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

Diagnostic performance of quantitative ultrasonography for hepatic steatosis in a health screening program: a prospective single-center study

PURPOSE

This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF) as the reference standard.

METHODS

This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses.

RESULTS

TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710).

CONCLUSION

QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

Methodology exploration and reproducibility evaluation of TAI and TSI for quantitative ultrasound assessment of hepatic steatosis

Background and aim

New quantitative ultrasound techniques can be used to quantify hepatic steatosis, including tissue attenuation imaging (TAI), tissue scatter -distribution imaging (TSI), and the hepatorenal index (HRI). However, the measurement norms and the effects of fasting on these measurements remain unclear. The present study performed a methodological exploration and investigated the reliability of these measurements.

Methods

In total, 103 participants were prospectively recruited for ultrasonography and magnetic resonance imaging (MRI) scans. For the TAI and TSI data, the upper (2 cm), middle (4 cm) and lower (6 cm) areas determined according to the depth of the region of interest from the liver capsule, were sampled three times. Correlation analyses were performed to compare the measurements of TAI, TSI, and HRI with the controlled attenuation parameter (CAP) or MRI-proton density fat fraction (MRI-PDFF). Intra- and inter-operator repeatability was assessed using intraclass correlation coefficients. The effects of fasting on these measurements were then compared.

Results

The TAI and TSI measurements obtained from the upper and middle depths exhibited stronger correlations with the CAP measurements than those obtained from the lower depth. Specifically, the mean TAI had a significant positive correlation with MRI-PDFF (r = 0.753, P < 0.0001). TAI and TSI measurements exhibited excellent intra- (0.933 and 0.925, respectively) and inter- (0.896 and 0.766, respectively) examiner reliability. However, the correlation between HRI and CAP measurements was only 0.281, with no significant correlation with MRI-PDFF, and intra- and inter-examiner reproducibility of 0.458 and 0.343, respectively. Fasting did not affect these measurements.

Conclusions

TAI and TSI measurements demonstrated good intra- and interobserver reliability and correlated well with CAP and MRI-PDFF measurements. However, in practice-based clinical applications, the sampling depth should be controlled within 2-4 cm of the hepatic capsule; no fasting is required before the examination.

Reliability and stability of ultrasound-guided attenuation parameter in evaluating hepatic steatosis

PURPOSE

This study aimed to explore the reliability and stability of ultrasound-guided attenuation parameter (UGAP) values obtained by two measuring methods and different measuring times.

METHODS

Patients who underwent liver UGAP examinations in our hospital from September 2022 to December 2022 were retrospectively analyzed. The clinical data and UGAP measurements results were collected. Two different measuring methods: static single-frame multi-point measuring and dynamic multi-frame single-point measuring, were performed for each patient, and 10 UGAP values of each measuring method were recorded. The medians of the UGAP values of the 1st-3rd, 1st-5th, 1st-7th and 1st-10th by each measuring method were taken as the final UGAP values of measuring 3, 5, 7 and 10 times. The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 or 10 times) were compared.

RESULTS

206 patients were included in this study. There was no statistical difference between UGAP values measured by static single-frame multi-point measuring and dynamic multi-frame single-point measuring (P = 0.689, P = 0.270, P = 0.298, P = 0.091), regardless of measuring times (3, 5, 7, 10 times). No significant difference between the UGAP values obtained by 3, 5, 7 and 10 measurements was found (P = 0.554, P = 0.916).

CONCLUSION

The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 and 10 times) are stable and reliable. Additionally, 3 times of UGAP measurements might be enough for each patient in clinical practice.

A prospective comparison of three ultrasound-based techniques in quantitative diagnosis of hepatic steatosis in NAFLD

PURPOSE

To investigate the correlation between different ultrasound attenuation-based techniques and to compare their diagnostic performances using proton magnetic resonance spectroscopy (1H-MRS) as a reference standard.

