Noninvasive Assessment Of Liver Fibrosis: Preliminary Experience With Acoustic Structure Quantification (ASQ)

ObjectiveTo explore the diagnostic value of acoustic structure of quantitative techniques(ASQ)in the assessment of liver fibrosis.Materials and Methods1. PatientsBetween2012and2013, three patients with cirrhosis for liver transplantation inShandong province Qianfo Mountain hospital and140patients with histologically provenchronic hepatitis B in Jinan infectious disease hospital were collected, and we also enrolled77healthy volunteers from physical examination center with the following criteria: nofocal liver disease or history of diffuse assessed through history taking laboratoryexaminations. We put the subjects in four groups: control group(aged20to62, average age,38,53males and47females, containing23patients with chronic hepatitis B histologicallyproven S0), mild liver fibrosis group (S1-S2,53), moderate liver fibrosis group(S3,37)andcirrhosis group(S4,30). All subjects signed an informed consent form.2. Methods100normal subjects and120patients with histologically proven chronic hepatitis Bvirus underwent conventional abdominal US and ASQ with dedicated equipment and5MHZ convex probe(Aplio XG790A, Toshiba Medical Systems, Japan) for the best liveracoustic window. In particular, we captured three images: at the level of segments7and8of right subcostal approach, one in the axial plane and another in the sagittal plane. Thethird image were captured at the axial plane of the left hepatic lobe. The raw echo signal ofimages was analyzed and parameters such as mean, average, standard deviation, the ratioof blue and red color histogram curve area were observed to evaluate the correlation between ASQ values and the pathologic result of liver fibrosis. For well-correlationparameter, ROC was analyzed to get the optimal cutoff value for liver fibrosis S≥1andS≥3.ResultsWith the degree of liver fibrosis increased, red histogram curve and blue histogramcurve in the horizontal distribution is rough, right moved, the area under blue curve ismuch larger than the red. RedMode, RedAverage, BlueMode and BlueAverage showed astatistical difference between each two groups(P<0.01). RedSD showed a statisticaldifference between each two groups(P<0.01)except that between S3subgroup and S4subgroup(P>0.05). The relative gap of standardized ratio of blue and red color histogramcurve area in each group are much larger than the other six indicators. The areas underROC curves were0.88for S≥1and0.96for S≥3.ConclusionThe ASQ technology is a novel, noninvasive and promising tool for the assessment ofliver fibrosis, especially in early cirrhosis.