Texture features of hepatic parenchyma based on high-frequency ultrasonic images in quantitative evaluation of liver function in cirrhosis patients / 中国医学影像技术

ABSTRACT

Objective: To explore the application value of quantitative evaluation on liver function in patients with hepatitis B cirrhosis based on texture features of liver parenchyma from high frequency ultrasound images. Methods: Two-dimensional high-frequency ultrasonograms of liver parenchyma in 95 patients with different levels of liver function (37 cases in Child-Pugh A group, 33 in Child-Pugh B group and 25 cases in Child-Pugh C group) and 21 healthy volunteers (control group) were collected. Based on the idea of machine learning, the defect detection method of computer technology was used to locate the defect in liver parenchyma images, and the defect maps of liver parenchyma were obtained. Then three parameters, i.e. the maximum number per unit area of defect maps x(D), the mean value of defect maps mean (D) and the entropy of defect maps ε(D) were extracted. The differences of three parameters among different groups were compared. Results: There were significant differences of x(D), mean (D) and ε(D) among 4 groups (all P<0.001). The value of x(D) and mean (D) in Child-Pugh A group, B group and C group were higher than those in control group (all P<0.05). The value of mean (D) in Child-Pugh A group and Child-Pugh B group were higher than that in control group (both P<0.05). The value of mena (D) and ε(D) in Child-Pugh B group were higher than those in Child-Pugh C group (both P<0.05). Conclusion: Texture features analysis of liver parenchyma based on high-frequency ultrasonic images can accurately assess liver cirrhosis with Child-Pugh A and Child-Pugh B, while the evaluation of liver cirrhosis with Child-Pugh C still needs to combine with other features of the liver.