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. 2023 Feb 11;28(1):75.
doi: 10.1186/s40001-023-01042-5.

Diagnostic efficiency on ultrasound shear wave elastography in evaluation of steatosis severity for non-alcoholic fatty liver disease: a rat model

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Diagnostic efficiency on ultrasound shear wave elastography in evaluation of steatosis severity for non-alcoholic fatty liver disease: a rat model

Yuhui Wu et al. Eur J Med Res. .

Abstract

Background: The pathological feature of steatosis affects the elasticity values measured by shear wave elastography (SWE) is still controversial in non-alcoholic fatty liver disease (NAFLD). The aim of this study is to demonstrate the influence of steatosis on liver stiffness measured by SWE on a rat model with NAFLD and analyze feasibility of SWE for grading steatosis in absence of fibrosis.

Methods: Sixty-six rats were fed with methionine choline deficient diet or standard diet to produce various stages of steatosis; 48 rats were available for final analysis. Rats underwent abdominal ultrasound SWE examination and pathological assessment. Liver histopathology was analyzed to assess the degree of steatosis, inflammation, ballooning, and fibrosis according to the non-alcoholic fatty liver disease activity score. The diagnostic performance of SWE for differentiating steatosis stages was estimated according to the receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was conducted to determine clinical usefulness and the areas under DCA (AUDCAs) calculated.

Results: In multivariate analysis, steatosis was an independent factor affecting the mean elastic modules (B = 1.558, P < 0.001), but not inflammation (B = - 0.031, P = 0.920) and ballooning (B = 0.216, P = 0.458). After adjusting for inflammation and ballooning, the AUROC of the mean elasticity for identifying S ≥ S1 was 0.956 (95%CI: 0.872-0.998) and the AUDCA, 0.621. The AUROC for distinguishing S ≥ S2 and S = S3 was 0.987 (95%CI: 0.951-1.000) and 0.920 (95%CI: 0.816-0.986) and the AUDCA was 0.506 and 0.256, respectively.

Conclusions: Steatosis is associated with liver stiffness and SWE may have the feasibility to be introduced as an assistive technology in grading steatosis for patients with NAFLD in absence of fibrosis.

Keywords: Fat quantification; Hepatic steatosis; Methionine choline deficiency; Non-alcoholic fatty liver disease; Shear wave elastography.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
US-SWE diagrams of steatosis with different degrees in NAFLD. A Normal B Mild steatosis C Moderate steatosis D Severe steatosis. Mean, minimum, maximum elastic modulus, and SD values of various degrees are illustrated in the corresponding graphs
Fig. 2
Fig. 2
Histological NAFLD sections with different degrees of steatosis. A and E Hematoxylin and eosin staining and masson trichrome staining demonstrating the pathological features of steatosis in normal liver, B and F mild fatty liver, C and G moderate liver, D and H severe fatty liver
Fig. 3
Fig. 3
Distribution of elasticity values in pathological features. The boundaries in box plots show upper and lower quartiles, and the lines in the box the median. Asterisks (*) indicate a Games–Howell test with significant differences
Fig. 4
Fig. 4
Correlation between elasticity value and pathological features. The red circle represents a negative correlation, the blue circle a positive correlation; the value in the lower left corner represents the correlation coefficient in Spearman's rank correlation analysis. MEM mean elastic modulus value, MaxEM maximum elastic modulus value, MinEM minimum elastic modulus value, SD standard deviation.
Fig. 5
Fig. 5
Decision curve analysis (DCA) of mean elastic modulus value of US-SWE. A AUDCA for identifying normal liver and mild steatosis or higher severity was 0.621. B AUDCA for distinguishing normal or mild steatosis and moderate or higher severity was 0.506. C AUDCA for differentiating severe steatosis and moderate or lower severity was 0.256. MEM mean elastic modulus value, AUDCA area under decision curve analysis

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