Computational Modeling

and Heart Disorders

Fast and Automatic Reconstruction of High Frame-Rate Cardiac Magnetic Resonance

DANIEL WELLER, Asst. Prof. Electrical and Computer Engineering (SEAS), CHRISTOPHER KRAMER, Prof. Medicine – Cardiovascular Medicine and Radiology (SOM), MICHAEL SALERNO, Assoc. Prof., Medicine – Cardiovascular Medicine (SOM)

Heart disease accounts for a large fraction of deaths and hospitalizations in the United States. Emerging new cardiac magnetic resonance imaging (CMR) techniques have the potential to improve both diagnosis and management of heart disease, but these new techniques often require intensive data processing that delays scan results and discourages routine clinical use. 

In this project, engineers from UVA’s Department for Electrical and Computer Engineering and doctors from UVA’s Department of Cardiovascular Medicine and Radiology will collaborate to develop and test fast, automated algorithms for processing high-resolution CMR. The ultimate goal of their work is to enable the widespread use of sophisticated imaging techniques that are currently only available at academic centers such at UVA.

In situ Bioengineering of Scar Formation after Myocardial Infarction

Brent French, Prof. Biomedical Engineering (SOM), Jeff Saucerman, Assoc. Prof. Biomedical Engineering (SOM), Matthew Wolf, Assoc. Prof. Medicine – Cardiovascular Medicine (SOM)

Myocardial infarction (MI), or heart attack, occurs in approximately 800,000 people in the United States every year. One of the most successful therapies following a heart attack is called reperfusion therapy, which brings blood flow back to the region of the heart that has been injured by MI. Besides restoring blood flow to oxygen-starved heart muscle, reperfusion also improves clinical outcomes by expediting the replacement of dead heart muscle with scar tissue after MI.

In this project, bioengineers from UVA’s Department of Biomedical Engineering and a cardiologist from UVA’s Department of Medicine will take a highly innovative approach that harnesses two technologies developed at UVA to design and test new therapies to further improve the wound healing response in the heart after MI. The team will use computational models of the complex biology of cardiac fibroblasts to identify specific proteins inside those cells that might be modulated to improve the healing response, and then test their predictions by using viral gene delivery to regulate the levels of those proteins in animal models.

Engineering-Medicine Partnership on Sleep and Cardiovascular Research

Hyojung Kang, Asst. Prof, Systems & Information Engineering (SEAS), Younghoon Kwon, Asst. Prof, Medicine-Cardiovascular (SOM), Jeongok Logan, Asst. Prof, Nursing – Acute & Specialty Care (SON), Jennifer Lobo, Asst. Prof, Public Health Sciences (SOM), Min-Woong Sohn, Assoc. Prof, Public Health Sciences (SOM)

Healthy sleep helps our bodies maintain normal homeostasis, while impaired sleep produces a wide range of adverse health outcomes, including increased risk for cardiovascular disease (CVD). Specifically, obstructive sleep apnea, insomnia, abnormal sleep duration and poor sleep quality are each known to increase the risk of CVD-related morbidity and mortality. 

This truly interdisciplinary team, with experts from the UVA Department of Systems and Information Engineering, Department of Medicine, Department of Public Health Sciences and the School of Nursing, aims to harness a unique database of over 5000 sleep studies to examine the relationship between sleep and cardiovascular disease and to find previously unknown relationships important to predictive and precise medical care.


and Voice Disorders

A New Engineering Protocol for Diagnosis and Treatment of Voice Disorders

James Daniero, Assist. Prof, Otolaryngology (SOM), Haibo Dong, Assoc. Prof, Mechanical & Aerospace Engineering (SEAS)

An estimated 7.5 million people in the United States have a voice disorder, one-third of which can be attributed to vocal cord paralysis or weakness. Diagnosis and treatment options are limited by the fact that characterization of voice conditions requires an understanding of a patient’s specific anatomy and how air flows through their larynx – a problem that could be solved by combining CT imaging and computer modeling. The University of Virginia is uniquely positioned to study and impact treatment for this population with a research team comprised of a voice disorder expert from the Department of Otolaryngology and an engineer who studies flow dynamics in the Department of Mechanical and Aerospace Engineering.