METHODS

Participants who had clinical suspicion of nonalcoholic fatty liver disease (NAFLD) were prospectively recruited. Each subject had ultrasound with attenuation imaging (ATI) or quantitative ultrasound including tissue attenuation imaging (TAI) and tissue scatter-distribution imaging (TSI), and controlled-attenuation parameter (CAP) and 1H-MRS if available. The technical success rates, intra-observer repeatabilities of attenuation and backscattering coefficient were evaluated. ATI, TAI and CAP were three attenuation-based techniques. Spearman coefficient was used to test correlations among them and 1H-MRS. In addition, the diagnostic performances of these parameters for detecting ≥ 5% or 10% hepatic steatosis were evaluated.

RESULTS

130 participants had ultrasound scanning. Among them, 67 had CAP and 48 had 1H-MRS. The technical success rates were all 100%. The intra-observer repeatabilities of them were also excellent (ICCs > 0.90) and AC-ATI correlated well with AC-TAI (r = 0.752). AC-ATI, AC-TAI showed moderate correlation with CAP, (rATI = 0.623, 95% CI 0.446-0.752, P < 0.001; rTAI = 0.573, 95% CI 0.377-0.720, P < 0.001). For correlation with 1H-MRS, ATI and TAI performed better than CAP(rATI = 0.587; rTAI = 0.712; r CAP = 0.485). The AUCs of ATI, TAI, TSI and CAP for detecting ≥ 5% hepatic steatosis were 0.883, 0.862, 0.870 and 0.868, respectively. The AUC improved to 0.907 when TAI and TSI were combined (P < 0.05). When detecting ≥ 10% hepatic steatosis, the AUCs were 0.855, 0.702, 0.822 and 0.838, respectively.

CONCLUSION

Different ultrasound attenuation-based techniques were well correlated and exhibited good diagnostic performances in quantitative diagnosis of hepatic steatosis, however, the threshold values were different. Combinations of multiple parameters may improve the diagnostic performance in detecting hepatic steatosis.

TRIAL REGISTRATION

The study has been registered online ( https://www.chictr.org.cn ; unique identifier: ChiCTR2300069459).

Ultrasound tissue scatterer distribution imaging: An adjunctive diagnostic tool for shear wave elastography in characterizing focal liver lesions

OBJECTIVES

Focal liver lesion (FLL) is a prevalent finding in cross-sectional imaging, and distinguishing between benign and malignant FLLs is crucial for liver health management. While shear wave elastography (SWE) serves as a conventional quantitative ultrasound tool for evaluating FLLs, ultrasound tissue scatterer distribution imaging (TSI) emerges as a novel technique, employing the Nakagami statistical distribution parameter to estimate backscattered statistics for tissue characterization. In this prospective study, we explored the potential of TSI in characterizing FLLs and evaluated its diagnostic efficacy with that of SWE.

METHODS

A total of 235 participants (265 FLLs; the study group) were enrolled to undergo abdominal examinations, which included data acquisition from B-mode, SWE, and raw radiofrequency data for TSI construction. The area under the receiver operating characteristic curve (AUROC) was used to evaluate performance. A dataset of 20 patients (20 FLLs; the validation group) was additionally acquired to further evaluate the efficacy of the TSI cutoff value in FLL characterization.

RESULTS

In the study group, our findings revealed that while SWE achieved a success rate of 49.43 % in FLL measurements, TSI boasted a success rate of 100 %. In cases where SWE was effectively implemented, the AUROCs for characterizing FLLs using SWE and TSI stood at 0.84 and 0.83, respectively. For instances where SWE imaging failed, TSI achieved an AUROC of 0.78. Considering all cases, TSI presented an overall AUROC of 0.81. There was no statistically significant difference in AUROC values between TSI and SWE (p > 0.05). In the validation group, using a TSI cutoff value of 0.67, the AUROC for characterizing FLLs was 0.80.

