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Excessive liver fat (steatosis) is now the most common cause of chronic liver disease worldwide and is an independent risk factor for cirrhosis and associated complications. Accurate and clinically useful diagnosis, risk stratification, prognostication, and therapy monitoring require accurate and reliable biomarker measurement at acceptable cost. This article describes a joint effort by the American Institute of Ultrasound in Medicine (AIUM) and the RSNA Quantitative Imaging Biomarkers Alliance (QIBA) to develop standards for clinical and technical validation of quantitative biomarkers for liver steatosis. The AIUM Liver Fat Quantification Task Force provides clinical guidance, while the RSNA QIBA Pulse-Echo Quantitative Ultrasound Biomarker Committee develops methods to measure biomarkers and reduce biomarker variability. In this article, the authors present the clinical need for quantitative imaging biomarkers of liver steatosis, review the current state of various imaging modalities, and describe the technical state of the art for three key liver steatosis pulse-echo quantitative US biomarkers: attenuation coefficient, backscatter coefficient, and speed of sound. Lastly, a perspective on current challenges and recommendations for clinical translation for each biomarker is offered.

Post-operative urinary retention is a medical condition where patients cannot urinate despite having a full bladder. Ultrasound imaging of the bladder is intermittently used to estimate urine volume for early diagnosis and management of urine retention. Moreover, the use of bladder ultrasound can reduce the need for an indwelling urinary catheter and the risk of catheter-associated urinary tract infection. Wearable ultrasound devices combined with machine-learning based bladder volume estimation algorithms reduce the burdens of nurses in hospital settings and improve outpatient care. However, existing algorithms are memory and computation intensive, thereby demanding the use of expensive GPUs. In this paper, we develop and validate a low-compute memory-efficient deep learning model for accurate bladder region segmentation and urine volume calculation. B-mode ultrasound bladder images of 360 patients were divided into training and validation sets; another 74 patients were used as the test dataset. Our 1-bit quantized models with 4-bits and 6-bits skip connections achieved an accuracy within 3.8% and 2.6%, respectively, of a full precision state-of-the-art neural network (NN) without any floating-point operations and with an 11.5× and 9.0× reduction in memory requirements to fit under 150 kB. The means and standard deviations of the volume estimation errors, relative to estimates from ground-truth clinician annotations, were 5.0±33 ml and 6.8±29 ml, respectively. This lightweight NN can be easily integrated on the wearable ultrasound device for automated and continuous monitoring of urine volume. Our approach can potentially be extended to other clinical applications such as monitoring blood pressure and fetal heart rate.

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Nonalcoholic fatty liver disease (NAFLD) affects 30% of adults in the United States and is characterized by accumulation of excess triglycerides in the liver (Younossi et al. 2016). NAFLD is also a common problem worldwide, affecting an estimated 1 billion or more people (Loomba et al, 2018). NAFLD can present as simple hepatic steatosis (i.e., nonalcoholic fatty liver (NAFL)), or as nonalcoholic steatohepatitis (NASH); the more advanced subtype, where inflammation, fibrosis, and histologic evidence of hepatocyte injury [e.g., ballooning] can be present. NASH, especially in those who have developed stage 2 or 3 fibrosis, can progress to cirrhosis, end-stage liver disease, liver transplantation, hepatocellular carcinoma, and death (Tong et al, 2022). The identification of patients with NASH and who are at risk for progression to cirrhosis and clinically meaningful adverse outcomes, and the development of effective therapies for these patients are public health priorities. NAFL is asymptomatic, and NASH is asymptomatic until advanced disease is present; these conditions cannot be readily diagnosed, or distinguished from each other clinically, or by routine laboratory testing. Diagnosis and staging of NASH therefore currently rely on liver biopsy with histologic assessment. However, liver biopsy is invasive and painful, and it carries a non-zero risk of catastrophic complication, including death. Further, histologic evaluation of liver biopsy is limited by moderate accuracy, sampling variability due to the small amount of material gathered for examination relative to the size of, and histologic diversity within the liver, and interpretation variability. Although biopsy is being used as the reference standard for diagnosis and staging of NASH in drug development clinical trials, and clinically, it has imperfect accuracy and precision. There is widely-recognized need to aid, improve, or augment liver biopsy acquisition and interpretation, or to develop non-invasive biomarkers to replace liver biopsy, or both. Ultrasound shear wave elastography (SWE) is an imaging based method to assess liver stiffness, a known surrogate marker for liver fibrosis. This imaging technology has emerged recently, but is now widely available clinically. However, there is a critical lack of consensus on diagnostic thresholds which vary widely based on hardware, context of use, and fibrosis level. The primary goal of this review is to synthesize the existing literature on ultrasound shear wave elastography and provide optimal thresholds for the diagnosis of clinically significant liver fibrosis (stage ≥ F2) and at-risk NASH via meta-analysis. SWE is a subset of ultrasound elastography imaging techniques, of which there are four. Strain elastography is a semi-quantitative elastographic technique that generates a relative tissue stiffness map. As this is non-quantitative, it will not be considered for this review. Vibration controlled transient elastography (VCTE), also known as Fibroscan, uses a vibrating probe tip to generate shear waves and ultrasound to measure tissue stiffness. This device does not generate traditional B-mode ultrasound images, is primarily used in gastroenterology clinics, and will not be included in this review. 2D-SWE and point-SWE are the two SWE techniques; they utilize an acoustic radiation force impulse (ARFI), a focused ultrasound pulse, to generate shear waves and high resolution B-mode imaging to estimate liver stiffness. This technology is deployed within radiology imaging centers and is often performed in conjunction with diagnostic ultrasound imaging. The test output is an estimate of liver stiffness reported in kPa (representing Young’s modulus) or m/s (representing shear wave speed). These values are interconvertible algebraically. Determining the diagnostic threshold for these two SWE techniques will be the focus of this review.

