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

The Kidneys Are Not All Normal: Transplanted Kidneys and Their Speckle Distributions

OBJECTIVE

Modelling ultrasound speckle to characterise tissue properties has generated considerable interest. As speckle is dependent on the underlying tissue architecture, modelling it may aid in tasks such as segmentation or disease detection. For the transplanted kidney, where ultrasound is used to investigate dysfunction, it is unknown which statistical distribution best characterises such speckle. This applies to the regions of the transplanted kidney: the cortex, the medulla and the central echogenic complex. Furthermore, it is unclear how these distributions vary by patient variables such as age, sex, body mass index, primary disease or donor type. These traits may influence speckle modelling given their influence on kidney anatomy. We investigate these two aims.

METHODS

B-mode images from n = 821 kidney transplant recipients (one image per recipient) were automatically segmented into the cortex, medulla and central echogenic complex using a neural network. Seven distinct probability distributions were fitted to each region's histogram, and statistical analysis was performed.

DISCUSSION

The Rayleigh and Nakagami distributions had model parameters that differed significantly between the three regions (p ≤ 0.05). Although both had excellent goodness of fit, the Nakagami had higher Kullbeck-Leibler divergence. Recipient age correlated weakly with scale in the cortex (Ω: ρ = 0.11, p = 0.004), while body mass index correlated weakly with shape in the medulla (m: ρ = 0.08, p = 0.04). Neither sex, primary disease nor donor type exhibited any correlation.

CONCLUSION

We propose the Nakagami distribution be used to characterize transplanted kidneys regionally independent of disease etiology and most patient characteristics.

Modeling for Quantitative Analysis of Nakagami Imaging in Accurate Detection and Monitoring of Therapeutic Lesions by High-Intensity Focused Ultrasound

OBJECTIVE

Nakagami imaging is an appealing monitoring and evaluation technique for high-intensity focused ultrasound treatment when bubbles are present in ultrasound images. This study aimed to investigate the accuracy of thermal lesion detection using Nakagami imaging.

METHODS

Simulations were conducted to explore and quantify the influence of the bubbles and the subresolvable effect at the boundary of the thermal lesion on thermal lesion detection. The thermal ablation experiments were conducted in phantom and porcine liver ex vivo.

RESULTS

In the simulation, the estimated lateral and axial size of the thermal lesion in the Nakagami image was 4.91 and 4.79 mm, close to the actual size (5 × 5 mm). The simulation results indicated that the subresolvable region in high-intensity focused ultrasound treatment thermal ablation mainly happened at the boundary between bubbles and the untreated region and does not affect the accuracy of thermal lesion detection. The accurate detection of the thermal lesion using Nakagami imaging mainly depends on bubbles and thermal lesion characterization. Our thermal ablation experiments confirmed that Nakagami imaging has the ability to accurately identify thermal lesions from bubbles.

CONCLUSION

The subresolvable effect is helpful for thermal lesion identification, and precision is related to the Nakagami values chosen for boundary division in Nakagami imaging. Therefore, Nakagami imaging is a promising method for accurately evaluating thermal lesions. Further studies in vivo and in clinical settings will be needed to explore its potential applications.

Nakagami statistics-based photoacoustic spectroscopy used for label-free assessment of bone tissue

Quick identification of abnormal molecular metabolism of bone tissues is challenging. Photoacoustic (PA) spectroscopy techniques have great potential in molecular imaging. However, most of them are amplitude-dependent and easily affected by the light deposition, especially for bone tissues with high optical scattering. In this Letter, we propose a Nakagami statistics-based PA spectroscopy (NSPS) method for characterizing molecules in bone tissues. We indicate that the NSPS curve can intelligently identify changes in the content of molecules in bone tissues, with a high disturbance-resisting ability. The NSPS has remarkable potential for use in the early and rapid detection of bone diseases.