CONCLUSIONS

In conclusion, ultrasound TSI holds promise as a supplementary diagnostic tool to SWE for characterizing FLLs.

The Calculation and Evaluation of an Ultrasound-Estimated Fat Fraction in Non-Alcoholic Fatty Liver Disease and Metabolic-Associated Fatty Liver Disease

We aimed to develop a non-linear regression model that could predict the fat fraction of the liver (UEFF), similar to magnetic resonance imaging proton density fat fraction (MRI-PDFF), based on quantitative ultrasound (QUS) parameters. We measured and retrospectively collected the ultrasound attenuation coefficient (AC), backscatter-distribution coefficient (BSC-D), and liver stiffness (LS) using shear wave elastography (SWE) in 90 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD), and 51 patients with clinically suspected metabolic-associated fatty liver disease (MAFLD). The MRI-PDFF was also measured in all patients within a month of the ultrasound scan. In the linear regression analysis, only AC and BSC-D showed a significant association with MRI-PDFF. Therefore, we developed prediction models using non-linear least squares analysis to estimate MRI-PDFF based on the AC and BSC-D parameters. We fitted the models on the NAFLD dataset and evaluated their performance in three-fold cross-validation repeated five times. We decided to use the model based on both parameters to calculate UEFF. The correlation between UEFF and MRI-PDFF was strong in NAFLD and very strong in MAFLD. According to a receiver operating characteristics (ROC) analysis, UEFF could differentiate between <5% vs. ≥5% and <10% vs. ≥10% MRI-PDFF steatosis with excellent, 0.97 and 0.91 area under the curve (AUC), accuracy in the NAFLD and with AUCs of 0.99 and 0.96 in the MAFLD groups. In conclusion, UEFF calculated from QUS parameters is an accurate method to quantify liver fat fraction and to diagnose ≥5% and ≥10% steatosis in both NAFLD and MAFLD. Therefore, UEFF can be an ideal non-invasive screening tool for patients with NAFLD and MAFLD risk factors.

Development and validation of multivariable quantitative ultrasound for diagnosing hepatic steatosis

This study developed and validated multivariable quantitative ultrasound (QUS) model for diagnosing hepatic steatosis. Retrospective secondary analysis of prospectively collected QUS data was performed. Participants underwent QUS examinations and magnetic resonance imaging proton density fat fraction (MRI-PDFF; reference standard). A multivariable regression model for estimating hepatic fat fraction was determined using two QUS parameters from one tertiary hospital (development set). Correlation between QUS-derived estimated fat fraction(USFF) and MRI-PDFF and diagnostic performance of USFF for hepatic steatosis (MRI-PDFF ≥ 5%) were assessed, and validated in an independent data set from the other health screening center(validation set). Development set included 173 participants with suspected NAFLD with 126 (72.8%) having hepatic steatosis; and validation set included 452 health screening participants with 237 (52.4%) having hepatic steatosis. USFF was correlated with MRI-PDFF (Pearson r = 0.799 and 0.824; development and validation set). The model demonstrated high diagnostic performance, with areas under the receiver operating characteristic curves of 0.943 and 0.924 for development and validation set, respectively. Using cutoff of 6.0% from development set, USFF showed sensitivity, specificity, positive predictive value, and negative predictive value of 87.8%, 78.6%, 81.9%, and 85.4% for diagnosing hepatic steatosis in validation set. In conclusion, multivariable QUS parameters-derived estimated fat fraction showed high diagnostic performance for detecting hepatic steatosis.

