Annals of Biomedical Engineering

, Volume 38, Issue 4, pp 1288–1313 | Cite as

Quantification of Hemodynamics in Abdominal Aortic Aneurysms During Rest and Exercise Using Magnetic Resonance Imaging and Computational Fluid Dynamics

  • Andrea S. Les
  • Shawn C. Shadden
  • C. Alberto Figueroa
  • Jinha M. Park
  • Maureen M. Tedesco
  • Robert J. Herfkens
  • Ronald L. Dalman
  • Charles A. Taylor
Article

Abstract

Abdominal aortic aneurysms (AAAs) affect 5–7% of older Americans. We hypothesize that exercise may slow AAA growth by decreasing inflammatory burden, peripheral resistance, and adverse hemodynamic conditions such as low, oscillatory shear stress. In this study, we use magnetic resonance imaging and computational fluid dynamics to describe hemodynamics in eight AAAs during rest and exercise using patient-specific geometric models, flow waveforms, and pressures as well as appropriately resolved finite-element meshes. We report mean wall shear stress (MWSS) and oscillatory shear index (OSI) at four aortic locations (supraceliac, infrarenal, mid-aneurysm, and suprabifurcation) and turbulent kinetic energy over the entire computational domain on meshes containing more than an order of magnitude more elements than previously reported results (mean: 9.0-million elements; SD: 2.3 M; range: 5.7–12.0 M). MWSS was lowest in the aneurysm during rest 2.5 dyn/cm2 (SD: 2.1; range: 0.9–6.5), and MWSS increased and OSI decreased at all four locations during exercise. Mild turbulence existed at rest, while moderate aneurysmal turbulence was present during exercise. During both rest and exercise, aortic turbulence was virtually zero superior to the AAA for seven out of eight patients. We postulate that the increased MWSS, decreased OSI, and moderate turbulence present during exercise may attenuate AAA growth.

Keywords

Turbulence Mean wall shear stress Oscillatory shear index Mesh independence Flow waveforms Blood pressure Windkessel boundary condition Patient-specific 

