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Chinese Journal of Radiology ; (12): 1376-1382, 2022.
Article in Chinese | WPRIM | ID: wpr-956796

ABSTRACT

Objective:To explore the value of proton density fat fraction(PDFF) based on histogram analysis for quantification hepatic steatosis and fibrosis in rabbit model and the interference of hepatic fibrosis to the evaluation of hepatic steatosis with PDFF.Methods:From March to November 2020, 135 New Zealand white rabbits were randomly divided into control group ( n=30) and experimental group ( n=105) using a random number table. The volume ratio of CCl 4 and olive oil was 1∶1 to prepare 50% CCl 4 oil solution, and experimental rabbits were subcutaneously injected with the oil solution. An equal dose of normal saline was subcutaneously injected for control group rabbits. At the end of the 4 th, 8 th, and 12 th week, 35 in the experimental group and 10 rabbits in the control group were randomly selected to conduct the mDixon-Quant scanning, and histogram analysis of PDFF was analyzed including volume, mean, median, standard deviation, 25 th, 50 th, 75 th, 90 th quantile, skewness, kurtosis, entropy and inhomogeneity. After the examination, the rabbits were sacrificed and the liver percentage of steatosis (PSH) and fibrosis (POF) were recorded by semi-quantitative analysis. Spearman correlation analysis was used to correlate PDFF with PSH and POF. Multiple linear regression analysis was used to determine independent PDFF histogram parameters for evaluating PSH and POF. A receiver operator characteristic (ROC) curve was used to assess the diagnostic accuracy of PDFF for discriminating mild from moderate-severe hepatic steatosis and mild from moderate-severe hepatic fibrosis with median of PSH or POF for dichotomy, and DeLong test was used to compare the area under the curve (AUC). With the correction of hepatic fibrosis, correlation coefficient and AUC were compared of PDFF for discrimination mild from moderate-severe hepatic steatosis. Results:The PDFF mean, median, standard deviation, 75 th, 90 th showed correlation with PSH ( r=0.558, 0.522, 0.319, 0.723, 0.646, -0.589, all P<0.05). The entropy and 75 th were independent parameters for evaluating PSH (β=2.347, -5.960, P=0.018, 0.001). The PDFF 75 th was the optimal parameter for discriminating mild from moderate-severe hepatic steatosis with AUC=0.915 ( P=0.001). The PDFF volume, mean, median, standard deviation, 75 th, 90 th, entropy showed correlation with POF ( r=0.355, 0.393, 0.376, 0.298, 0.485, 0.426, -0.681, all P<0.05). The entropy, standard deviation and volume (β=-11.041, 1.356, 0.190, P=0.001, 0.026, 0.016) were independent parameters for evaluation of hepatic fibrosis, and the entropy was the optimal parameter for hepatic fibrosis (AUC=0.771, P=0.001). The correlation between PSH and PDFF 75 th was less pronounced when fibrosis was present ( r=0.512, P=0.001) than when fibrosis was absent ( r=0.751, P=0.002). The PDFF 75 th showed a significant difference in discriminating mild hepatic steatosis from moderate-severe hepatic steatosis after correction of POF (AUC=0.895, 0.950, Z=2.970, P=0.025). Conclusions:PDFF based on histogram analysis provided a noninvasive, accurate estimation of quantification for hepatic steatosis and fibrosis. Hepatic fibrosis reduced the correlation between hepatic steatosis and PDFF and the presence of hepatic fibrosis can confound the quantification of hepatic steatosis with PDFF.

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