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide, and prevalence of NAFLD is increasing owing to upward trends of obesity and diabetes (24042449). Nonalcoholic steatohepatitis (NASH) is an advanced stage of NAFLD with a higher risk of progression to complications related to cirrhosis, is currently the second most common indication for liver transplantation in the United States, and is expected to become the leading cause in the near future (24768810, 25461851, 25920090). Despite the large societal burden of NASH, there is no safe, effective medication approved by the United States Food and Drug Administration (FDA) (27646933). Most clinical trials for NASH require as an eligibility criterion the presence of ‘at-risk NASH’, defined as diagnosed NASH, NAFLD activity score (NAS) ≥ 4 and significant fibrosis (F≥2). The rationale is that these patients are at substantial risk for progression to complications of cirrhosis, and so might benefit from participating in NASH drug development clinical trials. By comparison, patients without NASH, with NAS ≤ 3, or with F

Elastography has emerged as a preferred non-invasive imaging technique for the clinical assessment of liver fibrosis. Elastography methods provide liver stiffness measurement (LSM) as a surrogate quantitative biomarker for fibrosis burden in chronic liver disease (CLD). Elastography can be performed either with ultrasound or MRI. Currently available ultrasound-based methods include strain elastography, two-dimensional shear wave elastography (2D-SWE), point shear wave elastography (pSWE), and vibration-controlled transient elastography (VCTE). MR Elastography (MRE) is widely available as two-dimensional gradient echo MRE (2D-GRE-MRE) technique. US-based methods provide estimated Young's modulus (eYM) and MRE provides magnitude of the complex shear modulus. MRE and ultrasound methods have proven to be accurate methods for detection of advanced liver fibrosis and cirrhosis. Other clinical applications of elastography include liver decompensation prediction, and differentiation of non-alcoholic steatohepatitis (NASH) from simple steatosis (SS). In this review, we briefly describe the different elastography methods, discuss current clinical applications, and provide an overview of advances in the field of liver elastography.

Steatosis is the most common cause of chronic liver disease worldwide. Ultrasound helps diagnose steatosis due to its wide availability, non-invasiveness, and safety. The hepatorenal index (HRI) is a clinically used biomarker for diagnosing steatosis. To study the automated calculation of HRI from ultrasound images, we identified a retrospective cohort undergoing abdominal ultrasound with 1320 images, one image per patient. The patients were divided into training (n=1166) and test (n=154) sets. The test set consists of 48 patients without steatosis (S0) and 106 patients with steatosis (S1-S3). An automated method was proposed to calculate HRI using four steps (a) segment the liver and the renal cortex, (b) remove pixels associated with ducts, vessels, masses, cysts, and shadowing artifacts, (c) place two regions of interest (ROIs), one each in the liver and the renal cortex, and (d) calculate the HRI as the ratio of the mean pixel value of the liver ROI to the renal cortex ROI. We explored several sets of rules for ROI placement. The method minimizing the Euclidean distance between the two ROIs, the best performer, had an area under the ROC (AUROC) curve of 0.87 compared to physicians with an AUROC of 0.82 (p=0.159). In addition, the Euclidean distance constraint showed no dependence on depth for ROI placement. The proposed automated method can be translated into clinical care without modifying existing imaging protocols to optimize the diagnostic capability of ultrasound for hepatic steatosis and assist with triaging patients.

