A pilot approach for quantitative assessment of liver fibrosis using ultrasound: preliminary results in 79 cases

Liver cirrhosis in children - the role of imaging in the diagnostic pathway

Liver cirrhosis in children is a rare disease with multifactorial causes that are distinct from those in adults. Underlying reasons include cholestatic, viral, autoimmune, hereditary, metabolic and cardiac disorders. Early detection of fibrosis is important as clinical stabilization or even reversal of fibrosis can be achieved in some disorders with adequate treatment. This article focuses on the longitudinal evaluation of children with chronic liver disease with noninvasive imaging tools, which play an important role in detecting cirrhosis, defining underlying causes, grading fibrosis and monitoring patients during follow-up. Ultrasound is the primary imaging modality and it is used in a multiparametric fashion. Magnetic resonance imaging and computed tomography are usually applied second line for refined tissue characterization, clarification of nodular lesions and full delineation of abdominal vessels, including portosystemic communications.

In Vivo Quantitative Ultrasound on Dermis and Hypodermis for Classifying Lymphedema Severity in Humans

This study investigated the ability of in vivo quantitative ultrasound (QUS) assessment to evaluate lymphedema severity compared with the gold standard method, the International Society of Lymphology (ISL) stage. Ultrasonic measurements were made around the middle thigh (n = 150). Radiofrequency data were acquired using a clinical scanner and 8-MHz linear probe. Envelope statistical analysis was performed using constant false alarm rate processing and homodyned K (HK) distribution. The attenuation coefficient was calculated using the spectral log-difference technique. The backscatter coefficient (BSC) was obtained by the reference phantom method with attenuation compensation according to the attenuation coefficients in the dermis and hypodermis, and then effective scatterer diameter (ESD) and effective acoustic concentration (EAC) were estimated with a Gaussian model. Receiver operating characteristic curves of QUS parameters were obtained using a linear regression model. A single QUS parameter with high area under the curve (AUC) differed between the dermis (ESD and EAC) and hypodermis (HK) parameters. The combinations with ESD and EAC in the dermis, HK parameters in the hypodermis and typical features (dermal thickness and echogenic regions in the hypodermis) improved classification performance between ISL stages 0 and ≥I (AUC = 0.90 with sensitivity of 75% and specificity of 91%) in comparison with ESD and EAC in the dermis (AUC = 0.82) and HK parameters in the hypodermis (AUC = 0.82). In vivo QUS assessment by BSC and envelope statistical analyses can be valuable for non-invasively classifying an extremely early stage of lymphedema, such as ISL stage I, and following its progression.

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 Image Analysis Helps in the Differentiation of Hepatocellular Carcinoma (HCC) From Borderline Lesions and Predicting the Histologic Grade of HCC and Microvascular Invasion

OBJECTIVES

Quantitative image analysis is one of the methods to overcome the lack of objectivity of ultrasound (US). The aim of this study was to clarify the correlation between the features from a US image analysis and the histologic grade and microvascular invasion (MVI) of hepatocellular carcinoma (HCC) and differentiation of HCC smaller than 2 cm from borderline lesions.

METHODS

We retrospectively analyzed grayscale US images with histopathologic evidence of HCC or a precancerous lesion using ImageJ version 1.47 software (National Institutes of Health, Bethesda, MD).

RESULTS

A total of 148 nodules were included (borderline lesion, n = 31; early HCC [eHCC], n = 3; well-differentiated HCC [wHCC], n = 16; moderately differentiated HCC [mHCC], n = 79; and poorly differentiated HCC [pHCC], n = 19). A multivariate analysis selected lower minimum gray values (odds ratio [OR], 0.431; P = .003) and a higher standard deviation (OR, 1.880; P = .019) as predictors of HCC smaller than 2 cm. Median (range) minimum gray values of borderline lesions, eHCC, wHCC, mHCC, and pHCC were 29 (0-103), 7 (0-47), 6 (0-60), 10 (0-53), and 2 (0-38), respectively, and gradually decreased from borderline lesions to pHCC (P < 0.001). The multivariate analysis showed a higher aspect ratio (OR, 2.170; P = .001) and lower minimum gray value (OR, 0.475; P = .043) as predictors of MVI. An anechoic area diagnosed by a subjective evaluation was correlated with the minimum gray value (P < .0001). The proportion of the anechoic area gradually increased from eHCC to pHCC (P = .031).

