Developing Biomechanical Predictors of Ascending Thoracic Aortic Aneurysm Growth and Dissection
Developing Biomechanical Predictors of Ascending Thoracic Aortic Aneurysm Growth and Dissection
批准号:
10614562
负责人:
Elaine Evelina Tseng
金额:
$0.0万
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:
4D MRIAgeAneurysmAortaAortic AneurysmAreaAwardBiomechanicsBody Surface AreaCause of DeathCessation of lifeClinicalClinical ManagementDevelopmentDiameterDissectionEngineeringEquilibriumEventFailureFinite Element AnalysisFoundationsGeometryGoalsGrowthGuidelinesHealthcare SystemsHeightHospitalsIndividualLawsLeftLengthLiquid substanceMachine LearningMeasuresMechanicsMethodsMotivationOperative Surgical ProceduresOutcomePatientsPersonsProcessPublishingRiskRisk MarkerRoleRuptureServicesSpecific qualifier valueStressStructureSudden DeathSwellingSymptomsThoracic Aortic AneurysmThoracic aortaTimeUnited StatesVeteransVeterans Health Administrationcardiovascular emergencyclinical applicationclinical decision-makingclinical practiceclinical riskfollow-upimprovedin vivoindexingmechanical loadmortalitypatient stratificationpatient subsetspersonalized decisionprospectiverepairedrisk predictionrisk stratificationshear stresstool
中文摘要
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英文摘要
Veterans Affairs (VA) Healthcare System services >9 million veterans at 144 hospitals
nationwide. Aortic aneurysms are the 16th leading cause of death in patients >35 years old in
the United States. Dissection and rupture of aTAAs are catastrophic cardiovascular
emergencies carrying significant pre-hospital (40%) and operative (17-25%) mortality. Surgical
guidelines rely on aTAA maximum diameter, growth rate, and symptoms to guide elective
repair, which can be performed with low operative mortality. However, we and others have
demonstrated that diameter alone is not adequate to predict dissection or rupture—~60-90% of
type A dissection events occur in aTAAs with diameter <5.5cm and otherwise not meeting
elective surgical repair indications. From a biomechanics perspective, rupture or dissection is a
mechanical failure that can occur when aneurysm wall stress exceeds wall strength. Guidelines
simply use diameter as a surrogate for wall stress based on LaPlace’s Law for cylinders. Our
published studies showed that diameter was a poor predictor of wall stress due to the
complexity of individual aTAA geometries.
We propose to prospectively evaluate changes in aTAA wall stresses and distensibility to
determine their ability to improve on diameter criterion to predict dissection or death or need for
surgery in veterans with aneurysms that do not meet criteria for surgery. We propose to
prospectively evaluate changes in aneurysm wall shear stresses, flow velocities, and vortices in
veterans with nonsurgical sized aTAAs over time to determine their ability to predict aneurysm
growth and need for surgery. This proposal lays the foundation for practical clinical application
of patient-specific biomechanics and fluid dynamics to improve risk prediction of aortic
dissection, sudden death, aTAA growth, and need for surgery with the following aims:
Aim 1: To determine changes in longitudinal wall stresses using finite element analysis (FEA) to
correlate with clinical composite endpoint of aortic dissection, need for surgical repair, or sudden
death in prospectively followed veterans (n=400) with nonsurgical aTAA <5.5cm over 4 years.
Aim 2: To determine changes in aTAA wall strength using the surrogate of in vivo aortic
distensibility to correlate with clinical composite endpoint of aortic dissection, aTAA surgical
repair, or sudden death in prospectively followed veterans (n=400) with nonsurgical aTAA
<5.5cm over 4 years.
Aim 3: To determine changes in aTAA circumferential wall stresses and wall shear stresses,
flow velocities, and eccentricity using fluid structure interaction (FSI), validate with 4D flow
magnetic resonance imaging (MRI), and correlate with clinical composite endpoint of aortic
growth or need for surgical repair in prospectively followed veterans (n=400) with nonsurgical
aTAA <5.5cm over 4 years.
Aim 4: To develop a machine learning (ML) approach to determine biomechanical and fluid
dynamic parameters in Aim 1-3 in prospectively followed veterans (n=320) with nonsurgical
aTAA <5.5cm, validate the results (n=80), and simplify the process of personalized
biomechanics prediction.
At the end of the project, we will have developed a new biomechanics based clinical tool for
effective clinical management for non-surgical aTAA patients.
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批准号:9212382
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项目类别:
-
资助金额:$0.0万
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财政年份:2016
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负责人:Elaine Evelina Tseng
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依托单位:
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