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Quantifying the effect of uncertainty in input parameters in a simplified bidomain model of partial thickness
Barbara M Johnston1, Sam Coveney2, Eugene T Y Chang3
1Queensland Micro- and Nanotechnology Centre and School of Natural Sciences, Griffith University, Nathan, QLD, 4111, Australia.
Insights
Understanding myocardial ischaemia requires analyzing ST-segment changes. This study models cardiac electrical activity to explore how fibre angles and ischaemia depth influence these ECG patterns, improving diagnostic accuracy.
Area of Science:
- Cardiovascular Physiology
- Computational Biology
- Biomedical Engineering
Background:
- Reduced coronary blood flow causes myocardial ischaemia, damaging heart tissue.
- Electrocardiogram (ECG) ST-segment changes are used to detect ischaemia, but their link to subendocardial issues is unclear.
Purpose of the Study:
- To model ST-segment epicardial potentials in cardiac tissue with a central ischaemic region.
- To quantify the impact of parameter uncertainty on epicardial potential distribution.
Main Methods:
- Utilized the bidomain model for cardiac ventricular tissue simulation.
- Incorporated fibre rotation, ischaemic depth, blood conductivity, and bidomain conductivities as variables.
- Analyzed epicardial potential distributions and ST depression magnitude.
Main Results:
- Three distinct epicardial potential distributions were observed across various ischaemic depths.
- Fibre rotation angle and ischaemic depth influenced the location of potential minima, not conductivity values.
- ST depression magnitude was sensitive to longitudinal and normal conductivities, but not transverse ones.
Conclusions:
- The study clarifies the complex relationship between myocardial ischaemia and ECG manifestations.
- Accurate modelling of cardiac electrophysiology is crucial for understanding ischaemia detection.
Abstract:
Reduced blood flow in the coronary arteries can lead to damaged heart tissue (myocardial ischaemia). Although one method for detecting myocardial ischaemia involves changes in the ST segment of the electrocardiogram, the relationship between these changes and subendocardial ischaemia is not fully understood. In this study, we modelled ST-segment epicardial potentials in a slab model of cardiac ventricular tissue, with a central ischaemic region, using the bidomain model, which considers conduction longitudinal, transverse and normal to the cardiac fibres. We systematically quantified the effect of uncertainty on the input parameters, fibre rotation angle, ischaemic depth, blood conductivity and six bidomain conductivities, on outputs that characterise the epicardial potential distribution. We found that three typical types of epicardial potential distributions (one minimum over the central ischaemic region, a tripole of minima, and two minima flanking a central maximum) could all occur for a wide range of ischaemic depths. In addition, the positions of the minima were affected by both the fibre rotation angle and the ischaemic depth, but not by changes in the conductivity values. We also showed that the magnitude of ST depression is affected only by changes in the longitudinal and normal conductivities, but not by the transverse conductivities.