CONCLUSIONS

In a US image analysis, HCC smaller than 2 cm had features of greater heterogeneity and a lower minimum gray value than borderline lesions. Moderately differentiated HCC was smoother than borderline lesions, and the anechoic area correlated with histologic grading. Microvascular invasion was correlated with a slender shape and a lower minimum gray value.

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.

Ultrasound Detection of Liver Fibrosis in Individuals with Hepatic Steatosis Using the Homodyned K Distribution

Acoustic structure quantification (ASQ) based on the analysis of ultrasound backscattered statistics has been reported to detect liver fibrosis without significant hepatic steatosis. This study proposed using ultrasound parametric imaging based on the parameter α of the homodyned K (HK) distribution for staging liver fibrosis in patients with significant hepatic steatosis. Raw ultrasound image data were acquired from patients (n = 237) to construct B-mode and HK α parametric images, which were compared with the focal disturbance (FD) ratio obtained from ASQ on the basis of histologic evidence (METAVIR fibrosis score and hepatic steatosis severity). The data were divided into group I (n = 173; normal to mild hepatic steatosis) and group II (n = 64; with moderate to severe hepatic steatosis) for statistical analysis through one-way analysis of variance and receiver operating characteristic (ROC) curve analysis. The results showed that the HK α parameter monotonically decreased as the liver fibrosis stage increased (p < .05); concurrently, the FD ratio increased (p < .05). For group I, the areas under the ROC (AUROCs) obtained using the FD ratio and the α parameter (AUROC_FD and AUROC_α) were, respectively, 0.56 and 0.55, 0.68 and 0.68, 0.64 and 0.64 and 0.62 and 0.62 for diagnosing liver fibrosis ≥F1, ≥F2, ≥F3 and ≥F4. The values of AUROC_FD and AUROC_α for group II were, respectively, 0.88 and 0.91, 0.81 and 0.81, 0.77 and 0.76 and 0.78 and 0.73 for diagnosing liver fibrosis ≥F1, ≥F2, ≥F3 and ≥F4. As opposed to previous studies, ASQ was found to fail in characterizing liver fibrosis in group I; however, it was workable for identifying liver fibrosis in patients with significant hepatic steatosis (group II). Compared with ASQ, HK imaging provided improved diagnostic performance in the early detection of liver fibrosis coexisting with moderate to severe hepatic steatosis. Ultrasound HK imaging is recommended as a strategy to evaluate early fibrosis risk in patients with significant hepatic steatosis.

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.

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.

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.

Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis

Objective

To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning.

Materials and Methods

This prospective study consisted of 144 patients with chronic hepatitis B. Ultrasomics—high-throughput quantitative data from ultrasound imaging of liver fibrosis—were generated using conventional radiomics, original radiofrequency (ORF) and contrast-enhanced micro-flow (CEMF) features. Three categories of features were explored using pairwise correlation and hierarchical clustering. Features were selected using diagnostic tests for fibrosis, activity and steatosis stage, with the histopathological results as the reference. The fibrosis staging performance of ultrasomics models with combinations of the selected features was evaluated with machine-learning algorithms by calculating the area under the receiver-operator characteristic curve (AUC).

Results

ORF and CEMF features had better predictive power than conventional radiomics for liver fibrosis stage (both p < 0.01). CEMF features exhibited the highest diagnostic value for activity stage (both p < 0.05), and ORF had the best diagnostic value for steatosis stage (both p < 0.01). The machine-learning classifiers of adaptive boosting, random forest and support vector machine were found to be optimal algorithms with better (all mean AUCs = 0.85) and more stable performance (coefficient of variation = 0.01–0.02) for fibrosis staging than decision tree, logistic regression and neural network (mean AUC = 0.61–0.72, CV = 0.07–0.08). The multiparametric ultrasomics model achieved much better performance (mean AUC values of 0.78–0.85) than the features from a single modality in discriminating significant fibrosis (≥ F2).

Conclusion

Machine-learning-based analysis of multiparametric ultrasomics can help improve the discrimination of significant fibrosis compared with mono or dual modalities.

