Tissue Heating During Radiofrequency Catheter Ablation: A Thermodynamic Model and Observations in Isolated Perfused and Superfused Canine Right Ventricular Free Wall
- 30 June 1989
- journal article
- Published by Wiley in Pacing and Clinical Electrophysiology
- Vol. 12 (6), 962-976
- https://doi.org/10.1111/j.1540-8159.1989.tb05034.x
Abstract
Thecharacteristics of radiofrequency catheter ablation induced injury in the heart are not well characterized. Since the mechanism of injury by radiofrequency energy is thermal, this study was performed to determine the temperature gradient in myocardial tissue during radiofrequency (RF) catheter ablation, and to validate a thermodynamic model derived to describe these observations. Lesions were created by RF heating in an experimental model of isolated perfused and superfused canine right ventricular (RV) free wall. RF power output was adjusted to maintain electrode tip temperature at 80°C for 120 seconds in 153 serial lesions and radial temperature gradients were measured. With increasing distance from the electrode, the temperature of the myocardium decreased in a hyperbolic form that was closely predicted by a derived thermodynamic model (P = 0.0001, r = 0.98). This gradient and resultant lesion sizes were unafected by the rate of coronary perfusion. The utility of tip temperature monitoring as a predictor of lesion size was tested in 104 serial lesions with tip temperatures that were varied between 50 and 85°C. The tip temperature correlated closely with lesion depth (P = 0.0001, r = 0.92) and width (P = 0.0001, r = 0.88), and was a better predictor of lesion size than measurements of power, current or energy. The temperature at the margin between viable and nonviable tissue was estimated to be 47.9°C. These data demonstrate that during radiofrequency catheter ablation, the radial temperature gradient is predictably hyperbolic and appears to be independent of intramyocardial perfusion if constant electrode temperature is maintained. The use of tip temperature monitoring can accurately predict the ultimate size of radiofrequency‐induced lesions.Keywords
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