A Systemic Study on the Performance of Different Quantitative Ultrasound Imaging Techniques for Microwave Ablation Monitoring of Liver

Nakagami分布 微波消融 超声波 计算机科学 接收机工作特性 微波成像 生物医学工程 人工智能 物理 核医学 烧蚀 微波食品加热 算法 医学 声学 机器学习 电信 解码方法 衰退 内科学
作者
Guang Yang,Siyuan Zhang,Xiejing Li,Ting Shen,Xin Jia,Yunjie Ding,Bo Zhang,Hua Wang,Xiaopeng Li,Pengyu Ren
出处
期刊:IEEE Transactions on Instrumentation and Measurement [Institute of Electrical and Electronics Engineers]
卷期号:: 1-1
标识
DOI:10.1109/tim.2023.3267375
摘要

Many quantitative ultrasound imaging techniques based on tissue properties have been established to ensure the safety and efficacy of thermal ablation treatment. However, which quantitative ultrasound imaging technique has superior monitoring properties has not yet been revealed. In this study, we investigated and compared the performance of envelope data distribution-dependent ultrasonic Nakagami, envelope data distribution-independent horizontally normalized Shannon entropy (hNSE), and differential attenuation coefficient intercept (DACI) based on frequency domain imaging technique during liver thermal ablation treatments. Quantitative ultrasound parameter images were constructed simultaneously from radiofrequency (RF) data collected during the process of microwave ablation (MWA) treatments in ex vivo and in vivo porcine livers. Contrast-to-noise ratios (CNR) were calculated to evaluate the contrast resolution of different imaging techniques. The mean CNR value of hNSE images was 6.06 ± 2.34 dB, being significantly higher than that of Nakagami images ( p <0.05, statistical) and DACI images ( p <0.05, statistical). Furthermore, the receiver operating characteristic (ROC) was used to evaluate the thermal lesion detection ability. The area under the curve (AUC) of B-mode, Nakagami, hNSE and DACI was 0.823, 0.839, 0.86 and 0.825, respectively. Additionally, our data analysis exhibited that hNSE has the excellent property of ablation area detections in the present study, whose correlation coefficient is 0.91. In conclusion, our study suggests that hNSE imaging, which does not require the specific data distribution has the best performance in thermal ablation detections and is a promising imaging method for further clinical research and application.
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