Studying Perfusion Effects on Heat Transfer in Tissue-Mimicking Phantoms for Cardiac Ablation: A Preliminary...

Cardiac arrhythmias are commonly treated using radiofrequency ablation, a minimally invasive technique that has become standard practice. Despite its widespread use, the mechanisms of heat transfer through cardiac tissue during ablation and the factors determining lesion geometry remain incompletely understood. This study investigates the thermal behaviour of tissue-mimicking phantoms with and without perfusion channels to quantify the perfusion-mediated cooling effects present in cardiac ablation. A controlled experimental apparatus was engineered to simulate the in vivo thermal conditions of cardiac tissue. The experiments were performed in a water bath at 37°C, simulating body temperature, and a copper heating element manufactured with high accuracy was used instead of a radiofrequency ablation electrode. Several thermocouples were inserted into the phantom to record temperature changes over time and space, allowing for accurate monitoring of temperature fluctuations. The experiments were carried out in polyacrylamide phantoms containing microchannels, and the flow rate through the channels was varied between 15 and 25 mL/min. The temperature of the heating element was varied between 324 K and 364 K, a range that is relevant for radiofrequency ablation applications. The temperature distribution was affected by the flow in the microchannels, as perfusion reduced the temperature increase in the phantom. The cooling effect exhibited spatial heterogeneity, with temperature distribution varying significantly based on position relative to the perfusion channels. The downstream measurement points (downstream according to the direction of flow in the microchannels) exhibited a higher mean temperature decrease (22%) than the upstream points (10%), and perfusion decreased the temperature gradient between these two regions, homogenizing the heat distribution. These findings provide quantitative benchmarks for incorporating perfusion effects into computational ablation models, potentially enabling more accurate lesion prediction and improved procedural planning in clinical practice.