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

ABSTRACT Background Bipolar radiofrequency (RF) ablation can create deeper myocardial lesions than unipolar ablation, yet its optimal settings remain undefined. Objective To develop and validate predictive models for lesion transmurality and steam‐pop occurrence during bipolar ablation. Methods Ex vivo bipolar ablation was applied to porcine myocardium (5–20 mm thickness) with catheters placed bilaterally at 45‐degree and 10‐g contact‐force. RF power (20–50 W) and duration (20–180 s) were systematically varied. Generalized linear models (GLM) were trained on 194 applications to predict transmurality and steam‐pop from RF energy, tissue thickness, initial bipolar impedance, 5‐s impedance drop (absolute and percentage PercentImpDrop5), and RF duration; 111 independent applications served as the validation. Results Training yielded 95 transmural lesions (49%) and 11 steam‐pops (5.7%). For transmurality, the model incorporating RF energy, RF duration, initial impedance, and tissue thickness achieved an area under the receiver‐operating characteristics curve (AUC) of 0.95 (95% CI 0.91–0.99) with 88% sensitivity and 100% specificity. Omitting tissue thickness markedly degraded performance (AUC 0.68; DeLong, p = 0.003). For steam‐pop, the model combining RF energy and PercentImpDrop5 showed the best discrimination (AUC 0.90 0.82–0.97, sensitivity 84%, specificity 90%); notably, PercentImpDrop5 alone achieved comparable accuracy (AUC 0.89). Conclusion Tissue thickness is the dominant determinant of transmural lesion formation, whereas early impedance drop serves as a reliable real‐time indicator of steam‐pop risk during bipolar RF ablation. These algorithms may help standardize bipolar ablation protocols by enabling prospective titration of energy delivery based on tissue characteristics and intraprocedural impedance monitoring.