Predicting Transmural Lesion Formation and Steam-Pop Occurrence During Bipolar Ablation-Ex Vivo Porcine Model

Area of Science:

• Cardiovascular Ablation Technologies
• Electrophysiology
• Medical Device Engineering

Background:

• Bipolar radiofrequency (RF) ablation offers deeper myocardial lesions than unipolar ablation.
• Optimal settings for bipolar RF ablation remain undefined, impacting procedural efficacy and safety.

Purpose of the Study:

• Develop and validate predictive models for lesion transmurality.
• Predict steam-pop occurrence during bipolar ablation procedures.

Main Methods:

• Ex vivo porcine myocardium ablation with systematic variation of RF power and duration.
• Generalized linear models (GLM) trained to predict transmurality and steam-pops.
• Model validation using independent ablation applications.

Main Results:

• High accuracy achieved in predicting transmurality (AUC 0.95) with RF energy, duration, initial impedance, and tissue thickness.
• Tissue thickness was the dominant factor for transmural lesion formation.
• Steam-pop prediction model (AUC 0.90) utilizing RF energy and percentage impedance drop (PercentImpDrop5) showed high discrimination.
• PercentImpDrop5 alone demonstrated comparable accuracy for steam-pop prediction.

Conclusions:

• Tissue thickness is the primary determinant of transmural lesion formation in bipolar RF ablation.
• Early impedance drop is a reliable real-time indicator for steam-pop risk.
• Developed algorithms can standardize bipolar ablation protocols by enabling energy titration based on tissue characteristics and impedance monitoring.