Using ultrasound Nakagami imaging to assess liver fibrosis in rats

Quantitative Ultrasound: An Emerging Technology for Detecting, Diagnosing, Imaging, Evaluating, and Monitoring Disease

Ultrasound has been a popular clinical imaging modality for decades. It is a well-established means of displaying the macroscopic anatomy of soft-tissue structures. While conventional ultrasound methods, i.e., B-mode and Doppler methods, are well proven and continue to advance technically in many ways, e.g., by extending into higher frequencies and taking advantage of harmonic phenomena in tissues, fundamentally new so-called quantitative ultrasound (QUS) technologies also are emerging and offer exciting promise for making significant improvements in clinical imaging and characterization of disease. These emerging quantitative methods include spectrum analysis, image statistics, elasticity imaging, contrast-agent methods, and flow-detection and -measurement techniques. Each provides independent information. When used alone, each can provide clinically valuable imaging capabilities; when combined with each other, their capabilities may be more powerful in many applications. Furthermore, all can be used fused with other imaging modalities, such as computed tomography (CT), magnetic-resonance (MR), positron-emission-tomography (PET), or single-photon emission computerized tomography (SPECT) imaging, to offer possibly even greater improvements in detecting, diagnosing, imaging, evaluating, and monitoring disease. This chapter focuses on QUS methods that are based on spectrum analysis and image statistics.

Correlated-Weighted Statistically Modeled Contourlet and Curvelet Coefficient Image-Based Breast Tumor Classification Using Deep Learning

Deep learning-based automatic classification of breast tumors using parametric imaging techniques from ultrasound (US) B-mode images is still an exciting research area. The Rician inverse Gaussian (RiIG) distribution is currently emerging as an appropriate example of statistical modeling. This study presents a new approach of correlated-weighted contourlet-transformed RiIG (CWCtr-RiIG) and curvelet-transformed RiIG (CWCrv-RiIG) image-based deep convolutional neural network (CNN) architecture for breast tumor classification from B-mode ultrasound images. A comparative study with other statistical models, such as Nakagami and normal inverse Gaussian (NIG) distributions, is also experienced here. The weighted entitled here is for weighting the contourlet and curvelet sub-band coefficient images by correlation with their corresponding RiIG statistically modeled images. By taking into account three freely accessible datasets (Mendeley, UDIAT, and BUSI), it is demonstrated that the proposed approach can provide more than 98 percent accuracy, sensitivity, specificity, NPV, and PPV values using the CWCtr-RiIG images. On the same datasets, the suggested method offers superior classification performance to several other existing strategies.

The detection of prostate cancer based on ultrasound RF signal

Objective

The diagnosis of prostate cancer has been a challenging task. Compared with traditional diagnosis methods, the radiofrequency (RF) signal is not only non-invasive but also rich in microscopic lesion information. This paper proposes a novel and accurate method for detecting prostate cancer based on the ultrasound RF signal.

Method

Our approach is based on low-dimensional features in the frequency domain and high-throughput features in the spatial domain. The whole process could be divided into two parts: first, we calculate three feature maps from the ultrasound original RF signal, and 1,050 radiomics features are extracted from the three feature maps; second, we extracted 37 spectral features from the normalized frequency spectrum after Fourier transform.

Results

We use LASSO regression as the method for feature selection; moreover, we use support vector machine (SVM) for classification 10-fold cross-validation for examining the classification performance of the SVM. An AUC (area under the receiver operating characteristic curve) of 0.84 was obtained on 71 subjects.

Conclusions

Our method is feasible to detect prostate cancer based on the ultrasound RF signal with superior classification performance.

Stretch-Induced Healing of Injured Muscles Is Associated With Myogenesis and Decreased Fibrosis

BACKGROUND

Alghouth therapeutic stretching exercise has been applied to accelerate the healing of injured skeletal muscles, mechanisms behind the mechanical stretch-induced muscle recovery remain unclear.

PURPOSE

To examine stretch-associated antifibrotic and myogenic responses in injured muscles and to evaluate the feasibility of the ultrasonic Nakagami parametric index (NPI) in assessing muscle morphology during recovery.

STUDY DESIGN

Controlled laboratory study.

METHODS

Skeletal muscle fibrosis was induced in the right hind legs of 48 rats by making a posterior transverse incision in the gastrocnemius muscle; the left hind legs remained intact as a comparative normal reference. After surgery, the 48 rats were randomly divided into the stretch (S) and control (C) groups. The S group received stretching interventions on the injured hind leg from week 3 to week 7 after surgery, while the C group did not receive stretching throughout the study period. The muscle fibrosis percentage and the ultrasonic NPI were examined sequentially after surgery. Relative expressions of myogenesis-related proteins, including myoblast determination protein 1 (MyoD), myogenin, and embryonic myosin heavy chain (MHCemb), were also evaluated during the follow-up.

RESULTS

Mean fibrosis percentages in the injured hind leg were approximately 25% at week 3 in both groups, but they were significantly decreased by approximately 20% from week 4 to the end of the follow-up in the S group only (all, P < .05). Upon injury, the NPI values of injured hind legs in both groups dramatically dropped. Within the S group, stretching increased the NPI values of injured hind legs, which approached those of control hind legs at weeks 6 and 7. The highest MyoD, myogenin, and MHCemb levels were observed at week 6 in both groups. The NPI values corresponded to the MyoD expression in the S group during the follow-up.

CONCLUSION

Stretching induced a decrease in muscle fibrosis and an increase in myogenesis in injured muscles. The NPI values correspond to the myogenesis process.

CLINICAL RELEVANCE

The NPI may be capable of continuously monitoring the injured skeletal muscle morphology during the healing process in clinical settings.

Robust Scatterer Number Density Segmentation of Ultrasound Images

Quantitative ultrasound (QUS) aims to reveal information about the tissue microstructure using backscattered echo signals from clinical scanners. Among different QUS parameters, scatterer number density is an important property that can affect the estimation of other QUS parameters. Scatterer number density can be classified into high or low scatterer densities. If there are more than ten scatterers inside the resolution cell, the envelope data are considered as fully developed speckle (FDS) and, otherwise, as underdeveloped speckle (UDS). In conventional methods, the envelope data are divided into small overlapping windows (a strategy here we refer to as patching), and statistical parameters, such as SNR and skewness, are employed to classify each patch of envelope data. However, these parameters are system-dependent, meaning that their distribution can change by the imaging settings and patch size. Therefore, reference phantoms that have known scatterer number density are imaged with the same imaging settings to mitigate system dependency. In this article, we aim to segment regions of ultrasound data without any patching. A large dataset is generated, which has different shapes of scatterer number density and mean scatterer amplitude using a fast simulation method. We employ a convolutional neural network (CNN) for the segmentation task and investigate the effect of domain shift when the network is tested on different datasets with different imaging settings. Nakagami parametric image is employed for multitask learning to improve performance. Furthermore, inspired by the reference phantom methods in QUS, a domain adaptation stage is proposed, which requires only two frames of data from FDS and UDS classes. We evaluate our method for different experimental phantoms and in vivo data.

A Novel Method for Cataract Detection and Segmentation Using Nakagami Distribution

Early detection of cataract is considered as an important solution to prevent vision loss. An automatic detection of cataract is proposed in this work with the help of histogram approach. In the beginning, noises occur in an image which is also referred to as impulse noise. To eliminate this noise a non-linear type of median filter is matched especially for the morphological filter. These filtering methods help to extract the content of the image by edge detection and segmentation. The quality of the image is evaluated the image enhancing can be obtained by a histogram approach. A normalization method can be used to enhance the image which is also called Contrast stretching. To make morphological functions effective a top-hat filter is used to segment the cataract part in the given image. Nakagami distributions are usually used for extracting required important information of ultrasound details by matching histograms from the radio frequency signals. The extracted information from the Nakagami distribution is obtained by parameter values. The recent techniques used to improve the given image quality in histogram modification method are done by Intentional Camera Movement (ICM) and Unintentional Camera Movement (UCM) to recognize the real image more precisely. In the proposed method the result shows the noise reduction and a better contrast in the output image through parameters values such as Mean Squared Error (MSE) obtained as 17.23 and Peak-Signal-to-Noise Ratio (PSNR) obtained as 35.8.

