CT-based temperature monitoring during hepatic RF ablation: Feasibility in an animal model

Abstract

Purpose: The aim of this paper was to establish non-invasive CT-based temperature monitoring during hepatic radiofrequency (RF) ablation in an ex vivo porcine model followed by transfer of the technique into a feasibility in vivo experiment.

Materials and methods: Bipolar RF ablations were performed in 10 specimens of porcine liver. Parallel to the needle-shaped RF applicator three optical temperature probes were inserted into the liver specimens at fixed distances of 5, 10 and 15 mm from the RF probe. During energy application (20 W) unenhanced sequential MSCT scans were acquired using the following scan protocol: 140 kV tube voltage, 300 mAs/rotation tube current time product, collimation 24 × 1.2 mm, rotation time 0.5 s. Axial image data was reconstructed using a soft tissue convolution kernel. Temperature data was recorded during every CT scan. Using a circular 0.5 cm² region of interest local CT values were measured at the tips of the temperature probes and matched with the measured temperatures. Regression analysis was performed to analyse the relationship between local temperatures and CT values for each temperature probe position. Furthermore, the same experimental design was used in four anaesthetised female pigs in order to investigate the potential of this technique for an in vivo application.

Results: A negative correlation was found for the relationship between temperature and CT value. Regression coefficients were −0.44 (5 mm), −0.35 (10 mm) and −0.37 (15 mm) for ex vivo data. Analysis of in vivo experiments showed regression coefficients between −0.025 and −0.434.

Conclusion: Multislice computed tomography is able to depict temperature changes in liver tissue during RFA.

• radiofrequency ablation
• computed tomography
• thermometry
• attenuation values
• liver

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper. Bernhardt Schmidt is an emlpoyee of Siemens Healthcare.