Ultrasound Assessment of Hepatic Steatosis by Using the Double Nakagami Distribution: A Feasibility Study

Abstract

Ultrasound imaging is a first-line assessment tool for hepatic steatosis. Properties of tissue microstructures correlate with the statistical distribution of ultrasound backscattered signals, which can be described by the Nakagami distribution (a widely adopted approximation of backscattered statistics). The double Nakagami distribution (DND) model, which combines two Nakagami distributions, was recently proposed for using high-frequency ultrasound to analyze backscattered statistics corresponding to lipid droplets in the fat-infiltrated liver. This study evaluated the clinical feasibility of the DND model in ultrasound parametric imaging of hepatic steatosis by conducting clinical experiments using low-frequency ultrasound dedicated to general abdominal examinations. A total of 204 patients were recruited, and ultrasound image raw data were acquired using a 3.5 MHz array transducer for DND parametric imaging using the sliding window technique. The DND parameters were compared with hepatic steatosis grades identified histologically. A receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance. The results indicated that DND parametric imaging constructed using a sliding window with the side length of five times the pulse length of the transducer provided stable and reliable DND parameter estimations and visualized changes in the backscattered statistics caused by hepatic steatosis. The DND parameter increased with the hepatic steatosis grade. The areas under the ROC curve for identifying hepatic steatosis were 0.76 (≥mild), 0.81 (≥moderate), and 0.82 (≥severe). When using low-frequency ultrasound, DND imaging allows the clinical detection of hepatic steatosis and reflects information associated with lipid droplets in the fat-infiltrated liver.

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

“…Notably, as mentioned in Introduction, ultrasound parametric imaging using the Nakagami and HK distributions has been applied to clinical assessment of hepatic steatosis. It has been reported that the AUROCs for using Nakagami and HK imaging to detect hepatic steatosis ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\ge $ \end{document} mild, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\ge $ \end{document} moderate, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\ge $ \end{document} severe) were (0.75, 0.82, 0.82) and (0.76, 0.80, 0.83), respectively [11] , [12] , which exhibits worse diagnostic performances compared with that of sample entropy imaging. The proposed sample entropy not only outperformed the statistical distribution parameters and Shannon entropy in characterizing hepatic steatosis but also provides the diagnostic ability in clinical fibrosis risk evaluations of individuals with developing hepatic steatosis, as supported by the current findings.…”

“…Currently, the Nakagami and homodyned K (HK) distributions are the two primary general statistical models of ultrasound backscattering [9] . The progression of hepatic steatosis can be quantitatively described using these models with parameters estimated using raw envelope signals (before logarithmic compression) [10] – [12] .…”

Basic concept and clinical applications of quantitative ultrasound (QUS) technologies

“…Currently, basic studies that use clinical data most commonly employ the Nakagami model. A wide variety of targets have been evaluated in such studies, including vascular studies by Huang [ 81 ], ophthalmology and breast cancer by Tsui [ 82 , 83 ], and the liver by Tsui and Yamaguchi [ 84 , 85 ]. In the most recent research, the Nakagami distribution has been applied to evaluating the temperature of living tissues by Hasegawa [ 86 , 87 ], and Tamura and Yamaguchi have combined multiple distributions to evaluate fat and fiber in the liver simultaneously [ 88 , 89 ].…”

A deep learning approach for patchless estimation of ultrasound quantitative parametric image with uncertainty measurement

“…Among different QUS parameters, scatterer number density has been found to be useful for different clinical applications such as liver fibrosis detection 2 and Hepatic steatosis assessment. 3 Scatterer number density can be quantified by modeling the ultrasound echo amplitude using different probability density functions. The homodyned K-distribution (HK-distribution) is a well-known distribution that has been widely used to quantify the scatterer number density and characterizing the tissues.…”