Adaptive ultrasound temperature imaging for monitoring radiofrequency ablation

Liu, Yi-Da; Li, Qiang; Zhou, Zhuhuang; Yeah, Yao-Wen; Chang, Chien-Cheng; Lee, Chia-Yen; Tsui, Po-Hsiang

doi:10.1371/journal.pone.0182457

Cited by 20 publications

(23 citation statements)

References 38 publications

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“…It was demonstrated that the suggested method measured temperatures higher than 50°C, which could lead to coagulation and even to thermal necrosis, as observed in the ablated tissue images in Figure 8. However, previous studies have shown that the coefficient k can vary owing to the nonlinear tissue properties at high-temperature changes (>10°C) [28,29,33]. In this study, the dependency of the coefficient k (Equation (3)) on the temperature was observed by the conducted experiments on the ablated cardiac tissue ( Fig.…”

Section: Discussionmentioning

confidence: 61%

“…Thus, to calculate the k value for cardiac tissue, the temperature measurements from the thermocouple were used as the reference temperatures. A number of studies have already confirmed the feasibility of strain‐based US thermal imaging based on several thermocouple measurements . It should be noted that the temperature estimation in this study was not simply based on the time shifts as the k value was updated by the reference temperature measurement from the thermocouple.…”

Section: Discussionmentioning

confidence: 80%

“…If there was a discrepancy between the estimated and measured temperatures, the coefficient k was adaptively updated with the use of Equation ((i) in Fig. ) . The updated coefficient k was then used to estimate the temperature at other depths of T ( z ) ((g) in Fig.…”

Section: Methodsmentioning

confidence: 99%

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Application of Ultrasound Thermal Imaging for Monitoring Laser Ablation in Ex Vivo Cardiac Tissue

et al. 2019

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Background and Objective Laser ablation can be used to treat atrial fibrillation by thermally isolating pulmonary veins. In this study, we evaluated the feasibility of high‐resolution (<1 mm) ultrasound thermal imaging to monitor spatial temperature distribution during laser ablation on ex vivo cardiac tissue. Study Design/Materials and Methods Laser ablation (808 nm) was performed on five porcine cardiac tissue samples. A thermocouple was used to measure the interstitial tissue temperature during the laser ablation process. Tissue‐strain‐based ultrasound thermal imaging was conducted to monitor the spatial distribution of the temperature in the cardiac tissue. The tissue temperature was estimated from the time shifts of ultrasound signals owing to the changes in the speed of sound and was compared with the measured temperature. The temperature estimation coefficient k of porcine cardiac tissue was calculated from the estimated thermal strain and the measured temperature. The degree of tissue coagulation (temperatures > 50°C) was derived from the estimated temperature and was compared with that of the tested cardiac tissue. Results The estimated tissue temperature using strain‐based ultrasound thermal imaging at a depth of 1 mm agreed with thermocouple measurements. During the 30‐second period of the laser ablation process, the estimated tissue temperature increased from 25 to 70°C at a depth of 0.1 mm, while the estimated temperature at a depth of 1 mm increased up to 46°C. Owing to the uncertainty of the coefficient k, the k value of the porcine cardiac tissue varied from 160 to 220°C with temperature changes of up to 20°C. The estimated coagulation region in the ultrasound thermal imaging was 20% wider (+0.6 mm) but 9% shallower (−0.1 mm) than the measured region of the ablated porcine cardiac tissue. Conclusions The current study demonstrated the feasibility of temperature monitoring with the use of ultrasound thermal imaging during the laser ablation on ex vivo porcine cardiac tissue. The high‐resolution ultrasound thermal imaging could map the spatial distribution of the tissue temperature. The proposed method can be used to monitor the temperature and thermal coagulation to achieve effective laser ablation for atrial fibrillation. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

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Section: Discussionmentioning

confidence: 61%

Section: Discussionmentioning

confidence: 80%

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Application of Ultrasound Thermal Imaging for Monitoring Laser Ablation in Ex Vivo Cardiac Tissue

et al. 2019

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“…To solve this problem, Nagakami imaging is applied and an enhanced ablation zone visualization is obtained [12]. More recently, an adaptive ultrasound imaging scheme is applied to obtain better depth estimations with an algorithm that adjusts its parameters with changing medium properties, like temperatures higher than 50 C [13]. Yet another technique is optoacoustic imaging that uses an optical device that emits laser pulses to excite the target tissue and uses sensors to collect the acoustic emission data from these pulses [14,15].…”