Information Entropy and Its Applications

Ultrasound is a first-line diagnostic tool for imaging many disease states. A number of statistical distributions have been proposed to describe ultrasound backscattering measured from tissues having different disease states. As an example, in this chapter we use nonalcoholic fatty liver disease (NAFLD), which is a critical health issue on a global scale, to demonstrate the capabilities of ultrasound to diagnose disease. Ultrasound interaction with the liver is typically characterized by scattering, which is quantified for the purpose of determining the degree of liver steatosis and fibrosis. Information entropy provides an insight into signal uncertainty. This concept allows for the analysis of backscattered statistics without considering the distribution of data or the statistical properties of ultrasound signals. In this chapter, we examined the background of NAFLD and the sources of scattering in the liver. The fundamentals of information entropy and an algorithmic scheme for ultrasound entropy imaging are then presented. Lastly, some examples of using ultrasound entropy imaging to grade hepatic steatosis and evaluate the risk of liver fibrosis in patients with significant hepatic steatosis are presented to illustrate future opportunities for clinical use.

Tissue attenuation imaging and tissue scatter imaging for quantitative ultrasound evaluation of hepatic steatosis

We aimed to assess the feasibility of ultrasound-based tissue attenuation imaging (TAI) and tissue scatter distribution imaging (TSI) for quantification of liver steatosis in patients with nonalcoholic fatty liver disease (NAFLD). We prospectively enrolled 101 participants with suspected NAFLD. The TAI and TSI measurements of the liver were performed with a Samsung RS85 Prestige ultrasound system. Based on the magnetic resonance imaging proton density fat fraction (MRI-PDFF), patients were divided into ≤5%, 5-10%, and ≥10% of MRI-PDFF groups. We determined the correlation between TAI, TSI, and MRI-PDFF and used multiple linear regression analysis to identify any association with clinical variables. The diagnostic performance of TAI, TSI was determined based on the area under the receiver operating characteristic curve (AUC). The intraclass correlation coefficient (ICC) was calculated to assess interobserver reliability. Both TAI (rs = 0.78, P < .001) and TSI (rs = 0.68, P < .001) showed significant correlation with MRI-PDFF. TAI overperformed TSI in the detection of both ≥5% MRI-PDFF (AUC = 0.89 vs 0.87) and ≥10% (AUC = 0.93 vs 0.86). MRI-PDFF proved to be an independent predictor of TAI (β = 1.03; P < .001), while both MRI-PDFF (β = 50.9; P < .001) and liver stiffness (β = -0.86; P < .001) were independent predictors of TSI. Interobserver analysis showed excellent reproducibility of TAI (ICC = 0.95) and moderate reproducibility of TSI (ICC = 0.73). TAI and TSI could be used successfully to diagnose and estimate the severity of hepatic steatosis in routine clinical practice.

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.

Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis

Objective: Hepatic steatosis causes nonalcoholic fatty liver disease and may progress to fibrosis. Ultrasound is the first-line approach to examining hepatic steatosis. Fatty droplets in the liver parenchyma alter ultrasound radiofrequency (RF) signal statistical properties. This study proposes using sample entropy, a measure of irregularity in time-series data determined by the dimension [Formula: see text] and tolerance [Formula: see text], for ultrasound parametric imaging of hepatic steatosis and fibrosis. Methods: Liver donors and patients were enrolled, and their hepatic fat fraction (HFF) ([Formula: see text]), steatosis grade ([Formula: see text]), and fibrosis score ([Formula: see text]) were measured to verify the results of sample entropy imaging using sliding-window processing of ultrasound RF data. Results: The sample entropy calculated using [Formula: see text] 4 and [Formula: see text] was highly correlated with the HFF when a small window with a side length of one pulse was used. The areas under the receiver operating characteristic curve for detecting hepatic steatosis that was [Formula: see text]mild, [Formula: see text]moderate, and [Formula: see text]severe were 0.86, 0.90, and 0.88, respectively, and the area was 0.87 for detecting liver fibrosis in individuals with significant steatosis. Discussion/Conclusions: Ultrasound sample entropy imaging enables the identification of time-series patterns in RF signals received from the liver. The algorithmic scheme proposed in this study is compatible with general ultrasound pulse-echo systems, allowing clinical fibrosis risk evaluations of individuals with developing hepatic steatosis.