RiIG Modeled WCP Image-Based CNN Architecture and Feature-Based Approach in Breast Tumor Classification from B-Mode Ultrasound

This study presents two new approaches based on Weighted Contourlet Parametric (WCP) images for the classification of breast tumors from B-mode ultrasound images. The Rician Inverse Gaussian (RiIG) distribution is considered for modeling the statistics of ultrasound images in the Contourlet transform domain. The WCP images are obtained by weighting the RiIG modeled Contourlet sub-band coefficient images. In the feature-based approach, various geometrical, statistical, and texture features are shown to have low ANOVA p-value, thus indicating a good capacity for class discrimination. Using three publicly available datasets (Mendeley, UDIAT, and BUSI), it is shown that the classical feature-based approach can yield more than 97% accuracy across the datasets for breast tumor classification using WCP images while the custom-made convolutional neural network (CNN) can deliver more than 98% accuracy, sensitivity, specificity, NPV, and PPV values utilizing the same WCP images. Both methods provide superior classification performance, better than those of several existing techniques on the same datasets.

Ultrasound Scatterer Density Classification Using Convolutional Neural Networks and Patch Statistics

Quantitative ultrasound (QUS) can reveal crucial information on tissue properties, such as scatterer density. If the scatterer density per resolution cell is above or below 10, the tissue is considered as fully developed speckle (FDS) or underdeveloped speckle (UDS), respectively. Conventionally, the scatterer density has been classified using estimated statistical parameters of the amplitude of backscattered echoes. However, if the patch size is small, the estimation is not accurate. These parameters are also highly dependent on imaging settings. In this article, we adapt convolutional neural network (CNN) architectures for QUS and train them using simulation data. We further improve the network's performance by utilizing patch statistics as additional input channels. Inspired by deep supervision and multitask learning, we propose a second method to exploit patch statistics. We evaluate the networks using simulation data and experimental phantoms. We also compare our proposed methods with different classic and deep learning models and demonstrate their superior performance in the classification of tissues with different scatterer density values. The results also show that we are able to classify scatterer density in different imaging parameters with no need for a reference phantom. This work demonstrates the potential of CNNs in classifying scatterer density in ultrasound images.

Multiparametric Quantitative US Examination of Liver Fibrosis: A Feature-engineering and Machine-learning Based Analysis

Quantitative ultrasound (QUS), which is commonly used to extract quantitative features from the ultrasound radiofrequency (RF) data or the RF envelope signals for tissue characterization, is becoming a promising technique for noninvasive assessments of liver fibrosis. However, the number of feature variables examined and finally used in the existing QUS methods is typically small, to some extent limiting the diagnostic performance. Therefore, this paper devises a new multiparametric QUS (MP-QUS) method which enables the extraction of a large number of feature variables from US RF signals and allows for the use of feature-engineering and machinelearning based algorithms for liver fibrosis assessment. In the MP-QUS, eighty-four feature variables were extracted from multiple QUS parametric maps derived from the RF signals and the envelope data. Afterwards, feature reduction and selection were performed in turn to remove the feature redundancy and identify the best combination of features in the reduced feature set. Finally, a variety of machine-learning algorithms were tested for classifying liver fibrosis with the selected features, based on the results of which the optimal classifier was established and used for final classification. The performance of the proposed MPQUS method for staging liver fibrosis was evaluated on an animal model, with histologic examination as the reference standard. The mean accuracy, sensitivity, specificity and area under the receiver-operating-characteristic curve achieved by MP-QUS are respectively 83.38%, 86.04%, 80.82% and 0.891 for recognizing significant liver fibrosis, and 85.50%, 88.92%, 85.24% and 0.924 for diagnosing liver cirrhosis. The proposed MP-QUS method paves a way for its future extension to assess liver fibrosis in human subjects.

Diagnosis of liver fibrosis in patients with hepatitis B-related liver disease using ultrasound with wave-number domain attenuation coefficient

BACKGROUND/AIMS

The importance of identifying the stage of liver fibrosis has motivated the development of non-invasive methods. This study aimed to evaluate the applicability of ultrasound analysis involving the wave-number domain attenuation coefficient (W-Ac) in the non-invasive quantitative differentiation of liver fibrosis.

MATERIALS AND METHODS

This was a prospective study of inpatients with hepatitis B-related liver disease treated between October 2016 and January 2018. In ultrasound, the echo from the near-field liver tissue was selected as the reference signal. The W-Ac of liver tissues was based on the fast Fourier transform of the acquired post-beamforming radio frequency signals. These values were compared with fibrosis from biopsy METAVIR score results. A receiver operating characteristic (ROC) curve tested the W-Ac method.

RESULTS

A total of 46 patients were enrolled, including 27 males and 19 females. Fibrosis was stage F0 in 12 patients, F1 in 13 patients, F2 in 10 patients, F3 in 7 patients, and F4 in 4 patients. W-Ac increased with the progression of liver fibrosis up to stage F3. There were differences between F0 and F4 stages (p<0.001) and between any 2 stages of fibrosis (p<0.05), except for stages F3 and F4. There was a significant correlation between W-Ac and METAVIR score (r=0.795, p<0.001). W-Ac differed between non-fibrosis (F0) and fibrosis (F1-F4) groups (p<0.001) and in the normal (F0), early fibrosis (F1-2), and late fibrosis groups (F3-4) (p<0.001). ROC area under the curve was 0.890, and at a cut-off of 0.12153, sensitivity was 0.706 and specificity was 0.830.

CONCLUSIONS

W-Ac allowed assessment of liver fibrosis in clinical practice.

Window-Modulated Compounding Nakagami Parameter Ratio Approach for Assessing Muscle Perfusion with Contrast-Enhanced Ultrasound Imaging

The assessment of microvascular perfusion is essential for the diagnosis of a specific muscle disease. In comparison with the current available medical modalities, the contrast-enhanced ultrasound imaging is the simplest and fastest means for probing the tissue perfusion. Specifically, the perfusion parameters estimated from the ultrasound time-intensity curve (TIC) and statistics-based time-Nakagami parameter curve (TNC) approaches were found able to quantify the perfusion. However, due to insufficient tolerance on tissue clutters and subresolvable effects, these approaches remain short of reproducibility and robustness. Consequently, the window-modulated compounding (WMC) Nakagami parameter ratio imaging was proposed to alleviate these effects, by taking the ratio of WMC Nakagami parameters corresponding to the incidence of two different acoustic pressures from an employed transducer. The time-Nakagami parameter ratio curve (TNRC) approach was also developed to estimate perfusion parameters. Measurements for the assessment of muscle perfusion were performed from the flow phantom and animal subjects administrated with a bolus of ultrasound contrast agents. The TNRC approach demonstrated better sensitivity and tolerance of tissue clutters than those of TIC and TNC. The fusion image with the WMC Nakagami parameter ratio and B-mode images indicated that both the tissue structures and perfusion properties of ultrasound contrast agents may be better discerned.

