Congratulations to Alison Marsden for receiving the National Science Foundation CAREER Award!
ABSTRACT
For the past century, advances in cardiovascular surgery have mainly come about through a `trial and error' approach, using surgeon experience, and evaluation of patient outcomes to judge success. On the other hand, the engineering field has developed sophisticated tools for computational simulation and optimization that have now become commonplace in the the design process. Similar tools could greatly benefit the medical field by offering the means to systematically test new surgical designs at no risk to the patient, and to customize designs for individual patients. While great strides have been made in developing cardiovascular simulation methods, hurdles remain before ordering a patient-specific simulation is as easy as, for example, ordering a chest x-ray. Major roadblocks to adoption of these methods in the clinic include the current lack of cyberinfrastructure that can achieve clinically relevant time frames, as well as a lack of tools for efficient manipulation and optimization of surgical designs.
The main objective of this project is to pioneer the development of novel and efficient computational methods which can be applied for optimization in surgery and device design, and to demonstrate the use of these tools using high performance computing. Novel cyberinfrastructure will be developed, including new physics-based tools for patient specific geometry parameterization, and expanded optimization and uncertainty quantification methods for use in a parallel environment. This optimization and uncertainty framework will result in a multi-layered parallel computing structure, in which multiple cost function evaluations will be performed simultaneously, each requiring a multi-processor finite element simulation. These unique computational approaches will be applied to three cardiovascular shape optimization applications using high performance computing. In particular, the PI will apply the computational methods and tools to (1) perform customization of designs for surgery to treat children with single ventricle heart defects, (2) quantify hemodynamics in coronary aneurysms caused by Kawasaki disease, and (3) perform robust design to improve coronary artery bypass graft surgery. The PI will also use systematic uncertainty quantification tools to assess the reliability of cardiovascular simulations to improve confidence in results. In the future, this framework will be used to design individual treatments for patients suffering from a wide range of congenital and acquired heart diseases. These tools have potential to impact quality of life for patients, delay the need for a heart transplant, increase exercise tolerance for children with heart defects, and in some cases reduce mortality. The application of optimal design tools will bring a paradigm shift to the medical community by offering the first quantitative and systematic methods for optimizing surgeries and treatment plans at no risk to the patient. These tools will have broader use in a range of engineering applications requiring coupling between optimization and large scale numerical solvers, including turbulence, combustion, fluid structure interaction, and medical device design.
We will lead an integrated interdisciplinary education and outreach plan that will draw high school students, particularly women and minorities, to the field of engineering and computational science. Our education plan will address training needs in a new interdisciplinary area by exposing students to cardiovascular medicine, and doctors to quantitative simulation-based tools. The outreach program, including an after school science program and a booth at the San Diego Science Festival, will draw disadvantaged students to science and engineering by exposing them to emerging research and career options.