Rotor Tracking Using Phase of Electrograms Recorded During Atrial Fibrillation

Area of Science:

• Cardiology
• Biomedical Engineering
• Signal Processing

Background:

• Interpreting extracellular electrograms during atrial fibrillation (AF) is difficult due to signal variability.
• Phase mapping, applied to action potentials and unipolar electrograms, aids in understanding fibrillation dynamics.
• Phase mapping has not been previously applied to bipolar electrograms, which are clinically common.

Purpose of the Study:

• To develop and validate a novel algorithm for calculating phase from both unipolar and bipolar electrograms during AF.
• To assess the algorithm's robustness and accuracy in quantifying AF wavefronts and sources.

Main Methods:

• A sequence of signal filters and processing steps were employed to compute phase from simulated, experimental, and clinical unipolar and bipolar electrograms.
• The algorithm was validated against action potential phase in simulated data, compared between unipolar and bipolar phase in experimental data, and used for wavefront identification in clinical atrial tachycardia.

Main Results:

• The algorithm demonstrated high accuracy, with a trajectory center error <0.8 mm when validated against action potential phase in simulated data.
• Similar rotational content (R² = 0.79) and propagation maps (median correlation 0.73) were obtained using unipolar versus bipolar recordings in clinical AF.
• The algorithm proved robust and accurately quantified AF wavefronts and sources.

Conclusions:

• The developed algorithm enables accurate phase calculation from both unipolar and bipolar electrograms during AF.
• This method provides a reliable tool for identifying critical AF sources, such as rotors.
• Improved identification of AF sources can lead to more precise ablation therapy and better patient outcomes.