Quantitative ultrasound approaches for diagnosis and monitoring hepatic steatosis in nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease is a major global health concern with increasing prevalence, associated with obesity and metabolic syndrome. Recently, quantitative ultrasound-based imaging techniques have dramatically improved the ability of ultrasound to detect and quantify hepatic steatosis. These newer ultrasound techniques possess many inherent advantages similar to conventional ultrasound such as universal availability, real-time capability, and relatively low cost along with quantitative rather than a qualitative assessment of liver fat. In addition, quantitative ultrasound-based imaging techniques are less operator dependent than traditional ultrasound. Here we review several different emerging quantitative ultrasound-based approaches used for detection and quantification of hepatic steatosis in patients at risk for nonalcoholic fatty liver disease. We also briefly summarize other clinically available imaging modalities for evaluating hepatic steatosis such as MRI, CT, and serum analysis.

Ultrasound Backscatter Envelope Statistics Parametric Imaging for Liver Fibrosis Characterization: A Review

Early detection and diagnosis of liver fibrosis is of critical importance. Currently the gold standard for diagnosing liver fibrosis is biopsy. However, liver biopsy is invasive and associated with sampling errors and can lead to complications such as bleeding. Therefore, developing noninvasive imaging techniques for assessing liver fibrosis is of clinical value. Ultrasound has become the first-line tool for the management of chronic liver diseases. However, the commonly used B-mode ultrasound is qualitative and can cause interobserver or intraobserver difference. Ultrasound backscatter envelope statistics parametric imaging is an important group of quantitative ultrasound techniques that have been applied to characterizing different kinds of tissue. However, a state-of-the-art review of ultrasound backscatter envelope statistics parametric imaging for liver fibrosis characterization has not been conducted. In this paper, we focused on the development of ultrasound backscatter envelope statistics parametric imaging techniques for assessing liver fibrosis from 1998 to September 2019. We classified these techniques into six categories: constant false alarm rate, fiber structure extraction technique, acoustic structure quantification, quantile-quantile probability plot, the multi-Rayleigh model, and the Nakagami model. We presented the theoretical background and algorithms for liver fibrosis assessment by ultrasound backscatter envelope statistics parametric imaging. Then, the specific applications of ultrasound backscatter envelope statistics parametric imaging techniques to liver fibrosis evaluation were reviewed and analyzed. Finally, the pros and cons of each technique were discussed, and the future development was suggested.

Resolution of Murine Toxic Hepatic Injury Quantified With Ultrasound Entropy Metrics

Image-based classification of liver disease generally lacks specificity for distinguishing between acute, resolvable injury and chronic irreversible injury. We propose that ultrasound radiofrequency data acquired in vivo from livers subjected to toxic drug injury can be analyzed with information theoretic detectors to derive entropy metrics, which classify a statistical distribution of pathologic scatterers that dissipate over time as livers heal. Here we exposed 38 C57BL/6 mice to carbon tetrachloride to cause liver damage, and imaged livers in vivo 1, 4, 8, 12 and 18 d after exposure with a broadband 15-MHz probe. Selected entropy metrics manifested monotonic recovery to normal values over time as livers healed, and were correlated directly with progressive restoration of liver architecture by histologic assessment (r² ≥ 0.95, p < 0.004). Thus, recovery of normal liver microarchitecture after toxic exposure can be delineated sensitively with entropy metrics.

Acoustic Shadow Detection: Study and Statistics of B-Mode and Radiofrequency Data

An acoustic shadow is an ultrasound artifact occurring at boundaries between significantly different tissue impedances, resulting in signal loss and a dark appearance. Shadow detection is important as shadows can identify anatomical features or obscure regions of interest. A study was performed to scan human participants (N = 37) specifically to explore the statistical characteristics of various shadows from different anatomy and with different transducers. Differences in shadow statistics were observed and used for shadow detection algorithms with a fitted Nakagami distribution on radiofrequency (RF) speckle or cumulative entropy on brightness-mode (B-mode) data. The fitted Nakagami parameter and entropy values in shadows were consistent across different transducers and anatomy. Both algorithms utilized adaptive thresholding, needing only the transducer pulse length as an input parameter for easy utilization by different operators or equipment. Mean Dice coefficients (± standard deviation) of 0.90 ± 0.07 and 0.87 ± 0.08 were obtained for the RF and B-mode algorithms, which is within the range of manual annotators. The high accuracy in different imaging scenarios indicates that the shadows can be detected with high versatility and without expert configuration. The understanding of shadow statistics can be used for more specialized techniques to be developed for specific applications in the future, including pre-processing for machine learning and automatic interpretation.

High-Intensity Focused Ultrasound Thermal Lesion Detection Using Entropy Imaging of Ultrasound Radio Frequency Signal Time Series

Background:

During the past few decades, high-intensity focused ultrasound (HIFU) modality has been gaining surging interest in various therapeutic applications such as non- or minimally-invasive cancer treatment. Among other attributes, robust and real-time HIFU treatment monitoring and lesion detection have become essential issues for successful clinical acceptance of the modality. More recently, ultrasound radio frequency (RF) time series imaging has been studied by a number of researchers.

Materials and Methods:

The objective of this study is to investigate the applicability of entropy parameter of RF time series of ultrasound backscattered signals, a. k. a. Entropy imaging, toward HIFU thermal lesion detection. To this end, five fresh ex vivo porcine muscle tissue samples were exposed to HIFU exposures with total acoustic powers ranging from 30 to 110 Watts. The contrast-to-speckle ratio (CSR) values of the entropy images and their corresponding B-mode images of pre-, during- and post-HIFU exposure for each acoustic power were calculated.

Results:

The novelty of this study is the use of Entropy parameter on ultrasound RF time series for the first time. Statistically significant differences were obtained between the CSR values for the B mode and entropy images at various acoustic powers. In case of 110 Watt, a CSR value 3.4 times higher than B-mode images was accomplished using the proposed method. Furthermore, the proposed method is compared with the scaling parameter of Nakagami imaging and same data which are used in this study.

Conclusion:

Entropy has the potential for using as an imaging parameter for differentiating lesions in HIFU surgery.

Ex Vivo and In Vivo Monitoring and Characterization of Thermal Lesions by High-Intensity Focused Ultrasound and Microwave Ablation Using Ultrasonic Nakagami Imaging

The feasibility of ultrasonic Nakagami imaging to evaluate thermal lesions by high-intensity focused ultrasound and microwave ablation was explored in ex vivo and in vivo liver models. Dynamic changes of the ultrasonic Nakagami parameter in thermal lesions were calculated, and ultrasonic B-mode and Nakagami images were reconstructed simultaneously. The contrast-to-noise ratio (CNR) between thermal lesions and normal tissue was used to estimate the contrast resolution of the monitoring images. After thermal ablation, a bright hyper-echoic region appeared in the ultrasonic B-mode and Nakagami images, identifying the thermal lesion. During thermal ablation, mean values of Nakagami parameter showed an increasing trend from 0.72 to 1.01 for the ex vivo model and 0.54 to 0.72 for the in vivo model. After thermal ablation, mean CNR values of the ultrasonic Nakagami images were 1.29 dB (ex vivo) and 0.80 dB (in vivo), significantly higher ( ) than those for B-mode images. Thermal lesion size, assessed using ultrasonic Nakagami images, shows a good correlation to those obtained from the gross-pathology images (for the ex vivo model: length, = 0.96; width, = 0.90; for the in vivo model: length, = 0.95; width, = 0.85). This preliminary study suggests that ultrasonic Nakagami parameter may have a potential use in evaluating the formation of thermal lesions with better image contrast. Moreover, ultrasonic Nakagami imaging combined with B-mode imaging may be utilized as an alternative modality in developing monitoring systems for image-guided thermal ablation treatments.

