Hepatic Steatosis Quantification with Ultrasound
Hepatic Steatosis Quantification with Ultrasound
批准号:
10436480
负责人:
Shigao Chen
金额:
$57.66万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-04-01 至 2026-03-31
关键词:
AffectAgreementAlgorithmsAmericanBenchmarkingBiological MarkersCalibrationCardiovascular DiseasesClassificationClinicalDetectionDevelopmentDiabetes MellitusDiagnosisEvaluationFamilyFatty LiverFatty acid glycerol estersFibrosisFrequenciesGuidelinesHepatologyImageInterventionLeadLiverLiver CirrhosisLiver FibrosisMagnetic Resonance ElastographyMagnetic Resonance ImagingMeasurementMeasuresMethodsModelingModernizationNoiseOutcomePatientsPenetrationPerformancePhasePopulations at RiskProtonsROC CurveReference StandardsRegression AnalysisReproducibilityRiskScanningSerumSignal TransductionSpecificitySpeedStagingTechnologyTestingTimeX-Ray Computed Tomographyattenuationcostcost effectivedensitydiabetes managementfatty liver diseasefollow-upimprovednew technologynon-alcoholic fatty liver diseasenonalcoholic steatohepatitisnovelpatient populationpoint of careprototyperib bone structurescreeningserial imagingsignal processingsoundultrasoundwireless
中文摘要
项目摘要
肝脏脂肪变性的定量对非酒精性脂肪性肝病的治疗有重要意义(a
影响75-100万美国人的疾病),糖尿病和心血管疾病。血清
生物标志物、计算机断层扫描和现有的超声方法对于
脂肪变性分期。通过MRI测量的质子密度脂肪分数(PDFF)具有高准确性,但受到以下因素的限制:
可及性和成本。本文提出了一种新的超声技术--频谱归一化衰减技术
成像(SNAI),量化超声衰减系数,以准确进行肝脏脂肪变性分期。SNAI
不需要校准体模,并且对肋骨阴影以及相位畸变和混响具有鲁棒性
从墙里爬出来。SNAI对脂肪变性分期的准确性通过一个有希望的相关性得到证明
50例患者的MRI-PDFF相关系数为0.91。在这个项目中,我们将原型,优化和评估SNAI
一种低成本、口袋大小的无线超声探头,可以方便地用于筛查,
在护理点进行随访,如家庭医生或肝病学家的办公室。
具体目标1:技术发展。我们将使用体模和患者研究来推进和优化
无线超声探头上的SNAI。采集参数和后处理算法将
针对基波和谐波SNAI成像进行了优化。我们将抑制混响杂波和纠正
用于肝脏中的声速失配,以进行更准确的脂肪变性量化。
具体目标2:患者研究。我们将使用在Aim 1中优化的SNAI原型来研究250例脂肪变性
具有临床指征的MRI-PDFF患者,以研究SNAI用于脂肪变性定量的疗效。
将进行相关性分析,以评估SNAI与MRI-PDFF的相关性。脂肪变性也将是
根据PDFF分为S 0、S1和S2/S3。受试者操作特性分析将
评价SNAI检测≥S1和≥S2的性能。SNAI与
将使用Kappa统计量评价PDFF分类。Fibroscan CAP将用于基准测试。
具体目标3:生殖研究。两名超声医师和两名肝病住院医师将反复扫描
目标2中研究的受试者子集(50例患者)。组内相关系数将用于评价
SNAI测量的运营商间协议。模型中的患者内方差分量
将提供操作员间方差的估计值,其表示最小值的下限
纵向随访的可检测差异。
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
准确定量肝脏脂肪变性的解决方案,用于诊断和频繁随访这种非常大的
患者人群在床旁的护理设置,如一个肝病学家或家庭医生的办公室。
英文摘要
PROJECT SUMMARY
Quantification of liver steatosis has weighty implications in management of Nonalcoholic Fatty Liver Disease (a
condition affecting 75-100 million Americans), diabetes mellitus, and cardiovascular disease. Serum
biomarkers, computed tomography, and existing ultrasound methods have low sensitivity or specificity for
steatosis staging. Proton Density Fat Fraction (PDFF) measured by MRI has high accuracy, but is limited by
accessibility and cost. Here we propose a novel ultrasound technology, Spectrum Normalization Attenuation
Imaging (SNAI), to quantify ultrasound attenuation coefficient for accurate liver steatosis staging. SNAI does
not require a calibration phantom, and is robust to rib shadowing as well as phase aberration and reverberation
clutter from the body wall. Accuracy of SNAI for steatosis staging is demonstrated by a promising correlation
coefficient of 0.91 with MRI-PDFF in 50 patients. In this project, we will prototype, optimize, and evaluate SNAI
on a low-cost, pocket-sized, wireless ultrasound probe, which can be conveniently used for screening and
follow-up at the point-of-care setting such as the office of a family doctor or hepatologist.
Specific Aim 1: Technical Development. We will use phantom and patient studies to advance and optimize
SNAI on the the wireless ultrasound probe. Acquisition parameters and post processing algorithms will be
optimized for both fundamental and harmonic SNAI imaging. We will suppress reverberation clutter and correct
for sound speed mismatch in liver for more accurate steatosis quantification.
Specific Aim 2: Patient study. We will use the SNAI prototypes optimized in Aim 1 to study 250 steatosis
patients with clinically indicated MRI-PDFF to investigate the efficacy of SNAI for steatosis quantification.
Correlation analysis will be performed to assess the association of SNAI with MRI-PDFF. Steatosis will also be
categorized as S0, S1, and S2/S3 according to PDFF. Receiver operating characteristic analyses will be
performed to evaluate performance of SNAI for detecting ≥S1 and ≥S2. The agreement between SNAI and
PDFF classification will be evaluated using the Kappa statistic. Fibroscan CAP will be used for benchmarking.
Specific Aim 3: Reproducibility study. Two sonographers and two hepatology residents will repeatedly scan
a subset of subjects (50 patients) studied in Aim 2. Intraclass correlation coefficients will be used to evaluate
the inter-operator agreement for SNAI measurements. The within patient variance component from the model
will provide an estimate of the inter-operator variance, which represents a lower bound for the minimum
detectable difference for longitudinal follow-ups.
Successful completion of this project will result in a safe, cost-effective, and easily accessible ultrasound
solution for accurate quantification of liver steatosis for diagnosis and frequent follow-up of this very large
patient population at point-of-care settings such as the office of a hepatologist or family doctor.
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