Non-Invasive Photothermal Strain Imaging of Non-Alcoholic Fatty Liver Disease in Live Animals

The prevalence of non-alcoholic fatty liver diseases (NAFLD) has increased steadily over the past decade. Thus, diagnosing NAFLD at the earliest stage, which is a reversible condition, has become increasingly important. Here, photothermal strain imaging (pTSI) is presented as a novel non-invasive tool for NAFLD diagnosis. The pTSI uses ultrasound to detect the difference in thermal strain between fat and water during a light-induced temperature rise, which is directly related to the pathological evidence of NAFLD. To demonstrate its feasibility, fat accumulation in in vivo rat livers is monitored non-invasively using pTSI, based on clinical ultrasound B-mode images. A total of 21 male Wistar rats of 3 weeks of age were prepared. Of these, 18 rats received methionine-choline deficient diet for 1 to 6 weeks (n = 3 per week) to induce NAFLD, whereas 3 rats received normal diet as controls (n = 3). Livers were heated by a lipid-sensitive continuous-wave laser, and strain was measured. Quantitative results from the pTSI were compared with histological analysis results using Oil-Red-O (ORO). The receiver operating characteristic curve of in vivo pTSI results for detecting moderate steatosis (ORO-stained area ≥33%) was constructed based on strain change rate measured in the liver region. The sensitivity and specificity of pTSI were 90% and 82%, respectively, and the area-under-the-curve was measured as 0.85 ± 0.03 (95% confidence interval). The pTSI results tested in the rodent NAFLD model showed great potential for pTSI to be used as a new diagnostic tool for NAFLD in the future.

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.

Quantitative Ultrasound Radiofrequency Data Analysis for the Assessment of Hepatic Steatosis in Nonalcoholic Fatty Liver Disease Using Magnetic Resonance Imaging Proton Density Fat Fraction as the Reference Standard

Objective

To investigate the diagnostic performance of quantitative ultrasound (US) parameters for the assessment of hepatic steatosis in patients with nonalcoholic fatty liver disease (NAFLD) using magnetic resonance imaging proton density fat fraction (MRI-PDFF) as the reference standard.

Materials and Methods

In this single-center prospective study, 120 patients with clinically suspected NAFLD were enrolled between March 2019 and January 2020. The participants underwent US examination for radiofrequency (RF) data acquisition and chemical shift-encoded liver MRI for PDFF measurement. Using the RF data analysis, the attenuation coefficient (AC) based on tissue attenuation imaging (TAI) (AC-TAI) and scatter-distribution coefficient (SC) based on tissue scatter-distribution imaging (TSI) (SC-TSI) were measured. The correlations between the quantitative US parameters (AC and SC) and MRI-PDFF were evaluated using Pearson correlation coefficients. The diagnostic performance of AC-TAI and SC-TSI for detecting hepatic fat contents of ≥ 5% (MRI-PDFF ≥ 5%) and ≥ 10% (MRI-PDFF ≥ 10%) were assessed using receiver operating characteristic (ROC) analysis. The significant clinical or imaging factors associated with AC and SC were analyzed using linear regression analysis.

Results

The participants were classified based on MRI-PDFF: < 5% (n = 38), 5–10% (n = 23), and ≥ 10% (n = 59). AC-TAI and SC-TSI were significantly correlated with MRI-PDFF (r = 0.659 and 0.727, p < 0.001 for both). For detecting hepatic fat contents of ≥ 5% and ≥ 10%, the areas under the ROC curves of AC-TAI were 0.861 (95% confidence interval [CI]: 0.786–0.918) and 0.835 (95% CI: 0.757–0.897), and those of SC-TSI were 0.964 (95% CI: 0.913–0.989) and 0.935 (95% CI: 0.875–0.972), respectively. Multivariable linear regression analysis showed that MRI-PDFF was an independent determinant of AC-TAI and SC-TSI.