US Quantification of Liver Fat: Past, Present, and Future

Fatty liver disease has a high and increasing prevalence worldwide, is associated with adverse cardiovascular events and higher long-term medical costs, and may lead to liver-related morbidity and mortality. There is an urgent need for accurate, reproducible, accessible, and noninvasive techniques appropriate for detecting and quantifying liver fat in the general population and for monitoring treatment response in at-risk patients. CT may play a potential role in opportunistic screening, and MRI proton-density fat fraction provides high accuracy for liver fat quantification; however, these imaging modalities may not be suited for widespread screening and surveillance, given the high global prevalence. US, a safe and widely available modality, is well positioned as a screening and surveillance tool. Although well-established qualitative signs of liver fat perform well in moderate and severe steatosis, these signs are less reliable for grading mild steatosis and are likely unreliable for detecting subtle changes over time. New and emerging quantitative biomarkers of liver fat, such as those based on standardized measurements of attenuation, backscatter, and speed of sound, hold promise. Evolving techniques such as multiparametric modeling, radiofrequency envelope analysis, and artificial intelligence-based tools are also on the horizon. The authors discuss the societal impact of fatty liver disease, summarize the current state of liver fat quantification with CT and MRI, and describe past, currently available, and potential future US-based techniques for evaluating liver fat. For each US-based technique, they describe the concept, measurement method, advantages, and limitations. © RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

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.

Interobserver Variability in Ultrasound-Based Liver Fat Quantification

OBJECTIVES

To assess interobserver variability in ultrasound-based quantitative liver fat content measurements and to determine how much time these quantitative ultrasound (QUS) techniques require.

METHODS

One hundred patients with known or suspected of having nonalcoholic fatty liver disease were included in this prospective study. Two observers who were blinded to each other measurements performed tissue attenuation imaging (TAI) and tissue scatter distribution imaging (TSI) techniques independently. Both observers assessed hepatic steatosis visually and obtained 5 measurements for each QUS technique and the median values of the measurements were recorded. Spearman's correlation test was used to assess the correlation between QUS measurements and visual hepatic stetaosis grades. Intraclass correlation coefficient (ICC) test was used to assess interobserver variability in QUS measurements.

RESULTS

The median values of TAI measurements for the observers 1 and 2 were 0.75 and 0.74 dB/cm/MHz, respectively. The median values of TSI measurements for the observers 1 and 2 were 93.53 and 92.58, respectively. The interobserver agreement in TAI (ICC: 0.970) and TSI (ICC: 0.938) measurements were excellent. The mean of the required time period for TAI technique were 55.1 ± 7.8 and 59.9 ± 6.6 seconds for the observers 1 and 2, respectively. The mean of the required time period for TSI technique were 49.1 ± 5.8 and 54.1 ± 5.4 seconds for the observers 1 and 2, respectively.

CONCLUSION

The current study revealed that both TAI and TSI techniques are highly reproducible and can be implemented into daily practice with little additional time requirement.

Two-dimensional Convolutional Neural Network Using Quantitative US for Noninvasive Assessment of Hepatic Steatosis in NAFLD

Background Quantitative US (QUS) using radiofrequency data analysis has been recently introduced for noninvasive evaluation of hepatic steatosis. Deep learning algorithms may improve the diagnostic performance of QUS for hepatic steatosis. Purpose To evaluate a two-dimensional (2D) convolutional neural network (CNN) algorithm using QUS parametric maps and B-mode images for diagnosis of hepatic steatosis, with the MRI-derived proton density fat fraction (PDFF) as the reference standard, in patients with nonalcoholic fatty liver disease (NAFLD). Materials and Methods: Consecutive adult participants with suspected NAFLD were prospectively enrolled at a single academic medical center from July 2020 to June 2021. Using radiofrequency data analysis, two QUS parameters (tissue attenuation imaging [TAI] and tissue scatter-distribution imaging [TSI]) were measured. On B-mode images, hepatic steatosis was graded using visual scoring (none, mild, moderate, or severe). Using B-mode images and two QUS parametric maps (TAI and TSI) as input data, the algorithm estimated the US fat fraction (USFF) as a percentage. The correlation between the USFF and MRI PDFF was evaluated using the Pearson correlation coefficient. The diagnostic performance of the USFF for hepatic steatosis (MRI PDFF ≥5%) was evaluated using receiver operating characteristic curve analysis and compared with that of TAI, TSI, and visual scoring. Results Overall, 173 participants (mean age, 51 years ± 14 [SD]; 96 men) were included, with 126 (73%) having hepatic steatosis (MRI PDFF ≥5%). USFF correlated strongly with MRI PDFF (Pearson r = 0.86, 95% CI: 0.82, 0.90; P < .001). For diagnosing hepatic steatosis (MRI PDFF ≥5%), the USFF yielded an area under the receiver operating characteristic curve of 0.97 (95% CI: 0.93, 0.99), higher than those of TAI, TSI, and visual scoring (P = .015, .006, and < .001, respectively), with a sensitivity of 90% (95% CI: 84, 95 [114 of 126]) and a specificity of 91% (95% CI: 80, 98 [43 of 47]) at a cutoff value of 5.7%. Conclusion A deep learning algorithm using quantitative US parametric maps and B-mode images accurately estimated the hepatic fat fraction and diagnosed hepatic steatosis in participants with nonalcoholic fatty liver disease. ClinicalTrials.gov registration nos. NCT04462562, NCT04180631 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sidhu and Fang in this issue.