Abbreviations

AAA

Abdominal aortic aneurysm

DBP

Diastolic blood pressure

IR

Infrarenal

Mid-An

Mid-aneurysm

MRI

Magnetic resonance imaging

MWSS

Mean wall shear stress

OSI

Oscillatory shear index

SB

Suprabifurcation

SBP

Systolic blood pressure

SC

Supraceliac

TKE

Turbulent kinetic energy

References

  1. 1.
    Allardice, J. T., G. J. Allwright, J. M. Wafula, and A. P. Wyatt. High prevalence of abdominal aortic aneurysm in men with peripheral vascular disease: screening by ultrasonography. Brit. J. Surg. 75:240–242, 1988.CrossRefPubMedGoogle Scholar
  2. 2.
    Asbury, C. L., J. W. Ruberti, E. I. Bluth, and R. A. Peattie. Experimental investigation of steady flow in rigid models of abdominal aortic aneurysms. Ann. Biomed. Eng. 23:29–39, 1995.CrossRefPubMedGoogle Scholar
  3. 3.
    Bax, L., C. J. Bakker, W. M. Klein, N. Blanken, J. J. Beutler, and W. P. Mali. Renal blood flow measurements with use of phase-contrast magnetic resonance imaging: normal values and reproducibility. J. Vasc. Interv. Radiol. 16:807–814, 2005.PubMedGoogle Scholar
  4. 4.
    Berguer, R., J. L. Bull, and K. Khanafer. Refinements in mathematical models to predict aneurysm growth and rupture. Ann. N.Y. Acad. Sci. 1085:110–116, 2006.CrossRefPubMedGoogle Scholar
  5. 5.
    Bluestein, D., L. Niu, R. T. Schoephoerster, and M. K. Dewanjee. Steady flow in an aneurysm model: correlation between fluid dynamics and blood platelet deposition. J. Biomech. Eng. 118:280–286, 1996.CrossRefPubMedGoogle Scholar
  6. 6.
    Bluth, E. I., S. M. Murphey, L. H. Hollier, and M. A. Sullivan. Color flow doppler in the evaluation of aortic aneurysms. Int. Angiol. 9:8–10, 1990.PubMedGoogle Scholar
  7. 7.
    Boussel, L., V. Rayz, C. McCulloch, A. Martin, G. Acevedo-Bolton, M. Lawton, R. Higashida, W. S. Smith, W. L. Young, and D. Saloner. Aneurysm growth occurs at region of low wall shear stress: patient-specific correlation of hemodynamics and growth in a longitudinal study. Stroke 39:2997–3002, 2008.CrossRefPubMedGoogle Scholar
  8. 8.
    Brady, A. R., S. G. Thompson, F. G. Fowkes, R. M. Greenhalgh, and J. T. Powell. Abdominal aortic aneurysm expansion: risk factors and time intervals for surveillance. Circulation 110:16–21, 2004.CrossRefPubMedGoogle Scholar
  9. 9.
    Brewster, D. C., J. L. Cronenwett, J. W. Hallett, Jr., K. W. Johnston, W. C. Krupski, and J. S. Matsumura. Guidelines for the treatment of abdominal aortic aneurysms. Report of a subcommittee of the joint council of the american association for vascular surgery and society for vascular surgery. J. Vasc. Surg. 37:1106–1117, 2003.CrossRefPubMedGoogle Scholar
  10. 10.
    Cheng, C. P., R. J. Herfkens, and C. A. Taylor. Abdominal aortic hemodynamic conditions in healthy subjects aged 50–70 at rest and during lower limb exercise: in vivo quantification using mri. Atherosclerosis 168:323–331, 2003.CrossRefPubMedGoogle Scholar
  11. 11.
    Cornhill, J. F., E. E. Herderick, and H. C. Stary. Topography of human aortic sudanophilic lesions. Monogr. Atheroscler. 15:13–19, 1990.PubMedGoogle Scholar
  12. 12.
    Curci, J. A., and R. W. Thompson. Adaptive cellular immunity in aortic aneurysms: cause, consequence, or context? J. Clin. Invest. 114:168–171, 2004.PubMedGoogle Scholar
  13. 13.
    Dalman, R. L., M. M. Tedesco, J. Myers, and C. A. Taylor. AAA disease: mechanism, stratification, and treatment. Ann. N.Y. Acad. Sci. 1085:92–109, 2006.CrossRefPubMedGoogle Scholar
  14. 14.
    Draney, M. T., M. T. Alley, B. T. Tang, N. M. Wilson, R. J. Herfkens, and C. A. Taylor. Importance of 3d nonlinear gradient corrections for quantitative analysis of 3d mr angiographic data. In: International Society for Magnetic Resonance in Medicine, Honolulu, HI, 2002.Google Scholar
  15. 15.
    Egelhoff, C. J., R. S. Budwig, D. F. Elger, T. A. Khraishi, and K. H. Johansen. Model studies of the flow in abdominal aortic aneurysms during resting and exercise conditions. J. Biomech. 32:1319–1329, 1999.CrossRefPubMedGoogle Scholar
  16. 16.