Three-dimensional Visualization of Ultrasound Backscatter Statistics by Window-modulated Compounding Nakagami Imaging

In this study, the window-modulated compounding (WMC) technique was integrated into three-dimensional (3D) ultrasound Nakagami imaging for improving the spatial visualization of backscatter statistics. A 3D WMC Nakagami image was produced by summing and averaging a number of 3D Nakagami images (number of frames denoted as N) formed using sliding cubes with varying side lengths ranging from 1 to N times the transducer pulse. To evaluate the performance of the proposed 3D WMC Nakagami imaging method, agar phantoms with scatterer concentrations ranging from 2 to 64 scatterers/mm³ were made, and six stages of fatty liver (zero, one, two, four, six, and eight weeks) were induced in rats by methionine-choline-deficient diets (three rats for each stage, total n = 18). A mechanical scanning system with a 5-MHz focused single-element transducer was used for ultrasound radiofrequency data acquisition. The experimental results showed that 3D WMC Nakagami imaging was able to characterize different scatterer concentrations. Backscatter statistics were visualized with various numbers of frames; N = 5 reduced the estimation error of 3D WMC Nakagami imaging in visualizing the backscatter statistics. Compared with conventional 3D Nakagami imaging, 3D WMC Nakagami imaging improved the image smoothness without significant image resolution degradation, and it can thus be used for describing different stages of fatty liver in rats.

Effect of ultrasound frequency on the Nakagami statistics of human liver tissues

The analysis of the backscattered statistics using the Nakagami parameter is an emerging ultrasound technique for assessing hepatic steatosis and fibrosis. Previous studies indicated that the echo amplitude distribution of a normal liver follows the Rayleigh distribution (the Nakagami parameter m is close to 1). However, using different frequencies may change the backscattered statistics of normal livers. This study explored the frequency dependence of the backscattered statistics in human livers and then discussed the sources of ultrasound scattering in the liver. A total of 30 healthy participants were enrolled to undergo a standard care ultrasound examination on the liver, which is a natural model containing diffuse and coherent scatterers. The liver of each volunteer was scanned from the right intercostal view to obtain image raw data at different central frequencies ranging from 2 to 3.5 MHz. Phantoms with diffuse scatterers only were also made to perform ultrasound scanning using the same protocol for comparisons with clinical data. The Nakagami parameter-frequency correlation was evaluated using Pearson correlation analysis. The median and interquartile range of the Nakagami parameter obtained from livers was 1.00 (0.98-1.05) for 2 MHz, 0.93 (0.89-0.98) for 2.3 MHz, 0.87 (0.84-0.92) for 2.5 MHz, 0.82 (0.77-0.88) for 3.3 MHz, and 0.81 (0.76-0.88) for 3.5 MHz. The Nakagami parameter decreased with the increasing central frequency (r = -0.67, p < 0.0001). However, the effect of ultrasound frequency on the statistical distribution of the backscattered envelopes was not found in the phantom results (r = -0.147, p = 0.0727). The current results demonstrated that the backscattered statistics of normal livers is frequency-dependent. Moreover, the coherent scatterers may be the primary factor to dominate the frequency dependence of the backscattered statistics in a liver.

Evaluation of muscular changes by ultrasound Nakagami imaging in Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is the most common debilitating muscular disorder. Developing a noninvasive measure for monitoring the progression of this disease is critical. The present study tested the effectiveness of using ultrasound Nakagami imaging to evaluate the severity of the dystrophic process. A total of 47 participants (40 with DMD and 7 healthy controls) were recruited. Patients were classified into stage 1 (presymptomatic and ambulatory), stage 2 (early nonambulatory), and stage 3 (late nonambulatory). All participants underwent ultrasound examinations on the rectus femoris, tibialis anterior, and gastrocnemius. The results revealed that the ultrasound Nakagami parameter correlated positively with functional severity in the patients with DMD. The median Nakagami parameter of the gastrocnemius muscle increased from 0.50 to 0.85, corresponding to the largest dynamic range between normal and stage 3. The accuracy, sensitivity, and specificity of diagnosing walking function were 85.52%, 76.31%, and 94.73%, respectively. The Nakagami parameter of the rectus femoris and gastrocnemius muscles correlated negatively with the 6-minute walking distance in the ambulatory patients. Therefore, changes in the Nakagami parameter for the gastrocnemius muscle are suitable for monitoring disease progression in ambulatory patients and for predicting ambulation loss. Ultrasound Nakagami imaging shows potential for evaluating patients with DMD.

Detecting changes in ultrasound backscattered statistics by using Nakagami parameters: Comparisons of moment-based and maximum likelihood estimators

The Nakagami distribution is an approximation useful to the statistics of ultrasound backscattered signals for tissue characterization. Various estimators may affect the Nakagami parameter in the detection of changes in backscattered statistics. In particular, the moment-based estimator (MBE) and maximum likelihood estimator (MLE) are two primary methods used to estimate the Nakagami parameters of ultrasound signals. This study explored the effects of the MBE and different MLE approximations on Nakagami parameter estimations. Ultrasound backscattered signals of different scatterer number densities were generated using a simulation model, and phantom experiments and measurements of human liver tissues were also conducted to acquire real backscattered echoes. Envelope signals were employed to estimate the Nakagami parameters by using the MBE, first- and second-order approximations of MLE (MLE₁ and MLE₂, respectively), and Greenwood approximation (MLE_gw) for comparisons. The simulation results demonstrated that, compared with the MBE and MLE₁, the MLE₂ and MLE_gw enabled more stable parameter estimations with small sample sizes. Notably, the required data length of the envelope signal was 3.6 times the pulse length. The phantom and tissue measurement results also showed that the Nakagami parameters estimated using the MLE₂ and MLE_gw could simultaneously differentiate various scatterer concentrations with lower standard deviations and reliably reflect physical meanings associated with the backscattered statistics. Therefore, the MLE₂ and MLE_gw are suggested as estimators for the development of Nakagami-based methodologies for ultrasound tissue characterization.

Acoustic structure quantification by using ultrasound Nakagami imaging for assessing liver fibrosis

Acoustic structure quantification (ASQ) is a recently developed technique widely used for detecting liver fibrosis. Ultrasound Nakagami parametric imaging based on the Nakagami distribution has been widely used to model echo amplitude distribution for tissue characterization. We explored the feasibility of using ultrasound Nakagami imaging as a model-based ASQ technique for assessing liver fibrosis. Standard ultrasound examinations were performed on 19 healthy volunteers and 91 patients with chronic hepatitis B and C (n = 110). Liver biopsy and ultrasound Nakagami imaging analysis were conducted to compare the METAVIR score and Nakagami parameter. The diagnostic value of ultrasound Nakagami imaging was evaluated using receiver operating characteristic (ROC) curves. The Nakagami parameter obtained through ultrasound Nakagami imaging decreased with an increase in the METAVIR score (p < 0.0001), representing an increase in the extent of pre-Rayleigh statistics for echo amplitude distribution. The area under the ROC curve (AUROC) was 0.88 for the diagnosis of any degree of fibrosis (≥F1), whereas it was 0.84, 0.69, and 0.67 for ≥F2, ≥F3, and ≥F4, respectively. Ultrasound Nakagami imaging is a model-based ASQ technique that can be beneficial for the clinical diagnosis of early liver fibrosis.

Analysis of Coherent and Diffuse Scattering Using a Reference Phantom

The estimation of many spectral-based quantitative ultrasound parameters assumes that backscattered echo signals are from a stationary, incoherent scattering process. The accuracy of these assumptions in real tissue can limit the diagnostic value of these parameters and the physical insight about tissue microstructure they can convey. This work presents an empirical decision test to determine the presence of significant coherent contributions to echo signals and whether they are caused by low scatterer number densities or the presence of specular reflectors or scatterers with periodic spacing. This is achieved by computing parameters from echo signals that quantify stationary or nonstationary features related to coherent scattering, and then comparing their values to thresholds determined from a reference material providing diffuse scattering. The paper first presents a number of parameters with demonstrated sensitivity to coherent scattering and describes criteria to select those with the highest sensitivity using simulated and phantom-based echo data. Results showed that the echo amplitude signal-to-noise ratio and the multitaper-generalized spectrum were the parameters with the highest sensitivity to coherent scattering with stationary and nonstationary features, respectively. These parameters were incorporated into the reference-based decision test, which successfully identified regions in simulated and tissue-mimicking phantoms with different incoherent and coherent scattering conditions. When scatterers with periodic organization were detected, the combination of stationary and nonstationary analysis permitted the estimation of the mean spacing below and above the resolution limit imposed by the pulse size. Preliminary applications of this algorithm to human cervical tissue ex vivo showed correspondence between regions of B-mode images showing bright reflectors, tissue interfaces, and hypoechoic regions with regions classified as specular reflectors and low scatterer number density. These results encourage further application of the algorithm to more structurally complex phantoms and tissue.