US Backscatter for Liver Fat Quantification: An AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative

Nonalcoholic fatty liver disease (NAFLD) is believed to affect one-third of American adults. Noninvasive methods that enable detection and monitoring of NAFLD have the potential for great public health benefits. Because of its low cost, portability, and noninvasiveness, US is an attractive alternative to both biopsy and MRI in the assessment of liver steatosis. NAFLD is qualitatively associated with enhanced B-mode US echogenicity, but visual measures of B-mode echogenicity are negatively affected by interobserver variability. Alternatively, quantitative backscatter parameters, including the hepatorenal index and backscatter coefficient, are being investigated with the goal of improving US-based characterization of NAFLD. The American Institute of Ultrasound in Medicine and Radiological Society of North America Quantitative Imaging Biomarkers Alliance are working to standardize US acquisition protocols and data analysis methods to improve the diagnostic performance of the backscatter coefficient in liver fat assessment. This review article explains the science and clinical evidence underlying backscatter for liver fat assessment. Recommendations for data collection are discussed, with the aim of minimizing potential confounding effects associated with technical and biologic variables.

Ultrasound-Based Diagnostic Methods: Possible Use in Fatty Liver Disease Area

Liver steatosis is a chronic liver disease that is becoming one of the most important global health problems, due to its direct connection with metabolic syndrome, its significant impact on patients' socioeconomic status and frailty, and the occurrence of advanced chronic liver disease. In recent years, there has been rapid technological progress in the ultrasound-based diagnostics field that can help us to quantitatively assess liver steatosis, including continuous attenuation parameters in A and B ultrasound modes, backscatter coefficients (e.g., speed of sound) and ultrasound envelope statistic parametric imaging. The methods used in this field are widely available, have favorable time and financial profiles, and are well accepted by patients. Less is known about their reliability in defining the presence and degree of liver steatosis. Numerous study reports have shown the methods' favorable negative and positive predictive values in comparison with reference investigations (liver biopsy and MRI). Important research has also evaluated the role of these methods in diagnosing and monitoring non-alcoholic fatty liver disease (NAFLD). Since NAFLD is becoming the dominant global cause of liver cirrhosis, and due to the close but complex interplay of liver steatosis with the coexistence of liver fibrosis, knowledge regarding NAFLD's influence on the progression of liver fibrosis is of crucial importance. Study findings, therefore, indicate the possibility of using these same diagnostic methods to evaluate the impact of NAFLD on the patient's liver fibrosis progression risk, metabolic risk factors, cardiovascular complications, and the occurrence of hepatocellular carcinoma. The mentioned areas are particularly important in light of the fact that most of the known chronic liver disease etiologies are increasingly intertwined with the simultaneous presence of NAFLD.

