Spatio-Temporal Analysis of Acute Myocardial Ischaemia Based on Entropy-Complexity Plane.

Area of Science:

• Cardiology
• Information Theory
• Medical Signal Processing

Background:

• Myocardial ischaemia, often due to coronary atherosclerosis, disrupts cardiac electrical activity, raising arrhythmia risk.
• Understanding ECG changes during specific coronary artery occlusions is crucial for diagnosis and management.

Purpose of the Study:

• To differentiate the electrocardiogram (ECG) behavior during left anterior descending (LAD) and right anterior coronary artery (RCA) occlusions.
• To apply information theory quantifiers for analyzing spatio-temporal ECG dynamics during ischaemia.

Main Methods:

• Utilized a standard 12-lead ECG database, recording baseline and during percutaneous transluminal coronary angioplasty (PTCA) occlusion/reperfusion.
• Applied the Bandt and Pompe permutation method to estimate probability distributions from the ECG vector modulus.
• Analyzed ECG dynamics using H×C causal plane positioning for control and ischaemia states.

Main Results:

• LAD occlusion showed decreased entropy and increased complexity, indicating more predictable ECG patterns.
• RCA occlusion exhibited increased entropy and decreased complexity, signifying less predictable and organized ECG dynamics.
• Both LAD and RCA occlusions resulted in decreased entropy and complexity during reperfusion.

Conclusions:

• Information theory quantifiers effectively distinguish ECG alterations between LAD and RCA occlusions.
• ECG complexity and predictability change differentially based on the occluded coronary artery.
• Reperfusion normalizes ECG complexity and entropy, regardless of the initially occluded artery.