Skip to main content
SpringerLink
Log in

The Effect of Uncertainty in Vascular Wall Material Properties on Abdominal Aortic Aneurysm Wall Mechanics

  • Conference paper
  • First Online:
Computational Biomechanics for Medicine

Abstract

Clinical management of abdominal aortic aneurysms (AAA) can benefit from patient-specific computational biomechanics-based assessment of the disease. Individual variations in shape and aortic material properties are expected to influence the assessment of AAA wall mechanics. While patient-specific geometry can be reproduced using medical images, the accurate individual and regionally varying tissue material property estimation is currently not feasible. This work addresses the relative uncertainties arising from variations in AAA material properties and its effect on the ensuing wall mechanics. Computational simulations were performed with five different isotropic material models based on an ex-vivo AAA wall material characterization and a subject population sample of 28 individuals. Care was taken to exclude the compounding effects of variations in all other geometric and biomechanical factors. To this end, the spatial maxima of the principal stress (σ max), principal strain (ε max), strain-energy density (ψ max), and displacement (δ max) were calculated for the diameter-matched cohort of 28 geometries for each of the five different constitutive materials. This led to 140 quasi-static simulations, the results of which were assessed on the basis of intra-patient (effect of material constants) and inter-patient (effect of individual AAA shape) differences using statistical averages, standard deviations, and Box and Whisker plots. Mean percentage variations for σ max, ε max, ψ max, and δ max for the intra-patient analysis were 1.5, 7.1, 8.0, and 6.1, respectively, whereas for the inter-patient analysis these were 11.1, 4.5, 15.3, and 12.9, respectively. Changes in the material constants of an isotropic constitutive model for the AAA wall have a negligible influence on peak wall stress. Hence, this study endorses the use of population-averaged material properties for the purpose of estimating peak wall stress, strain-energy density, and wall displacement. Conversely, strain is more dependent on the material constant variation than on the differences in AAA shape in a diameter-matched population cohort.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Thompson RW (2005) Aneurysm treatments expand. Nat Med 11(12):1279–1281

    Article  Google Scholar 

  2. Gretarsdottir S, Baas AF, Thorleifsson G et al (2010) Genome-wide association study identifies a sequence variant within the DAB2IP gene conferring susceptibility to abdominal aortic aneurysm. Nat Genet 42(8):692–697

    Article  Google Scholar 

  3. Limet R, Sakalihasan N, Defawe OD (2005) Abdominal aortic aneurysm. Lancet 365(9470):1577–1589

    Article  Google Scholar 

  4. Chaikof EL, Brewster DC, Dalman RL et al (2009) The care of patients with an abdominal aortic aneurysm: the Society for Vascular Surgery practice guidelines. J Vasc Surg 50(4 suppl):S2–S49

    Article  Google Scholar 

  5. Raghavan ML, Vorp DA, Federle MP et al (2000) Wall stress distribution on three-dimensionally reconstructed models of human abdominal aortic aneurysm. J Vasc Surg 31(4):760–769

    Article  Google Scholar 

  6. Choke E, Cockerill G, Wilson WR et al (2005) A review of biological factors implicated in abdominal aortic aneurysm rupture. Eur J Vasc Endovasc Surg 30(3):227–244

    Article  Google Scholar 

  7. Lederle FA, Johnson GR, Wilson SE et al (2002) Rupture rate of large abdominal aortic aneurysms in patients refusing or unfit for elective repair. JAMA 287(22):2968–2972

    Article  Google Scholar 

  8. Brown LC, Epstein D, Manca A et al (2004) The UK Endovascular Aneurysm Repair (EVAR) trials: design, methodology and progress. Eur J Vasc Endovasc Surg 27(4):372–381

    Article  Google Scholar 

  9. Stenbaek J, Kalin B, Swedenborg J (2000) Growth of thrombus may be a better predictor of rupture than diameter in patients with abdominal aortic aneurysms. Eur J Vasc Endovasc Surg 20(5):466–469

    Article  Google Scholar 

  10. Pappu S, Dardik A, Tagare H et al (2008) Beyond fusiform and saccular: a novel quantitative tortuosity index may help classify aneurysm shape and predict aneurysm rupture potential. Ann Vasc Surg 22(1):88–97

    Article  Google Scholar 

  11. Vorp DA, Raghavan ML, Webster MW (1998) Mechanical wall stress in abdominal aortic aneurysm: influence of diameter and asymmetry. J Vasc Surg 27(4):632–639

    Article  Google Scholar 

  12. Doyle BJ, Callanan A, Burke PE et al (2009) Vessel asymmetry as an additional diagnostic tool in the assessment of abdominal aortic aneurysms. J Vasc Surg 49(2):443–454

    Article  Google Scholar 

  13. Darling RC, Messina CR, Brewster DC et al (1977) Autopsy study of unoperated abdominal aortic aneurysms: the case for early resection. Circulation 56(3 suppl):II161–II164

    Google Scholar 

  14. Powell JT, Sweeting MJ, Brown LC et al (2011) Systematic review and meta-analysis of growth rates of small abdominal aortic aneurysms. Br J Surg 98(5):609–618

