grant

4D Flow MRI in Assessment of True Severe Low-Gradient Aortic Stenosis

Organization UNIVERSITY OF LOUISVILLELocation LOUISVILLE, UNITED STATESPosted 1 Sept 2023Deadline 31 May 2027
NIHUS FederalResearch GrantFY2024(4D) flow MRI3-D3-Dimensional3D4-D MR imaging4-D MRI4-D flow MR imaging4-D flow MRI4-D flow imaging4-D flow magnetic resonance imaging4-D magnetic resonance imaging4D MR imaging4D MRI4D flow MR imaging4D flow MRI4D flow imaging4D flow magnetic resonance imaging4D magnetic resonance imagingAdoptedAffectAnatomic SitesAnatomic structuresAnatomyAortic DiseasesAortic StenosisAortic Valve StenosisAortic valvular disordersAreaArtifactsBreathingCatheterizationCessation of lifeChestChronicClassificationClinicalCorrelation StudiesDeathDiagnosticDiagnostic MethodDiagnostic ProcedureDiagnostic TechniqueDobutamineDobutamine Stress EchocardiographyDoppler EchocardiographyDoppler StudyDropsEchocardiogramEchocardiographyEmbolization TherapyEmbolotherapyEnrollmentEquationFaintingGoalsHeartHeart Valve DiseasesHeart failureImageLVEFLearningLeft Ventricular Ejection FractionLiquid substanceMR ImagingMR TomographyMRIMRIsMagnetic Resonance ImagingMapsMeasurementMeasuresMedical Imaging, Magnetic Resonance / Nuclear Magnetic ResonanceMethodsModalityMorphologic artifactsNMR ImagingNMR TomographyNatureNoiseNuclear Magnetic Resonance ImagingOperative ProceduresOperative Surgical ProceduresPatientsProtocolProtocols documentationRespiratory AspirationRespiratory InspirationRestRiskSafetyScanningSeveritiesSeverity of illnessStatistical CorrelationStratificationStressSubgroupSurgicalSurgical InterventionsSurgical ProcedureSurvival RateSymptomsSyncopeSystematicsTherapeutic EmbolizationThoraceThoracicThoraxTransthoracic EchocardiographyValvular Heart DiseasesValvular Heart DisorderWorkZeugmatographyadverse consequenceadverse outcomeaged groupaged groupsaged individualaged individualsaged peopleaged personaged personsaged populationaged populationsaging populationanatomic imaginganatomical imagingaortic disorderaortic valveaortic valve defectaortic valve diseaseaortic valve disorderaortic valve replacementaortic valvular diseasecardiac failurecardiac valve diseasecardiac valve disordercardiac valvular diseasedata spacedata to traindataset to traindeep learningdeep learning methoddeep learning strategydegenerative valvular heart diseasedisease severityembolizationenrollfluidfour dimensional MR imagingfour dimensional MRIfour dimensional flowfour dimensional magnetic resonance imagingheart sonographyheart valve disorderhemodynamicshuman subjectimage-based methodimagingimaging methodimaging modalityimprovedinspirationliquidpopulation agingpressurerespiratorysimulationsurgerythree dimensionaltomographytraining dataultrasound
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Full Description

Degenerative aortic stenosis is a progressive valvular heart disease affecting the aging population and when
hemodynamically significant is associated with serious adverse outcomes, such as heart failure, syncope, and

death. Although, symptomatic classical severe aortic stenosis (AS), wherein aortic valve anatomical or effective

area is ≤ 1.0 𝑐𝑚2 and mean gradient ≥ 40 mmHg raises no diagnostic dilemma, patients with low gradient aortic

stenosis (i.e., mean gradient < 40 mmHg) that may be severe (i.e., aortic valve area ≤ 1.0 𝑐𝑚2) remain a

challenge for determining the true severity of aortic stenosis and present a significant unmet clinical need. The

discordance between aortic valve area of ≤ 1.0 𝑐𝑚2 and mean gradient < 40 mmHg is encountered in as many

as 30 to 40% of patients with aortic valve area ≤ 1.0 𝑐𝑚2 by transthoracic echocardiography (TTE). In patients

with these discordant findings, the true severity is uncertain and have led to the use of dobutamine stress

echocardiography (DSE). Based on DSE, one can classify the potentially severe low-gradient subjects into 4

distinct subgroups a) Low gradient severe aortic stenosis (LGS): aortic valve area of ≤ 1.0 𝑐𝑚2 and a mean

gradient of ≥ 40 mmHg with DSE. b) Low gradient pseudo-severe aortic stenosis (LGPS): aortic valve area of >

1.0 𝑐𝑚2 and a mean gradient of < 40 mmHg with DSE. c) Low gradient indeterminate aortic stenosis severity

(LGI): aortic valve area of ≤ 1.0 𝑐𝑚2 and a mean gradient of < 40 mmHg with DSE. d) Finally, aortic valve area

of > 1.0 𝑐𝑚2 and a mean gradient of ≥ 40 mmHg with DSE are classified as moderate or less severe aortic

stenosis (LSA). Nearly one-third of patients classified as LGS are classified as LGPS with DSE (6). Further,

compounding the concern in patients classified as LGPS, LGI, LSA is that they often manifest with symptoms

potentially attributable to severe AS suggesting an initial misclassification perhaps due to measurement errors.

Compared to echo, with MRI, the velocities can be measured in all 3D directions and due to its tomographic

nature, no geometric assumptions are required. The hypothesis of the study is that our planned CMR methods

which we will develop based on previous work will be able to better stratify these AS subjects. Our specific aims

are: 1) We will develop efficient rest and dobutamine stress 4D Spiral flow imaging protocols based on k-space

dependent respiratory gating. 2) We have recently developed a Deep Learning framework which based on

Computational Fluid Dynamics (CFD) simulations of training data learns to directly map velocities to pressures.

This will be adapted to measure the transvalvular pressure gradients (TVPG) in human subjects and validated.

3) In 40 subjects with potentially severe low gradient AS (10 in each of the LGS, LGPS, LGI, LSA), a TTE study,

and a CMR study will be performed both at rest and under dobutamine stress. To validate, TVPG will be

measured with cath in a group with n=10 of moderate AS (MAS) subjects undergoing cath for other purposes.

This group will also undergo TTE and CMR studies. Subjects with severe AS were not selected for cath for safety

reasons. Classification across modalities, flow, velocity, pressure, and orifice area will be statistically correlated.

Grant Number: 5R21AG080859-02
NIH Institute/Center: NIH

Principal Investigator: AMIR AMINI

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