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: | , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4c3e490f3e9a4004a743bbebc0b6ef95 |
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| Sumario: | <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. |
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