    Article  Google Scholar 

  15. Raghavan ML, Vorp DA (2000) Toward a biomechanical tool to evaluate rupture potential of abdominal aortic aneurysm: identification of a finite strain constitutive model and evaluation of its applicability. J Biomech 33(4):475–482

    Article  Google Scholar 

  16. Rodriguez JF, Ruiz C, Doblare M et al (2008) Mechanical stresses in abdominal aortic aneurysms: influence of diameter, asymmetry, and material anisotropy. J Biomech Eng 130(2):021023

    Article  Google Scholar 

  17. Vande Geest JP, Schmidt DE, Sacks MS et al (2008) The effects of anisotropy on the stress analyses of patient-specific abdominal aortic aneurysms. Ann Biomed Eng 36(6):921–932

    Article  Google Scholar 

  18. Vande Geest JP, Simon BR, Mortazavi A (2006) Toward a model for local drug delivery in abdominal aortic aneurysms. Ann NY Acad Sci 1085:396–399

    Article  Google Scholar 

  19. Vande Geest JP, Wang DH, Wisniewski SR et al (2006) Towards a noninvasive method for determination of patient-specific wall strength distribution in abdominal aortic aneurysms. Ann Biomed Eng 34(7):1098–1106

    Article  Google Scholar 

  20. Vande Geest JP, Di Martino ES, Bohra A et al (2006) A biomechanics-based rupture potential index for abdominal aortic aneurysm risk assessment: demonstrative application. Ann NY Acad Sci 1085:11–21

    Article  Google Scholar 

  21. Maier A, Gee MW, Reeps C et al (2010) A comparison of diameter, wall stress, and rupture potential index for abdominal aortic aneurysm rupture risk prediction. Ann Biomed Eng 38(10):3124–3134

    Article  Google Scholar 

  22. Wang DH, Makaroun MS, Webster MW et al (2002) Effect of intraluminal thrombus on wall stress in patient-specific models of abdominal aortic aneurysm. J Vasc Surg 36(3):598–604

    Article  Google Scholar 

  23. Doyle BJ, Callanan A, McGloughlin TM (2007) A comparison of modelling techniques for computing wall stress in abdominal aortic aneurysms. Biomed Eng Online 6:38

    Article  Google Scholar 

  24. Reeps C, Gee M, Maier A et al (2010) The impact of model assumptions on results of computational mechanics in abdominal aortic aneurysm. J Vasc Surg 51(3):679–688

    Article  Google Scholar 

  25. Speelman L, Schurink GW, Bosboom EM et al (2010) The mechanical role of thrombus on the growth rate of an abdominal aortic aneurysm. J Vasc Surg 51(1):19–26

    Google Scholar 

  26. Doyle BJ, McGloughlin TM (2011) Computer-aided diagnosis of abdominal aortic aneurysms. In: McGloughlin TM (ed) Biomechanics and mechanobiology of aneurysms. Springer, Berlin, pp 119–138. doi:http://dx.doi.org/10.1007/8415_2011_70

    Chapter  Google Scholar 

  27. Shum J, Martufi G, Di Martino ES et al (2011) Quantitative assessment of abdominal aortic aneurysm geometry. Ann Biomed Eng 39(1):277–286

    Article  Google Scholar 

  28. Shum J, DiMartino ES, Goldhammer A et al (2010) Semiautomatic vessel wall detection and quantification of wall thickness in computed tomography images of human abdominal aortic aneurysms. Med Phys 37(2):638–648

    Article  Google Scholar 

  29. Raut SS, Jana A, Finol EA (2014) AAAmesh: a framework for patient-specific multi-domain vascular mesh generation with a capability for modeling spatially varying wall thickness. Comput Methods Biomech Biomed Eng Imaging Vis (in press)

    Google Scholar 

  30. Raut SS (2012) Patient-specific 3D vascular reconstruction and computational assessment of biomechanics—an application to abdominal aortic aneurysm. PhD Thesis, Carnegie Mellon University, Pittsburgh, PA

    Google Scholar 

  31. CGAL: computational geometry algorithms library. http://www.cgal.org

  32. Raghavan ML, Kratzberg J, Castro de Tolosa EM et al (2006) Regional distribution of wall thickness and failure properties of human abdominal aortic aneurysm. J Biomech 39(16): 3010–3016

    Article  Google Scholar 

  33. Bathe K-J (1996) Finite element procedures. Prentice Hall, Englewood Cliffs

    Google Scholar 

  34. Sussman T, Bathe K-J (1987) A finite element formulation for nonlinear incompressible elastic and inelastic analysis. Comp Struct 26(1–2):357–409

    Article  MATH  Google Scholar 

  35. ADINA R&D Inc. (2011) ADINA theory and modeling guide: volume I -ADINA solids & structures. ADINA R&D Inc., Watertown

    Google Scholar 

  36. Fillinger MF, Marra SP, Raghavan ML et al (2003) Prediction of rupture risk in abdominal aortic aneurysm during observation: wall stress versus diameter. J Vasc Surg 37(4):724–732