Key Points

• Multiparametric ultrasomics has achieved much better performance in the discrimination of significant fibrosis (≥ F2) than the single modality of conventional radiomics, original radiofrequency and contrast-enhanced micro-flow.

• Adaptive boosting, random forest and support vector machine are the optimal algorithms for machine learning.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5680-z) contains supplementary material, which is available to authorized users.

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 hepatic fibrosis: a review from the society of abdominal radiology disease focus panel

Hepatic fibrosis is potentially reversible; however early diagnosis is necessary for treatment in order to halt progression to cirrhosis and development of complications including portal hypertension and hepatocellular carcinoma. Morphologic signs of cirrhosis on ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) alone are unreliable and are seen with more advanced disease. Newer imaging techniques to diagnose liver fibrosis are reliable and accurate, and include magnetic resonance elastography and US elastography (one-dimensional transient elastography and point shear wave elastography or acoustic radiation force impulse imaging). Research is ongoing with multiple other techniques for the noninvasive diagnosis of hepatic fibrosis, including MRI with diffusion-weighted imaging, hepatobiliary contrast enhancement, and perfusion; CT using perfusion, fractional extracellular space techniques, and dual-energy, contrast-enhanced US, texture analysis in multiple modalities, quantitative mapping, and direct molecular imaging probes. Efforts to advance the noninvasive imaging assessment of hepatic fibrosis will facilitate earlier diagnosis and improve patient monitoring with the goal of preventing the progression to cirrhosis and its complications.

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.

Small-window parametric imaging based on information entropy for ultrasound tissue characterization

Constructing ultrasound statistical parametric images by using a sliding window is a widely adopted strategy for characterizing tissues. Deficiency in spatial resolution, the appearance of boundary artifacts, and the prerequisite data distribution limit the practicability of statistical parametric imaging. In this study, small-window entropy parametric imaging was proposed to overcome the above problems. Simulations and measurements of phantoms were executed to acquire backscattered radiofrequency (RF) signals, which were processed to explore the feasibility of small-window entropy imaging in detecting scatterer properties. To validate the ability of entropy imaging in tissue characterization, measurements of benign and malignant breast tumors were conducted (n = 63) to compare performances of conventional statistical parametric (based on Nakagami distribution) and entropy imaging by the receiver operating characteristic (ROC) curve analysis. The simulation and phantom results revealed that entropy images constructed using a small sliding window (side length = 1 pulse length) adequately describe changes in scatterer properties. The area under the ROC for using small-window entropy imaging to classify tumors was 0.89, which was higher than 0.79 obtained using statistical parametric imaging. In particular, boundary artifacts were largely suppressed in the proposed imaging technique. Entropy enables using a small window for implementing ultrasound parametric imaging.

Diagnostic Utility of Acoustic Structure Quantification for Evaluation of Radiation Sialadenitis after Radioactive Iodine Therapy

Acoustic structure quantification (ASQ) software was used to analyze statistical information on acquired echo signals, to determine the ability of ASQ to distinguish normal salivary glands of asymptomatic patients from glands of patients with radiation sialadenitis (RS) after radioactive iodine therapy. The ASQ values of 192 salivary glands were compared by multinomial logistic regression analysis, and receiver operating characteristic curves were constructed. Between-observer agreement was assessed by calculating the intra-class correlation coefficient. The mean ASQ values of patients with chronic RS or asymptomatic patients who had undergone radioactive iodine therapy were greater than those of patients with normal glands (p < 0.001). The ratio was associated with the highest odds ratio in patients with chronic RS compared with normal patients. Diagnostic performance was moderate; the intra-class correlation coefficient between observers was very good. ASQ can objectively differentiate RS-affected tissue from normal salivary tissue and is thus valuable for clinically diagnosing RS after radioactive iodine therapy.

Analysis of fluctuation for pixel-pair distance in co-occurrence matrix applied to ultrasonic images for diagnosis of liver fibrosis

PURPOSE

Chronic liver disease requires careful follow-up during long-term treatment, and development of a quantitative diagnosis method for liver fibrosis based on an ultrasonic imaging system is highly desired.

METHODS

Texture analysis using a co-occurrence matrix was applied to both clinical and simulated ultrasonic images of fibrotic livers. A sequence of matrices was generated for pixel-pair distance, r, and texture feature contrast was chosen to examine the response to r in combination with statistical analysis of echo amplitude distribution using a multi-Rayleigh model.

