Abstract

Radiofrequency ablation (RFA) has been widely used as an alternative treatment modality for liver tumors. Monitoring the temperature distribution in the tissue during RFA is required to assess the thermal dosage. Ultrasound temperature imaging based on the detection of echo time shifts has received the most attention in the past decade. The coefficient k, connecting the temperature change and the echo time shift, is a medium-dependent parameter used to describe the confounding effects of changes in the speed of sound and thermal expansion as temperature increases. The current algorithm of temperature estimate based on echo time shift detection typically uses a constant k, resulting in estimation errors when ablation temperatures are higher than 50°C. This study proposes an adaptive-k algorithm that enables the automatic adjustment of the coefficient k during ultrasound temperature monitoring of RFA. To verify the proposed algorithm, RFA experiments on in vitro porcine liver samples (total n = 15) were performed using ablation powers of 10, 15, and 20 W. During RFA, a clinical ultrasound system equipped with a 7.5-MHz linear transducer was used to collect backscattered signals for ultrasound temperature imaging using the constant- and adaptive-k algorithms. Concurrently, an infrared imaging system and thermocouples were used to measure surface temperature distribution of the sample and internal ablation temperatures for comparisons with ultrasound estimates. Experimental results demonstrated that the proposed adaptive-k method improved the performance in visualizing the temperature distribution. In particular, the estimation errors were also reduced even when the temperature of the tissue is higher than 50°C. The proposed adaptive-k ultrasound temperature imaging strategy has potential to serve as a thermal dosage evaluation tool for monitoring high-temperature RFA.

Highlights

  • Liver cancer is a common cause of cancer mortality [1]

  • To improve the performance of echo time shift detection using the constant k in monitoring radiofrequency ablation (RFA), this study developed ultrasound temperature imaging algorithm based on an adaptive estimation of k

  • The yellow cross marks and red circles in the B-mode images indicate the locations of the RF electrode and thermocouples, respectively

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Summary

Introduction

Liver cancer is a common cause of cancer mortality [1]. Hepatocellular carcinoma (HCC) accounts for 85%–90% of primary liver cancers [2]. Surgical resection and liver transplants are currently considered mainstream HCC treatments; not every patient is suitable for undergoing these treatments due to clinical considerations. In such a situation, minimally invasive radiofrequency ablation (RFA) is used as the primary alternative modality for clinical HCC treatment [3,4,5,6]. During clinical RFA, the insertion of the RF electrode into the tumor is widely guided by computed tomography (CT) and ultrasound B-mode imaging. Note that RFA-induced high temperature typically results in the formation of gas bubbles in the ablation zone. Thanks to the advances in data analysis methods, ultrasonography has gradually become popular and attractive in monitoring RFA

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