    Article  Google Scholar 

  37. Fillinger MF, Racusin J, Baker RK et al (2004) Anatomic characteristics of ruptured abdominal aortic aneurysm on conventional CT scans: implications for rupture risk. J Vasc Surg 39(6):1243–1252

    Article  Google Scholar 

  38. Raut SS, Jana A, De Oliveira V et al (2013) The importance of patient-specific regionally varying wall thickness in abdominal aortic aneurysm biomechanics. J Biomech Eng 135(8):081010

    Article  Google Scholar 

  39. Volokh KY (2010) Comparison of biomechanical failure criteria for abdominal aortic aneurysm. J Biomech 43(10):2032–2034

    Article  Google Scholar 

  40. Gasser TC, Auer M, Labruto F et al (2010) Biomechanical rupture risk assessment of abdominal aortic aneurysms: model complexity versus predictability of finite element simulations. Eur J Vasc Endovasc Surg 40(2):176–185

    Article  Google Scholar 

  41. Polzer S, Gasser TC, Bursa J et al (2013) Importance of material model in wall stress prediction in abdominal aortic aneurysms. Med Eng Phys 35(9):1282–1289

    Article  Google Scholar 

  42. Inzoli F, Boschetti F, Zappa M et al (1993) Biomechanical factors in abdominal aortic aneurysm rupture. Eur J Vasc Surg 7(6):667–674

    Article  Google Scholar 

  43. Elger DF, Blackketter DM, Budwig RS et al (1996) The influence of shape on the stresses in model abdominal aortic aneurysms. J Biomech Eng 118(3):326–332

    Article  Google Scholar 

  44. Stringfellow MM, Lawrence PF, Stringfellow RG (1987) The influence of aorta-aneurysm geometry upon stress in the aneurysm wall. J Surg Res 42(4):425–433

    Article  Google Scholar 

  45. Shum J, Martufi G, Di Martino ES et al (2011) Quantitative assessment of abdominal aortic aneurysm geometry. Ann Biomed Eng 39(1):277–286

    Article  Google Scholar 

  46. Speelman L, Bosboom EM, Schurink GW et al (2008) Patient-specific AAA wall stress analysis: 99-percentile versus peak stress. Eur J Vasc Endovasc Surg 36(6):668–676

    Article  Google Scholar 

  47. Rodriguez JF, Martufi G, Doblare M et al (2009) The effect of material model formulation in the stress analysis of abdominal aortic aneurysms. Ann Biomed Eng 37(11):2218–2221

    Article  Google Scholar 

  48. Lee K, Zhu J, Shum J et al (2013) Surface curvature as a classifier of abdominal aortic aneurysms: a comparative analysis. Ann Biomed Eng 41(3):562–576

    Article  Google Scholar 

  49. Scotti CM, Shkolnik AD, Muluk SC et al (2005) Fluid-structure interaction in abdominal aortic aneurysms: effects of asymmetry and wall thickness. Biomed Eng Online 4:64

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge research funding from NIH grants R21EB007651, R21EB008804, and R15HL087268, and NSF grant HRD-0932339. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the National Science Foundation. This research was also supported by an allocation of advanced computing resources supported by the National Science Foundation (Teragrid grant TG-CTS050051N). Some of the computations were performed on the Blacklight system at the Pittsburgh Supercomputing Center.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA

    Samarth S. Raut

  2. Department of Biomedical Engineering, The University of Texas at San Antonio, AET 1.360, One UTSA Circle, San Antonio, TX, 78249, USA

    Samarth S. Raut & Ender A. Finol

  3. Scientific Applications and User Services, Pittsburgh Supercomputing Center, Pittsburgh, PA, USA

    Anirban Jana

  4. Department of Management Science and Statistics, The University of Texas at San Antonio, San Antonio, TX, USA

    Victor De Oliveira

  5. Division of Vascular Surgery, Western Pennsylvania Allegheny Health System, Allegheny General Hospital, 320 East North Avenue, Pittsburgh, PA, USA

    Satish C. Muluk

Authors
  1. Samarth S. Raut
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anirban Jana
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victor De Oliveira
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Satish C. Muluk
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ender A. Finol
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ender A. Finol .

Editor information

Editors and Affiliations

  1. Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, West Australia, Australia

    Barry Doyle

  2. Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, West Australia, Australia

    Karol Miller

  3. Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, West Australia, Australia

    Adam Wittek

  4. Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand

    Poul M.F. Nielsen

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this paper

Cite this paper

Raut, S.S., Jana, A., De Oliveira, V., Muluk, S.C., Finol, E.A. (2014). The Effect of Uncertainty in Vascular Wall Material Properties on Abdominal Aortic Aneurysm Wall Mechanics. In: Doyle, B., Miller, K., Wittek, A., Nielsen, P. (eds) Computational Biomechanics for Medicine. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0745-8_6

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-0745-8_6

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4939-0744-1

  • Online ISBN: 978-1-4939-0745-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation