An automated technique for identification and analysis of activation fronts in a two-dimensional electrogram array

Area of Science:

• Cardiovascular physiology
• Computational biology
• Biomedical engineering

Background:

• Cardiac activation mapping traditionally relies on manual or semi-automated methods.
• These methods are insufficient for distorted electrograms or rapidly changing rhythms like ventricular fibrillation, leading to subjective and time-consuming analyses.

Purpose of the Study:

• To develop and validate a computer-based method for automated identification and analysis of cardiac activation fronts.
• To overcome the limitations of manual mapping in complex cardiac electrophysiological scenarios.

Main Methods:

• Utilized a large array of closely spaced electrodes (1 mm) to eliminate the need for interpolation.
• Defined activation detection based on the temporal derivative of the potential exceeding a user-specified threshold.
• Grouped spatially and temporally proximate activations to identify distinct activation fronts and quantified their characteristics.

Main Results:

• The automated method demonstrated comparable repeatability to human investigators.
• The system successfully quantified characteristics of activation fronts, including number, size, and phenomena like reentry or collision.
• The automated approach significantly reduced the time and subjectivity associated with traditional mapping methods.

Conclusions:

• The developed computer-based method provides a rapid, repeatable, and objective approach for analyzing cardiac activation sequences.
• This automation is particularly beneficial for complex cardiac conditions where traditional mapping methods are inadequate.
• The algorithm offers a significant advancement in the field of cardiac electrophysiology mapping.