The Detection of Liver Fibrosis based on the First-Order Statistics of the Backscattered Ultrasonic Signal of Liver Tissue

Liver fibrosis was common symptoms caused by chronic hepatitis, in addition to evolve into liver cirrhosis, is also a course record of the liver damage, so the diagnosis of liver fibrosis in chronic hepatitis has been key indicators. The gold standard for diagnosis of liver fibrosis is liver biopsy, but liver biopsy is invasive surgery, it is difficult to universal, so that the first-line treatment of liver fibrosis is abdominal ultrasound imaging apparatus equipment. However, ultrasound imaging of liver fibrosis in the diagnosis has been difficult to have reliable accuracy and difficult to quantify, so we want to use the RF signal of ultrasound imaging assisted medical diagnosis.
Know from the previous studies, although liver ultrasonography is composed of speckle, but not without information. Using first-order statistical parameters can be inferred scattering state. By the pathological process of liver fibrosis, we found that the impact of the structure of the scattering characteristics of the severe liver fibrosis is divided into two effect: one is the upset of the regularity; while the other is caused by the uneven cross section. In previous studies we know the value of the parameter m or the parameter of the Nakagami distribution can be effectively described in these two characteristics. Therefore, we will use the estimated value of this parameter to detect liver fibrosis.
However, in practical there are some difficult issues, which lead to statistical parameter estimation problems of the real liver signal. We developed a method which makes ROI image divided into many smaller blocks were used for parameter statistics, and statistics obtained from the statistical distribution of the trend estimate.
The results obtained in this way we compared the results of liver biopsy and found that this method of estimating the parameter will be able to effectively detect severe fibrosis.