A computational modeling framework for pre-clinical evaluation of cardiac mapping systems.

Area of Science:

• Computational modeling
• Cardiac electrophysiology
• Medical device evaluation

Background:

• Evaluating clinical cardiac mapping systems is challenging due to the lack of a
• gold standard
• for transmembrane potential recording.
• Cardiac mapping systems integrate hardware, software, and algorithms, all undergoing rapid development.

Purpose of the Study:

• To develop a computational modeling framework for evaluating cardiac mapping system performance.
• To enable rigorous assessment of the ability to localize and characterize arrhythmogenic cardiac sources.
• To provide a standardized method for assessing system accuracy and reliability.

Main Methods:

• Created a library of computer simulations of cardiac electrical activity with known arrhythmogenic source types and locations.
• Enabled evaluation across diverse electrode configurations, heart geometries, arrhythmias, and electrogram noise levels.
• Utilized a
• silver standard
• of known transmembrane potentials for blind comparison with mapping systems.

Main Results:

• A feasibility study simulated human left atrial patterns with virtual catheter arrays.
• Identified that average root mean squared difference of activation times (AcTs) below 1 ms is an insufficient performance metric.
• Introduced a novel metric quantifying correct and spurious activation pattern (AcP) identification, arrhythmia misclassification, and localization accuracy.

Conclusions:

• The developed computational framework offers a rigorous, quantitative analysis of cardiac mapping system performance.
• Proof of concept demonstrates the framework's potential to ensure mapping systems function as expected.
• The framework can provide crucial estimates of cardiac mapping system accuracy and reliability.