A Quantitative Ultrasound Technology to Identify Patients with NAFLD and Quantify Steatohepatitis
A new quantitative ultrasound (QUS) can accurately identify patients with non-alcoholic fatty liver disease (NAFLD) and quantify hepatic steatosis, researchers report in the July issue of Clinical Gastroenterology and Hepatology. With further validation, QUS could be an inexpensive, widely used technique to screen the general or at-risk population for NAFLD.
The estimated prevalence of NAFLD in the US ranges from 17% to 51%; NAFLD is even more prevalent among individuals with severe obesity (90%), type 2 diabetes (69%), and older Hispanic men. Most cases are identified by liver biopsy, which is invasive, causes complications, and is unreliable for quantification of steatosis, due to sampling error and variations in pathologist interpretation. So, there is much interest in noninvasive methods to identify hepatic steatosis.
Steven C. Lin et al explain that in diagnosis of NAFLD, conventional ultrasonography is inaccurate and limited by operator dependency and low sensitivity and specificity values. Computerized tomography is limited by radiation exposure and inaccurate quantification of steatosis. Advanced magnetic resonance (MR) imaging techniques that measure the proton density fat fraction (MRI-PDFF) and MR spectroscopy can be used to quantify steatosis, but are expensive and not routinely accessible.
QUS was developed to better characterize tissue microstructure by measuring fundamental acoustic parameters, including the backscatter coefficient (BSC). Lin et al explain that BSC is analogous (but not equal) to the qualitative echogenicity of tissue, which is used as a component for grading liver status in conventional clinical ultrasonography. Studies have shown the QUS findings to be highly reproducible and independent of operator and imaging system factors.
Lin et al therefore performed a prospective study to determine the accuracy of QUS in the diagnosis and quantification of hepatic steatosis in patients – the technique has already been shown to identify steatosis in animal models. Lin et al compared their findings with those from MRI-PDFF analysis. They explain that they used MRI-PDFF as the standard, rather than liver biopsy, because MRI-PDFF more accurately quantifies liver fat.
They performed PDFF and QUS analyses of 204 adults with NAFLD (MRI-PDFF, ≥5%) and without NAFLD (controls) on the same day. Subjects were assigned to training and validation groups.
Lin et al found the BSC values to correlate with measurements from MRI-PDFF (Spearman ρ = 0.80). In the training group, the BSC analysis identified patients with NAFLD with an area under the curve value of 0.98. The optimal BSC cut-off value identified patients with NAFLD in the training and validation groups with 93% and 87% sensitivity, 97% and 91% specificity, 86% and 76% negative predictive values, and 99% and 95% positive predictive values, respectively.
The authors conclude that their findings support the potential for noninvasive quantification of liver fat content. They explain that the QUS methodology overcomes previous limitations of conventional ultrasonography, because QUS parameters are estimated using a reference phantom and objective computer algorithms. The phantom reference addresses machine (transducer format, gain, dynamic range, focusing, frequency, and so forth) and operator dependencies, reducing both sources of variability.
Lin et al state that training of an experienced sonographer in QUS requires less than 1 hr. Because the QUS procedures and measures are platform-independent, it can be performed on any conventional ultrasonography scanner from any manufacturer. This accessibility, along with the advantages of QUS as a noninvasive and relatively cost-effective imaging technique, could allow QUS to be used in large-scale screens of the population and in clinical trials.