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OUR RESEARCH FOCUS

• Establishing a Non-invasive Smartphone-Based Methods for Cardiovascular Monitoring and Diagnosis

• Project Team Members: Michael W Fong MD (Clinical Collaborator), Soren Cole BS, Jing Liu PhD, Robert Kloner MD PhD (HMRI)

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• The main goal of this project is to establish a noninvasive smartphone based system to measure various cardiovascular functions such as LVEF. Our second goal is to use the phonocardiogram signal of our smartphone-based system to detect heart valve diseases. We validate our findings with Cardiac MRI.

• Hemodynamics of Heart-Aorta-Brain Coupling

• Project Team Members: Soha Niroumandi MS


• The general hypothesis of this project is that wave dynamics in the aorta dominate the pulsatile hemodynamics of the heart, the brain, and the nonlinear interaction between the two. This project aims to elucidate systems-level effects of aortic hemodynamics on heart-brain interactions. The research efforts of this work combine state-of-the-art experimentation, cutting-edge numerical simulation, and novel hybrid physics-informed machine learning to elucidate the underlying fluid dynamics mechanisms of heart-aorta-brain (H-A-B) coupling. This research will also provide a new fundamental understanding about the physics of waves in deformable tubes.

• Hemodynamic Mechanisms Linking Aortic Arch Stiffness with Brain Insult

• Project Team Members: Kevin King MD (Co-PI), Coskun Bilgi MS, Faisal Amlani PhD


• This study is designed to enhance understanding of vascular pathology that leads to dementia, comparing data generated with advanced MRI tools, wet lab fluid dynamics simulation tuned to the MRI-derived variables, and a mathematical description of the healthy vs. hypertensive aged vasculature; insights from this work may point to novel targets for preventing dementia. Our long-term goal is to develop non-invasive, inexpensive, and easy-to-use predictive measures of brain vascular health- including later in life- that can be used to estimate disease risk, and monitor disease progression and response to therapy.

• Brain Injury in Heart Failure

• Project Team Members: Kevin King MD (Co-PI), Coskun Bilgi MS, Soha Niroumandi MS


• Heart failure is not just disease of the heart and the systems-based description of the disease includes several physical and physiological abnormalities. In this project, we take a systems (engineering) approach to investigate the effects of changes in LV–aortic system on brain insult. The systems approach is necessary to characterize higher-order interactions between the LV and aorta and the effect of that interaction on brain function in HF patients. Brain insults will be quantified by automated WMH volume for microvascular disease, cerebrospinal (CSF) fluid beta-amyloid (Aβ) measurements and indices of global function, memory and executive function from a comprehensive neuropsychological battery.

• Noninvasive and Early Detection of Acute Cardiovascular Events

• Project Team Members: Robert A Kloner MD PhD (Collaborator), Rashid Alavi PhD, Jiajun Li, MS, Wangde Dai MD (Collaborator, HMRI)


• We are using combination of in-vivo animal model (Sprague Dawley rats), in-vitro experiments (LV-Aortic simulator), and computational simulations to develop methods that can capture changes in the dynamics of cardiovascular system during acute myocardial infarction (MI) and acute hemorrhage. Our goal in this project is to develop a noninvasive and easy-to-use method for early detection of acute cardiovascular events such as MI (heart attack) and internal hemorrhage.

• Cardiac Triangle Mapping Theory for Noninvasive Measurement of LV End Diastolic Pressure (LVEDP)

• Project Team Members: Ray Matthews MD (Co-PI), Melissa Ramos BSN RN CCRP, Kathryn Huang BS, Deniz Rafiei MS


• Dr. Pahlevan has recently developed a new cardiovascular dynamics theory called “Cardiac Triangle Mapping (CTM)” that enables clinician to measure LVEDP noninvasively. In collaboration with Dr. Matthews group, we are testing our hypothesis that a noninvasive CTT method can be used to compute LVEDP. Various noninvasive methodologies can be adopted to compute LVEDP from CTM method. We are also using in-vitro fluid mechanic experiments for further development of CTM method.

• New mathematical and computational analysis tools for physics-based cardiovascular predictions

• Project Team Members: Faisal Amlani PhD, Heng Wei MS


• We are developing a novel, high-performance framework for comprehensive numerical analysis of hemodynamics in the entire circulatory system. Based on a new spectral and dispersionless method for accurate resolution of the partial differential equation governing the fluid-structure interactions, we are building a complete and versatile solver suite---with stable and consistent multiphysics (e.g., heart models, mass transport) and multiscale coupling (e.g., 1D-3D). We will use such fast, stable and accurate methodologies (together with clinical data) towards developing AI-based surrogate models for the study of new biomarkers and for the solution of optimization problems in clinical parameter/outcome identification.

• Cardiac Radial MRI Tagging Application in Heart Failure and Coronary Heart Diseases

• Project Team Members: Abbas Moghaddam PhD (Co-PI)


• Dr. Moghaddam has recently developed a couple of novel tools for evaluation of cardiac deformation, rotation, and function. His works on radial tagging are an essential part of our ongoing projects on heart failure and coronary heart diseases. This project has both theoretical and clinical aspects. Our specific clinical goals are: i) early detection of cardiac deterioration; ii) diagnosis of heart failure with preserved ejection fraction; and iii) detection of coronary artery stenosis. We also aim to further improve these techniques to make it fast and even real-time.

• Percutaneous left ventricular assist device (PeLVAD)

• Project Team Members: Robert A Kloner MD PhD (Collaborator), Wangde Dai MD (Collaborator, HMRI), Deniz Rafiei, MS


• Based on our recent work on optimization of aortic wave dynamics and Dr. Kloner group's research, we are developing a novel percutaneous device and system that can be personalized based on an individual cardiovascular condition to favor a specific clinical need such as reducing workload on the heart, increasing blood flow to renal system, or increasing cerebral blood flow. This project is a combination of in-vitro fluid mechanic experiments and CFD simulations followed by in-vivo animal models.

• Noninvasive Hemodynamic Monitoring of Pediatric Patients

• Project Team Members: Andrew Cheng MD (Co-PI), Jennifer Miller MD PhD


• Our goal in this project is to modify our smartphone-based hemodynamic monitoring system for pediatric application to detect cardiomyopathy, low cardiac output, and left heart valve diseases.

• Artificial Intelligence Technology for Heart Monitoring

• Project Team Members: Ajay Vaydia MD (Co-PI), Aaron Wolfson MD, Abbas Moghaddam PhD, Coskun Bilgi MS, Soha Niroumandi MS, Deniz Rafiei MS, Myra Ziad MS


• The main goal of this project is to develop a noninvasive, inexpensive machine learning- based intervention for heart failure (HF) patients to reduce morbidity, hospitalizations, and improve their quality of life. We validate our findings with both Cardiac MRI and Echocardiogram. We assess the efficacy and implement our method for noninvasive monitoring of acute and chronic heart failure (HF). We will implement our technologies in resource limited settings including in a public health system with a high burden of disease and an ability to improve quality of life and health care outcomes for marginalized populations.