Ling Wenwu, Quan Jierong, Lin Jiangli, Qiu Tingting, Li Jiawu, Lu Qiang, Lu Changli, Luo Yan
Department of Ultrasound, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, Sichuan 610041, P.R. China.
Department of Ultrasound, Sichuan Academy of Medical Science & Sichuan Provincial People's Hospital, No. 32 Yi Huan Lu Xi Er Duan, Chengdu, Sichuan 610041, P.R. China.
Exp Anim. 2018 May 10;67(2):249-257. doi: 10.1538/expanim.17-0124. Epub 2018 Jan 12.
This study aimed to assess the severity of fatty liver (FL) by analyzing ultrasound radiofrequency (RF) signals in rats. One hundred and twenty rats (72 in the FL group and 48 in the control group) were used for this purpose. Histological results were the golden standard: 42 cases had normal livers (N), 30 cases had mild FL (L1), 25 cases had moderate FL (L2), 13 cases presented with severe FL (L3), and 10 cases were excluded from the study. Four RF parameters (Mean, Mean/SD ratio [MSR], skewness [SK], and kurtosis [KU] were extracted. Univariate analysis, spearman correlation analysis, and stepwise regression analysis were used to select the most powerful predictors. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic efficacy of single indexes with a combined index (Y) expressed by a regression equation. Mean, MSR, SK, and KU were significantly correlated with FL grades (r=0.71, P<0.001; r=0.81, P<0.001; r=-0.79, P<0.001; and r=-0.74, P<0.001). The regression equation was Y=-4.48 + 3.20 × 10X1 + 3.15X2 (P<0.001), where Y=hepatic steatosis grade, X1 =Mean, and X2 =MSR. ROC analysis showed that the curve areas of the combined index (Y) were superior to simple indexes (Mean, MSR, SK, and KU) in evaluating hepatic steatosis grade, and they were 0.95 (L≥L1), 0.98 (L≥L2), and 0.99 (L≥L3). Ultrasound radiofrequency signal quantitative technology was a new, noninvasive, and promising sonography-based approach for the assessment of FL.
本研究旨在通过分析大鼠的超声射频（RF）信号来评估脂肪肝（FL）的严重程度。为此使用了120只大鼠（FL组72只，对照组48只）。组织学结果为金标准：42例肝脏正常（N），30例轻度FL（L1），25例中度FL（L2），13例重度FL（L3），10例被排除在研究之外。提取了四个RF参数（均值、均值/标准差比值[MSR]、偏度[SK]和峰度[KU]）。采用单因素分析、Spearman相关分析和逐步回归分析来选择最有力的预测指标。采用受试者操作特征（ROC）分析来比较单一指标与由回归方程表示的组合指标（Y）的诊断效能。均值、MSR、SK和KU与FL分级显著相关（r = 0.71，P < 0.001；r = 0.81，P < 0.001；r = -0.79，P < 0.001；r = -0.74，P < 0.001）。回归方程为Y = -4.48 + 3.20×10X1 + 3.15X2（P < 0.001），其中Y =肝脂肪变性分级，X1 =均值，X2 = MSR。ROC分析表明，在评估肝脂肪变性分级方面，组合指标（Y）的曲线面积优于单一指标（均值、MSR、SK和KU），其曲线下面积分别为0.95（L≥L1）、0.98（L≥L2）和0.99（L≥L3）。超声射频信号定量技术是一种新型的、非侵入性的且有前景的基于超声的FL评估方法。