Comparative Study of Raw Ultrasound Data Representations in Deep Learning to Classify Hepatic Steatosis

Adiposity accumulation in the liver is an early-stage indicator of non-alcoholic fatty liver disease. Analysis of ultrasound (US) backscatter echoes from liver parenchyma with deep learning (DL) may offer an affordable alternative for hepatic steatosis staging. The aim of this work was to compare DL classification scores for liver steatosis using different data representations constructed from raw US data. Steatosis in N = 31 patients with confirmed or suspected non-alcoholic fatty liver disease was stratified based on fat-fraction cutoff values using magnetic resonance imaging as a reference standard. US radiofrequency (RF) frames (raw data) and clinical B-mode images were acquired. Intermediate image formation stages were modeled from RF data. Power spectrum representations and phase representations were also calculated. Co-registered patches were used to independently train 1-, 2- and 3-D convolutional neural networks (CNNs), and classifications scores were compared with cross-validation. There were 67,800 patches available for 2-D/3-D classification and 1,830,600 patches for 1-D classification. The results were also compared with radiologist B-mode annotations and quantitative ultrasound (QUS) metrics. Patch classification scores (area under the receiver operating characteristic curve [AUROC]) revealed significant reductions along successive stages of the image formation process (p &lt; 0.001). Patient AUROCs were 0.994 for RF data and 0.938 for clinical B-mode images. For all image formation stages, 2-D CNNs revealed higher patch and patient AUROCs than 1-D CNNs. CNNs trained with power spectrum representations converged faster than those trained with RF data. Phase information, which is usually discarded in the image formation process, provided a patient AUROC of 0.988. DL models trained with RF and power spectrum data (AUROC = 0.998) provided higher scores than conventional QUS metrics and multiparametric combinations thereof (AUROC = 0.986). Radiologist annotations indicated lower hepatic steatosis classification accuracies (Acc = 0.914) with respect to magnetic resonance imaging proton density fat fraction that DL models (Acc = 0.989). Access to raw ultrasound data combined with artificial intelligence techniques may offer superior opportunities for quantitative tissue diagnostics than conventional sonographic images.

Ultrasound Methods for the Assessment of Liver Steatosis: A Critical Appraisal

The prevalence of the non-alcoholic fatty liver disease has reached major proportions, being estimated to affect one-quarter of the global population. The reference techniques, which include liver biopsy and the magnetic resonance imaging proton density fat fraction, have objective practical and financial limitations to their routine use in the detection and quantification of liver steatosis. Therefore, there has been a rising necessity for the development of new inexpensive, widely applicable and reliable non-invasive diagnostic tools. The controlled attenuation parameter has been considered the point-of-care technique for the assessment of liver steatosis for a long period of time. Recently, many ultrasound (US) system manufacturers have developed proprietary software solutions for the quantification of liver steatosis. Some of these methods have already been extensively tested with very good performance results reported, while others are still under evaluation. This manuscript reviews the currently available US-based methods for diagnosing and grading liver steatosis, including their classification and performance results, with an appraisal of the importance of this armamentarium in daily clinical practice.

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.

Clinical evaluation of grayscale and linear scale hepatorenal indices for fatty liver quantification: a prospective study of a native Chinese population

BACKGROUND AND AIMS

Hepato-renal index (HRI) has been investigated extensively in various clinical studies. New linear scale HRI (LS-HRI) is proposed as an alternative to conventional grayscale HRI (GS-HRI) that suffers from lack of a widely accepted cut-off value for differentiation of fatty from normal livers. To investigate the diagnostic performance of conventional GS-HRI and new LS-HRI for a relatively large Chinese population with NAFLD using a well-established ultrasonographic fatty liver indicator (US-FLI) as the reference standard for steatosis grades.

