Ultrasound Evaluation of Liver Steatosis
肝脏脂肪变性的超声评估
基本信息
- 批准号:10264795
- 负责人:
- 金额:$ 23.85万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-09-16 至 2023-06-30
- 项目状态:已结题
- 来源:
- 关键词:AgreementAlgorithmsAmericanBenchmarkingBiological MarkersCalibrationCardiovascular DiseasesCardiovascular systemClassificationClinicalDetectionDiabetes MellitusDiagnosisEvaluationFatty LiverFatty acid glycerol estersFrequenciesGuidelinesImageIndividualInterventionLateralLeadLiverLiver CirrhosisLiver FibrosisLiver diseasesLogistic RegressionsMagnetic Resonance ImagingMeasurementMeasuresMethodsNoiseOutcomePatientsPenetrationPopulationProtonsROC CurveReproducibilityRiskScanningSeriesSerumSignal TransductionStagingTechnologyTestingTimeTransducersUltrasonographyUnited StatesX-Ray Computed Tomographyattenuationclinical practiceclinical translationcostcost effectivedensitydiabetes managementimprovedimproved outcomeliver biopsyliver imagingnew technologynonalcoholic steatohepatitisnovelpatient populationscreeningscreening guidelines
项目摘要
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.
项目总结
据估计,约有7500万至1亿美国人患有脂肪肝,这可能会导致非酒精性肝病
脂肪性肝炎(NASH)和肝纤维化。肝脏脂肪变性的检测对NASH的早期诊断具有重要意义
及时干预以改善结果的阶段。肝脏脂肪变性的诊断也很重要
糖尿病和心血管疾病的管理。血清生物标记物、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)测量
MRI具有较高的准确性,但受可及性和成本的限制。超声衰减系数的取值
(UAC)用于脂肪变性的评估已被许多研究证实。因此,技术是
与临床超声扫描仪兼容测量UAC可以满足这一关键需求,通过提供低-
成本低廉,可广泛获取,并可准确地对脂肪变性进行分期。
本文提出了一种新的测量技术--频谱归一化衰减测量(SNAM
肝脏UAC。SNAM不需要校准模体,而是使用附近两个光谱的比率
为了准确测量UAC,可消除聚焦和随深度变化的增益对频率的影响。
SNAM与临床超声扫描仪兼容,可提供2D UAC图像。在幻影研究中,
使用聚焦光束或平面波进行的SNAM测量与校准值匹配良好。新名
10例患者的检测结果与PDFF的相关系数为0.97,具有较高的应用前景。
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,它们代表了广泛的商用扫描仪(带
聚焦光束或平面波成像)在临床实践中使用。基波和基波的采集参数
将优化谐波成像模式和后处理算法。一种新的降噪方法
将研究抑制噪声和提高SNAM渗透率。信噪比将计算为
指导自动选择用于SNAM测量的频率范围。
具体目标2:患者研究。我们将使用目标1中优化的SNAM来研究50例临床上
提示PDFF-MRI可用于评价SNAM对脂肪变性分级的疗效。每个病人都将接受扫描
两次都是由两个超声波技师做的。组内相关系数将被用来评估
SNAM测量。将执行相关分析以评估所获得的UAC的关联性
通过带有PDFF的SNAM。根据PDFF,脂肪变性也将被归类为S0、S1、S2和S3。接收机
将执行操作特性分析,以建立检测≥S1、≥S2和
≥S3。SNAM和PDFF分类之间的一致性将使用Kappa统计进行评估。
该项目的成功完成将带来一种安全、经济、易于获得的超声波
用于频繁和准确地评估肝脏脂肪变性的技术。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Shigao Chen其他文献
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