Can early hepatic fibrosis stages be discriminated by combining ultrasonic parameters?

In this study, we put forward a new approach to classify early stages of fibrosis based on a multiparametric characterization using backscatter ultrasonic signals. Ultrasonic parameters, such as backscatter coefficient (Bc), speed of sound (SoS), attenuation coefficient (Ac), mean scatterer spacing (MSS), and spectral slope (SS), have shown their potential to differentiate between healthy and pathologic samples in different organs (eye, breast, prostate, liver). Recently, our group looked into the characterization of stages of hepatic fibrosis using the parameters cited above. The results showed that none of them could individually distinguish between the different stages. Therefore, we explored a multiparametric approach by combining these parameters in two and three, to test their potential to discriminate between the stages of liver fibrosis: F0 (normal), F1, F3, and/without F4 (cirrhosis), according to METAVIR Score. Discriminant analysis showed that the most relevant individual parameter was Bc, followed by SoS, SS, MSS, and Ac. The combination of (Bc, SoS) along with the four stages was the best in differentiating between the stages of fibrosis and correctly classified 85% of the liver samples with a high level of significance (p<0.0001). Nevertheless, when taking into account only stages F0, F1, and F3, the discriminant analysis showed that the parameters (Bc, SoS) and (Bc, Ac) had a better classification (93%) with a high level of significance (p<0.0001). The combination of the three parameters (Bc, SoS, and Ac) led to a 100% correct classification. In conclusion, the current findings show that the multiparametric approach has great potential in differentiating between the stages of fibrosis, and thus could play an important role in the diagnosis and follow-up of hepatic fibrosis.

Recombinant soluble gp130 protein reduces DEN-induced primary hepatocellular carcinoma in mice

IL-6 (interleukin 6) plays an important role in the development and growth of hepatocellular carcinoma (HCC) via both classic signaling and trans-signaling pathways. Soluble gp130 (sgp130) is known to be a natural inhibitor of the trans-signaling pathway. In the present study, our goal was to investigate whether recombinant sgp130 could suppress the initiation and progression of HCC in mouse models. Our results demonstrate that sgp130 induced an apoptosis of HepG2 cells and inhibited the clonogenicity of HepG2 in vitro. Moreover, the IL-6 trans-signaling pathway is significantly suppressed by sgp130 as reflected by the decrease in the level of STAT3 phosphorylation and other inflammatory factors both in vitro and in vivo. In the DEN-induced HCC mouse model, intravenous injection of sgp130 attenuated hepatic fibrosis at 16 weeks and reduced the initiation and progression of primary HCC at 36 weeks. Furthermore, our results also demonstrate that intravenous administration of sgp130 significantly suppressed the growth and metastasis of xenograft human HCC in NOD/SCID mice.

Cross-Sectional Nakagami Images in Passive Stretches Reveal Damage of Injured Muscles

Muscle strain is still awanting a noninvasive quantitatively diagnosis tool. High frequency ultrasound (HFU) improves image resolution for monitoring changes of tissue structures, but the biomechanical factors may influence ultrasonography during injury detection. We aim to illustrate the ultrasonic parameters to present the histological damage of overstretched muscle with the consideration of biomechanical factors. Gastrocnemius muscles from mice were assembled and ex vivo passive stretching was performed before or after injury. After injury, the muscle significantly decreased mechanical strength. Ultrasonic images were obtained by HFU at different deformations to scan in cross and longitudinal orientations of muscle. The ultrasonography was quantified by echogenicity and Nakagami parameters (NP) for structural evaluation and correlated with histological results. The injured muscle at its original length exhibited decreased echogenicity and NP from HFU images. Cross-sectional ultrasonography revealed a loss of correlation between NP and passive muscle stretching that suggested a special scatterer pattern in the cross section of injured muscle. The independence of NP during passive stretching of injured muscle was confirmed by histological findings in ruptured collagen fibers, decreased muscle density, and increased intermuscular fiber space. Thus, HFU analysis of NP in cross section represents muscle injury that may benefit the clinical diagnosis.

Automatic Cataract Hardness Classification Ex Vivo by Ultrasound Techniques

To demonstrate the feasibility of a new methodology for cataract hardness characterization and automatic classification using ultrasound techniques, different cataract degrees were induced in 210 porcine lenses. A 25-MHz ultrasound transducer was used to obtain acoustical parameters (velocity and attenuation) and backscattering signals. B-Scan and parametric Nakagami images were constructed. Ninety-seven parameters were extracted and subjected to a Principal Component Analysis. Bayes, K-Nearest-Neighbours, Fisher Linear Discriminant and Support Vector Machine (SVM) classifiers were used to automatically classify the different cataract severities. Statistically significant increases with cataract formation were found for velocity, attenuation, mean brightness intensity of the B-Scan images and mean Nakagami m parameter (p < 0.01). The four classifiers showed a good performance for healthy versus cataractous lenses (F-measure ≥ 92.68%), while for initial versus severe cataracts the SVM classifier showed the higher performance (90.62%). The results showed that ultrasound techniques can be used for non-invasive cataract hardness characterization and automatic classification.

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation, and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years, QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient (BSC), estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and preclinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.

Effects of Estimators on Ultrasound Nakagami Imaging in Visualizing the Change in the Backscattered Statistics from a Rayleigh Distribution to a Pre-Rayleigh Distribution

Ultrasound Nakagami imaging has recently attracted interest as an imaging technique for analyzing envelope statistics. Because the presence of structures has a strong effect on estimation of the Nakagami parameter, previous studies have indicated that Nakagami imaging should be used specifically for characterization of soft tissues with fewer structures, such as liver tissues. Typically, changes in the properties of the liver parenchyma cause the backscattered statistics to transform from a Rayleigh distribution to a pre-Rayleigh distribution, and this transformation can be visualized using a Nakagami imaging technique. However, different estimators result in different estimated values; thus, the performance of a Nakagami image may depend on the type of estimator used. This study explored the effects of various estimators on ultrasound Nakagami imaging to describe the backscattered statistics as they change from a Rayleigh distribution to a pre-Rayleigh distribution. Simulations and clinical measurements involving patients with liver fibrosis (n = 85) yielded image data that were used to construct B-mode and conventional Nakagami images based on the moment estimator (denoted as mINV images) and maximum-likelihood estimator (denoted as mML images). In addition, novel window-modulated compounding Nakagami images based on the moment estimator (denoted as mWMC images) were also obtained. The means and standard deviations of the Nakagami parameters were examined as a function of the backscattered statistics. The experimental results indicate that the mINV, mML and mWMC images enabled quantitative visualization of the change in backscattered statistics from a Rayleigh distribution to a pre-Rayleigh distribution. Importantly, the mWMC image is superior to both mINV and mML images because it simultaneously realizes sensitive detection of the backscattered statistics and a reduction of estimation variance for image smoothness improvement. We therefore recommend using mWMC image as a novel strategy in Nakagami imaging technique for liver tissue characterization.