OBJECTIVES—: To quantify the bias of shear wave speed (SWS) measurements between different commercial ultrasonic shear elasticity systems and a magnetic resonance elastography (MRE) system in elastic and viscoelastic phantoms. METHODS—: Two elastic phantoms, representing healthy through fibrotic liver, were measured with 5 different ultrasound platforms, and 3 viscoelastic phantoms, representing healthy through fibrotic liver tissue, were measured with 12 different ultrasound platforms. Measurements were performed with different systems at different sites, at 3 focal depths, and with different appraisers. The SWS bias across the systems was quantified as a function of the system, site, focal depth, and appraiser. A single MRE research system was also used to characterize these phantoms using discrete frequencies from 60 to 500 Hz. RESULTS—: The SWS from different systems had mean difference 95% confidence intervals of ±0.145 m/s (±9.6%) across both elastic phantoms and ± 0.340 m/s (±15.3%) across the viscoelastic phantoms. The focal depth and appraiser were less significant sources of SWS variability than the system and site. Magnetic resonance elastography best matched the ultrasonic SWS in the viscoelastic phantoms using a 140 Hz source but had a − 0.27 ± 0.027-m/s (−12.2% ± 1.2%) bias when using the clinically implemented 60-Hz vibration source. CONCLUSIONS—: Shear wave speed reconstruction across different manufacturer systems is more consistent in elastic than viscoelastic phantoms, with a mean difference bias of < ±10% in all cases. Magnetic resonance elastographic measurements in the elastic and viscoelastic phantoms best match the ultrasound systems with a 140-Hz excitation but have a significant negative bias operating at 60 Hz. This study establishes a foundation for meaningful comparison of SWS measurements made with different platforms.

Background Stiffness thresholds for liver MR elastography in children vary between studies and may differ from thresholds in adults. Normative liver stiffness data are needed to optimize diagnostic thresholds for children. Purpose To determine normal liver stiffness, and associated normal ranges for children, as measured with MR elastography across vendors and field strengths. Materials and Methods This was a prospective multicenter cohort study (ClinicalTrials.gov identifier: NCT03235414). Volunteers aged 7-17.9 years without a known history of liver disease were recruited at four sites for a research MRI and blood draw between February 2018 and October 2019. MRI was performed on three vendor platforms and at two field strengths (1.5 T and 3.0 T). All MRI scans were centrally analyzed; stiffness, proton density fat fraction (PDFF), and R2* values were expressed as means of means. Mean and 95% confidence intervals (CIs) for liver stiffness were calculated. Pearson correlation coefficient (r), two-sample t test, or analysis of variance was used to assess univariable associations. Results Seventy-one volunteers had complete data and no documented exclusion criterion (median age, 12 years; interquartile range [IQR], 10-15 years; 39 female participants). Median body mass index percentile was 54% (IQR, 32.5%-69.5%). Mean liver stiffness was 2.1 kPa (95% CI: 2.0, 2.2 kPa) with mean ± 1.96 kPa standard deviation of 1.5-2.8 kPa. Median liver PDFF was 2.0% (IQR, 1.7%-2.6%). There was no association between liver stiffness and any patient variable or MRI scanner factor. Conclusion Mean liver stiffness measured with MR elastography in children without liver disease was 2.1 kPa (similar to that in adults). The 95th percentile of normal liver stiffness was 2.8 kPa. Liver stiffness was independent of sex, age, or body mass index and did not vary with MRI scanner vendor or field strength. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Yin in this issue.

Objectives Thyroid shear wave elastography (SWE) has been shown to have advantages compared to biopsy or other imaging modalities in the evaluation of thyroid nodules. However, studies show variability in its assessment. The objective of this study was to evaluate whether stiffness measurements of the normal thyroid, as estimated by SWE, varied due to preload force or the pressure applied between the transducer and the patient. Methods In this study, a measurement system was attached to the ultrasound transducer to measure the applied load. Shear wave elastographic measurements were obtained from the left lobe of the thyroid at applied transducer forces between 2 and 10 N. A linear mixed-effects model was constructed to quantify the association between the preload force and stiffness while accounting for correlations between repeated measurements within each participant. The preload force effect on elasticity was modeled by both linear and quadratic terms to account for a possible nonlinear association between these variables. Results Nineteen healthy volunteers without known thyroid disease participated in the study. The participants had a mean age ± SD of 36 ± 8 years; 74% were female; 74% had a normal body mass index; and 95% were white non-Hispanic/Latino. The estimated elastographic value at a 2-N preload force was 16.7 kPa (95% confidence interval, 14.1-19.3 kPa), whereas the value at 10 N was 29.9 kPa (95% confidence interval, 24.9-34.9 kPa). Conclusions The preload force was significantly and nonlinearly associated with SWE estimates of thyroid stiffness. Quantitative standardization of preload forces in the assessment of thyroid nodules using elastography is an integral factor for improving the accuracy of thyroid nodule evaluation.

