grant

Hepatic Steatosis Quantification with Ultrasound

Organization MAYO CLINIC ROCHESTERLocation ROCHESTER, UNITED STATESPosted 1 Apr 2022Deadline 31 Mar 2027
NIHUS FederalResearch GrantFY2025Active Follow-upAffectAgreementAlgorithmsAmericanBenchmarkingBest Practice AnalysisBindingBiological MarkersBlood SerumCAT scanCT X RayCT XrayCT imagingCT scanCalibrationCardiovascular DiseasesCategoriesCell Communication and SignalingCell SignalingClassificationClinicalClutteringsComputed TomographyDetectionDevelopmentDiabetes MellitusDiagnosisEvaluationExclusionFamilyFatsFatty LiverFatty acid glycerol estersFibrosisFrequenciesGroups at riskGuidelinesH+ elementHepatic CirrhosisHepatologyHydrogen IonsImageInterventionIntracellular Communication and SignalingLiverLiver CirrhosisLiver FibrosisLiver SteatosisMR ImagingMR TomographyMRIMRIsMagnetic Resonance ElastographyMagnetic Resonance ImagingMeasurementMeasuresMedical Imaging, Magnetic Resonance / Nuclear Magnetic ResonanceMethodsModelingModernizationMolecular InteractionNAFLDNASHNMR ImagingNMR TomographyNoiseNuclear Magnetic Resonance ImagingOutcomePatientsPenetrationPeople at riskPerformancePersons at riskPhasePopulations at RiskProtonsROC AnalysesROC CurveRandom AllocationRandom SelectionRecommendationReference StandardsRegression AnalysesRegression AnalysisRegression DiagnosticsReproducibilityRibsRiskScanningSerumSignal TransductionSignal Transduction SystemsSignalingSpecificitySpeedStagingStatistical RegressionSystematicsTechnologyTestingTimeTomodensitometryX-Ray CAT ScanX-Ray Computed TomographyX-Ray Computerized TomographyXray CAT scanXray Computed TomographyXray computerized tomographyZeugmatographyactive followupattenuationbenchmarkbio-markersbiologic markerbiological signal transductionbiomarkercardiovascular disordercatscancomputed axial tomographycomputer tomographycomputerized axial tomographycomputerized tomographycostcost effectivedensitydetection sensitivitydevelopmentaldiabetesdiabetes managementdiabetes mellitus managementdiabetic managementfatty liver diseasefibrotic liverfollow upfollow-upfollowed upfollowuphepatic body systemhepatic fibrosishepatic organ systemhepatic steatosishepatosteatosisimagingimaging detectionimaging-based detectionimaging-based disease detectionimprovedlongitudinal imagingnew technologynon-alcohol fatty liver diseasenon-alcohol induced steatohepatitisnon-alcoholic fatty liver diseasenon-alcoholic liver diseasenon-alcoholic steato-hepatitisnon-alcoholic steatohepatitisnon-contrast CTnonalcoholic fatty liver diseasenonalcoholic steato-hepatitisnonalcoholic steatohepatitisnoncontrast CTnoncontrast computed tomographynovelnovel technologiespatient populationpoint of careprototypereceiver operating characteristic analysesreceiver operating characteristic curverib bone structurescreeningscreeningsserial imagingsignal processingsoundstatisticsultrasoundwireless
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Full Description

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.

Grant Number: 5R01DK127978-04
NIH Institute/Center: NIH

Principal Investigator: Shigao Chen

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