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

Hsien-Jung Chan,Po-Hsiang Tsui,Tadashi Yamaguchi,Bao-Yu Hsieh,Jeng-Hwei Tseng,Ming-Wei Lai,Zhuhuang Zhou,Jui Fang,Dar-In Tai

doi:10.1109/jtehm.2021.3124937

Abstract

Objective: Hepatic steatosis causes nonalcoholic fatty liver disease and may progress to fibrosis. Ultrasound is the first-line approach to examining hepatic steatosis. Fatty droplets in the liver parenchyma alter ultrasound radiofrequency (RF) signal statistical properties. This study proposes using sample entropy, a measure of irregularity in time-series data determined by the dimension n}{}mn and tolerance n}{}rn, for ultrasound parametric imaging of hepatic steatosis and fibrosis. Methods: Liver donors and patients were enrolled, and their hepatic fat fraction (HFF) (n}{}n =72n), steatosis grade (n}{}n =286n), and fibrosis score (n}{}n =65n) were measured to verify the results of sample entropy imaging using sliding-window processing of ultrasound RF data. Results: The sample entropy calculated using n}{}m =n 4 and n}{}r =0.1n was highly correlated with the HFF when a small window with a side length of one pulse was used. The areas under the receiver operating characteristic curve for detecting hepatic steatosis that was n}{}ge nmild, n}{}ge nmoderate, and n}{}ge nsevere were 0.86, 0.90, and 0.88, respectively, and the area was 0.87 for detecting liver fibrosis in individuals with significant steatosis. Discussion/Conclusions: Ultrasound sample entropy imaging enables the identification of time-series patterns in RF signals received from the liver. The algorithmic scheme proposed in this study is compatible with general ultrasound pulse-echo systems, allowing clinical fibrosis risk evaluations of individuals with developing hepatic steatosis.

Highlights

IntroductionHepatic steatosis, defined as the accumulation of triacylglycerol-rich lipid droplets within hepatocytes (at least 5% of hepatocytes contain lipid vacuoles), may progress to steatohepatitis, fibrosis, cirrhosis, or hepatocellular carcinoma [1]
Hepatic steatosis, defined as the accumulation of triacylglycerol-rich lipid droplets within hepatocytes, may progress to steatohepatitis, fibrosis, cirrhosis, or hepatocellular carcinoma [1]
The brightness and distribution of the false coloring of Shannon entropy images varied at higher hepatic fat fraction (HFF); the same phenomenon was observed in sample entropy images

Summary

Introduction

Hepatic steatosis, defined as the accumulation of triacylglycerol-rich lipid droplets within hepatocytes (at least 5% of hepatocytes contain lipid vacuoles), may progress to steatohepatitis, fibrosis, cirrhosis, or hepatocellular carcinoma [1]. Liver biopsy is the gold standard approach for hepatic steatosis diagnosis [2]. Ultrasound imaging is a cost-effective, real-time, portable technique without ionizing radiation that could serve as a first-line approach to evaluating hepatic steatosis. Researchers have focused on developing quantitative ultrasound approaches for characterizing and grading hepatic steatosis to address this variability [5]. The liver parenchyma could be modeled as a scattering medium and form a speckle pattern in an ultrasound B-scan [6]. Because of the randomness of ultrasound backscattering, using statistical distribution models to perform passive parametrization of speckle patterns is a well-accepted method of characterizing the microstructures of tissues (i.e., scatterer arrangements and concentrations) [7], [8]. The progression of hepatic steatosis can be quantitatively described using these models with parameters estimated using raw envelope signals (before logarithmic compression) [10]–[12]

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Conclusion