Conclusion

AC-TAI and SC-TSI derived from quantitative US RF data analysis yielded a good correlation with MRI-PDFF and provided good performance for detecting hepatic steatosis and assessing its severity in NAFLD.

Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver

Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined duration and/or periodically injecting them with CCl₄. The ground truth of the liver state was based on lipid liver percents estimated via the Folch assay and hydroxyproline concentration to quantify fibrosis. Rabbits were scanned ultrasonically in vivo using a SonixOne scanner and an L9-4/38 linear array. Liver fat percentage was classified based on the ultrasonic backscattered radiofrequency (RF) signals from the livers using either QUS or a 1-D convolutional neural network (CNN). Use of QUS parameters with linear regression and canonical correlation analysis demonstrated that the QUS parameters could differentiate between livers with lipid levels above or below 5%. However, the QUS parameters were not sensitive to fibrosis. The CNN was implemented by analyzing raw RF ultrasound signals without using separate reference data. The CNN outputs the classification of liver as either above or below a threshold of 5% fat level in the liver. The CNN outperformed the classification utilizing the QUS parameters combined with a support vector machine in differentiating between low and high lipid liver levels (i.e., accuracies of 74% versus 59% on the testing data). Therefore, although the CNN did not provide a physical interpretation of the tissue properties (e.g., attenuation of the medium or scatterer properties) the CNN had much higher accuracy in predicting fatty liver state and did not require an external reference scan.

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.

Basic concept and clinical applications of quantitative ultrasound (QUS) technologies

In the field of clinical ultrasound, the full digitalization of diagnostic equipment in the 2000s enabled the technological development of quantitative ultrasound (QUS), followed by multiple diagnostic technologies that have been put into practical use in recent years. In QUS, tissue characteristics are quantified and parameters are calculated by analyzing the radiofrequency (RF) echo signals returning to the transducer. However, the physical properties (and pathological level structure) of the biological tissues responsible for the imaging features and QUS parameters have not been sufficiently verified as there are various conditions for observing living tissue with ultrasound and inevitable discrepancies between theoretical and actual measurements. A major issue of QUS in clinical application is that the evaluation results depend on the acquisition conditions of the RF echo signal as the source of the image information, and also vary according to the model of the diagnostic device. In this paper, typical examples of QUS techniques for evaluating attenuation, speed of sound, amplitude envelope characteristics, and backscatter coefficient in living tissues are introduced. Exemplary basic research and clinical applications related to these technologies, and initiatives currently being undertaken to establish the QUS method as a true tissue characterization technology, are also discussed.

Detection of pediatric hepatic steatosis through ultrasound backscattering analysis

OBJECTIVES

Hepatic steatosis has become a considerable concern in the pediatric population. The objective of this study was to evaluate the feasibility of using ultrasound Nakagami imaging to produce a parametric image for analyzing the echo amplitude distribution to assess pediatric hepatic steatosis.

METHODS

A total of 68 pediatric participants were enrolled in healthy control (n = 26) and study groups (n = 42). Raw data from ultrasound imaging were acquired for each participant analysis using AmCAD-US, a software approved by the US Food and Drug Administration for ultrasound Nakagami imaging. The Nakagami parameters were compared with the hepatic steatosis index (HSI) and the steatosis grade (G0: HSI < 30; G1: 30 ≤ HSI < 36; G2: 36 ≤ HSI < 41.6; G3: 41.6 ≤ HSI < 43; G4: HSI ≥ 43) using correlation analysis, one-way analysis of variance (ANOVA), and receiver operating characteristic (ROC) curve analysis.