Evaluation of thrombolysis by using ultrasonic imaging: an in vitro study

The hematocrit of a thrombus is a key factor associated with the susceptibility to thrombolysis. Ultrasonic imaging is currently the first-line screening tool for thrombus examinations. Different hematocrits result in different acoustical structures of thrombi, which alter the behavior of ultrasonic backscattering. This study explored the relationships among thrombolytic efficiencies, hematocrits, and ultrasonic parameters (the echo intensity and backscattered statistics). Porcine thrombi with different hematocrits, ranging from 0% to 50%, were induced in vitro. An ultrasonic scanner was used to scan thrombi and acquire raw image data for B-mode (echo intensity measurements) and Nakagami imaging (backscattered statistics analysis). Experiments on thrombolysis were performed using urokinase to explore the effect of the hematocrit on thrombolytic efficiency. Results showed that the weight loss ratio of thrombi exponentially decreased as the hematocrit increased from 0% to 50%. Compared with the echo intensity obtained from the conventional B-scan, the Nakagami parameter predicts the weight loss ratio, increasing from 0.6 to 1.2 as the weight loss ratio decreased from 0.67 to 0.26. The current findings suggest that using Nakagami imaging characterizing thrombi provides information of backscattered statistics, which may be associated with the thrombolytic efficiency.

Quantitative Ultrasonic Nakagami Imaging of Neck Fibrosis After Head and Neck Radiation Therapy

PURPOSE

To investigate the feasibility of ultrasound Nakagami imaging to quantitatively assess radiation-induced neck fibrosis, a common sequela of radiation therapy (RT) to the head and neck.

METHODS AND MATERIALS

In a pilot study, 40 study participants were enrolled and classified into 3 subgroups: (1) a control group of 12 healthy volunteers; (2) an asymptomatic group of 11 patients who had received intensity modulated RT for head and neck cancer and had experienced no neck fibrosis; and (3) a symptomatic group of 17 post-RT patients with neck fibrosis. Each study participant underwent 1 ultrasound study in which scans were performed in the longitudinal orientation of the bilateral neck. Three Nakagami parameters were calculated to quantify radiation-induced tissue injury: Nakagami probability distribution function, shape, and scaling parameters. Physician-based assessments of the neck fibrosis were performed according to the Radiation Therapy Oncology Group late morbidity scoring scheme, and patient-based fibrosis assessments were rated based on symptoms such as pain and stiffness.

RESULTS

Major discrepancies existed between physician-based and patient-based assessments of radiation-induced fibrosis. Significant differences in all Nakagami parameters were observed between the control group and 2 post-RT groups. Moreover, significant differences in Nakagami shape and scaling parameters were observed among asymptomatic and symptomatic groups. Compared with the control group, the average Nakagami shape parameter value increased by 32.1% (P<.001), and the average Nakagami scaling parameter increased by 55.7% (P<.001) for the asymptomatic group, whereas the Nakagami shape parameter increased by 74.1% (P<.001) and the Nakagami scaling parameter increased by 83.5% (P<.001) for the symptomatic group.

CONCLUSIONS

Ultrasonic Nakagami imaging is a potential quantitative tool to characterize radiation-induced asymptomatic and symptomatic neck fibrosis.

Changes in backscattered ultrasonic envelope statistics as a function of thrombus age: an in vitro study

It is necessary to determine the age of thrombi in planning clinical treatment for thrombolysis. Ultrasound imaging can potentially be used to evaluate thrombus age in real time. The backscattered signals from thrombi may contain useful information regarding their age. On the basis of the randomness of ultrasound backscattering, this study explored changes in backscattered US statistics as a function of thrombus age. Porcine blood samples were used for the in vitro induction of fresh thrombi (day 0) with hematocrits ranging from 0%-40% and aged thrombi (days 0-8) with a hematocrit of 40%. Each thrombus was imaged using a pulse-echo ultrasound scanner equipped with a 7.5-MHz linear array transducer to acquire raw backscattered signals for B-mode and Nakagami imaging, by which the backscattered statistics were visualized. Hematoxylin and eosin staining and scanning electron microscopy were used to observe the histology of fresh and aged thrombi. The results indicated that a decrease in the number of red blood cells in the thrombus caused by the aging effect was observed in the in vitro model, indicating that the proposed model could simulate the structural changes in the thrombus during aging. Compared with fresh thrombi with various hematocrits, the aged thrombi exhibited a trend toward more substantial decreases in the Nakagami parameter with increasing thrombus age (the Nakagami parameter decreased from 1.1 to 0.6 as thrombus age increased from day 0 to day 8), indicating that thrombus aging causes the backscattered statistics to follow a pre-Rayleigh distribution to a high degree. This finding may be applied to the determination of thrombus age using conventional ultrasound imaging in the future.

Ultrasonic Nakagami-parameter characterization of parotid-gland injury following head-and-neck radiotherapy: a feasibility study of late toxicity

PURPOSE

The study aims to investigate whether Nakagami parameters--estimated from the statistical distribution of the backscattered ultrasound radio-frequency (RF) signals--could provide a means for quantitative characterization of parotid-gland injury resulting from head-and-neck radiotherapy.

METHODS

A preliminary clinical study was conducted with 12 postradiotherapy patients and 12 healthy volunteers. Each participant underwent one ultrasound study in which ultrasound scans were performed in the longitudinal, i.e., vertical orientation on the bilateral parotids. For the 12 patients, the mean radiation dose to the parotid glands was 37.7 ± 9.5 Gy, and the mean follow-up time was 16.3 ± 4.8 months. All enrolled patients experienced grade 1 or 2 late salivary-gland toxicity (RTOG/EORTC morbidity scale). The normal parotid glands served as the control group. The Nakagami-scaling and Nakagami-shape parameters were computed from the RF data to quantify radiation-induced parotid-gland changes.

RESULTS

Significant differences in Nakagami parameters were observed between the normal and postradiotherapy parotid glands. Compared with the control group, the Nakagami-scaling parameter of the postradiotherapy group decreased by 25.8% (p < 0.001), and the Nakagami-shape parameter decreased by 31.3% (p < 0.001). The area under the receiver operating characteristic curve was 0.85 for the Nakagami-scaling parameter and was 0.95 for the Nakagami-shape parameter, which further demonstrated the diagnostic efficiency of the Nakagami parameters.

CONCLUSIONS

Nakagami parameters could be used to quantitatively measure parotid-gland injury following head-and-neck radiotherapy. Moreover, the clinical feasibility was demonstrated and this study provides meaningful preliminary data for future clinical investigation.

Early detection of liver fibrosis in rats using 3-D ultrasound Nakagami imaging: a feasibility evaluation

We investigated the feasibility of using 3-D ultrasound Nakagami imaging to detect the early stages of liver fibrosis in rats. Fibrosis was induced in livers of rats (n = 60) by intraperitoneal injection of 0.5% dimethylnitrosamine (DMN). Group 1 was the control group, and rats in groups 2-6 received DMN injections for 1-5 weeks, respectively. Each rat was sacrificed to perform 3-D ultrasound scanning of the liver in vitro using a single-element transducer of 6.5 MHz. The 3-D raw data acquired at a sampling rate of 50 MHz were used to construct 3-D Nakagami images. The liver specimen was further used for histologic analysis with hematoxylin and eosin and Masson staining to score the degree of liver fibrosis. The results indicate that the Metavir scores of the hematoxylin and eosin-stained sections in Groups 1-4 were 0 (defined as early liver fibrosis in this study), and those in groups 5 and 6 ranged from 1 to 2 and 2 to 3, respectively. To quantify the degree of early liver fibrosis, the histologic sections with Masson stain were analyzed to calculate the number of fiber-related blue pixels. The number of blue pixels increased from (2.36 ± 0.79) × 10(4) (group 1) to (7.68 ± 2.62) × 10(4) (group 4) after DMN injections for 3 weeks, indicating that early stages of liver fibrosis were successfully induced in rats. The Nakagami parameter increased from 0.36 ± 0.02 (group 1) to 0.55 ± 0.03 (group 4), with increasing numbers of blue pixels in the Masson-stained sections (p-value < 0.05, t-test). We concluded that 3-D Nakagami imaging has potential in the early detection of liver fibrosis in rats and may serve as an image-based pathologic model to visually track fibrosis formation and growth.