The purpose of this study was to develop an automated method for classifying liver fibrosis stage ≥F2 based on ultrasound shear wave elastography (SWE) and to assess the system's performance in comparison with a reference manual approach. The reference approach consists of manually selecting a region of interest from each of eight or more SWE images, computing the mean tissue stiffness within each of the regions of interest and computing a resulting stiffness value as the median of the means. The 527-subject database consisted of 5526 SWE images and pathologist-scored biopsies, with data collected from a single system at a single site. The automated method integrates three modules that assess SWE image quality, select a region of interest from each SWE measurement and perform machine learning-based, multi-image SWE classification for fibrosis stage ≥F2. Several classification methods were developed and tested using fivefold cross-validation with training, validation and test sets partitioned by subject. Performance metrics were area under receiver operating characteristic curve (AUROC), specificity at 95% sensitivity and number of SWE images required. The final automated method yielded an AUROC of 0.93 (95% confidence interval: 0.90–0.94) versus 0.69 (95% confidence interval: 0.65–0.72) for the reference method, 71% specificity with 95% sensitivity versus 5% and four images per decision versus eight or more. In conclusion, the automated method reported in this study significantly improved the accuracy for ≥F2 classification of SWE measurements as well as reduced the number of measurements needed, which has the potential to reduce clinical workflow.

Tissue stiffness has long been known to be a biomarker of tissue pathology. Ultrasound elastography measures tissue mechanical properties by monitoring the response of tissue to acoustic energy. Different elastographic techniques have been applied to many different tissues and diseases. Depending on the pathology, patient-based factors, and ultrasound operator-based factors, these techniques vary in accuracy and reliability. In this review, we discuss the physical principles of ultrasound elastography, discuss differences between different ultrasound elastographic techniques, and review the advantages and disadvantages of these techniques in clinical practice.

In this study, we evaluated the diagnostic accuracy of shear wave elastography (SWE) for differentiating high-risk non-alcoholic steatohepatitis (hrNASH) from non-alcoholic fatty liver and low-risk non-alcoholic steatohepatitis (NASH). Patients with non-alcoholic fatty liver disease scheduled for liver biopsy underwent pre-biopsy SWE. Ten SWE measurements were obtained. Biopsy samples were reviewed using the NASH Clinical Research Network Scoring System and patients with hrNASH were identified. Receiver operating characteristic curves for SWE-based hrNASH diagnosis were charted. One hundred sixteen adult patients underwent liver biopsy at our institution for the evaluation of non-alcoholic fatty liver disease. The area under the receiver operating characteristic curve of SWE for hrNASH diagnosis was 0.73 (95% confidence interval: 0.61-0.84, p < 0.001). The Youden index-based optimal stiffness cutoff value for hrNASH diagnosis was calculated as 8.4 kPa (1.67 m/s), with a sensitivity of 77% and specificity of 66%. SWE may be useful for the detection of NASH patients at risk of long-term liver-specific morbidity and mortality.

Liver fibrosis is a histological hallmark of most chronic liver diseases, which can progress to cirrhosis and liver failure, and predisposes to hepatocellular carcinoma. Accurate diagnosis of liver fibrosis is necessary for prognosis, risk stratification, and treatment decision-making. Liver biopsy, the reference standard for assessing liver fibrosis, is invasive, costly, and impractical for surveillance and treatment response monitoring. Elastography offers a noninvasive, objective, and quantitative alternative to liver biopsy. This article discusses the need for noninvasive assessment of liver fibrosis and reviews the comparative advantages and limitations of ultrasound and magnetic resonance elastography techniques with respect to their basic concepts, acquisition, processing, and diagnostic performance. Variations in clinical contexts of use and common pitfalls associated with each technique are considered. In addition, current challenges and future directions to improve the diagnostic accuracy and clinical utility of elastography techniques are discussed. Level of Evidence: 5 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:25-42.

Non-alcoholic fatty liver disease is a condition that is characterized by the presence of >5% fat in the liver and affects more than one billion people worldwide. If adequate and early precautions are not taken, non-alcoholic fatty liver disease can progress to cirrhosis and death. The current reference standard for detecting hepatic steatosis is a liver biopsy. However, because of the potential morbidity associated with liver biopsies, non-invasive imaging biomarkers have been extensively investigated. Magnetic resonance imaging-based methods have proven accuracy in quantifying liver steatosis; however, these techniques are costly and have limited availability. Ultrasound-based quantitative imaging techniques are increasingly utilized because of their widespread availability, ease of use and relative cost-effectiveness. Several ultrasound-based liver fat quantification techniques have been investigated, including techniques that measure changes in the acoustic properties of the liver caused by the presence of fat. In this review, we focus on quantitative ultrasound approaches and their diagnostic performance in the realm of non-alcoholic fatty liver disease.