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Review: The Evolving Role of Quantitative Ultrasound for Fatty Liver Disease

Key findings

  • This review focuses on currently available and emerging ultrasound methods for evaluating liver steatosis, inflammation, and fibrosis
  • Established techniques include the hepatorenal index, attenuation coefficient, backscatter coefficient, and shear-wave elastography
  • Accumulating evidence supports the use of speed of sound quantification, ultrasound-derived fat fraction, speckle statistics, and shear-wave dispersion and tissue viscosity
  • Innovative research that makes use of machine learning techniques is expected to improve further the clinical utility of ultrasound for diagnosis, risk stratification, and treatment monitoring in metabolic liver disease

Estimating inflammation and fibrosis in patients with metabolic dysfunction-associated steatotic liver disease (MASLD, previously termed NAFLD) provides prognostic information. It helps identify patients who have Metabolic dysfunction-associated steatohepatitis (MASH, previously termed NASH) and are at higher risk of long-term adverse outcomes. Ultrasound-based methods are low-cost and widely available, making them more suitable for population-level diagnosis and risk stratification than MRI-based methods or liver biopsy.

In Radiology, researchers at Massachusetts General Hospital recently reviewed current and emerging ultrasound methods for evaluating liver steatosis, inflammation, and fibrosis. The authors are Arinc Ozturk, MD, of the Center for Ultrasound Research & Translation and instructor in the Department of Radiology, Anthony E. Samir, MD, MPH, director of the Center and associate chair of Imaging Sciences at Mass General, and colleagues.

This summary focuses on commercially available techniques whose evidence base is still evolving.

Acoustic Parameters

Backscatter coefficient—Increased number and/or size of intracellular fat vacuoles in liver steatosis produces a hyperechoic appearance compared with normal tissue or kidney. Techniques to distinguish these properties from the level of the acoustic echoes—termed the backscatter coefficient—may perform as well as MRI-derived steatosis estimates. More research is needed to understand the effects of operator training and experience and other potential confounding factors.

The speed of sound in liver tissue is negatively correlated with steatosis severity. However, this parameter can be difficult to obtain with many commercially available ultrasound devices, and the literature on its diagnostic performance is still limited.

Fat fraction—By combining two measures, such as the attenuation coefficient and the backscatter coefficient, it's possible to estimate an ultrasound-based fat fraction. This measure has shown good performance for steatosis diagnosis. Studies with biopsy-proven MASLD subjects are still needed to understand the effects of potential confounders such as fibrosis on the measurements.

Speckle Statistics

Speckle patterns appear in ultrasound images because of scattered signals from tissue microstructures. Statistical features in these signals—speckle patterns—are potential steatosis biomarkers:

  • Acoustic structure quantification assesses the degree of deviation from the Rayleigh distribution to evaluate liver tissue characteristics. It is used to compute a focal disturbance ratio, which is inversely related to liver fat content.
  • Normalized local variance, an extension of acoustic structure quantification, relies on regional image analysis to evaluate the intensity and homogeneity of liver tissue. Lower values have been associated with higher steatosis severity.
  • The Nakagami parameter is the variation in the shape of the envelope distribution of the backscattered ultrasound signal. Increased values have been associated with more severe steatosis.

Further research is needed to understand how these techniques compare with each other and existing ultrasound tools for MASLD evaluation.

Shear-wave Parameters

The use of shear-wave elastography for liver fibrosis diagnosis and staging is well established. In the same ultrasound examination, two related parameters can be estimated:

  • Shear-wave dispersion, proposed as an inflammation biomarker
  • Shear-wave viscosity, which appears to be higher at higher fibrosis stages

Combining these techniques to evaluate fibrosis, steatosis, and inflammation might identify patients with MASLD who have MASH or are at risk of developing it. Such screening would be particularly valuable if performed with point-of-care devices at primary care visits.

Artificial Intelligence

Many innovative applications of AI have been reported for liver ultrasound:

  • Deep learning to decrease the burden of manually drawing regions of interest and to more accurately estimate the hepatorenal index.
  • Enhanced screening of B-mode images for steatosis to identify patients who should be referred to more sophisticated methods, such as attenuation coefficient measurement.
  • Automated calculation of Doppler waveform–based biomarkers for fibrosis, such as the portal venous pulsatility index.

Currently, most published ultrasound algorithms for imaging MASLD focus on disease diagnosis. Continued work is expected to improve early disease detection, prioritization of at-risk cases, and monitoring of treatment response.

Learn more about the Center for Ultrasound Research & Translation (CURT)

Learn more about research in the Department of Radiology

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