Window-modulated compounding Nakagami imaging for ultrasound tissue characterization

Ultrasound Nakagami parametric imaging is a useful tool for tissue characterization. Previous literature has suggested using a square with side lengths corresponding to 3 times the transducer pulse length as the minimum window for constructing the Nakagami image. This criterion does not produce sufficiently smooth images for the Nakagami image to characterize homogeneous tissues. To improve image smoothness, we proposed window-modulated compounding (WMC) Nakagami imaging based on summing and averaging the Nakagami images formed using sliding windows with varying window side lengths from 1 to N times the transducer pulse length in 1 pulse length step. Simulations (the number densities of scatterers: 2-16 scatterers/mm(2)) and experiments on fully developed speckle phantoms (the scatterer diameters: 20-106 μm) were conducted to suggest an appropriate number of frames N and to evaluate the image smoothness and resolution by analyzing the full width at half maximum (FWHM) of the parameter distribution and the widths of the image autocorrelation function (ACF), respectively. In vivo ultrasound measurements on rat livers without and with cirrhosis were performed to validate the practical performance of the WMC Nakagami image in tissue characterization. The simulation results showed that using a range of N from 7 to 10 as the number of frames for image compounding reduces the estimation error to less than 5%. Based on this criterion, the Nakagami parameter obtained from the WMC Nakagami image increased from 0.45 to 0.95 after increasing the number densities of scatterers from 2 to 16 scatterers/mm(2). The FWHM of the parameter distribution (bins=40) was 13.5±1.4 for the Nakagami image and 9.1±1.43 for the WMC Nakagami image, respectively (p-value<.05). The widths of the ACF for the Nakagami and WMC Nakagami images were 454±5.36 and 458±4.33, respectively (p-value>.05). In the phantom experiments, we also found that the FWHM of the parameter distribution for the WMC Nakagami image was smaller than that of the conventional Nakagami image (p-value<.05), and there was no significant difference of the ACF width between the Nakagami and WMC Nakagami images (p-value>.05). In the animal experiments, the Nakagami parameters obtained from the WMC Nakagami image for normal and cirrhotic rat livers were 0.62±0.08 and 0.92±0.07, respectively (p-value<.05). The results demonstrated that the WMC technique significantly improved the image smoothness of Nakagami imaging without resolution degradation, giving Nakagami model-based imaging the ability to visualize scatterer properties with enhanced image quality.

Scatterer number density considerations in reference phantom-based attenuation estimation

Attenuation estimation and imaging have the potential to be a valuable tool for tissue characterization, particularly for indicating the extent of thermal ablation therapy in the liver. Often the performance of attenuation estimation algorithms is characterized with numerical simulations or tissue-mimicking phantoms containing a high scatterer number density (SND). This ensures an ultrasound signal with a Rayleigh distributed envelope and a signal-to-noise ratio (SNR) approaching 1.91. However, biological tissue often fails to exhibit Rayleigh scattering statistics. For example, across 1647 regions of interest in five ex vivo bovine livers, we obtained an envelope SNR of 1.10 ± 0.12 when the tissue was imaged with the VFX 9L4 linear array transducer at a center frequency of 6.0 MHz on a Siemens S2000 scanner. In this article, we examine attenuation estimation in numerical phantoms, tissue-mimicking phantoms with variable SNDs and ex vivo bovine liver before and after thermal coagulation. We find that reference phantom-based attenuation estimation is robust to small deviations from Rayleigh statistics. However, in tissue with low SNDs, large deviations in envelope SNR from 1.91 lead to subsequently large increases in attenuation estimation variance. At the same time, low SND is not found to be a significant source of bias in the attenuation estimate. For example, we find that the standard deviation of attenuation slope estimates increases from 0.07 to 0.25 dB/cm-MHz as the envelope SNR decreases from 1.78 to 1.01 when estimating attenuation slope in tissue-mimicking phantoms with a large estimation kernel size (16 mm axially × 15 mm laterally). Meanwhile, the bias in the attenuation slope estimates is found to be negligible (<0.01 dB/cm-MHz). We also compare results obtained with reference phantom-based attenuation estimates in ex vivo bovine liver and thermally coagulated bovine liver.

Modeling of errors in Nakagami imaging: illustration on breast mass characterization

Nakagami imaging is an attractive tissue characterization method, as the parameter estimated at each location is related to properties of the tissues. The application to clinical ultrasound images is problematic, as the estimation of the parameters is disturbed by the presence of complex structures. We propose to consider separately the different aspects potentially affecting the value of the Nakagami parameters and quantify their effects on the estimation. This framework is applied to the classification of breast masses. Quantitative parameters are computed on two groups of ultrasound images of benign and malignant tumors. A statistical analysis of the result indicated that the previously observed difference between average values of the Nakagami parameters is explained mostly by estimation errors. In the future, new methods for reliable computation of Nakagami parameters need to be developed, and factors of error should be considered in studies using Nakagami parameters.

Entropic imaging of cataract lens: an in vitro study

Phacoemulsification is a common surgical method for treating advanced cataracts. Determining the optimal phacoemulsification energy depends on the hardness of the lens involved. Previous studies have shown that it is possible to evaluate lens hardness via ultrasound parametric imaging based on statistical models that require data to follow a specific distribution. To make the method more system-adaptive, nonmodel-based imaging approach may be necessary in the visualization of lens hardness. This study investigated the feasibility of applying an information theory derived parameter - Shannon entropy from ultrasound backscatter to quantify lens hardness. To determine the physical significance of entropy, we performed computer simulations to investigate the relationship between the signal-to-noise ratio (SNR) based on the Rayleigh distribution and Shannon entropy. Young's modulus was measured in porcine lenses, in which cataracts had been artificially induced by the immersion in formalin solution in vitro. A 35-MHz ultrasound transducer was used to scan the cataract lenses for entropy imaging. The results showed that the entropy is 4.8 when the backscatter data form a Rayleigh distribution corresponding to an SNR of 1.91. The Young's modulus of the lens increased from approximately 8 to 100 kPa when we increased the immersion time from 40 to 160 min (correlation coefficient r = 0.99). Furthermore, the results indicated that entropy imaging seemed to facilitate visualizing different degrees of lens hardening. The mean entropy value increased from 2.7 to 4.0 as the Young's modulus increased from 8 to 100 kPa (r = 0.85), suggesting that entropy imaging may have greater potential than that of conventional statistical parametric imaging in determining the optimal energy to apply during phacoemulsification.

Nakagami imaging for detecting thermal lesions induced by high-intensity focused ultrasound in tissue

High-intensity focused ultrasound induces focalized tissue coagulation by increasing the tissue temperature in a tight focal region. Several methods have been proposed to monitor high-intensity focused ultrasound-induced thermal lesions. Currently, ultrasound imaging techniques that are clinically used for monitoring high-intensity focused ultrasound treatment are standard pulse-echo B-mode ultrasound imaging, ultrasound temperature estimation, and elastography-based methods. On the contrary, the efficacy of two-dimensional Nakagami parametric imaging based on the distribution of the ultrasound backscattered signals to quantify properties of soft tissue has recently been evaluated. In this study, ultrasound radio frequency echo signals from ex vivo tissue samples were acquired before and after high-intensity focused ultrasound exposures and then their Nakagami parameter and scaling parameter of Nakagami distribution were estimated. These parameters were used to detect high-intensity focused ultrasound-induced thermal lesions. Also, the effects of changing the acoustic power of the high-intensity focused ultrasound transducer on the Nakagami parameters were studied. The results obtained suggest that the Nakagami distribution's scaling and Nakagami parameters can effectively be used to detect high-intensity focused ultrasound-induced thermal lesions in tissue ex vivo. These parameters can also be used to understand the degree of change in tissue caused by high-intensity focused ultrasound exposures, which could be interpreted as a measure of degree of variability in scatterer concentration in various parts of the high-intensity focused ultrasound lesion.

