Sound Speed Contribution to Quantitative Ultrasound for Improving Liver Fat Assessment

Local speed of sound estimation is an emerging technique that enhances ultrasound (US) image quality through aberration correction and can also aid in identifying pathological tissue conditions. We propose to incorporate speed of sound into quantitative ultrasound (QUS) multiparametric analysis for assessing the progression of steatosis.We performed an in vivo study with an animal model of metabolic dysfunction-associated fatty liver disease (MAFLD), enrolling 20 rats; 16 on a high-fat diet and 4 control rats on a normal diet. Ultrasound scanning was performed, capturing channel radiofrequency data (RF data), which were analyzed to estimate local speed of sound as well as the four quantitative ultrasound parameters: H-scan frequency, frequency-dependent attenuation, B-mode intensity, and Nakagami parameter. Our multiparametric analysis utilizing principal component analysis (PCA) produced a combined parameter predictive of steatosis progression, which was validated against reference fat fraction (fat %) obtained via biochemical analysis of liver samples.Multiparametric analysis incorporating speed of sound estimation resulted in a Pearson’s correlation coefficient (R) of 0.88 with the reference fat %, outperforming the model excluding speed of sound (R = 0.83). These findings demonstrate enhanced monitoring of liver conditions. We anticipate that integrating speed of sound into quantitative ultrasound will improve the accuracy of fat quantification, thereby facilitating more precise diagnosis of steatosis.