First clinical experience using a novel automated mapping algorithm for mapping of ventricular arrhythmias

Area of Science:

• Cardiology
• Electrophysiology
• Medical Imaging

Background:

• Ventricular arrhythmias (VA) pose a significant challenge in managing cardiac conditions.
• Current mapping techniques may not always identify all critical substrate areas for ablation.
• Novel approaches are needed to enhance the precision of catheter ablation for VA.

Purpose of the Study:

• To evaluate the utility of a new automated vector-based mapping algorithm (AMA) for identifying ventricular arrhythmia (VA) ablation targets.
• To assess the correlation between AMA-identified decelerated conduction velocity vectors (CVV) and scar tissue in patients undergoing VA ablation.
• To determine if AMA can improve the understanding of individual VA substrates.

Main Methods:

• Employed a novel automated vector-based mapping algorithm (AMA) for 3D mapping in 16 patients with VA.
• Utilized AMA to identify zones of decelerated conduction velocity vectors (CVV) post-bipolar voltage mapping.
• Superimposed CVV data onto 3D reconstructions and compared with scar characteristics from unipolar voltage mapping.

Main Results:

• Decelerating CVV zones were identified in all patients, with a mean conduction velocity threshold of 39.3±13%.
• Correlation between CVV zones and bipolar low-voltage areas was observed in only 37.5% of patients.
• A strong correlation (94%) was found between CVV deceleration zones and scar identified by unipolar voltage mapping (p=0.008).

Conclusions:

• The automated vector-based mapping algorithm (AMA) effectively visualizes decelerated conduction velocity vectors in patients with ventricular arrhythmias.
• AMA provides valuable insights into individual VA substrates, particularly when correlated with unipolar voltage mapping for scar identification.
• This novel approach may enhance the identification of catheter ablation targets and improve substrate modification strategies for VA.