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

<italic>Objective:</italic> 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 propert...

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Autores principales:	Hsien-Jung Chan, Zhuhuang Zhou, Jui Fang, Dar-In Tai, Jeng-Hwei Tseng, Ming-Wei Lai, Bao-Yu Hsieh, Tadashi Yamaguchi, Po-Hsiang Tsui
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Fatty liver hepatic steatosis sample entropy Computer applications to medicine. Medical informatics R858-859.7 Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/4c3e490f3e9a4004a743bbebc0b6ef95
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spelling	oai:doaj.org-article:4c3e490f3e9a4004a743bbebc0b6ef952021-11-18T00:00:34ZUltrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis2168-237210.1109/JTEHM.2021.3124937https://doaj.org/article/4c3e490f3e9a4004a743bbebc0b6ef952021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9599701/https://doaj.org/toc/2168-2372<italic>Objective:</italic> 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 <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> and tolerance <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>, for ultrasound parametric imaging of hepatic steatosis and fibrosis. <italic>Methods:</italic> Liver donors and patients were enrolled, and their hepatic fat fraction (HFF) (<inline-formula> <tex-math notation="LaTeX">$n =72$ </tex-math></inline-formula>), steatosis grade (<inline-formula> <tex-math notation="LaTeX">$n =286$ </tex-math></inline-formula>), and fibrosis score (<inline-formula> <tex-math notation="LaTeX">$n =65$ </tex-math></inline-formula>) were measured to verify the results of sample entropy imaging using sliding-window processing of ultrasound RF data. <italic>Results:</italic> The sample entropy calculated using <inline-formula> <tex-math notation="LaTeX">$m =$ </tex-math></inline-formula> 4 and <inline-formula> <tex-math notation="LaTeX">$r =0.1$ </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">$\ge $ </tex-math></inline-formula>mild, <inline-formula> <tex-math notation="LaTeX">$\ge $ </tex-math></inline-formula>moderate, and <inline-formula> <tex-math notation="LaTeX">$\ge $ </tex-math></inline-formula>severe were 0.86, 0.90, and 0.88, respectively, and the area was 0.87 for detecting liver fibrosis in individuals with significant steatosis. <italic>Discussion/Conclusions:</italic> 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.Hsien-Jung ChanZhuhuang ZhouJui FangDar-In TaiJeng-Hwei TsengMing-Wei LaiBao-Yu HsiehTadashi YamaguchiPo-Hsiang TsuiIEEEarticleFatty liverhepatic steatosissample entropyComputer applications to medicine. Medical informaticsR858-859.7Medical technologyR855-855.5ENIEEE Journal of Translational Engineering in Health and Medicine, Vol 9, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Fatty liver hepatic steatosis sample entropy Computer applications to medicine. Medical informatics R858-859.7 Medical technology R855-855.5
spellingShingle	Fatty liver hepatic steatosis sample entropy Computer applications to medicine. Medical informatics R858-859.7 Medical technology R855-855.5 Hsien-Jung Chan Zhuhuang Zhou Jui Fang Dar-In Tai Jeng-Hwei Tseng Ming-Wei Lai Bao-Yu Hsieh Tadashi Yamaguchi Po-Hsiang Tsui Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis
description	<italic>Objective:</italic> 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 <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> and tolerance <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>, for ultrasound parametric imaging of hepatic steatosis and fibrosis. <italic>Methods:</italic> Liver donors and patients were enrolled, and their hepatic fat fraction (HFF) (<inline-formula> <tex-math notation="LaTeX">$n =72$ </tex-math></inline-formula>), steatosis grade (<inline-formula> <tex-math notation="LaTeX">$n =286$ </tex-math></inline-formula>), and fibrosis score (<inline-formula> <tex-math notation="LaTeX">$n =65$ </tex-math></inline-formula>) were measured to verify the results of sample entropy imaging using sliding-window processing of ultrasound RF data. <italic>Results:</italic> The sample entropy calculated using <inline-formula> <tex-math notation="LaTeX">$m =$ </tex-math></inline-formula> 4 and <inline-formula> <tex-math notation="LaTeX">$r =0.1$ </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">$\ge $ </tex-math></inline-formula>mild, <inline-formula> <tex-math notation="LaTeX">$\ge $ </tex-math></inline-formula>moderate, and <inline-formula> <tex-math notation="LaTeX">$\ge $ </tex-math></inline-formula>severe were 0.86, 0.90, and 0.88, respectively, and the area was 0.87 for detecting liver fibrosis in individuals with significant steatosis. <italic>Discussion/Conclusions:</italic> 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.
format	article
author	Hsien-Jung Chan Zhuhuang Zhou Jui Fang Dar-In Tai Jeng-Hwei Tseng Ming-Wei Lai Bao-Yu Hsieh Tadashi Yamaguchi Po-Hsiang Tsui
author_facet	Hsien-Jung Chan Zhuhuang Zhou Jui Fang Dar-In Tai Jeng-Hwei Tseng Ming-Wei Lai Bao-Yu Hsieh Tadashi Yamaguchi Po-Hsiang Tsui
author_sort	Hsien-Jung Chan
title	Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis
title_short	Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis
title_full	Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis
title_fullStr	Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis
title_full_unstemmed	Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis
title_sort	ultrasound sample entropy imaging: a new approach for evaluating hepatic steatosis and fibrosis
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/4c3e490f3e9a4004a743bbebc0b6ef95
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_version_	1718425223503544320

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

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