Abstract:Temperature monitoring is essential for various medical treatments. In this work, we investigate the impact of temperature on backscattered ultrasound echo statistics during a high intensity focused ultrasound treatment. A tissue mimicking phantom was heated with a spherical ultrasonic transducer up to 56 • C in order to imitate tissue necrosis. During the heating, an imaging scanner was used to acquire backscattered echoes from the heated region. These data was then modeled with the homodyned K distribution. … Show more
“…The results showed that the shape parameter of the K distribution was the best marker of temperature variations. Byra et al 61 used the homodyned-K distribution to model the RF envelope collected during HIFU heating of tissue phantoms in vitro. It was found that a combination of echo mean intensity and the effective number of scatterers per resolution cell was the best temperature indicator.…”
Percutaneous thermal therapy is an important clinical treatment method for some solid tumors. It is critical to use effective image visualization techniques to monitor the therapy process in real time because precise control of the therapeutic zone directly affects the prognosis of tumor treatment. Ultrasound is used in thermal therapy monitoring because of its real-time, non-invasive, non-ionizing radiation, and low-cost characteristics. This paper presents a review of nine quantitative ultrasound-based methods for thermal therapy monitoring and their advances over the last decade since 2011. These methods were analyzed and compared with respect to two applications: ultrasonic thermometry and ablation zone identification. The advantages and limitations of these methods were compared and discussed, and future developments were suggested.
“…The results showed that the shape parameter of the K distribution was the best marker of temperature variations. Byra et al 61 used the homodyned-K distribution to model the RF envelope collected during HIFU heating of tissue phantoms in vitro. It was found that a combination of echo mean intensity and the effective number of scatterers per resolution cell was the best temperature indicator.…”
Percutaneous thermal therapy is an important clinical treatment method for some solid tumors. It is critical to use effective image visualization techniques to monitor the therapy process in real time because precise control of the therapeutic zone directly affects the prognosis of tumor treatment. Ultrasound is used in thermal therapy monitoring because of its real-time, non-invasive, non-ionizing radiation, and low-cost characteristics. This paper presents a review of nine quantitative ultrasound-based methods for thermal therapy monitoring and their advances over the last decade since 2011. These methods were analyzed and compared with respect to two applications: ultrasonic thermometry and ablation zone identification. The advantages and limitations of these methods were compared and discussed, and future developments were suggested.
“…The HK model has been applied to characterizing cell pellet biophantoms [43], tissue phantom heated by focused ultrasound [44], reperfused infarcted porcine myocardium in vivo [45], mice breast cancer in vivo [46], human breast lesions in vivo [47,48], response of advanced human breast cancer to neoadjuvant chemotherapy in vivo [49], cancerous human lymph nodes ex vivo [50], porcine red blood cell aggregation ex vivo [51], human carotid artery plaque in vivo [52], human skin ulcer ex vivo [53], nonalcoholic steatohepatitis of rats in vivo [54], and hepatic steatosis of rabbit livers ex vivo [55] and rat livers in vivo [20]. Using a rat model, Ghoshal et al [55] demonstrated that there is a significant increase in the HK µ parameter with increasing fat content in the liver samples.…”
Hepatic steatosis is a key manifestation of non-alcoholic fatty liver disease (NAFLD). Early detection of hepatic steatosis is of critical importance. Currently, liver biopsy is the clinical golden standard for hepatic steatosis assessment. However, liver biopsy is invasive and associated with sampling errors. Ultrasound has been recommended as a first-line diagnostic test for the management of NAFLD. However, B-mode ultrasound is qualitative and can be affected by factors including image post-processing parameters. Quantitative ultrasound (QUS) aims to extract quantified acoustic parameters from the ultrasound backscattered signals for ultrasound tissue characterization and can be a complement to conventional B-mode ultrasound. QUS envelope statistics techniques, both statistical model-based and non-model-based, have shown potential for hepatic steatosis characterization. However, a state-of-the-art review of hepatic steatosis assessment using envelope statistics techniques is still lacking. In this paper, envelope statistics-based QUS parametric imaging techniques for characterizing hepatic steatosis are reviewed and discussed. The reviewed ultrasound envelope statistics parametric imaging techniques include acoustic structure quantification imaging, ultrasound Nakagami imaging, homodyned-K imaging, kurtosis imaging, and entropy imaging. Future developments are suggested.
“…1,4 Therefore, with the development of effective parameter estimators, the HK model has been used in ultrasound parametric imaging for various medical applications, such as classification of breast lesions, temperature monitoring during focused ultrasound treatment, and hepatic steatosis evaluation. 2,7,21,29 -31…”
Section: Introductionmentioning
confidence: 99%
“…1,4 Therefore, with the development of effective parameter estimators, the HK model has been used in ultrasound parametric imaging for various medical applications, such as classification of breast lesions, temperature monitoring during focused ultrasound treatment, and hepatic steatosis evaluation. 2,7,21,[29][30][31] To estimate the parameters of the statistical distribution models, methods based on maximum likelihood estimator (MLE), moments, or artificial neural networks (ANNs) are commonly adopted. For the HK distribution, Dutt and Greenleaf 32 first proposed a method based on the moments of the intensity (i.e., MI estimator).…”
The homodyned K distribution (HK) can generally describe the ultrasound backscatter envelope statistics distribution with parameters that have specific physical meaning. However, creating robust and reliable HK parameter estimates remains a crucial concern. The maximum likelihood estimator (MLE) usually yields a small variance and bias in parameter estimation. Thus, two recent studies have attempted to use MLE for parameter estimation of HK distribution. However, some of the statements in these studies are not fully justified and they may hinder the application of parameter estimation of HK distribution based on MLE. In this study, we propose a new parameter estimator for the HK distribution based on the MLE (i.e., MLE1), which overcomes the disadvantages of conventional MLE of HK distribution. The MLE1 was compared with other estimators, such as XU estimator (an estimation method based on the first moment of the intensity and tow log-moments) and ANN estimator (an estimation method based on artificial neural networks). We showed that the estimations of parameters α and k are the best overall (in terms of the relative bias, normalized standard deviation, and relative root mean squared errors) using the proposed MLE1 compared with the others based on the simulated data when the sample size was N = 1000. Moreover, we assessed the usefulness of the proposed MLE1 when the number of scatterers per resolution cell was high (i.e., α up to 80) and when the sample size was small (i.e., N = 100), and we found a satisfactory result. Tests on simulated ultrasound images based on Field II were performed and the results confirmed that the proposed MLE1 is feasible and reliable for the parameter estimation from the ultrasonic envelope signal. Therefore, the proposed MLE1 can accurately estimate the HK parameters with lower uncertainty, which presents a potential practical value for further ultrasonic applications.
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