RESULTS

The contrast converged with a larger value and fluctuated more significantly in response to r as fibrosis progressed in both the clinical and simulated ultrasonic images. The convergent value rapidly increased at the early stage of fibrosis, and the fluctuation became larger at the advanced stage of fibrosis. Analysis using simulated ultrasonic images with a known fibrous tissue structure theoretically clarified the relationship between contrast behavior and fibrosis progression.

CONCLUSION

It was revealed that contrast convergent value and contrast fluctuation provided information on the fibrous tissue structure, and they are expected to be used for quantitative diagnosis of the degree of liver fibrosis.

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.

Ultrasound window-modulated compounding Nakagami imaging: Resolution improvement and computational acceleration for liver characterization

Ultrasound Nakagami imaging is an attractive method for visualizing changes in envelope statistics. Window-modulated compounding (WMC) Nakagami imaging was reported to improve image smoothness. The sliding window technique is typically used for constructing ultrasound parametric and Nakagami images. Using a large window overlap ratio may improve the WMC Nakagami image resolution but reduces computational efficiency. Therefore, the objectives of this study include: (i) exploring the effects of the window overlap ratio on the resolution and smoothness of WMC Nakagami images; (ii) proposing a fast algorithm that is based on the convolution operator (FACO) to accelerate WMC Nakagami imaging. Computer simulations and preliminary clinical tests on liver fibrosis samples (n=48) were performed to validate the FACO-based WMC Nakagami imaging. The results demonstrated that the width of the autocorrelation function and the parameter distribution of the WMC Nakagami image reduce with the increase in the window overlap ratio. One-pixel shifting (i.e., sliding the window on the image data in steps of one pixel for parametric imaging) as the maximum overlap ratio significantly improves the WMC Nakagami image quality. Concurrently, the proposed FACO method combined with a computational platform that optimizes the matrix computation can accelerate WMC Nakagami imaging, allowing the detection of liver fibrosis-induced changes in envelope statistics. FACO-accelerated WMC Nakagami imaging is a new-generation Nakagami imaging technique with an improved image quality and fast computation.

Acoustic Structure Quantification Analysis of the Thyroid in Patients with Diffuse Autoimmune Thyroid Disease

The aim of this study was to assess whether acoustic structure quantification (ASQ) can differentiate normal from pathological thyroid parenchyma in patients with diffuse autoimmune thyroid disease (AITD). We evaluated 83 subjects (72 [87%] women and 11 [13%] men) aged 19 to 94 years with a mean age of 53 years. We performed a prospective study (from March 2011 to November 2014) that included 43 (52%) patients with chronic autoimmune thyroiditis (CAT), 22 (26%) patients with Graves' disease (GD), and 18 (22%) healthy volunteers. The ASQ values were significantly lower in normal subjects than in subjects with CAT and GD (p < 0.001). In contrast, the differences between the GD and the CAT patients (p = 0.23) were not statistically significant. The optimal cutoff ASQ value for which the sum of sensitivity and specificity was the highest for the prediction of diffuse thyroid pathology was 103 (95% confidence interval = [0.79, 0.95]). At this cutoff value, the sensitivity was 83% and the specificity was 89%. Our findings suggest that ASQ is a useful method for the assessment of the thyroid in patients with AITD.

Using Acoustic Structure Quantification During B-Mode Sonography for Evaluation of Hashimoto Thyroiditis

OBJECTIVES

This study aimed to evaluate the usefulness of Acoustic Structure Quantification (ASQ; Toshiba Medical Systems Corporation, Nasushiobara, Japan) values in the diagnosis of Hashimoto thyroiditis using B-mode sonography and to identify a cutoff ASQ level that differentiates Hashimoto thyroiditis from normal thyroid tissue.

METHODS

A total of 186 thyroid lobes with Hashimoto thyroiditis and normal thyroid glands underwent sonography with ASQ imaging. The quantitative results were reported in an echo amplitude analysis (Cm(2)) histogram with average, mode, ratio, standard deviation, blue mode, and blue average values. Receiver operating characteristic curve analysis was performed to assess the diagnostic ability of the ASQ values in differentiating Hashimoto thyroiditis from normal thyroid tissue. Intraclass correlation coefficients of the ASQ values were obtained between 2 observers.

