

“…12, 13, 20 While schematic computational approaches have been useful in highlighting the electrical effects of ischemia within the heart, 20 they do not fully represent the complexity of ischemic injury as illustrated by the distributed potential patterns reported during experiments. 2,3 This novel discovery necessitates an equally novel simulation approach to elucidate the effects of these sources on computational cardiac models.…”

Section: Introductionmentioning

confidence: 99%

“…To validate our approach, we further constructed a series of subject-specific ischemia simulations that incorporated experimentally obtained electrical signals into image-based, subject-specific cardiac models. 3 By applying image-based modeling approaches, we constructed realistic, three-dimensional cardiac meshes into which we imposed measured EC potentials acquired throughout both the ischemic and the nearby unaffected regions. These potentials acted as boundary conditions from which we computed potential values throughout the heart and over the epicardium.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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“…Each ischemic episode lasted 5–8 minutes with a 30-minute rest between episodes to allow the tissue to return to baseline electrical recordings. The electrocardiographic response to ischemia was measured using 20–40 transmural plunge needles, each with 10 unipolar electrodes evenly distributed within the myocardial tissue, and a 247-electrode eplcardlal sock array that surrounded the ventricles of the heart [8] [9]. Anywhere from 3–8 interventions were performed per animal, using protocols designed to produce ischemia via a supply-demand mismatch in the tissue perfused by the left anterior descending (LAD) artery.…”

Section: Methodsmentioning

confidence: 99%

Temporal Performance of Laplacian Eigenmaps and 3D Conduction Velocity in Detecting Ischemic Stress

Good

Erem

Zenger

et al. 2018

Journal of Electrocardiology

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Background: Myocardial ischemia has a complex and time-varying electrocardiographic signature that is used to diagnose and stratify severity. Despite the ubiquitous clinical use of the ECG to detect ischemia, the sensitivity and specificity of ECG based detection of myocardial ischemia are still inadequate. Purpose: The purpose of this study was to compare, using animal models, the performance of several traditional ECG-based metrics for detecting acute ischemia against two novel metrics, the Laplacian Eigenmap (LE) parameters and a three-dimensional estimate of Conduction Velocity (CV). Methods: LE is a machine learning technique that reduces the dimensions of simultaneously recorded time signals using a non-linear embedding followed by an singular value decomposition to represent each multichannel recording as a single trajectory on a manifold. Perturbations in the trajectories suggest the presence of myocardial ischemia. CV was computed using a tetrahedral mesh created from the electrode locations of transmural plunge needles. To validate the results, we used electrograms collected over 95 episodes of acutely induced myocardial ischemia in 15 canine and 2 porcine subjects. The LE and CV metrics were compared against traditional metrics derived from the ST segment, the T wave, the QRS of the same electrograms. The response time and robustness of each metric was quantified using parameters we defined as time to threshold (TTT) and contrast ratio (CR). Results: The temporal performance of the metrics evaluated throughout the ischemic episodes showed a consistent relationship; the LE metrics changed earlier than those from the T wave, which were followed by those from the ST segment, and finally from the QRS. The CV results showed median drops in conduction velocity throughout the perfusion bed of more than 23 % in canines and over 12% during half of the induced ischemia episodes in swine. The other half of the episodes in swine produced a 76% drop. Conclusions: Our results suggest that the LE metric is more sensitive to acute ischemia than traditional single parameters used in previous studies, likely because it incorporates the entire QRST across multiple electrodes in a way that captures their most salient features in a low-dimensional space. The estimates of conduction velocity suggest substantial, in some cases dramatic slowing of the spread of activation, a finding that is not surprising but has not been documented in such three-dimensional detail before. The experiments and these new metrics provide a means to both explore details of the acute ischemic response not available from humans and suggest a path to translate this knowledge into improvements in clinical scoring of ischemia.

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