In-vivo study of quantitative ultrasound parameters in fatty rabbit livers

Abstract

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease and can often lead to fibrosis, cirrhosis, cancer and complete liver failure. Liver biopsy is the current standard of care to quantify hepatic steatosis, but it comes with increased patient risk and only samples a small portion of the liver. Imaging approaches to assess NAFLD include proton density fat fraction (PDFF) estimated via MRI and shear wave elastography. However, MRI is often prohibitively expensive and shear wave elastography is not sensitive to fat content of the liver [1]. On the other hand, ultrasonic attenuation and the backscatter coefficient (BSC) have been observed to be sensitive to levels of fat in the liver. In this study, we explored the use of attenuation and a principal component analysis (PCA) of the BSC to detect and quantify hepatic steatosis in vivo in a rabbit model of fatty liver. Rabbits were maintained on a high fat diet for 0, 1, 2, 3 or 6 weeks with three rabbits per diet group (total N = 15). For analysis, rabbits were separated into three classes based on the total lipid content of the livers estimated using the Folch method: low fat ( 10%). An array transducer L9-4 with center frequency of 4 MHz connected to a SonixOne scanner was used to gather RF backscattered data in vivo from rabbits. The RF signals were used to estimate an average attenuation and BSC for each rabbit. The first five principal components of the PCA from the BSCs were used as input features to a support vector machine (SVM) for classification and comparison to total liver lipid levels. The slope of the attenuation coefficient provided statistically significant differences (p < 0.00058, using two-sample t-test) between low and high lipid fat groups. The proposed PCA-SVM based classification system yielded a classification accuracy of 63.7%, 32.6% and 71.2% for the low, medium and high fat groups, respectively. The results suggest that attenuation and BSC analysis can differentiate low versus high fat livers in a rabbit model. This work was supported by a grant from NIH (R21EB020766).