A Pull-Back Algorithm to Determine the Unloaded Vascular Geometry in Anisotropic Hyperelastic AAA Passive Mechanics
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Biomechanical studies on abdominal aortic aneurysms (AAA) seek to provide for better decision criteria to undergo surgical intervention for AAA repair. More accurate results can be obtained by using appropriate material models for the tissues along with accurate geometric models and more realistic boundary conditions for the lesion. However, patient-specific AAA models are generated from gated medical images in which the artery is under pressure. Therefore, identification of the AAA zero pressure geometry would allow for a more realistic estimate of the aneurysmal wall mechanics. This study proposes a novel iterative algorithm to find the zero pressure geometry of patient-specific AAA models. The methodology allows considering the anisotropic hyperelastic behavior of the aortic wall, its thickness and accounts for the presence of the intraluminal thrombus. Results on 12 patient-specific AAA geometric models indicate that the procedure is computational tractable and efficient, and preserves the global volume of the model. In addition, a comparison of the peak wall stress computed with the zero pressure and CT-based geometries during systole indicates that computations using CT-based geometric models underestimate the peak wall stress by 59 ± 64 and 47 ± 64 kPa for the isotropic and anisotropic material models of the arterial wall, respectively.
KeywordsAbdominal aortic aneurysm (AAA) Patient-specific Image-based Zero pressure geometry FEA Anisotropy
The authors would like to acknowledge research funding from project 071/UPB10/12 from the University of Zaragoza, and from NIH grants R21EB007651, R21EB008804 and R15HL087268. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
- 1.Alastrué, V., A. García, E. Peña, J. F. Rodríguez, M. Martínez, and M. Doblaré. Numerical framework for patient-specific computational modelling of vascular tissue. Commun. Numer. Methods Eng. 6:1–30, 2006.Google Scholar
- 3.Brown, L. C., and J. L. Powell. Risk factors for aneurysm rupture in patients kept under ultrasound surveillance. UK small aneurysm trial participants. Ann. Surg. 230(3):289–296, 1999; discussion 296–297.Google Scholar
- 12.Gasser, T. C. Bringing vascular biomechanics into clinical practice. Simulation-based decisions for elective abdominal aortic aneurysms repair. In: Patient-Specific Computational Modeling. Lecture Notes in Computational Vision and Biomechanics, edited by B. Calvo, and E. Pena. Dordrecht: Springer, 2012.Google Scholar
- 19.Holzapfel, G. A. Nonlinear Solid Mechanics. A Continuum Approach for Engineering. Chichester: John Wiley & Sons Ltd., 2000, 455 pp.Google Scholar
- 37.Shum, J., E. S. Di Martino, A. Goldhammer, D. Goldman, L. Acker, G. Patel, J. H. Ng, G. Martufi, and E. A. Finol. Semi-automatic vessel wall detection and quantification of wall thickness in computed tomography images of human abdominal aortic aneurysms. Med. Phys. 37(2):638–648, 2010.PubMedCrossRefGoogle Scholar
- 41.Thompson, S. G., H. A. Ashton, L. Gao, R. A. P. Scott, and Multicentre Aneurysm Screening Study Group. Screening men for abdominal aortic aneurysm: 10 year mortality and cost effectiveness results from the randomised Multicentre Aneurysm Screening Study. Brit. Med. J. 338:2307, 2009.Google Scholar
- 45.Venkatasubramaniam, A. K., M. J. Fagan, T. Mehta, K. J. Mylankal, B. Ray, G. Kuhan, I. C. Chetter, and P. T. McCollum. A comparative study of aortic wall stress using finite element analysis for rupture and non-ruptured abdominal aortic aneurysms. Eur. J. Vasc. Endovasc. Surg. 28:168–176, 2004.PubMedGoogle Scholar