Ph.D. Students Excel in Heart Research
Recently, the American Heart Association (AHA) awarded eight pre-doctoral fellowships, chosen from 72 applicants within the highly competitive AHA Founders Region (CT, RI, MA, VT, ME, NH, NY, NJ). UConn’s own Qian Wang was awarded one of these coveted pre-doctoral fellowships. In earning this award, Qian joins three fellow graduate students – Thuy Pham, Eric Sirois and Caitlin Martin – working in the Tissue Mechanics Laboratory (TML) under the mentorship of Prof. Wei Sun (Mechanical Engineering and Biomedical Engineering) to win a prestigious, highly competitive national pre-doctoral fellowship.
The students, all doctoral candidates, are involved in work aimed at improving the treatments of cardiovascular diseases by applying state-of-the-art experimental evaluation and rigorous computational models to better understand the cardiovascular system’s functioning and how the body interacts with implantable devices. Their research projects are described briefly below.
Thuy Pham, who began working at the TML as a BME senior student in 2007, received a four-year Ruth L. Kirchstein National Research Service Award pre-doctoral fellowship from the National Institute of Health (NIH) in 2009. Her research focuses on the investigation of the feasibility and durability of new minimally invasive mitral valve repair devices used to treat patients with functional mitral regurgitation disease. Her research integrates experimental and computational approaches to evaluate the underlying mechanisms that may lead to device failure and to facilitate future improvement and development of the device design.
Eric Sirois (read more about Eric here) received a three-year Graduate Research Fellowship Program (GRFP) award from National Science Foundation (NSF)in 2010. Eric’s research involves the customization and combination of computational simulations, including fluid, solid, and fluid-structure interactions, to analyze heart valve mechanics. The aortic valve has three small flaps or “leaflets” that allow blood to flow one way, from the heart to the aorta. He is focusing on ways to optimize the design of replacement valves and also on the development of valve selection and placement protocols prior to surgery that will achieve higher success rates. His work to date has allowed him to accurately simulate blood flow through an amended heart valve for one patient following transcatheter aortic valve replacement (TAVR). Eric hopes that, one day, individualized pre-operative planning using simulations will become available to all patients.
Caitlin Martin, who began working at the TML as a senior BME student in 2009, received a four-year Ruth L. Kirchstein National Research Service Award pre-doctoral fellowship from NIH in 2012 to fund her research on “Patient-Specific Modeling for Analysis of Aortic Aneurysms.” Her work, collaborating with cardiac surgeons at the Yale-New Haven hospital, involves measuring the mechanical properties of aortic aneurysm tissue, extracting the aortic geometry from clinical (CT) images, and using this data to develop finite element models to assess aortic aneurysm rupture risk on a patient-specific level. Her goal is to identify the clinical indicators of rupture risk which are more accurate than the currently used maximum aneurysm diameter criterion. Watch Caitlin in our graduate video.
Qian Wang’s AHA pre-doctoral fellowship supports his research focusing on the potential use of TAVR for bicuspid aortic valve patients, who are afflicted with an aortic valve deformity in which there are only two flaps, rather than the normal three. TAVR is currently reserved for those individuals with a severe narrowing of the aortic valve opening, who are not candidates for traditional open heart surgery or are deemed too high risk for surgery. Currently, bicuspid valve patients are excluded from TAVR clinical trials. Qian’s research aims are to investigate the biomechanics involved in TAVR for bicuspid valve patients by examining patient-specific medical images and conducting computational simulations.