Temperature map of kidneys undergoing microwave ablation using computed tomography-thermometry: ex-vivo experiments and numerical simulations

Abstract

This study aims at assessing the temperature distribution in kidney undergoing a two-antennae Microwave Ablation (MWA) at 2.45GHz. The feasibility of thermometry based on Computed Tomography (CT) images were studied, and a 3D finite element model was developed to obtain the organ thermal distribution during the treatment. MWA is a minimally invasive technique used to ablate solid tumors: the tissues electrical properties enable absorption of electromagnetic energy, resulting into heat generation. Hence, the monitoring of tissue temperature during the procedure is pivotal to assure the optimal treatment outcome. CT imaging can be used to monitor the tissue temperature change with a contactless approach and should be calibrated for each organ. The thermal sensitivity of CT thermometry was investigated at two CT scan settings. Four fresh pig kidneys were treated using two MW antennae at 65 W and for 4 minutes, and reference temperature was measured by thermocouples. The relationship between the CT number and the increase of tissue temperature was obtained by using a linear regression analysis, and the thermal sensitivity was estimated as the slope of the best fitting line. The CT number shows an inverse linear relationship with tissue temperature with a thermal sensitivity of approximately -0.34 HU•°C-1. The scan settings have a negligible influence on thermal sensitivity; conversely, at higher kVp and mAs there is a better agreement between the temperature values estimated by CT thermometry and the reference ones. The predictions of the FEM model are confirmed by the measured temperature values, e.g., 80 °C at 1.5 cm from the antennae at the end of the ablation, even though a slight difference exists at bigger distance (33 °C theoretical vs <42 °C experimental). For the deviation of the simplified theoretical model to the real scenario, CT thermometry can be a great benefit: the 2D thermal image can correct the model predictions and has the potential to support the medical doctor in the immediate evaluation of the outcome at clinically relevant locations.