grant

Renal Microvessel Imaging for Characterization of Chronic Kidney Disease

Organization MAYO CLINIC ROCHESTERLocation ROCHESTER, UNITED STATESPosted 16 Feb 2023Deadline 31 Dec 2027
NIHUS FederalResearch GrantFY2026ANOVAAffectAgreementAmericanAnalysis of VarianceAnimalsBenchmarkingBest Practice AnalysisBindingBiopsyBlood Flow VelocityBlood flowCAT scanCT X RayCT XrayCT imagingCT scanCell Communication and SignalingCell SignalingChronic Kidney FailureChronic Renal DiseaseChronic Renal FailureClinicalClinical ResearchClinical StudyComputed TomographyContrast AgentContrast DrugsContrast MediaCortical vasculatureDecision MakingDevelopmentDiameterEchographyEchotomographyEuthanasiaFamily suidaeGlomerular Filtration RateHealth Care CostsHealth CostsHistologyHumanImageImage EnhancementImaging technologyIntracellular Communication and SignalingKidneyKidney DiseasesKidney Urinary SystemLengthLogistic RegressionsMR ImagingMR TomographyMRIMRIsMagnetic Resonance ImagingMeasurementMeasuresMedical Imaging, Magnetic Resonance / Nuclear Magnetic ResonanceMedical UltrasoundMercy KillingMethodsMicrobubblesModelingModern ManMolecular InteractionMorphologyNMR ImagingNMR TomographyNephropathyNoiseNormal RangeNormal ValuesNuclear Magnetic Resonance ImagingOutcomePathologyPatientsPenetrationPerformancePerfusionPigsProteinuriaROC AnalysesROC CurveRadiopaque MediaRandom AllocationRandom SelectionReceiver Operating CharacteristicsReceiver Operator CharacteristicsReference StandardsRegression AnalysesRegression AnalysisRegression DiagnosticsRenal Artery StenosisRenal DiseaseRenal VascularRenal vesselsSamplingScanningSignal TransductionSignal Transduction SystemsSignalingSpeedStagingStatistical RegressionSuidaeSwineTechnologyTestingThickThicknessTomodensitometryToxic effectToxicitiesUltrasonic ImagingUltrasonogramUltrasonographyUltrasound DiagnosisUltrasound Medical ImagingUltrasound TestValidationVariance AnalysesX-Ray CAT ScanX-Ray Computed TomographyX-Ray Computerized TomographyX-ray microtomographyXray CAT scanXray Computed TomographyXray computerized tomographyXray microtomographyZeugmatographyarteriolebenchmarkbiological signal transductioncatscanchronic kidney diseasecomputed axial tomographycomputer tomographycomputerized axial tomographycomputerized tomographycontrast CTcontrast enhancedcontrast enhanced CTcontrast enhanced computed tomographycortical blood vesselscortical microvascularcortical microvesselscortical vascularcortical vesselscost effectivedamage to kidneydensitydevelopmentaldiagnostic ultrasoundelastic imagingelasticity imagingelastographyexperimentexperimental researchexperimental studyexperimentshealthy volunteerimage-based methodimagingimaging methodimaging modalityimaging studyimaging systemimprovedindexingkidney biopsykidney cortexkidney cortical portionkidney damagekidney disorderkidney imagingkidney vascularkidney vascular structuremetermicro CTmicro computed tomographymicroCTmicrotomographynon-contrast CTnoncontrast CTnoncontrast computed tomographynovelperfusion imagingporcinereceiver operating characteristic analysesreceiver operating characteristic curverenalrenal biopsyrenal cortexrenal damagerenal disorderrenovascularsonogramsonographysound measurementsuidsuper high resolutionsuperresolutiontechnology implementationtechnology validationtoolultra high resolutionultra resolutionultrafine resolutionultrasoundultrasound imagingultrasound scanningvalidationsvascular bedvenule
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Full Description

PROJECT SUMMARY
Chronic kidney disease (CKD) is estimated to affect 30 million Americans and incur healthcare cost of $30.9

billion every year. There is an urgent need of a safe and noninvasive clinical tool for accurate staging of CKD,

which is essential for its management. The importance of renal parenchyma perfusion and vasculature

morphology for CKD characterization has been documented by many studies, but is not used clinically due to

lack of translatable imaging solutions. In this project, we will use a novel super-resolution ultrasound imaging

(SRUI) technology, which can resolve 50-micron renal cortex microvessels and measure their blood flow speed

in human, to quantify cortex microvessel morphology and perfusion for accurate CKD characterization.

Aim 1: Technical development. New acquisition and processing methods will be developed to enhance

performance of SRUI through phantom and patient experiments. Novel quantitative parameters of SRUI for

renal cortex will be developed, which includes vessel density, diameter, and tortuosity, as well as mean blood

flow velocity, micro- Resistive Index of arterioles and venules, and perfusion index.

Aim 2: Animal validations. We will study 7 normal pigs and 14 CKD pigs with renal artery stenosis (RAS) to

validate SRUI measurements using independent measurements obtained through contrast enhanced CT,

micro-CT, and histology.

Aim 3: Clinical study. We will study 50 healthy volunteers to establish the normal range of SRUI parameters

and study 116 CKD patients with clinically indicated renal biopsy to investigate the efficacy of SRUI for CKD

staging, using biopsy histology as the reference standard. Statistical difference between CKD patients and

healthy controls and differences across CKD stages defined by histology will be evaluated. The association of

each ultrasound parameter with histology CKD score will be assessed. Univariate and multivariate logistic

regression and ROC analyses (receiver operating characteristic) analyses will be performed to assess the

performance of SRUI, conventional ultrasound (renal length, cortex thickness, Doppler renal resistive index,

and shear wave elastography), and clinical parameters (eGFR and proteinuria) for distinguishing histology

CKD stages. A subset (N=45) of patients will be scanned by two sonographers randomly selected from a pool

of five sonographers. Intraclass correlation coefficients will be used to evaluate the inter-sonographer

agreement. The inter-sonographer variance will be calculated to estimate the minimum detectable difference

for longitudinal follow-ups.

Successful completion of this project will result in a safe, noninvasive, cost-effective, and accessible ultrasound

technology for accurate characterization of chronic kidney disease to guide treatment decision making.

Grant Number: 5R01DK129205-04
NIH Institute/Center: NIH

Principal Investigator: Shigao Chen

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