Section: Introductionmentioning

confidence: 99%

Real-time monitoring radiofrequency ablation using tree-based ensemble learning models

Besler

Wang

Chan

et al. 2019

International Journal of Hyperthermia

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Background: Radiofrequency ablation is a minimally-invasive treatment method that aims to destroy undesired tissue by exposing it to alternating current in the 100 kHz-800 kHz frequency range and heating it until it is destroyed via coagulative necrosis. Ablation treatment is gaining momentum especially in cancer research, where the undesired tissue is a malignant tumor. While ablating the tumor with an electrode or catheter is an easy task, real-time monitoring the ablation process is a must in order to maintain the reliability of the treatment. Common methods for this monitoring task have proven to be accurate, however, they are all time-consuming or require expensive equipment, which makes the clinical ablation process more cumbersome and expensive due to the time-dependent nature of the clinical procedure. Methods: A machine learning (ML) approach is presented that aims to reduce the monitoring time while keeping the accuracy of the conventional methods. Two different hardware setups are used to perform the ablation and collect impedance data at the same time and different ML algorithms are tested to predict the ablation depth in 3 dimensions, based on the collected data. Results: Both the random forest and adaptive boosting (adaboost) models had over 98% R 2 on the data collected with the embedded system-based hardware instrumentation setup, outperforming Neural Network-based models. Conclusions: It is shown that an optimal pair of hardware setup and ML algorithm (Adaboost) is able to control the ablation by estimating the lesion depth within a test average of 0.3mm while keeping the estimation time within 10ms on a Â86-64 workstation.

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“…In addition, the echotime-shift technique fails in estimating high temperatures [27]. Compared with echo-time shifts, the usability of ultrasound attenuation is highly dependent on conditions with temperatures above 50 C [19,28]. Therefore, attenuation is not a suitable method for monitoring small temperature variations.…”

Section: Introductionmentioning

confidence: 99%

Ultrasound single-phase CBE imaging for monitoring radiofrequency ablation

Zhang

Wang

et al. 2018

International Journal of Hyperthermia

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Radiofrequency (RF) ablation (RFA) is the most commonly used minimally invasive procedure for thermal ablation of liver tumors. Ultrasound not only provides real-time feedback of the electrode location for RFA guidance but also enables visualization of the tissue temperature. Changes in backscattered energy (CBE) have been widely applied to ultrasound temperature imaging for assessing thermal ablation. Pilot studies have revealed that significant shadowing features appear in CBE imaging and are caused by the electrode and RFA-induced gas bubbles. To resolve this problem, the current study proposed ultrasound single-phase CBE imaging based on positive CBE values. An in vitro model with tissue samples derived from the porcine tenderloin was used to validate the proposed method. During RFA with various electrode lengths, ultrasound scans of tissue samples were obtained using a clinical ultrasound scanner equipped with a convex array transducer of 3 MHz. Raw image data comprising 256 scan lines of backscattered RF signals were acquired for B-mode, conventional CBE, and singlephase CBE imaging by using the proposed algorithmic scheme. The ablation sizes estimated using CBE imaging and gross examinations were compared to calculate the correlation coefficient. The experimental results indicated that single-phase CBE imaging largely suppressed artificial CBE information in the shadowed region. Moreover, compared with conventional CBE imaging, single-phase CBE imaging provided a more accurate estimation of ablation sizes (the correlation coefficient was higher than 0.8).

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Adaptive ultrasound temperature imaging for monitoring radiofrequency ablation

Cited by 20 publications

References 38 publications

Application of Ultrasound Thermal Imaging for Monitoring Laser Ablation in Ex Vivo Cardiac Tissue

Application of Ultrasound Thermal Imaging for Monitoring Laser Ablation in Ex Vivo Cardiac Tissue

Real-time monitoring radiofrequency ablation using tree-based ensemble learning models

Ultrasound single-phase CBE imaging for monitoring radiofrequency ablation

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