RESULTS

Of the 186 thyroid lobes, 103 (55%) had Hashimoto thyroiditis, and 83 (45%) were normal. There was a significant difference between the ASQ values of Hashimoto thyroiditis glands and those of normal glands (P < .001). The ASQ values in patients with Hashimoto thyroiditis were significantly greater than those in patients with normal thyroid glands. The areas under the receiver operating characteristic curves for the ratio, blue average, average, blue mode, mode, and standard deviation were: 0.936, 0.902, 0.893, 0.855, 0.846, and 0.842, respectively. The ratio cutoff value of 0.27 offered the best diagnostic performance, with sensitivity of 87.38% and specificity of 95.18%. The intraclass correlation coefficients ranged from 0.86 to 0.94, which indicated substantial agreement between the observers.

CONCLUSIONS

Acoustic Structure Quantification is a useful and promising sonographic method for diagnosing Hashimoto thyroiditis. Not only could it be a helpful tool for quantifying thyroid echogenicity, but it also would be useful for diagnosis of Hashimoto thyroiditis.

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.

Estimating steatosis and fibrosis: Comparison of acoustic structure quantification with established techniques

AIM: To compare ultrasound-based acoustic structure quantification (ASQ) with established non-invasive techniques for grading and staging fatty liver disease.

METHODS: Type 2 diabetic patients at risk of non-alcoholic fatty liver disease (n = 50) and healthy volunteers (n = 20) were evaluated using laboratory analysis and anthropometric measurements, transient elastography (TE), controlled attenuation parameter (CAP), proton magnetic resonance spectroscopy (¹H-MRS; only available for the diabetic cohort), and ASQ. ASQ parameters mode, average and focal disturbance (FD) ratio were compared with: (1) the extent of liver fibrosis estimated from TE and non-alcoholic fatty liver disease (NAFLD) fibrosis scores; and (2) the amount of steatosis, which was classified according to CAP values.

RESULTS: Forty-seven diabetic patients (age 67.0 ± 8.6 years; body mass index 29.4 ± 4.5 kg/m²) with reliable CAP measurements and all controls (age 26.5 ± 3.2 years; body mass index 22.0 ± 2.7 kg/m²) were included in the analysis. All ASQ parameters showed differences between healthy controls and diabetic patients (P < 0.001, respectively). The ASQ FD ratio (logarithmic) correlated with the CAP (r = -0.81, P < 0.001) and ¹H-MRS (r = -0.43, P = 0.004) results. The FD ratio [CAP < 250 dB/m: 107 (102-109), CAP between 250 and 300 dB/m: 106 (102-114); CAP between 300 and 350 dB/m: 105 (100-112), CAP ≥ 350 dB/m: 102 (99-108)] as well as mode and average parameters, were reduced in cases with advanced steatosis (ANOVA P < 0.05). However, none of the ASQ parameters showed a significant difference in patients with advanced fibrosis, as determined by TE and the NAFLD fibrosis score (P > 0.08, respectively).

CONCLUSION: ASQ parameters correlate with steatosis, but not with fibrosis in fatty liver disease. Steatosis estimation with ASQ should be further evaluated in biopsy-controlled studies.

Imaging modalities for the diagnosis of hepatic fibrosis and cirrhosis

Non-invasive methods for liver fibrosis diagnosis are now commonly used as first-intention tests for liver fibrosis diagnosis in chronic liver diseases. Even morphological parameters provided by ultrasound is now challenged by blood fibrosis tests and transient elastography, in experienced hands, it performed well and in certain situations, imaging can still be useful to detect patients with fibrosis. In parallel, to ultrasound and Doppler imaging, various methodologies have been explored. Some of them remain confined to clinical research for the moment, as perfusion, MR diffusion-weighted imaging, intravoxel incoherent motion or acoustic structure quantification; others have already taken a place in clinical practice. Regarding fast growing of new technology some methods may become available for daily practice in the near future. Ultrasound tools or automated quantification of different physical parameters of imaging data could provide an opportunity for early diagnosis of liver diseases; MRI techniques could lead to the development of a "global" liver examination.

Ultrasound evaluation of liver fibrosis: preliminary experience with acoustic structure quantification (ASQ) software

PURPOSE

The aim of our study was to assess the diagnostic accuracy of acoustic structure quantification (ASQ) ultrasound software in estimating the degree of hepatic fibrosis compared to Fibroscan and liver biopsy.

