Phase singularity detection through phase map interpolation: Theory, advantages and limitations.

Area of Science:

• Cardiac Electrophysiology
• Computational Cardiology
• Medical Imaging Analysis

Background:

• Cardiac arrhythmias involve reentrant waves rotating around phase singularities (PS).
• Accurate PS detection is crucial for understanding arrhythmia dynamics and identifying ablation targets.
• Phase interpolation methods are proposed to enhance the precision of PS localization.

Purpose of the Study:

• To establish a theoretical foundation for phase interpolation techniques in PS detection.
• To conduct a comparative analysis of different phase interpolation methods.
• To evaluate the impact of noise on PS localization accuracy.

Main Methods:

• Simulated synthetic phase maps with PS and varying levels of background noise.
• Employed different electrode configurations (triangular, square, circular arrays).
• Utilized linear, spline, and inverse squared distance interpolation methods.
• Performed Monte-Carlo simulations over millions of realizations to assess performance.

Main Results:

• Linear interpolation was equivalent to standard discrete methods.
• Spline interpolation reduced false negatives but increased false positives with noise.
• Inverse squared distance interpolation decreased false positives and improved noise robustness but risked missing PS detection.
• Phase interpolation reduced PS localization error to 0.17 interelectrode distance, with errors increasing near electrodes.

Conclusions:

• Phase interpolation methods provide adjustable trade-offs between minimizing false positives and false negatives.
• These techniques enhance the accuracy and reliability of phase singularity detection in cardiac mapping.