scholarly journals Ultrasound Entropy Imaging of Nonalcoholic Fatty Liver Disease: Association with Metabolic Syndrome

Entropy ◽  
2018 ◽  
Vol 20 (12) ◽  
pp. 893 ◽  
Author(s):  
Ying-Hsiu Lin ◽  
Yin-Yin Liao ◽  
Chih-Kuang Yeh ◽  
Kuen-Cheh Yang ◽  
Po-Hsiang Tsui

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.

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Kei Nakajima

Nonalcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are multidisciplinary liver diseases that often accompany type 2 diabetes or metabolic syndrome, which are characterized by insulin resistance. Therefore, effective treatment of type 2 diabetes and metabolic syndrome should target not only the cardiometabolic abnormalities, but also the associated liver disorders. In the last decade, it has been shown that metformin, thiazolidinediones, vitamin E, ezetimibe, n-3 polyunsaturated fatty acids, renin-angiotensin system (RAS) blockers, and antiobesity drugs may improve hepatic pathophysiological disorders as well as clinical parameters. Accordingly, insulin sensitizers, antioxidative agents, Niemann-Pick C1-like 1 (NPC1L1) inhibitors, RAS blockers, and drugs that target the central nervous system may represent candidate pharmacotherapies for NAFLD and possibly NASH. However, the efficacy, safety, and tolerability of long-term treatment (potentially for many years) with these drugs have not been fully established. Furthermore, clinical trials have not comprehensively examined the efficacy of lipid-lowering drugs (i.e., statins, fibrates, and NPC1L1 inhibitors) for the treatment of NAFLD. Although clinical evidence for RAS blockers and incretin-based agents (GLP-1 analogs and dipeptidyl peptidase-4 inhibitors) is also lacking, these agents are promising in terms of their insulin-sensitizing and anti-inflammatory effects without causing weight gain.


2017 ◽  
Vol 37 (9) ◽  
pp. 1389-1396 ◽  
Author(s):  
Salvatore Petta ◽  
Mohammed Eslam ◽  
Luca Valenti ◽  
Elisabetta Bugianesi ◽  
Marco Barbara ◽  
...  

2021 ◽  
Vol 5 (2) ◽  
pp. 34-37
Author(s):  
Zhahid Hassan ◽  
Muzamil Latief ◽  
Mahroosa Ramzan ◽  
Farhat Abbas ◽  
Summyia Farooq

Nonalcoholic fatty liver disease (NAFLD) is associated with insulin resistance, obesity, and other features of metabolic syndrome. It is identified as the most common cause of liver enzyme derangement. Lately, NAFLD has generated interest in exploring treatment options, including weight loss and dietary interventions. An association of NAFLD with metabolic syndrome has been suggested in contemporary literature. In this study, we attempted to look into the association of NAFLD with metabolic syndrome. In this study, 80 adult NAFLD patients were recruited from a tertiary care hospital. Among these, 42 were males and 38 females with a mean age of 44.46±13.146 years (range 18–82 years). Grades of fatty liver and presence or absence of metabolic syndrome were studied in this patient population. Patients who did not qualify for the criteria of met-abolic syndrome were placed in Group 1 and those who fulfilled the stated criteria were considered in Group 2. There were 29 (36.25%) patients in Group 1 and 51 (63.75%) in Group 2. All the patients in Group 1 were having Grade I fatty liver whereas patients in Group 2 were found to having varying grades of fatty liver, with six patients having Grade III fatty liver. We found statistically significant difference in various parameters of study (liver enzymes, high-density lipoprotein (HDL), triglycerides, and blood pressure) between Group 1 and Group 2. Ultrasound evidence of a fatty liver should be considered as a predictor of metabolic syndrome, and these patients must be investigated for the different components of metabolic syndrome so as to have early diagnosis and intervention to alter development of long-term metabolic disorders and their inherent complications.


2003 ◽  
Vol 98 (9) ◽  
pp. 2064-2071 ◽  
Author(s):  
Arun J. Sanyal ◽  
Melissa J. Contos ◽  
Richard K. Sterling ◽  
Velimir A. Luketic ◽  
Mitchell L. Shiffman ◽  
...  

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