Considerations for Thermal Injury Analysis for RF Ablation Devices

Abstract

Abstract:Background: The estimation of lesion size is an integral part of treatment planning for the clinical applications of radiofrequency ablation. However, to date, studies have not directly evaluated the impact of different computational estimation techniques for predicting lesion size. In this study, we focus on three common methods used for predicting tissue injury: (1) iso-temperature contours, (2) Cumulative equivalent minutes, (3) Arrhenius based thermal injury. Methods:We created a geometric model of a multi-tyne ablation electrode and simulated thermal and tissue injury profiles that result from three calculation methods after 15 minutes exposure to a constant RF voltage source. A hybrid finite element technique was used to calculate temperature and tissue injury. Time-temperature curves were used in the assessment of iso-temperature thresholds and the method of cumulative equivalent minutes. An Arrhenius-based formulation was used to calculate sequential and recursive thermal injury to tissues. Results: The data demonstrate that while iso-temperature and cumulative equivalent minute contours are similar in shape, these two methodologies grossly over-estimate the amount of tissue injury when compared to recursive thermal injury calculations, which have previously been shown to correlate closely with in vitro pathologic lesion volume measurement. In addition, Arrhenius calculations that do not use a recursive algorithm result in a significant underestimation of lesion volume. The data also demonstrate that lesion width and depth are inadequate means of characterizing treatment volume for multi-tine ablation devices. Conclusions: Recursive thermal injury remains the most physiologically relevant means of computationally estimating lesion size for hepatic tumor applications. Iso-thermal and cumulative equivalent minute approaches may produce significant errors in the estimation of lesion size.

Review of the mathematical functions used to model the temperature dependence of electrical and thermal conductivities of biological tissue in radiofrequency ablation

“…where  b is density of blood (1000 kg/m 3 ) [14], c b specific heat of blood (4180 J/Kg·K) [8], T b blood temperature (37 ºC),  b blood perfusion coefficient (6.410 -3 s -1 ) [32] and  is a coefficient which took the values of 0 and 1, depending on the value of the local thermal damage : = 0 for   1, and = 1 for  < 1. The parameter  was assessed by the Arrhenius damage model [32], which associates temperature with exposure time using a first-order kinetics relationship:…”

“…The parameter  was assessed by the Arrhenius damage model [32], which associates temperature with exposure time using a first-order kinetics relationship:…”

Radiofrequency cardiac ablation with catheters placed on opposing sides of the ventricular wall: Computer modelling comparing bipolar and unipolar modes

“…The thermal lesions created in the ventricular wall were assessed using the Arrhenius damage model [12][13][14][15], which associates temperature with exposure time using a first order kinetics relationship:…”

Ex Vivo Liver Tissue Radiofrequency Thermal Ablation: Ir Measurements and Simulations

“… and are calibration parameters while ()  is the temperature integral of the Gaussian function (i.e., the relative amount of absorbed latent heat) that can be taken as the vapor volume fraction. The thermal lesion boundary is approximated either using an Arrhenius damage model (Schutt and Haemmerich, 2008;Haemmerich and Schutt, 2011) or simply through a temperature isotherm; both 50°C (Mulier et al, 2012;Viglianti et al, 2014) and 60°C isotherms (Chang, 2010;Wood et al, 2011) …”