MATERIALS AND METHODS

A total of 106 patients with various stages of NAFLD were prospectively enrolled. All ultrasound images for these patients were first acquired by a highly experienced ultrasound doctor and their US-FLI scores then obtained by the same doctor. Both GS-HRI and LS-HRI values were measured off-line by two additional ultrasound doctors. Four steatosis grades were determined from US-FLI scores for steatosis detection and staging.

RESULTS

Inter-observer agreements for both GS-HRI and LS-HRI were excellent with the respective concordance correlation coefficient (CCC) of 0.900 for GS-HRI and 0.822 for LS-HRI. A linear correlation to US-FLI for LS-HRI (R = 0.74) was substantially superior to that for GS-HRI (R = 0.46). LS-HRI had a sensitivity of 85.9% and a specificity of 96.3% to differentiate steatosis from the normal liver (AUROC: 95.5%) while GS-HRI had a sensitivity of 85.9% and a specificity of 92.6% to distinguish steatosis from the normal liver (AUROC: 94.7%).

CONCLUSIONS

Both GS-HRI and LS-HRI measurements are reproducible between two ultrasonographic clinicians and are evidently effective for steatosis detection.

Ultrasound biomicroscopy for the assessment of early-stage nonalcoholic fatty liver disease induced in rats by a high-fat diet

PURPOSE

The aim of this study was to assess the ability of ultrasound biomicroscopy (UBM) to diagnose the initial stages of nonalcoholic fatty liver disease (NAFLD) in a rat model.

METHODS

Eighteen male Wistar rats were allocated to control or experimental groups. A high-fat diet (HFD) with 20% fructose and 2% cholesterol, resembling a common Western diet, was fed to animals in the experimental groups for up to 16 weeks; those in the control group received a regular diet. A 21 MHz UBM system was used to acquire B-mode images at specific times: baseline (T0), 10 weeks (T10), and 16 weeks (T16). The sonographic hepatorenal index (SHRI), based on the average ultrasound image gray-level intensities from the liver parenchyma and right renal cortex, was determined at T0, T10, and T16. The liver specimen histology was classified using the modified Nonalcoholic Steatohepatitis Clinical Research Network NAFLD activity scoring system.

RESULTS

The livers in the animals in the experimental groups progressed from sinusoidal congestion and moderate macro- and micro-vesicular steatosis to moderate steatosis and frequent hepatocyte ballooning. The SHRI obtained in the experimental group animals at T10 and T16 was significantly different from the SHRI of pooled control group. No significant difference existed between the SHRI in animals receiving HFD between T10 and T16.

CONCLUSION

SHRI measurement using UBM may be a promising noninvasive tool to characterize early-stage NAFLD in rat models.

US Attenuation for Liver Fat Quantification: An AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an estimated prevalence of up to 30% in the general population and higher in people with type 2 diabetes. The assessment of liver fat content is essential to help identify patients with or who are at risk for NAFLD and to follow their disease over time. The American Institute of Ultrasound in Medicine-RSNA Quantitative Imaging Biomarkers Alliance Pulse-Echo Quantitative Ultrasound Initiative was formed to help develop and standardize acquisition protocols and to better understand confounding factors of US-based fat quantification. The three quantitative US parameters explored by the initiative are attenuation, backscatter coefficient, and speed of sound. The purpose of this review is to present the current state of attenuation imaging for fat quantification and to provide expert opinion on examination performance and interpretation. US attenuation methods that need further study are outlined.

Quantitative Evaluation of Hepatic Steatosis Using Advanced Imaging Techniques: Focusing on New Quantitative Ultrasound Techniques

Nonalcoholic fatty liver disease, characterized by excessive accumulation of fat in the liver, is the most common chronic liver disease worldwide. The current standard for the detection of hepatic steatosis is liver biopsy; however, it is limited by invasiveness and sampling errors. Accordingly, MR spectroscopy and proton density fat fraction obtained with MRI have been accepted as non-invasive modalities for quantifying hepatic steatosis. Recently, various quantitative ultrasonography techniques have been developed and validated for the quantification of hepatic steatosis. These techniques measure various acoustic parameters, including attenuation coefficient, backscatter coefficient and speckle statistics, speed of sound, and shear wave elastography metrics. In this article, we introduce several representative quantitative ultrasonography techniques and their diagnostic value for the detection of hepatic steatosis.

