An automated fractionation mapping algorithm for mapping of scar-based ventricular tachycardia

Area of Science:

• Cardiovascular Electrophysiology
• Medical Device Technology

Background:

• Scar-based ventricular tachycardia (VT) treatment involves mapping and ablating fractionated electrograms.
• Automated fractionation mapping algorithms offer a rapid approach to identify these targets.

Purpose of the Study:

• To evaluate the sensitivity and specificity of an automated fractionation mapping (fMap) algorithm for identifying ablation sites in scar-based VT.
• To determine optimal signal processing parameters for accurate fMap generation.

Main Methods:

• Retrospective analysis of electroanatomic maps from 21 ablation procedures (14 scar-based VT, 7 controls).
• Generation of 30 fMaps using varying width, refractory time, sensitivity, and fractionation threshold parameters.
• Assessment of parameter sensitivity by overlap with successful ablation sites and specificity by presence in control patients.

Main Results:

• Three parameter combinations met criteria for high sensitivity and specificity.
• The optimal parameter set (20/30/0.1/2) identified 79% of VT ablation sites with significantly less fractionation in controls (42.3 vs 4.9 cm², P=.001).
• VT recurrence was 23% in scar-based VT patients versus 0% in controls at 15-month follow-up.

Conclusions:

• Careful selection of signal processing parameters is crucial for optimizing automated fractionation mapping in scar-based VT.
• Real-time application of fMap algorithms may shorten ablation procedure duration and enhance substrate modification, potentially improving patient outcomes.