About 75-100 million Americans are estimated to have fatty liver disease, which can lead to nonalcoholic steatohepatitis (NASH) and liver fibrosis. Detection of liver steatosis is important for diagnosis of NASH at early stage for timely intervention to improve outcome. Diagnosis of hepatic steatosis is also important for management of diabetes and cardiovascular disease. Serum biomarkers, computed tomography, and B-mode ultrasound have limited sensitivity for detecting steatosis. Proton Density Fat Fraction (PDFF) measured by MRI has high accuracy, but is limited by accessibility and cost. The value of ultrasound attenuation coefficient (UAC) for steatosis evaluation has been confirmed by many studies. Therefore, technologies that are compatible with clinical ultrasound scanners to measure UAC can meet this critical need by providing a low- cost, widely accessible, and accurate staging of steatosis. Here we propose a novel technology, Spectrum Normalization Attenuation Measurement (SNAM), to measure liver UAC. SNAM does not require a calibration phantom, and instead uses the ratio of spectra at two nearby frequencies to cancel the effects of focusing and depth-dependent gain for accurate measurement of UAC. SNAM is compatible with clinical ultrasound scanners and can provide 2D UAC images. In phantom studies, SNAM measurements using focused beams or plane waves matched well with calibrated values. SNAM results obtained in 10 patients had a correlation coefficient of 0.97 with PDFF, showing its high promise.
Specific Aim 1 : Optimization of SNAM. We will use phantom and patient studies to optimize SNAM on the GE Logiq E9 and the Verasonics scanners, which represent the wide spectrum of commercial scanners (with focused beam or plane wave imaging) used in clinical practice. Acquisition parameters of fundamental and harmonic imaging modes and post-processing algorithms will be optimized. A novel noise subtraction method will be studied to suppress noise and improve SNAM penetration. Signal-to-noise ratio will be calculated to guide automatic selection of frequency range used for SNAM measurements.
Specific Aim 2 : Patient study. We will use the SNAM optimized in Aim 1 to study 50 patients with clinically indicated PDFF-MRI to investigate the efficacy of SNAM for steatosis grading. Each patient will be scanned twice by two sonographers. The intraclass correlation coefficient will be used to assess the reproducibility of SNAM measurements. Correlation analysis will be performed to assess the association of the UAC obtained via SNAM with PDFF. Steatosis will also be categorized as S0, S1, S2, and S3 according to PDFF. Receiver operating characteristic analyses will be performed to establish SNAM cut-points which detect ?S1, ?S2, and ?S3. The agreement between SNAM and PDFF classification will be evaluated using the Kappa statistic. Successful completion of this project will result in a safe, cost-effective, and easily accessible ultrasound technology for frequent and accurate evaluation of liver steatosis.
About 75-100 million Americans are estimated to have fatty liver disease, which can lead to nonalcoholic steatohepatitis (NASH) and liver fibrosis. Detection of liver steatosis is important for management of NASH, diabetes, and cardiovascular disease. In this study, we will develop and test a new ultrasound technology for safe, cost-effective, accurate, and frequent evaluation of liver steatosis.
