Ultrasound Evaluation of Liver Steatosis

项目摘要 据估计，大约有75-100万美国人患有脂肪肝，这可能导致非酒精性肝病。 脂肪性肝炎（NASH）和肝纤维化。检测肝脏脂肪变性对NASH的早期诊断具有重要意义 及时干预以改善结果阶段。肝脂肪变性的诊断也很重要， 糖尿病和心血管疾病的管理。血清生物标志物、计算机断层扫描和B超 超声检测脂肪变性的灵敏度有限。质子密度脂肪分数（PDFF），通过 MRI具有很高的准确性，但受到可及性和成本的限制。超声衰减系数值 (UAC)对于脂肪变性的评估已经被许多研究所证实。因此， 与临床超声扫描仪兼容以测量UAC可以通过提供低- 脂肪变性的成本、广泛可及性和准确分期。 在这里，我们提出了一种新的技术，频谱归一化衰减测量（SNAM），以测量 肝脏UAC。SNAM不需要校准体模，而是使用两个附近的光谱的比率， 频率，以消除聚焦和深度相关增益的影响，以准确测量UAC。 SNAM与临床超声扫描仪兼容，可提供2D UAC图像。在幻影研究中， 使用聚焦波束或平面波的SNAM测量与校准值匹配良好。Snam 在10名患者中获得的结果与PDFF的相关系数为0.97，显示出其高前景。 具体目标1：SNAM的优化。我们将使用体模和患者研究来优化SNAM GE Logiq E9和Verasonics扫描仪，代表了广泛的商用扫描仪（具有 聚焦波束或平面波成像）。采集基波和 将优化谐波成像模式和后处理算法。一种新的噪声消减方法 将研究抑制噪声和提高SNAM渗透。信噪比将计算为 引导自动选择用于SNAM测量的频率范围。 具体目标2：患者研究。我们将使用在目标1中优化的SNAM来研究50例临床上患有 表明PDFF-MRI研究SNAM对脂肪变性分级的有效性。每个病人都要接受扫描 两次都是由两个超声波医生做的组内相关系数将用于评估以下各项的重现性： SNAM测量。将进行相关性分析，以评估获得的UAC 通过SNAM和PDFF。根据PDFF，脂肪变性也将被分类为S 0、S1、S2和S3。接收器 将进行操作特性分析，以确定SNAM临界点，检测≥S1、≥S2，以及 ≥S3。将使用Kappa统计量评价SNAM和PDFF分类之间的一致性。 该项目的成功完成将导致一个安全，具有成本效益，易于获得的超声 用于频繁和准确评估肝脏脂肪变性的技术。

PROJECT SUMMARY 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.