MATERIALS AND METHODS

Seventy-seven patients with chronic viral hepatitis B and C underwent standard ultrasound examination, ASQ, Fibroscan and liver biopsy. ASQ analysis was conducted by placing a single region of interest (ROI) on each image captured, and calculating mode, average and standard deviation. The sonographic technique was developed through a preliminary evaluation of 20 healthy volunteers.

RESULTS

The area under the receiver operating characteristic (AUROC) curve for the diagnosis of cirrhosis (F≥4) with ASQ was 0.77, whereas for the diagnosis of any degree of fibrosis (F≥1) it was 0.71. The AUROC for the diagnosis of cirrhosis (F≥4) with Fibroscan was 0.98, while for the diagnosis of any degree of fibrosis (F≥1) it was 0.94. The difference between the AUROC was statistically significant (p<0.05).

CONCLUSIONS

ASQ is a promising new ultrasound software programme which offers encouraging results in the diagnosis of both liver cirrhosis (F=4) and fibrosis (F≥1). However, to date it has not attained the same level of diagnostic performance as Fibroscan.

Using ultrasound Nakagami imaging to assess liver fibrosis in rats

This study explored the feasibility of using the ultrasound Nakagami image to assess the degree of liver fibrosis in rats. The rat has been widely used as a model in investigations of liver fibrosis. Ultrasound grayscale imaging makes it possible to observe fibrotic rat livers in real time. Statistical analysis of the envelopes of signals backscattered from rat livers may provide useful clues about the degree of liver fibrosis. The Nakagami-model-based image has been shown to be useful for characterizing scatterers in tissues by reflecting the echo statistics, and hence the Nakagami image may serve as a functional imaging tool for quantifying rat liver fibrosis. To validate this idea, fibrosis was induced in each rat liver (n=21) by an intraperitoneal injection of 0.5% dimethylnitrosamine. Livers were excised from rats for in vitro ultrasound scanning using a single-element transducer. The backscattered-signal envelopes of the acquired raw ultrasound signals were used for Nakagami imaging. The Metavir score determined by a pathologist was used to histologically quantify the degree of liver fibrosis. It was found that the Nakagami image could be used to distinguish different degrees of liver fibrosis in rats, since the average Nakagami parameter increased from 0.55 to 0.83 as the fibrosis score increased from 0 (i.e., normal) to 4. This correlation may be due to liver fibrosis in rats involving an increase in the concentration of local scatterers and the appearance of the periodic structures or clustering of scatterers that would change the backscattering statistics. The current findings indicate that the ultrasound Nakagami image has great potential as a functional imaging tool to complement the use of the conventional B-scan in animal studies of liver fibrosis.

Influence of expert-dependent variability over the performance of noninvasive fibrosis assessment in patients with chronic hepatitis C by means of texture analysis

Texture analysis is viewed as a method to enhance the diagnosis power of classical B-mode ultrasound image. The present paper aims to evaluate and eliminate the dependence between the human expert and the performance of such a texture analysis system in predicting the cirrhosis in chronic hepatitis C patients. 125 consecutive chronic hepatitis C patients were included in this study. Ultrasound images were acquired from each patient and four human experts established regions of interest. Textural analysis tool was evaluated. The performance of this approach depends highly on the human expert that establishes the regions of interest (P < 0.05). The novel algorithm that automatically establishes regions of interest can be compared with a trained radiologist. In classical form met in the literature, the noninvasive diagnosis through texture analysis has limited utility in clinical practice. The automatic ROI establishment tool is very useful in eliminating the expert-dependent variability.

