During the past two decades, there have been significant advances in understanding of pathophysiology and biomechanics of abdominal aortic aneurysms (AAAs). In particular, incorporation of patient-specific geometries in computational biomechanical analysis promises that the computational biomechanics becomes an essential tool for AAA risk assessment. Conventional finite element analysis, however, uses advances in medical imaging only to define patient-specific lesion geometry, but do not relate the geometrical features with alterations in biomechanics from long-term vascular adaptation during the enlargement. We previously studied CT images of small AAAs obtained from longitudinal studies of three patients and, using a growth and remodeling (G&R) model of AAAs developed from our group, found that the stress distribution of AAAs can be altered by interacting with spine vertebrae during the enlargement. In collaboration with Dr. Whal Lee at Seoul National University Hospital in South Korea, we have obtained two to nine sets of follow-up CT images from eight more patients with the mean surveillance interval of 355 days. The main goals of this project, therefore, are i) to exploit this unique data ad to understand biomechanically why the observed changes in morphology of AAAs occur, ii) to identify specific morphological features that will estimate the stress distribution better and iii) to develop a computational framework to better predict rupture risk for small AAAs based on medical images and computational analyses over a small number of longitudinal studies.
The specific aims are: (1) to develop a quantitative image analysis to characterize morphological changes of AAAs using series of 3D CT images, and investigate correlations between geometrical parameters and the local expansion, (2) to develop a numerical inverse method using a novel G&R model and two longitudinal images from the same patient to predict the evolution of lesion geometry, and (3) to utilize the results from Aim &2 and the G&R model of AAAs to study effects of local wall expansion and interactions with the spinal vertebrae on the lesion geometry, stress distribution, and rupture risk. The uniqueness of this research stems from our novel G&R model and the unique set of longitudinal patient data that is essential for building and validating such models. The proposed research will significantly increase our understanding of biomechanics of AAAs during their progression and will provide a necessary step toward the clinical application of vascular G&R models for AAA risk assessment and treatment.

Public Health Relevance

Even with vast increase in understanding of abdominal aortic aneurysm pathology and advances in biomedical imaging and biomechanical analysis, rupture of small aneurysms continues to cause a high rate of mortality. In the proposed research, we will develop a new biomechanical method that can utilize multiple medical images from a patient to increase our understanding of biomechanics of enlarging aneurysms and to provide better prediction of likelihood of rupture of abdominal aortic aneurysms.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL115185-01
Application #
8345771
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Danthi, Narasimhan
Project Start
2012-08-01
Project End
2016-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
1
Fiscal Year
2012
Total Cost
$184,235
Indirect Cost
$59,235
Name
Michigan State University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
193247145
City
East Lansing
State
MI
Country
United States
Zip Code
48824
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Farsad, Mehdi; Zeinali-Davarani, Shahrokh; Choi, Jongeun et al. (2015) Computational Growth and Remodeling of Abdominal Aortic Aneurysms Constrained by the Spine. J Biomech Eng 137:
Seyedsalehi, Sajjad; Zhang, Liangliang; Choi, Jongeun et al. (2015) Prior Distributions of Material Parameters for Bayesian Calibration of Growth and Remodeling Computational Model of Abdominal Aortic Wall. J Biomech Eng 137:101001
Kwon, Sebastian T; Burek, William; Dupay, Alexander C et al. (2015) Interaction of expanding abdominal aortic aneurysm with surrounding tissue: Retrospective CT image studies. J Nat Sci 1:e150
Gharahi, H; Zambrano, B A; Lim, C et al. (2015) On growth measurements of abdominal aortic aneurysms using maximally inscribed spheres. Med Eng Phys 37:683-91
Kim, Jungsil; Peruski, Brooke; Hunley, Chris et al. (2013) Influence of surrounding tissues on biomechanics of aortic wall. Int J Exp Comput Biomech 2:105-117