Identification of Denatured Biological Tissues Based on Compressed Sensing and Improved Multiscale Dispersion Entropy during HIFU Treatment

Identification of denatured biological tissue is crucial to high-intensity focused ultrasound (HIFU) treatment, which can monitor HIFU treatment and improve treatment efficiency. In this paper, a novel method based on compressed sensing (CS) and improved multiscale dispersion entropy (IMDE) is proposed to evaluate the complexity of ultrasonic scattered echo signals during HIFU treatment. In the analysis of CS, the method of orthogonal matching pursuit (OMP) is employed to reconstruct the denoised signal. CS-OMP can denoise the ultrasonic scattered echo signal effectively. Comparing with traditional multiscale dispersion entropy (MDE), IMDE improves the coarse-grained process in the multiscale analysis, which improves the stability of MDE. In the analysis of simulated signals, the entropy value of the IMDE method has less fluctuation compared with MDE, indicating that the IMDE method has better stability. In addition, MDE and IMDE are applied to the 300 cases of ultrasonic scattered echo signals after denoising (including 150 cases of normal tissues and 150 cases of denatured tissues). The experimental results show that the MDE and IMDE values of denatured tissues are higher than normal tissues. Both the MDE and IMDE method can be used to identify whether biological tissue is denatured. However, the multiscale entropy curve of IMDE is smoother and more stable than MDE. The interclass distance of IMDE is greater than MDE, and the intraclass distance of IMDE is less than MDE at different scale factors. This indicates that IMDE can better distinguish normal tissues and denatured tissues to obtain more accurate clinical diagnosis during HIFU treatment.

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Identification of Denatured Biological Tissues Based on Time-Frequency Entropy and Refined Composite Multi-Scale Weighted Permutation Entropy during HIFU Treatment

Entropy ◽

10.3390/e21070666 ◽

2019 ◽

Vol 21 (7) ◽

pp. 666 ◽

Cited By ~ 1

Author(s):

Bei Liu ◽

Shengyou Qian ◽

Weipeng Hu

Keyword(s):

Biological Tissues ◽

High Intensity Focused Ultrasound ◽

Permutation Entropy ◽

Hifu Treatment ◽

Echo Signal ◽

Frequency Spectra ◽

Time Frequency ◽

Normal Tissues ◽

Multi Scale ◽

Ultrasonic Echo

Identification of denatured biological tissue is crucial to high intensity focused ultrasound (HIFU) treatment. It is not easy for intercepting ultrasonic scattered echo signals from HIFU treatment region. Therefore, this paper employed time-frequency entropy based on generalized S-transform (GST) to intercept ultrasonic echo signals. First, the time-frequency spectra of ultrasonic echo signal is obtained by GST, which is concentrated around the real instantaneous frequency of the signal. Then the time-frequency entropy is calculated based on time-frequency spectra. The experimental results indicate that the time-frequency entropy of ultrasonic echo signal will be abnormally high when ultrasonic signal travels across the boundary between normal region and treatment region in tissues. Ultrasonic scattered echo signals from treatment region can be intercepted by time-frequency entropy. In addition, the refined composite multi-scale weighted permutation entropy (RCMWPE) is proposed to evaluate the complexity of nonlinear time series. Comparing with multi-scale permutation entropy (MPE) and multi-scale weighted permutation entropy (MWPE), RCMWPE not only measures complexity of signal including amplitude information, but also improves the stability and reliability of multi-scale entropy. The RCMWPE and MPE are applied to 300 cases of actual ultrasonic scattered echo signals (including 150 cases in normal status and 150 cases in denatured status). It is found that the RCMWPE and MPE values of denatured tissues are higher than those of the normal tissues. Both RCMWPE and MPE can be used to distinguish normal tissues and denatured tissues. However, there are fewer feature points in the overlap region between RCMWPE of denatured tissues and normal tissues compared with MPE. The intra-class distance and the inter-class distance of RCMWPE are less and greater respectively than MPE. The difference between denatured tissues and normal tissues is more obvious when RCMWPE is used as the characteristic parameter. The results of this study will be helpful to guide doctors to obtain more accurate assessment of treatment effect during HIFU treatment.

