Computational Stability Analysis to Predict Heart Failure after Myocardial Infarction
Computational Stability Analysis to Predict Heart Failure after Myocardial Infarction
批准号:
10669258
负责人:
Martin R Pfaller
金额:
$15.74万
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:
已结题
起止时间:
2022-09-01 至 2024-08-31
关键词:
AmericanBiologyBiomechanicsCalibrationCardiacCardiovascular ModelsCardiovascular systemCell modelCellsClinicalClinical DataCollagenCompensationComputer ModelsConfidence IntervalsDataData SetDevelopmentDevelopment PlansDiagnosticDimensionsElastinEngineeringEnvironmentEquilibriumFamily suidaeFeedbackFibrosisFoundationsFundingGeneticGoalsGrowthHeartHeart DiseasesHeart failureHomeostasisHumanImpairmentInfarctionKnowledgeLeft ventricular structureLinkLocationMeasurementMechanicsMedical Device DesignsMedical ImagingMentorsModelingMuscle CellsMyocardial InfarctionMyocardial tissueMyocardiumOrganPatient-Focused OutcomesPatientsPatternPerformancePhasePhysiologic intraventricular pressurePrediction of Response to TherapyProcessProductivityPropertyPublicationsPublishingQuality of lifeRecordsResearchResourcesRiskRisk FactorsSarcomeresScientistShapesStimulusStructureTestingTherapeuticTimeTissuesTrainingUniversitiesValidationVentricularbiobankcardiac magnetic resonance imagingcareercareer developmentclinical decision-makingclinical predictorsclinical translationextracellularheart functionhemodynamicshuman subjectimprovedin vivoinsightkinematicsmulti-scale modelingneglectnovelpersonalized diagnosticspersonalized medicinepredictive modelingpressurepreventskillstargeted treatmenttheoriesvirtual environment
中文摘要
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英文摘要
PROJECT SUMMARY
Myocardial infarction (MI) can lead to heart failure (HF), which severely impacts the quality of life of millions of
Americans. MI triggers a cascade of cardiac growth and remodeling (G&R) patterns. They change ventricular
size, shape, and function, driven by biomechanical, neurohormonal, and genetic stimuli. Adaptive short-term
G&R can stabilize cardiac performance. Yet, in many patients, adverse long-term G&R is unstable and
progresses to HF. Unfortunately, those patients lack robust clinical predictors because the biomechanical
stimuli of adverse G&R patterns are still unclear. Computational models of full-heart biomechanics, informed by
cardiac magnetic resonance imaging (CMR), show high potential to fill this gap. The foundation of this project
is a novel microstructure-based model of cell-scale G&R based on the homogenized constrained mixture
theory, co-developed by the applicant, Dr. Pfaller. In addition, this research plan will leverage a multiscale
model that combines cell-scale G&R and organ-scale cardiac contraction and validation with CMR in swine
and humans to predict the propensity to develop HF with the mechanobiological stability theory. In Aim 1, Dr.
Pfaller will refine and validate a framework for subject-specific models of cardiac G&R. After calibrating the
model to pressure and kinematic CMR measurements in control swine, he will introduce MI to the multiscale
model and validate the prediction of G&R with matching measurements in post-MI swine. In Aim 2, Dr. Pfaller
will quantify the propensity of developing adverse G&R with the mechanobiological stability theory and identify
risk factors of post-MI HF from infarct properties. He will test the validity of his HF prediction with longitudinal
human CMR and clinical data from the UK Biobank. Dr. Pfaller has excellent prior training in cardiac
biomechanics, medical imaging, and computational engineering with an established publication record in
cardiac and cardiovascular biomechanics. His career development plan (K99-phase) will provide additional
training in cardiac biology and using CMR for human subjects. Dr. Pfaller will also receive a wealth of informal
and didactic training at Stanford University, which will be critical for Dr. Pfaller to gain autonomy and launch a
productive career as an independent engineering-scientist. Mentor Dr. Marsden is a leading expert in patient-
specific modeling of the cardiovascular system. Co-Mentor Dr. Ennis (CMR) and advisors Drs. Humphrey (cell-
scale modeling), Cyron (stability theory), Kuhl (organ-scale modeling), Yang (cardiac biology), Salerno (heart
failure) offer complementary expertise. Dr. Pfaller will receive the necessary guidance and resources to
accomplish these goals and efficiently transition to independence (R00-phase). In summary, the strong
mentoring environment and training plan will fully prepare Dr. Pfaller to launch his independent career. The
proposed studies promise to offer insights into biomechanical stimuli of adverse G&R and help optimize
diagnostics and therapies that predict and ultimately prevent HF after MI.
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Learning reduced-order models for cardiovascular simulations with graph neural networks.
使用图神经网络学习心血管模拟的降阶模型。
DOI:
10.1016/j.compbiomed.2023.107676
发表时间:
2024
期刊:
Computers in biology and medicine
影响因子:
7.7
作者:
[Pegolotti,Luca, Pfaller,MartinR, Rubio,NataliaL, Ding,Ke, BrugarolasBrufau,Rita, Darve,Eric, Marsden,AlisonL]
通讯作者:
Marsden,AlisonL
A probabilistic neural twin for treatment planning in peripheral pulmonary artery stenosis.
用于外周肺动脉狭窄治疗计划的概率神经双胞胎。
DOI:
10.1002/cnm.3820
发表时间:
2024
期刊:
International journal for numerical methods in biomedical engineering
影响因子:
2.1
作者:
[Lee,JohnD, Richter,Jakob, Pfaller,MartinR, Szafron,JasonM, Menon,Karthik, Zanoni,Andrea, Ma,MichaelR, Feinstein,JeffreyA, Kreutzer,Jacqueline, Marsden,AlisonL, Schiavazzi,DanieleE]
通讯作者:
Schiavazzi,DanieleE
DOI:
10.1007/s10237-023-01747-w
发表时间:
2023-12
期刊:
BIOMECHANICS AND MODELING IN MECHANOBIOLOGY
影响因子:
3.5
作者:
[Gebauer, Amadeus M., Pfaller, Martin R., Braeu, Fabian A., Cyron, Christian J., Wall, Wolfgang A.]
通讯作者:
Wall, Wolfgang A.
Non-invasive estimation of pressure drop across aortic coarctations: validation of 0D and 3D computational models with in vivo measurements.
主动脉缩窄压降的无创估计:通过体内测量验证 0D 和 3D 计算模型。
DOI:
10.1101/2023.09.05.23295066
发表时间:
2023
期刊:
medRxiv : the preprint server for health sciences
影响因子:
--
作者:
[Nair,PriyaJ, Pfaller,MartinR, Dual,SerainaA, McElhinney,DoffB, Ennis,DanielB, Marsden,AlisonL]
通讯作者:
Marsden,AlisonL
Computational Stability Analysis to Predict Heart Failure after Myocardial Infarction
-
批准号:10525749
-
项目类别:
-
资助金额:$16.71万
-
财政年份:2022
-
负责人:Martin R Pfaller
-
依托单位:
国内基金
海外基金
Journal of Integrative Plant Biology
-
批准号:31024801
-
项目类别:专项基金项目
-
资助金额:24.0万元
-
批准年份:2010
-
负责人:贺萍
-
依托单位: