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Computational Stability Analysis to Predict Heart Failure after Myocardial Infarction

预测心肌梗死后心力衰竭的计算稳定性分析

基本信息

批准号：
10525749
负责人：
Martin R Pfaller
金额：
$ 16.71万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10525749
关键词：
American Biology Biomechanics Cardiac Cardiovascular Models Cardiovascular system Cell model Cells Clinical Clinical Data Collagen Computer Models Confidence Intervals Data Data Set Development Development Plans Diagnostic Dimensions Elastin Engineering Environment Equilibrium Family suidae Feedback Fibrosis Foundations Funding Genetic Goals Growth Heart Heart Diseases Heart failure Homeostasis Human Impairment Infarction Knowledge Lead Left ventricular structure Link Location Measurement Mechanics Medical Device Designs Medical Imaging Mentors Modeling Muscle Cells Myocardial Infarction Myocardial tissue Myocardium Organ Patient-Focused Outcomes Patients Pattern Performance Phase Physiologic intraventricular pressure Process Property Publications Publishing Quality of life Records Research Resources Risk Risk Factors Sarcomeres Scientist Shapes Stimulus Testing Therapeutic Time Tissues Training Universities Validation Ventricular Yang base biobank cardiac magnetic resonance imaging career career development clinical decision-making clinical predictors clinical translation extracellular heart function hemodynamics human subject improved in vivo insight kinematics multi-scale modeling neglect novel personalized diagnostics personalized medicine predictive modeling pressure prevent skills targeted treatment theories virtual environment

项目摘要

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.

项目总结