Quantitative ultrasound imaging of soft biological tissues: a primer for radiologists and medical physicists

Quantitative ultrasound (QUS) aims at quantifying interactions between ultrasound and biological tissues. QUS techniques extract fundamental physical properties of tissues based on interactions between ultrasound waves and tissue microstructure. These techniques provide quantitative information on sub-resolution properties that are not visible on grayscale (B-mode) imaging. Quantitative data may be represented either as a global measurement or as parametric maps overlaid on B-mode images. Recently, major ultrasound manufacturers have released speed of sound, attenuation, and backscatter packages for tissue characterization and imaging. Established and emerging clinical applications are currently limited and include liver fibrosis staging, liver steatosis grading, and breast cancer characterization. On the other hand, most biological tissues have been studied using experimental QUS methods, and quantitative datasets are available in the literature. This educational review addresses the general topic of biological soft tissue characterization using QUS, with a focus on disseminating technical concepts for clinicians and specialized QUS materials for medical physicists. Advanced but simplified technical descriptions are also provided in separate subsections identified as such. To understand QUS methods, this article reviews types of ultrasound waves, basic concepts of ultrasound wave propagation, ultrasound image formation, point spread function, constructive and destructive wave interferences, radiofrequency data processing, and a summary of different imaging modes. For each major QUS technique, topics include: concept, illustrations, clinical examples, pitfalls, and future directions.

Noninvasive Assessment of Hepatitis C Virus Infected Patients Using Vibration-Controlled Transient Elastography

Chronic infection with hepatitis C virus (HCV) is one of the leading causes of cirrhosis and hepatocellular carcinoma (HCC). Surveillance of these patients is an essential strategy in the prevention chain, including in the pre/post-antiviral treatment states. Ultrasound elastography techniques are emerging as key methods in the assessment of liver diseases, with a number of advantages such as their rapid, noninvasive, and cost-effective characters. The present paper critically reviews the performance of vibration-controlled transient elastography (VCTE) in the assessment of HCV patients. VCTE measures liver stiffness (LS) and the ultrasonic attenuation through the embedded controlled attenuation parameter (CAP), providing the clinician with a tool for assessing fibrosis, cirrhosis, and steatosis in a noninvasive manner. Moreover, standardized LS values enable proper staging of the underlying fibrosis, leading to an accurate identification of a subset of HCV patients that present a high risk for complications. In addition, VCTE is a valuable technique in evaluating liver fibrosis prior to HCV therapy. However, its applicability in monitoring fibrosis regression after HCV eradication is currently limited and further studies should focus on extending the boundaries of VCTE in this context. From a different perspective, VCTE may be effective in identifying clinically significant portal hypertension (CSPH). An emerging prospect of clinical significance that warrants further study is the identification of esophageal varices. Our opinion is that the advantages of VCTE currently outweigh those of other surveillance methods.

Ultrasound Elastography-Cornerstone of Non-Invasive Metabolic Dysfunction-Associated Fatty Liver Disease Assessment

Metabolic dysfunction-associated fatty liver disease has become the most common chronic liver disease as well as the most common cause for liver transplantation. With its different methods types, elastography of the liver can be used for non-invasive evaluation of the liver fibrosis and steatosis degree. The article focuses on the description, use, advantages, and limitations of the currently known elastographic techniques. It proposes a simple risk assessment algorithm for the liver fibrosis progress evaluation. The following is an overview of the use of liver and spleen elastography in the detection of clinically relevant portal hypertension. It concludes with research and technological possibilities that could be important to the field in the upcoming years.

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.