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Ultrasound Entropy Imaging of Nonalcoholic Fatty Liver Disease: Association with Metabolic Syndrome
by Ying-Hsiu Lin 1,Yin-Yin Liao 2,Chih-Kuang Yeh 3,Kuen-Cheh Yang 4,5,*ORCID andPo-Hsiang Tsui 1,6,7,*
1
Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
2
Department of Biomedical Engineering, Hungkuang University, Taichung 43302, Taiwan
3
Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu 30013, Taiwan
4
Department of Family Medicine, National Taiwan University Hospital, Beihu Branch, Taipei 10800, Taiwan
5
Health Science & Wellness Center, National Taiwan University, Taipei 10617, Taiwan
6
Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 33305, Taiwan
7
Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan
*
Authors to whom correspondence should be addressed.
Entropy 2018, 20(12), 893; https://doi.org/10.3390/e20120893
Received: 17 October 2018 / Revised: 18 November 2018 / Accepted: 20 November 2018 / Published: 22 November 2018
(This article belongs to the Special Issue Entropy in Image Analysis)
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Abstract
Nonalcoholic fatty liver disease (NAFLD) is the leading cause of advanced liver diseases. Fat accumulation in the liver changes the hepatic microstructure and the corresponding statistics of ultrasound backscattered signals. Acoustic structure quantification (ASQ) is a typical model-based method for analyzing backscattered statistics. Shannon entropy, initially proposed in information theory, has been demonstrated as a more flexible solution for imaging and describing backscattered statistics without considering data distribution. NAFLD is a hepatic manifestation of metabolic syndrome (MetS). Therefore, we investigated the association between ultrasound entropy imaging of NAFLD and MetS for comparison with that obtained from ASQ. A total of 394 participants were recruited to undergo physical examinations and blood tests to diagnose MetS. Then, abdominal ultrasound screening of the liver was performed to calculate the ultrasonographic fatty liver indicator (US-FLI) as a measure of NAFLD severity. The ASQ analysis and ultrasound entropy parametric imaging were further constructed using the raw image data to calculate the focal disturbance (FD) ratio and entropy value, respectively. Tertiles were used to split the data of the FD ratio and entropy into three groups for statistical analysis. The correlation coefficient r, probability value p, and odds ratio (OR) were calculated. With an increase in the US-FLI, the entropy value increased (r = 0.713; p < 0.0001) and the FD ratio decreased (r = –0.630; p < 0.0001). In addition, the entropy value and FD ratio correlated with metabolic indices (p < 0.0001). After adjustment for confounding factors, entropy imaging (OR = 7.91, 95% confidence interval (CI): 0.96–65.18 for the second tertile; OR = 20.47, 95% CI: 2.48–168.67 for the third tertile; p = 0.0021) still provided a more significant link to the risk of MetS than did the FD ratio obtained from ASQ (OR = 0.55, 95% CI: 0.27–1.14 for the second tertile; OR = 0.42, 95% CI: 0.15–1.17 for the third tertile; p = 0.13). Thus, ultrasound entropy imaging can provide information on hepatic steatosis. In particular, ultrasound entropy imaging can describe the risk of MetS for individuals with NAFLD and is superior to the conventional ASQ technique.
Keywords: ultrasound; hepatic steatosis; Shannon entropy; fatty liver; metabolic syndrome |