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Biological Tissue Damage Monitoring Method Based on IMWPE and PNN during HIFU Treatment

Information ◽

10.3390/info12100404 ◽

2021 ◽

Vol 12 (10) ◽

pp. 404

Author(s):

Bei Liu ◽

Xian Zhang ◽

Xiao Zou ◽

Jing Cao ◽

Ziqi Peng

Keyword(s):

Tissue Damage ◽

Biological Tissue ◽

Biological Tissues ◽

Coarse Grained ◽

Permutation Entropy ◽

Hifu Treatment ◽

Monitoring Method ◽

Multi Scale ◽

Damage Monitoring ◽

The Stability

Biological tissue damage monitoring is an indispensable part of high-intensity focused ultrasound (HIFU) treatment. As a nonlinear method, multi-scale permutation entropy (MPE) is widely used in the monitoring of biological tissue. However, the traditional MPE method neglects the amplitude information when calculating the time series complexity, and the stability of MPE is poor due to the defects in the coarse-grained process. In order to solve the above problems, the method of improved coarse-grained multi-scale weighted permutation entropy (IMWPE) is proposed in this paper. Compared with the MPE, the IMWPE method not only includes the amplitude of signal when calculating the signal complexity, but also improves the stability of entropy value. The IMWPE method is applied to the HIFU echo signals during HIFU treatment, and the probabilistic neural network (PNN) is used for monitoring the biological tissue damage. The results show that compared with multi-scale sample entropy (MSE)-PNN and MPE-PNN methods, the proposed IMWPE-PNN method can correctly identify all the normal tissues, and can more effectively identify damaged tissues and denatured tissues. The recognition rate for the three kinds of biological tissues is higher, up to 96.7%. This means that the IMWPE-PNN method can better monitor the status of biological tissue damage during HIFU treatment.

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Recognition study of denatured biological tissues based on multi-scale rescaled range permutation entropy

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2022005 ◽

2021 ◽

Vol 19 (1) ◽

pp. 102-114

Author(s):

Bei Liu ◽

◽

Wenbin Tan ◽

Xian Zhang ◽

Ziqi Peng ◽

...

Keyword(s):

Biological Tissue ◽

Focused Ultrasound ◽

Recognition Rate ◽

Biological Tissues ◽

High Intensity Focused Ultrasound ◽

Permutation Entropy ◽

Support Vector ◽

Nonlinear Method ◽

Multi Scale ◽

Rescaled Range

<abstract> <p>The recognition of denatured biological tissue is an indispensable part in the process of high intensity focused ultrasound treatment. As a nonlinear method, multi-scale permutation entropy (MPE) is widely used in the recognition of denatured biological tissue. However, the traditional MPE method neglects the amplitude information when calculating the time series complexity. The disadvantage will affect the recognition effect of denatured tissues. In order to solve the above problems, the method of multi-scale rescaled range permutation entropy (MRRPE) is proposed in this paper. The simulation results show that the MRRPE not only includes the amplitude information of the signal when calculating the signal complexity, but also extracts the extreme volatility characteristics of the signal effectively. The proposed method is applied to the HIFU echo signals during HIFU treatment, and the support vector machine (SVM) is used for recognition. The results show that compared with MPE and the multi-scale weighted permutation entropy (MWPE), the recognition rate of denatured biological tissue based on the MRRPE is higher, up to 96.57%, which can better recognize the non-denatured biological tissues and the denatured biological tissues.</p> </abstract>

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OPTIMIZATION OF THERMAL ABLATION OF BIOLOGICAL TISSUES WITH HIGH INTENSITY FOCUSED ULTRASOUND

10.26678/abcm.encit2020.cit20-0151 ◽

2020 ◽

Author(s):

Rodrigo Silva ◽

mohsen alaeian ◽

Helcio Orlande

Keyword(s):

