Currently, aortic aneurysm rupture potential is primarily evaluated based on the aneurysm diameter;however, the overall aneurysm diameter has been shown to be an unreliable predictor of aneurysm rupture. Specific aneurysm geometry and aortic tissue properties can have a profound effect on the vessel wall stress for each individual patient;therefore, it is critical to consider the patient-specific aortic root and ascending aorta geometry and elastic properties to accurately assess the risk of aneurysm rupture. Therefore, my goal in this study is to utilize clinical diagnostic 64-slice CT images, coupled with experimentally derived aneurismal tissue properties, to develop patient-specific finite element models for the analysis of ascending aortic aneurysm in bicuspid aortic valve (BAV) patients. To accomplish this goal, I will study and compare healthy tricuspid valve patients with no aortic aneurysm and BAV patients with aortic aneurysm. Specifically, I will perform 1) Modeling of patient-specific aortic geometries using statistical shape models;2) Integration of patient-specific aortic tissue properties with their geometries in the development of patient-specific finite element models of the aortic root and the ascending aorta;and 3) Analysis of vessel wall stress and aneurysm rupture potential and elicitation of a more reliable predictor than the current size criterion. This research training fellowship will provide me with the unique opportunity to learn the interdisciplinary knowledge of cardiovascular disease and its treatment using engineering tools. Throughout this training, I will work closely with my sponsor Dr. Wei Sun, an expert in the field of cardiovascular biomechanics, my co-sponsor, Dr. James Duncan, an expert in the field of medical image analysis, and my cosponsor, Dr. John Elefteriades, a renowned cardiac surgeon and expert on aortic aneurysms. I will learn how to apply imaging analysis techniques, engineering mechanics principles, and computational sciences to analyze aortic biomechanics. I will also be trained on the process of the design, implementation, and evaluation of biomedical research. Completion of this training fellowship will be a vital stepping stone in my journey to become an independent researcher in the field of cardiovascular biomechanics.

Public Health Relevance

Bicuspid aortic valve is a common variant of the normal three-leaflet aortic valve, and patients with this condition are prone to developing aneurysms in the ascending aorta. This study is aimed to define the correlation between bicuspid valve anatomy and aortic aneurysm development by utilizing clinical computed tomography scans and experimentally derived tissue properties to develop patient-specific finite element models for the biomechanical analysis of aneurysms in these patients.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
7F31HL112632-03
Application #
8762692
Study Section
Special Emphasis Panel (ZRG1-F15-P (20))
Program Officer
Meadows, Tawanna
Project Start
2014-01-06
Project End
2016-01-05
Budget Start
2014-01-06
Budget End
2015-01-05
Support Year
3
Fiscal Year
2014
Total Cost
$42,232
Indirect Cost
Name
Georgia Institute of Technology
Department
Type
DUNS #
097394084
City
Atlanta
State
GA
Country
United States
Zip Code
30332
Martin, Caitlin; Sun, Wei (2014) Simulation of long-term fatigue damage in bioprosthetic heart valves: effects of leaflet and stent elastic properties. Biomech Model Mechanobiol 13:759-70
Martin, Caitlin; Sun, Wei; Pham, Thuy et al. (2013) Predictive biomechanical analysis of ascending aortic aneurysm rupture potential. Acta Biomater 9:9392-400