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Locating Order-Disorder Phase Transition in a Cardiac System
Hiroshi Ashikaga1, Ameneh Asgari-Targhi2
1Cardiac Arrhythmia Service, Johns Hopkins University School of Medicine, 600 N Wolfe Street, Carnegie 568, Baltimore, Maryland, 21287, USA. hashika1@jhmi.edu.
Scientific Reports
|February 2, 2018
Summary
Predicting the origin of cardiac fibrillation wavebreaks is crucial for preventing sudden cardiac death. This study introduces an efficient information-theoretic method to pinpoint these critical locations, aiding in early intervention.
Area of Science:
- Computational Biology
- Cardiac Electrophysiology
- Information Theory
Background:
- Sudden cardiac death is a significant health concern, often caused by ventricular fibrillation.
- Predicting the onset and location of cardiac arrhythmias is vital for effective intervention.
- Understanding phase transitions in cardiac systems is key to preventing fibrillation.
Purpose of the Study:
- To develop a computationally efficient method for predicting the spatial initiation sites of cardiac wavebreaks.
- To apply information-theoretic measures to identify the origins of order-disorder transitions leading to ventricular fibrillation.
- To provide a framework for early detection and prevention of sudden cardiac death.
Main Methods:
- Utilizing an information-theoretic approach to analyze communication between system components.
- Employing measures such as channel capacity, mutual information, and transfer entropy.
- Modeling cardiac systems with a single driving component to mimic electrical misfiring.
Main Results:
- Successfully located critical wavebreak initiation sites using communication analysis.
- Demonstrated the efficacy of channel capacity, mutual information, and transfer entropy in identifying fibrillation origins.
- Validated the approach in a simplified cardiac system model.
Conclusions:
- The proposed information-theoretic method efficiently predicts wavebreak locations, crucial for preventing sudden cardiac death.
- This approach offers a novel strategy for interventional therapies targeting cardiac arrhythmias.
- The methodology is broadly applicable to predicting phase transitions in various complex systems.
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