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Published on: November 3, 2023
Mechanisms of ischemia-induced ST-segment changes
Robert S MacLeod1, Shibaji Shome, Jeroen Stinstra
1Bioengineering Department, University of Utah, Salt Lake City, Utah 84112-5000, USA. macleod@cvrti.utah.edu
Insights
Electrocardiogram (ECG) ST-segment changes during ischemia are poorly understood. Myocardial anisotropy significantly influences ECG responses to ischemia, impacting diagnostic accuracy.
Area of Science:
- Biophysics
- Computational Biology
- Cardiology
Background:
- Electrocardiogram (ECG) ST-segment variations are crucial for diagnosing myocardial ischemia, yet their biophysical basis remains incompletely understood.
- Current ECG-based ischemia detection methods show limitations, particularly for subendocardial ischemia.
Purpose of the Study:
- To develop a comprehensive mechanistic model of the electrocardiographic effects of myocardial ischemia.
- To elucidate the biophysical underpinnings of ECG changes during ischemia, focusing on the role of myocardial anisotropy.
Main Methods:
- Developed a computational model using realistic heart geometry and anisotropic fiber structure to simulate ischemic action potentials.
- Incorporated a high-resolution myocardial tissue model to define electrical characteristics, including gap junctional coupling.
- Conducted experimental studies using isolated and in situ dog hearts to replicate ischemic conditions by controlling coronary blood flow.
Main Results:
- The study reveals that the electrocardiographic response to ischemia is strongly dependent on the anisotropic conductivity of the myocardium.
- Ischemic injury currents interact with local fiber orientation and conductivity, generating secondary currents that determine epicardial ST-segment potentials.
- Experimental results qualitatively support simulation findings, highlighting the critical role of myocardial anisotropy.
Conclusions:
- Myocardial anisotropy is a key factor in generating electrocardiographic changes during ischemia.
- Understanding these anisotropic effects can improve the accuracy of ECG-based ischemia detection and characterization.
- The developed mechanistic model provides a framework for further investigation into ECG-ischemia relationships.
Abstract:
Many aspects of ischemia-induced changes in the electrocardiogram lack solid biophysical underpinnings although variations in ST segments form the predominant basis for diagnostic and monitoring of patients. This incomplete knowledge certainly plays a role in the poor performance of some forms of electrocardiogram-based detection and characterization of ischemia, especially when it is limited to the subendocardium. The focus of our recent studies has been to develop a comprehensive mechanistic model of the electrocardiographic effects of ischemia. The computational component of this model is based on highly realistic heart geometry with anisotropic fiber structure and allows us to assign ischemic action potentials to contiguous regions that can span a prescribed thickness of the ventricles. A separate, high-resolution model of myocardial tissue provides us with a means of setting electrical characteristics of the heart, including the status of gap junctional coupling between cells. The experimental counterpart of this model consists of dog hearts, either in situ or isolated and perfused with blood, in which we control coronary blood flow by means of a cannula and blood pump. By reducing blood flow through the cannula for various durations, we can replicate any phase of ischemia from hyper acute to early infarction. Based on the results of these models, there is emerging a mechanism of the electrocardiographic response to ischemia that depends strongly on the anisotropic conductivity of the myocardium. Ischemic injury currents flow across the boundary between healthy and ischemic tissue, but it is their interaction with local fiber orientation and the associated conductivity that generates secondary currents that determine epicardial ST-segment potentials. Results from experiments support qualitatively the findings of the simulations and underscore the role of myocardial anisotropy in electrocardiography.
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