RESULTS

The Nakagami parameter increased from 0.53 ± 0.13 to 0.82 ± 0.05 with increasing severity of hepatic steatosis from G0 to G4 and were significantly different between the different grades of hepatic steatosis (p < .05). The areas under the ROC curves were 0.96, 0.92, 0.85, and 0.82 for diagnosing hepatic steatosis ≥ G1, ≥ G2, ≥ G3, and ≥ G4, respectively.

CONCLUSIONS

The Nakagami parameter value quantifies changes in the echo amplitude distribution of ultrasound backscattered signals caused by fatty infiltration, providing a novel, noninvasive, and effective data analysis technique to detect pediatric hepatic steatosis.

KEY POINTS

• Ultrasound Nakagami imaging enabled quantification of the echo amplitude distribution for tissue characterization. • The Nakagami parameter increased with the increasing severity of pediatric hepatic steatosis. • The Nakagami parameter demonstrated promising diagnostic performance in evaluating pediatric hepatic steatosis.

Nakagami imaging with related distributions for advanced thermogram pseudocolorization

Pseudocoloring algorithms embedded in the software of thermal cameras gradually colorize original intensity thermograms generated by detecting temperatures and contrast. Maximum and minimum based algorithms, however, executed by thresholding, applied to intensity thermograms for revealing and coloring the outliers instead. Although the common pseudocoloring protocols employed for general purposes may provide crucial information on the superficial contrast between radiation emitted by various sources; their common kernel is not sufficient for detecting and differentiating high radiated regions from surrounding areas, which is mandatory for recognition of abnormalities. Therefore, we propose novel imaging methodology based on Nakagami and related distributions, including gamma, Rayleigh, Weibull, chi-square and exponential, for enhancing thermal images and also for creating adequate discrimination. We initially define the boundaries of tumor and surrounding area in a synthetically generated breast thermogram already diagnosed as retroareolar tumor. Using Nakagami and transformations supported by mathematical foundations, we conducted several experiments to find the discrimination factor of the pseudocoloring techniques by calculating difference of average contrast between the tumor and the surrounding area. The performance is greatly encouraging that we achieved considerably better discrimination factor, designated for this study, up to 106.80 compared to the results of existing built-in pseudocolorization methods computed as 11.56.

Multiple information extracted from photoacoustic radio-frequency signal and the application on tissue classification

Photoacoustic imaging is a hybrid biomedical imaging technique, combining rich optical contrasts and good acoustic resolution in deep tissues. As a noninvasive and nonionized imaging method, photoacoustic imaging has shown great potentials in biomedicine in the past decade. In this review, we give a brief introduction of the physical principle and three major implementations of photoacoustic imaging. Then, we present pictures of some recent progress about the extraction of new imaging parameters from photoacoustic radio-frequency signals. These parameters are highly associated with the tissue microstructure characteristics, including characteristic size, number density, and elasticity. This information could give us insight into various properties of tissue in-depth and be applied to tissue classification for basic research and clinical settings.

Quantitative ultrasound radiofrequency data analysis for the assessment of hepatic steatosis using the controlled attenuation parameter as a reference standard

Purpose

This study was aimed to investigate the value of quantitative ultrasound (US) parameters from radiofrequency (RF) data analysis for assessing hepatic steatosis, using controlled attenuation parameter (CAP)-based steatosis grades as the reference standard.

Methods

We analyzed 243 participants with both B-mode liver US with RF data acquisition and CAP measurements. On B-mode US images, hepatic steatosis was visually scored (0/1/2/3, none/mild/moderate/severe), and the hepatorenal index (HRI) was calculated. From the RF data analysis, the tissue scatter-distribution imaging parameter (TSI-p) and tissue attenuation imaging parameter (TAI-p) of the liver parenchyma were measured. US parameters were correlated with CAP-based steatosis grades (S0/1/2/3, none/mild/moderate/severe) and their diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Multivariate linear regression analysis was performed to identify determinants of TSI-p and TAI-p.