Three-dimensional ultrasonic Nakagami imaging for tissue characterization

The two-dimensional (2D) Nakagami image complements the ultrasound B-scan image when attempting to visualize the scatterer properties of tissues. The resolution of the Nakagami image is lower than that of the B-scan image, since the former is produced by processing the raw envelope data using a 2D sliding window with side lengths typically corresponding to three times the pulse length of the incident ultrasound. This paper proposes using three-dimensional (3D) Nakagami imaging for improving the resolution of the obtained Nakagami image and providing more complete information of scatterers for a better tissue characterization. The 3D Nakagami image is based on a voxel array composed of the Nakagami parameters constructed using a 3D sliding cube to process the 3D backscattered raw data. Experiments on phantoms with different scatterer concentrations were carried out to determine the optimal size of the sliding cube for a stable estimation of the Nakagami parameter. Tissue measurements on rat livers without and with fibrosis formation were further used to explore the practical feasibility of 3D Nakagami imaging. The results indicated that the side length of the cube used to construct the 3D Nakagami image must be at least two times the pulse length, which improved the resolution for each Nakagami image frame in the 3D Nakagami image. The results further demonstrated that the 3D Nakagami image is better than the conventional 2D Nakagami image for complementing the B-scan in detecting spatial variations in the scatterer concentration and classifying normal and fibrotic livers. This study suggests that 3D Nakagami imaging has the potential to become a new 3D quantitative imaging approach.

B-mode ultrasound with algorithm based on statistical analysis of signals: evaluation of liver fibrosis in patients with chronic hepatitis C

OBJECTIVE

The purpose of this study was to evaluate the degree of liver fibrosis in patients with chronic hepatitis C by use of a method in which the homogeneity of the tissue texture of the liver on B-mode ultrasound images is analyzed on the basis of results of a statistical chi-square test of the echo amplitudes. The method includes an algorithm for removing small structures, such as cross sections of the thin vessels, in the background texture to minimize differences in analysis results between users.

SUBJECTS AND METHODS

Analysis was performed on images of 148 patients with histologically proven chronic hepatitis C without cirrhosis. The peak value of the C(m)(2) (modified chi-square distribution) histogram was calculated from B-mode ultrasound images, and the resulting value was compared with the histologic fibrosis grade.

RESULTS

The peak C(m)(2) histogram value for grade F3 fibrosis was higher than that for grades F0 and F1 (p < 0.0001) and F2 (p = 0.0003). The value for grade F2 was higher than that for grades F0 and F1 (p = 0.0027). The values gradually increased with an increase in liver fibrosis grade, although no difference was found between grades F0 and F1.

CONCLUSION

The grades of liver fibrosis in patients with chronic hepatitis C are well discriminated with the B-mode ultrasound-based analysis algorithm without discrimination between grades F0 and F1. Findings on conventional ultrasound images may reflect progression of liver fibrosis even in the absence of cirrhosis.

Systematic review: non-invasive methods of fibrosis analysis in chronic hepatitis C

BACKGROUND

Accurate determination of the presence and degree of liver fibrosis is essential for prognosis and for planning treatment of patients with chronic hepatitis C virus (HCV). Non-invasive methods of assessing fibrosis have been developed to reduce the need for biopsy.

AIM

To perform a review of these non-invasive measures and their ability to replace biopsy for assessing hepatic fibrosis in patients with chronic HCV.

METHODS

A systematic review of PUBMED and EMBASE was performed through 2008 using the following search terms: HCV, liver, elastography, hepatitis, Fibroscan, SPECT, noninvasive liver fibrosis, ultrasonography, Doppler, MRI, Fibrotest, Fibrosure, Actitest, APRI, Forns and breath tests, alone or in combination.

RESULTS

We identified 151 studies: 87 using biochemical, 57 imaging and seven breath tests either alone or in combination.

CONCLUSIONS

Great strides are being made in the development of accurate non-invasive methods for determination of fibrosis. Although no single non-invasive test or model developed to date can match that information obtained from actual histology (i.e. inflammation, fibrosis, steatosis), combinations of two modalities of non-invasive methods can reliably differentiate between minimal and significant fibrosis, and thereby avoid liver biopsy in a significant percentage of patients.

Aflatoxin exposure and viral hepatitis in the etiology of liver cirrhosis in the Gambia, West Africa

BACKGROUND

Cirrhosis of the liver is thought to be a major cause of morbidity and mortality in sub-Saharan Africa, but few controlled studies on the etiology of cirrhosis have been conducted in this region.

OBJECTIVES

We aimed to elucidate the association between environmental and infectious exposures and cirrhosis in The Gambia.

METHODS

Ninety-seven individuals were diagnosed with cirrhosis using a validated ultrasound scoring system and were compared with 397 controls. Participants reported demographic and food frequency information. Blood samples were tested for hepatitis B surface antigen (HBsAg), hepatitis B e antigen (HBeAg), hepatitis C virus (HCV) antibody, HCV RNA, and the aflatoxin-associated 249(ser) TP53 mutation.