High-frequency ultrasound imaging to evaluate liver fibrosis progression in rats and yi guan jian herbal therapeutic effects

The animals used in liver fibrosis studies must usually be sacrificed. Ultrasound has been demonstrated to have the ability to diagnose hepatic fibrosis and cirrhosis in experimental small-animal models. However, few studies have used high-frequency ultrasound (HFU, 40 MHz) to monitor changes in the rat liver and other hollow organs longitudinally. In this study, liver fibrosis was induced by administering dimethylnitrosamine (DMN) in SD rats, aged 8 weeks, for three consecutive days per week for up to 4 weeks. A Chinese herbal medicine Yi Guan Jian (YGJ) was orally administered (1.8 g/kg daily) to DMN-induced liver fibrosis rats for 2 weeks. Compared with the normal control rats, rats treated with DMN for either 2 weeks or 4 weeks had significantly lower body weights, liver indexes and elevation of hydroxyproline, GOT, and GPT contents. YGJ herbal treatment remarkably prevented rats from DMN-induced liver fibrosis. The HFU scoring results among the normal controls, 2-week DMN-treated rats, 4-week DMN-treated rats, and combined 2-week YGJ therapy with 4-week DMN-treated rats also reached statistical significance. Thus, HFU is an accurate tool for the longitudinal analysis of liver fibrosis progression in small-animal models, and the YGJ may be useful in reversing the development of hepatic fibrosis.

Noninvasive evaluation of vaginal fibrosis following radiotherapy for gynecologic malignancies: a feasibility study with ultrasound B-mode and Nakagami parameter imaging

PURPOSE

This study's purpose is to develop a quantitative ultrasound technology to evaluate radiation-induced vaginal fibrosis. Radiation therapy (RT) is an important treatment modality for most gynecologic (GYN) malignancies. However, vaginal fibrosis is a common chronic side-effect, affecting 80% of women post vaginal or pelvic RT. Vaginal fibrosis leads to pain, sexual dysfunction, and poor quality of life.

METHODS

The authors propose a novel ultrasound approach that combines conventional B-mode imaging with Nakagami parameter imaging to quantitatively evaluate post-RT vaginal injury. From the B-mode image, vaginal wall thickness and echo intensity were calculated to capture the anatomy and echogenicity of the vaginal wall. From Nakagami imaging, two statistical parameters, Nakagami probability density function (PDF) and Nakagami shape, were computed to measure the concentration and arrangement of vaginal tissue microstructures. This novel ultrasound imaging concept was investigated in a pilot study of 12 patients, who were previously diagnosed and treated for endometrial cancer. The 12 participants were stratified into two groups: (1) the control group consisted of 6 patients who received surgery (hysterectomy) alone and (2) the post-RT group consisted of 6 patients who received surgery plus radiotherapy, with a follow-up time of 12-38 months. Each participant underwent one transvaginal ultrasound study (6 MHz). Three transverse images of the anterior vaginal wall were acquired in a 2 cm step from the apex (vaginal cuff) to the introitus (vagina opening). The vaginal wall thickness, echo intensity, Nakagami PDF, and Nakagami parameter were calculated to evaluate radiation-induced vaginal fibrosis.

RESULTS

Both B-mode and Nakagami methods showed significant differences in parameters between the post-RT and nonirradiated vaginal walls. Compared with the control group, the vaginal wall thickness of the post-RT group increased by 153.2% (p = 0.002), the echo intensity increased by 11.6% (p = 0.017), the Nakagami PDF increased by 72.3% (p < 0.001), and the Nakagami shape valued increased by 33.0% (p = 0.028).

CONCLUSIONS

Vaginal fibrosis appears to be associated with a thickened vaginal wall, higher echogenicity, as well as increased Nakagami PDF and shape parameters. This pilot study shows the authors' quantitative ultrasound approach combining B-mode and Nakagami imaging is a promising imaging method to evaluate vaginal fibrosis. This imaging method may be useful as physicians try to address vaginal toxicities and sexual dysfunction in women after radiotherapy for GYN malignancies.

Ex vivo study of quantitative ultrasound parameters in fatty rabbit livers

Nonalcoholic fatty liver disease (NAFLD) affects more than 30% of Americans, and with increasing problems of obesity in the United States, NAFLD is poised to become an even more serious medical concern. At present, accurate classification of steatosis (fatty liver) represents a significant challenge. In this study, the use of high-frequency (8 to 25 MHz) quantitative ultrasound (QUS) imaging to quantify fatty liver was explored. QUS is an imaging technique that can be used to quantify properties of tissue giving rise to scattered ultrasound. The changes in the ultrasound properties of livers in rabbits undergoing atherogenic diets of varying durations were investigated using QUS. Rabbits were placed on a special fatty diet for 0, 3, or 6 weeks. The fattiness of the livers was quantified by estimating the total lipid content of the livers. Ultrasonic properties, such as speed of sound, attenuation, and backscatter coefficients, were estimated in ex vivo rabbit liver samples from animals that had been on the diet for varying periods. Two QUS parameters were estimated based on the backscatter coefficient: effective scatterer diameter (ESD) and effective acoustic concentration (EAC), using a spherical Gaussian scattering model. Two parameters were estimated based on the backscattered envelope statistics (the k parameter and the μ parameter) according to the homodyned K distribution. The speed of sound decreased from 1574 to 1565 m/s and the attenuation coefficient increased from 0.71 to 1.27 dB/cm/MHz, respectively, with increasing fat content in the liver. The ESD decreased from 31 to 17 μm and the EAC increased from 38 to 63 dB/cm(3) with increasing fat content in the liver. A significant increase in the μ parameter from 0.18 to 0.93 scatterers/mm(3) was observed with increasing fat content in the liver samples. The results of this study indicate that QUS parameters are sensitive to fat content in the liver.

Minimum requirement of artificial noise level for using noise-assisted correlation algorithm to suppress artifacts in ultrasonic Nakagami images

The Nakagami image is a complementary imaging mode for pulse-echo ultrasound B-scan to characterize tissues. White noise in anechoic areas induces artifacts in the Nakagami image. Recently, we proposed a noise-assisted correlation algorithm (NCA) for suppressing the Nakagami artifact. In the NCA, artificial white noise is intentionally added twice to backscattered signals to produce two noisy data, which are used to establish a correlation profile for rejecting noise. This study explored the effects of artificial noise level on the NCA to suppress the artifact of the Nakagami image. Simulations were conducted to produce B-mode images of anechoic regions under signal-to-noise ratios (SNRs) of 20, 10 and 5 dB. Various artificial noise levels ranging from 0.1- to 1-fold of the intrinsic noise amplitude were used in the NCA for constructing the Nakagami images. Phantom experiments were conducted to validate the performance of using the optimal artificial noise level suggested by the simulation results to suppress the Nakagami artifacts by the NCA. The simulation results indicated that the artifacts of the Nakagami image in the anechoic regions can be gradually suppressed by increasing the artificial noise level used in the NCA to improve the image contrast-to-noise ratio (CNR). The CNR of the Nakagami image reached 20 dB when the artificial noise level was 0.7-fold of the intrinsic noise amplitude. This criterion was demonstrated by the phantom results to provide the NCA with an excellent ability to obtain artifact-free Nakagami images.