Results

Participants were classified as having S0 (n=152), S1 (n=54), S2 (n=14), and S3 (n=23) on CAP measurements. TSI-p and TAI-p were significantly correlated with steatosis grades (ρ =0.593 and ρ=-0.617, P<0.001 for both). For predicting ≥S1, ≥S2, and S3, the areas under the ROC curves (AUCs) of TSI-p were 0.827/0.914/0.917; TAI-p, 0.844/0.914/0.909; visual scores, 0.659/0.778/0.794; and HRI, 0.629/0.751/0.759, respectively. TSI-p and TAI-p had significantly higher AUCs than did visual scores or HRI for ≥S1 or ≥S2 (P≤0.003). In the multivariate analysis, the transient elastography-based fibrosis grade (P=0.034) and steatosis grade (P<0.001) were independent determinants of TSI-p, while steatosis grade (P<0.001) was an independent determinant of TAI-p.

Conclusion

TSI-p and TAI-p derived from US RF data may be useful for detecting hepatic steatosis and assessing its severity.

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.

Monitoring of Adult Zebrafish Heart Regeneration Using High-Frequency Ultrasound Spectral Doppler and Nakagami Imaging

This paper reports the feasibility of Nakagami imaging in monitoring the regeneration process of zebrafish hearts in a noninvasive manner. In addition, spectral Doppler waveforms that are typically used to access the diastolic function were measured to validate the performance of Nakagami imaging. A 30-MHz high-frequency ultrasound array transducer was used to acquire backscattered echo signal for spectral Doppler and Nakagami imaging. The performances of both methods were validated with flow and tissue-mimicking phantom experiments. For in vivo experiments, both spectral Doppler and Nakagami imaging were simultaneously obtained from adult zebrafish with amputated hearts. Longitudinal measurements were performed for five zebrafish. From the experiments, the E/A ratio measured using spectral Doppler imaging increased at 3 days post-amputation (3 dpa) and then decreased to the value before amputation, which were consistent with previous studies. Similar results were obtained from the Nakagami imaging where the Nakagami parameter value increased at 3 dpa and decreased to its original value. These results suggested that the Nakagami and spectral Doppler imaging would be useful techniques in monitoring the regeneration of heart or tissues.

Considerations of Ultrasound Scanning Approaches in Non-alcoholic Fatty Liver Disease Assessment through Acoustic Structure Quantification

Non-alcoholic fatty liver disease (NAFLD) is a risk factor for hepatic fibrosis and cirrhosis. Acoustic structure quantification (ASQ), based on statistical analysis of ultrasound echoes, is an emerging technique for hepatic steatosis diagnosis. A standardized measurement protocol for ASQ analysis was suggested previously; however, an optimal ultrasound scanning approach has not been concluded thus far. In this study, the suitability of scanning approaches for the ASQ-based evaluation of hepatic steatosis was investigated. Hepatic fat fractions (HFFs; liver segments VIII, III and VI) of 70 living liver donors were assessed with magnetic resonance spectroscopy. A clinical ultrasound machine equipped with a 3-MHz convex transducer was used to scan each participant using the intercostal, epigastric and subcostal planes to acquire raw data for estimating two ASQ parameters (C_m² and focal disturbance [FD] ratio) of segments VIII, III and VI, respectively. The parameters were plotted as functions of the HFF for calculating the values of the correlation coefficient (r) and probability value (p). The diagnostic performance of the parameters in discriminating between the normal and steatotic (≥5 and ≥10%) groups was also compared using receiver operating characteristic (ROC) curves. The C_m² and FD ratio values measured using the epigastric and subcostal planes did not correlate with the severity of hepatic steatosis. However, intercostal imaging exhibited a higher correlation between the ASQ parameters and HFF (r = -0.64, p < 0.001). The diagnostic performance of C_m² and FD ratio in detecting hepatic steatosis using intercostal imaging was also satisfactory (areas under ROC curves >0.8). Intercostal imaging is an appropriate scanning approach for ASQ analysis of the liver.

