Real-time sonoelastography of hepatic thermal lesions in a swine model.
ABSTRACT Sonoelastography has been developed as an ultrasound-based elasticity imaging technique. In this technique, external vibration is induced into the target tissue. In general, tissue stiffness is inversely proportional to the amplitude of tissue vibration. Imaging tissue vibration will provide the elasticity distribution in the target region. This study investigated the feasibility of using real-time sonoelastography to detect and estimate the volume of thermal lesions in porcine livers in vivo. A total of 32 thermal lesions with volumes ranging from 0.2 to 5.3 cm3 were created using radiofrequency ablation (RFA) or high-intensity focused ultrasound (HIFU) technique. Lesions were imaged using sonoelastography and coregistered B-mode ultrasound. Volumes were reconstructed from a sequence of two-dimensional scans. The comparison of sonoelastographic measurements and pathology findings showed good correlation with respect to the area of the lesions (r2 = 0.8823 for RFA lesions, r2 = 0.9543 for HIFU lesions). In addition, good correspondence was found between three-dimensional sonoelastography and gross pathology (3.6% underestimate), demonstrating the feasibility of sonoelastography for volume estimation of thermal lesions. These results support that sonoelastography outperforms conventional B-mode ultrasound and could potentially be used for assessment of thermal therapies.
SourceAvailable from: Zhuhuang Zhou[Show abstract] [Hide abstract]
ABSTRACT: Gas bubbles induced during the radiofrequency ablation (RFA) of tissues can affect the detection of ablation zones (necrosis zone or thermal lesion) during ultrasound elastography. To resolve this problem, our previous study proposed ultrasound Nakagami imaging for detecting thermal-induced bubble formation to evaluate ablation zones. To prepare for future applications, this study (i) created a novel algorithmic scheme based on the frequency and temporal compounding of Nakagami imaging for enhanced ablation zone visualization, (ii) integrated the proposed algorithm into a clinical scanner to develop a real-time Nakagami imaging system for monitoring RFA, and (iii) investigated the applicability of Nakagami imaging to various types of tissues. The performance of the real-time Nakagami imaging system in visualizing RFA-induced ablation zones was validated by measuring porcine liver (n = 18) and muscle tissues (n = 6). The experimental results showed that the proposed algorithm can operate on a standard clinical ultrasound scanner to monitor RFA in real time. The Nakagami imaging system effectively monitors RFA-induced ablation zones in liver tissues. However, because tissue properties differ, the system cannot visualize ablation zones in muscle fibers. In the future, real-time Nakagami imaging should be focused on the RFA of the liver and is suggested as an alternative monitoring tool when advanced elastography is unavailable or substantial bubbles exist in the ablation zone.PLoS ONE 02/2015; 10(2):e0118030. DOI:10.1371/journal.pone.0118030 · 3.53 Impact Factor
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ABSTRACT: High-intensity focused ultrasound (HIFU) induces thermal lesions by increasing the tissue temperature in a tight focal region. The main ultrasound imaging techniques currently used to monitor HIFU treatment are standard pulse-echo B-mode ultrasound imaging, ultrasound temperature estimation and elastography-based methods. The present study was carried out on ex vivo animal tissue samples, in which backscattered radiofrequency (RF) signals were acquired in real time at time instances before, during and after HIFU treatment. The manifold learning algorithm, a non-linear dimensionality reduction method, was applied to RF signals which construct B-mode images to detect the HIFU-induced changes among the image frames obtained during HIFU treatment. In this approach, the embedded non-linear information in the region of interest of sequential images is represented in a 2-D manifold with the Isomap algorithm, and each image is depicted as a point on the reconstructed manifold. Four distinct regions are chosen in the manifold corresponding to the four phases of HIFU treatment (before HIFU treatment, during HIFU treatment, immediately after HIFU treatment and 10-min after HIFU treatment). It was found that disorganization of the points is achieved by increasing the acoustic power, and if the thermal lesion has been formed, the regions of points related to pre- and post-HIFU significantly differ. Moreover, the manifold embedding was repeated on 2-D moving windows in RF data envelopes related to pre- and post-HIFU exposure data frames. It was concluded that if mean values of the points related to pre- and post-exposure frames in the reconstructed manifold are estimated, and if the Euclidean distance between these two mean values is calculated and the sliding window is moved and this procedure is repeated for the whole image, a new image based on the Euclidean distance can be formed in which the HIFU thermal lesion is detectable.Ultrasound in Medicine & Biology 10/2014; DOI:10.1016/j.ultrasmedbio.2014.07.021 · 2.10 Impact Factor
Biomedical Engineering Applications Basis and Communications 02/2014; 26(01-01). DOI:10.4015/S1016237214500094 · 0.23 Impact Factor