High Intensity ◽

Thermal Ablation ◽

Focused Ultrasound ◽

Biological Tissues ◽

High Intensity Focused Ultrasound

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The feasibility of a noise elimination method using continuous wave response of therapeutic ultrasound signals for ultrasonic monitoring of high-intensity focused ultrasound treatment

Journal of Medical Ultrasonics ◽

10.1007/s10396-021-01083-5 ◽

2021 ◽

Author(s):

Ryo Takagi ◽

Toshikatsu Washio ◽

Yoshihiko Koseki

Keyword(s):

Noise Reduction ◽

High Intensity ◽

Focused Ultrasound ◽

Continuous Wave ◽

High Intensity Focused Ultrasound ◽

Hifu Treatment ◽

Noise Elimination ◽

Tissue Samples ◽

Wave Response ◽

Failure Conditions

Abstract Purpose In this study, the robustness and feasibility of a noise elimination method using continuous wave response of therapeutic ultrasound signals were investigated when tissue samples were moved to simulate the respiration-induced movements of the different organs during actual high-intensity focused ultrasound (HIFU) treatment. In addition to that, the failure conditions of the proposed algorithm were also investigated. Methods The proposed method was applied to cases where tissue samples were moved along both the lateral and axial directions of the HIFU transducer to simulate respiration-induced motions during HIFU treatment, and the noise reduction level was investigated. In this experiment, the speed of movement was increased from 10 to 40 mm/s to simulate the actual movement of the tissue during HIFU exposure, with the intensity and driving frequency of HIFU set to 1.0–5.0 kW/cm2 and 1.67 MHz, respectively. To investigate the failure conditions of the proposed algorithm, the proposed method was applied with the HIFU focus located at the boundary between the phantom and water to easily cause cavitation bubbles. The intensity of HIFU was set to 10 kW/cm2. Results Almost all HIFU noise was constantly able to be eliminated using the proposed method when the phantom was moved along the lateral and axial directions during HIFU exposure. The noise reduction level (PRL in this study) at an intensity of 1.0, 3.0, and 5.0 kW/cm2 was in the range of 28–32, 38–40, and 42–45 dB, respectively. On the other hand, HIFU noise was not basically eliminated during HIFU exposure after applying the proposed method in the case of cavitation generation at the HIFU focus. Conclusions The proposed method can be applicable even if homogeneous tissues or organs move axially or laterally to the direction of HIFU exposure because of breathing. A condition under which the proposed algorithm failed was when instantaneous tissue changes such as cavitation bubble generation occurred in the tissue, at which time the reflected continuous wave response became less steady.

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High-Intensity Focused Ultrasound Treatment for Advanced Pancreatic Cancer

Gastroenterology Research and Practice ◽

10.1155/2014/205325 ◽

2014 ◽

Vol 2014 ◽

pp. 1-11 ◽

Cited By ~ 20

Author(s):

Yufeng Zhou

Keyword(s):

Pancreatic Cancer ◽

High Intensity ◽

Focused Ultrasound ◽

Advanced Pancreatic Cancer ◽

High Intensity Focused Ultrasound ◽

Treatment Modalities ◽

Karnofsky Performance Scale ◽

Great Success ◽

Hifu Treatment ◽

Performance Scale

Pancreatic cancer is under high mortality but has few effective treatment modalities. High-intensity focused ultrasound (HIFU) is becoming an emerging approach of noninvasively ablating solid tumor in clinics. A variety of solid tumors have been tried on thousands of patients in the last fifteen years with great success. The principle, mechanism, and clinical outcome of HIFU were introduced first. All 3022 clinical cases of HIFU treatment for the advanced pancreatic cancer alone or in combination with chemotherapy or radiotherapy in 241 published papers were reviewed and summarized for its efficacy, pain relief, clinical benefit rate, survival, Karnofsky performance scale (KPS) score, changes in tumor size, occurrence of echogenicity, serum level, diagnostic assessment of outcome, and associated complications. Immune response induced by HIFU ablation may become an effective way of cancer treatment. Comments for a better outcome and current challenges of HIFU technology are also covered.

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