Quantification of number density of random microstructure from a photoacoustic signal by using Nakagami statistics

Tissue microstructure characterization is a valuable tool in diagnosis and staging of many diseases. In this study, we propose a photoacoustic Nakagami statistics method to noninvasively evaluate the number density of random microstructure. The Nakagami parameters are acquired by fitting the photoacoustic signal envelope histogram with Nakagami distribution function. Theoretical calculations and phantom experiments demonstrate that the Nakagami shape parameter is only related to the number density of random microstructure and monotonically increases with the number density. Based on this finding, we propose a photoacoustic tomography modality with the imaging contrast of the Nakagami shape parameter. Experiments show that the proposed method can provide more comprehensive and accurate description of tissue microstructure.

Comparison of Acoustic Structure Quantification, Transient Elastography (FibroScan) and Histology in Patients with Chronic Hepatitis B and without Moderate to Severe Hepatic Steatosis

The purpose of this study was to compare acoustic structure quantification (ASQ) with transient elastography for staging liver fibrosis. One hundred eighty-two patients with chronic hepatitis B and without moderate to severe hepatic steatosis scheduled for liver biopsy underwent ASQ and transient elastography examinations. All ASQ parameters, including total mode, total average, red mode, red average, red standard deviation, blue mode, blue average, blue standard deviation and focal disturbance (FD) ratio and liver stiffness obtained via transient elastography were found to correlate with fibrosis stage (Spearman's r = 0.783, 0.791, 0.750, 0.771, 0.544, 0.718, 0.691, 0.439, 0.815 and 0.814, respectively; all p values < 0.001). Among the ASQ parameters, the FD ratio had the highest correlation with the stage of fibrosis. The areas under the receiver operating characteristic curves (AUCs) of FD ratio and liver stiffness were 0.911 and 0.906 for F ≥ F1, 0.918 and 0.882 for F ≥ F2, 0.911 and 0.914 for F ≥ F3 and 0.926 and 0.978 for F = F4, respectively. There was no significant difference in AUCs between FD ratio and liver stiffness in predicting different stages of fibrosis (p = 0.062-0.912). ASQ is a promising technique for assessing liver fibrosis in the absence of moderate to severe hepatic steatosis.

Hepatic Steatosis Assessment with Ultrasound Small-Window Entropy Imaging

Nonalcoholic fatty liver disease is a type of hepatic steatosis that is not only associated with critical metabolic risk factors but can also result in advanced liver diseases. Ultrasound parametric imaging, which is based on statistical models, assesses fatty liver changes, using quantitative visualization of hepatic-steatosis-caused variations in the statistical properties of backscattered signals. One constraint with using statistical models in ultrasound imaging is that ultrasound data must conform to the distribution employed. Small-window entropy imaging was recently proposed as a non-model-based parametric imaging technique with physical meanings of backscattered statistics. In this study, we explored the feasibility of using small-window entropy imaging in the assessment of fatty liver disease and evaluated its performance through comparisons with parametric imaging based on the Nakagami distribution model (currently the most frequently used statistical model). Liver donors (n = 53) and patients (n = 142) were recruited to evaluate hepatic fat fractions (HFFs), using magnetic resonance spectroscopy and to evaluate the stages of fatty liver disease (normal, mild, moderate and severe), using liver biopsy with histopathology. Livers were scanned using a 3-MHz ultrasound to construct B-mode, small-window entropy and Nakagami images to correlate with HFF analyses and fatty liver stages. The diagnostic values of the imaging methods were evaluated using receiver operating characteristic curves. The results demonstrated that the entropy value obtained using small-window entropy imaging correlated well with log₁₀(HFF), with a correlation coefficient r = 0.74, which was higher than those obtained for the B-scan and Nakagami images. Moreover, small-window entropy imaging also resulted in the highest area under the receiver operating characteristic curve (0.80 for stages equal to or more severe than mild; 0.90 for equal to or more severe than moderate; 0.89 for severe), which indicated that non-model-based entropy imaging-using the small-window technique-performs more favorably than other techniques in fatty liver assessment.

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.

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.