RESULTS

HBsAg seropositivity was associated with a significant increase in risk of cirrhosis [odds ratio (OR) = 8.0; 95% confidence interval (CI), 4.4-14.7] as was the presence of HBeAg (OR = 10.3; 95% CI, 2.0-53.9) and HCV infection (OR = 3.3; 95% CI, 1.2-9.5). We present novel data that exposure to aflatoxin, as assessed both by high lifetime groundnut (peanut) intake and by the presence of the 249(ser) TP53 mutation in plasma, is associated with a significant increase in the risk for cirrhosis (OR = 2.8; 95% CI, 1.1-7.7 and OR = 3.8; 95% CI, 1.5-9.6, respectively). Additionally, aflatoxin and hepatitis B virus exposure appeared to interact synergistically to substantially increase the risk of cirrhosis, although this was not statistically significant.

CONCLUSIONS

Our results suggest that the spectrum of morbidity associated with aflatoxin exposure could include cirrhosis.

Statistical relevance of ultrasonographic criteria in the assessment of diffuse liver disease in dogs and cats

OBJECTIVE

To determine whether objectively applied ultrasonographic interpretive criteria are statistically useful in differentiating among 7 defined categories of diffuse liver disease in dogs and cats.

SAMPLE POPULATION

Ultrasonographic images of 229 dogs and 104 cats.

PROCEDURES

Liver parenchymal or related sonographic criteria established by the authors were retrospectively and independently applied by 3 radiologists who were not aware of patient status or patient laboratory data. Seven histologic or cytologic categories of diffuse (infiltrative but not nodular) liver diseases were jointly established by the authors and included normal liver; inflammation; round-cell neoplasia; non-round-cell infiltrative, prenodular (early) metastatic neoplasia; lipidosis; vacuolar hepatopathy; and other. Liver parenchymal sonographic criteria included parenchymal sound attenuation with increasing depth, comparative organ echogenicity (liver, spleen, and kidneys), diffuse or patchy hyperechoic or hypoechoic echotexture, uniform or coarse echotexture, portal venous clarity, and liver lobe geometry. Related extrahepatic criteria included gallbladder wall thickness, bile duct diameter, amount and character of gallbladder precipitate, nondependent shadowing in the gallbladder, hepatic vein diameter versus caudal vena cava diameter, peritoneal fluid, spleen echotexture (normal vs abnormal [characterized]), and kidney echotexture. Ultrasonographic criteria were statistically compared to the 7 categories of diffuse liver disease in search of clinically exploitable relationships.

RESULTS

Statistical evaluation of the applied ultrasonographic criteria did not yield clinically acceptable accuracy for discrimination among the 7 categories of diffuse liver diseases (including normal liver) in either species.

CONCLUSIONS AND CLINICAL RELEVANCE

Criterion-based ultrasonographic appearance was insufficient to discriminate among canine and feline diffuse infiltrative liver diseases.

Sampling variability of computer-aided fractal-corrected measures of liver fibrosis in needle biopsy specimens

AIM: To assess the sampling variability of computer-aided, fractal-corrected measures of fibrosis in liver biopsies.

METHODS: Samples were derived from six to eight different parts of livers removed from 12 patients with clinically and histologically proven cirrhosis undergoing orthotopic liver transplantation. Sirius red-stained sections with a thickness of 2 μm were digitized using a computer-aided image analysis system that automatically measures the surface of fibrosis, as well as its outline perimeter, fractal surface and outline dimensions, wrinkledness, and Hurst coefficient.

RESULTS: We found a high degree of inter-sample variability in the measurements of the surface [coefficient of variation (CV) = 43% ± 13%] and wrinkledness (CV = 28% ± 9%) of fibrosis, but the inter-sample variability of Hurst’s exponent was low (CV = 14% ± 2%).

CONCLUSION: This study suggests that Hurst’s exponent might be used in clinical practice as the best histological estimate of fibrosis in the whole organ, and evidences the fact that biopsy sections, which are fundamental for the qualitative diagnosis of chronic hepatitis, play a key role in the quantitative estimate of architectural changes in liver tissue.