Validation of predictive models for lesion transmurality and steam-pop using ex-vivo porcine bipolar ablation model

Abstract

Abstract Introduction Bipolar ablation has been reported to create deeper myocardial ablation lesion as compared to unipolar ablation, however, there is currently no standardized strategy for bipolar ablation settings such as energy and ablation time. Purpose The aim of the present study is to test our hypothesis that both transmural lesion creation and steam-pop occurrence during bipolar ablation can be predicted by the settings of bipolar ablation and the myocardial tissue characteristics such as tissue thickness and initial impedance prior to RF. Methods Using porcine cardiac tissues, we conducted ex-vivo ablation experiments. Commercially available radiofrequency (RF) ablation catheters were utilized for the procedures. Each ablation catheter was positioned bilaterally on the myocardial slices at a 45-degree angle, maintaining a targeted contact force of 10g. We documented the occurrence of steam-pop under various conditions, modulating tissue thickness (5-20 mm), RF power (20, 30, 40, 50 Watt) and ablation duration (20 sec, 40 sec, 60 sec, 180 sec). Generalized linear models (GLM) were developed to forecast the creation of transmural lesion and steam-pop incidents, drawing on the bipolar ablation settings and myocardial tissue characteristics. Subsequently, we engaged in an additional series of experiments to validate the models. Results In total, 194 bipolar applications were utilized as training data. Transmural lesions and steam-pops were observed in 95 (49%), and 11 applications (5.7%), respectively. We constructed GLM using the RF energy (Watt), tissue thickness (mm), initial bipolar impedance (Ohm), impedance drop during the first 5 seconds of application (Ohm), and RF duration (seconds). For transmurality prediction the model validation was conducted with another independent 111 RF applications (102 transmural, and 25 steam-pops). The GLM, which utilized RF energy, tissue thickness, initial bipolar impedance, and RF duration, performed the best performance in predicting transmural lesion creation (AUC 0.94 [0.90-0.99], sensitivity 86 %, specificity 100 %). However, the exclusion of ‘tissue thickness’ from this model led to a significant decrease in its predictive performance (AUC 0.69 [0.48-0.89], sensitivity 47%, specificity 100%, P=0.0057). For pop prediction in validation data, the GLM utilizing RF energy, initial bipolar impedance and impedance drop showed the best performance (AUC 0.90 [0.83-0.97], sensitivity 76 %, specificity 92 %). Conclusion Our data show that accurate assessment of tissue thickness is pivotal for predicting transmural lesion creation. To predict lesion transmurality and steam-pop incidents through RF parameters and tissue characteristics within a beating heart, further research is warranted. This could facilitate the calibration of RF settings, potentially enhancing the safety of bipolar ablation procedures.