    Finol, E. A., K. Keyhani, and C. H. Amon. The effect of asymmetry in abdominal aortic aneurysms under physiologically realistic pulsatile flow conditions. J. Biomech. Eng. 125:207–217, 2003.CrossRefPubMedGoogle Scholar
  17. 17.
    Fleming, C., E. P. Whitlock, T. L. Beil, and F. A. Lederle. Screening for abdominal aortic aneurysm: a best-evidence systematic review for the us preventive services task force. Ann. Intern. Med. 142:203–211, 2005.PubMedGoogle Scholar
  18. 18.
    Gillum, R. F. Epidemiology of aortic aneurysm in the United States. J. Clin. Epidemiol. 48:1289–1298, 1995.CrossRefPubMedGoogle Scholar
  19. 19.
    Hance, K. A., M. Tataria, S. J. Ziporin, J. K. Lee, and R. W. Thompson. Monocyte chemotactic activity in human abdominal aortic aneurysms: role of elastin degradation peptides and the 67-kd cell surface elastin receptor. J. Vasc. Surg. 35:254–261, 2002.CrossRefPubMedGoogle Scholar
  20. 20.
    He, X., and D. N. Ku. Pulsatile flow in the human left coronary artery bifurcation: average conditions. J. Biomech. Eng. 118:74–82, 1996.CrossRefPubMedGoogle Scholar
  21. 21.
    Holenstein, R., and D. N. Ku. Reverse flow in the major infrarenal vessels—a capacitive phenomenon. Biorheology 25:835–842, 1988.PubMedGoogle Scholar
  22. 22.
    Hope, S. A., D. B. Tay, I. T. Meredith, and J. D. Cameron. Waveform dispersion, not reflection, may be the major determinant of aortic pressure wave morphology. Am. J. Physiol. Heart Circul. Physiol. 289:H2497–H2502, 2005.CrossRefGoogle Scholar
  23. 23.
    Hoshina, K., E. Sho, M. Sho, T. K. Nakahashi, and R. L. Dalman. Wall shear stress and strain modulate experimental aneurysm cellularity. J. Vasc. Surg. 37:1067–1074, 2003.PubMedGoogle Scholar
  24. 24.
    Hughes, T. J. The Finite Element Method: Linear Static and Dynamic Finite Element Analysis. Mineola, NY: Dover Publications, 107 pp., 2000.Google Scholar
  25. 25.
    Humphrey, J. D., and C. A. Taylor. Intracranial and abdominal aortic aneurysms: similarities, differences, and need for a new class of computational models. Annu. Rev. Biomed. Eng. 10:221–246, 2008.CrossRefPubMedGoogle Scholar
  26. 26.
    Khanafer, K. M., J. L. Bull, G. R. Upchurch, Jr., and R. Berguer. Turbulence significantly increases pressure and fluid shear stress in an aortic aneurysm model under resting and exercise flow conditions. Ann. Vasc. Surg. 21:67–74, 2007.CrossRefPubMedGoogle Scholar
  27. 27.
    Khanafer, K. M., P. Gadhoke, R. Berguer, and J. L. Bull. Modeling pulsatile flow in aortic aneurysms: effect of non-newtonian properties of blood. Biorheology 43:661–679, 2006.PubMedGoogle Scholar
  28. 28.
    Kim, H. J., C. A. Figueroa, T. J. R. Hughes, K. E. Jansen, and C. A. Taylor. Augmented lagrangian method for constraining the shape of velocity profiles at outlet boundaries for three-dimensional finite element simulations of blood flow. Comput. Meth. Appl. Mech. Eng. 198:3551–3566, 2009.CrossRefGoogle Scholar
  29. 29.
    Koch, A. E., S. L. Kunkel, W. H. Pearce, M. R. Shah, D. Parikh, H. L. Evanoff, G. K. Haines, M. D. Burdick, and R. M. Strieter. Enhanced production of the chemotactic cytokines interleukin-8 and monocyte chemoattractant protein-1 in human abdominal aortic aneurysms. Am. J. Pathol. 142:1423–1431, 1993.PubMedGoogle Scholar
  30. 30.
    Laskey, W. K., H. G. Parker, V. A. Ferrari, W. G. Kussmaul, and A. Noordergraaf. Estimation of total systemic arterial compliance in humans. J. Appl. Physiol. 69:112–119, 1990.PubMedGoogle Scholar
  31. 31.
    Lederle, F. A., G. R. Johnson, S. E. Wilson, E. P. Chute, R. J. Hye, M. S. Makaroun, G. W. Barone, D. Bandyk, G. L. Moneta, and R. G. Makhoul. The aneurysm detection and management study screening program: validation cohort and final results. Aneurysm detection and management veterans affairs cooperative study investigators. Arch. Intern. Med. 160:1425–1430, 2000.CrossRefPubMedGoogle Scholar
  32. 32.
    Long, A., L. Rouet, F. Vitry, J. N. Albertini, C. Marcus, and C. Clement. Compliance of abdominal aortic aneurysms before and after stenting with tissue Doppler imaging: evolution during follow-up and correlation with aneurysm diameter. Ann. Vasc. Surg. 23:49–59, 2009.CrossRefPubMedGoogle Scholar
  33. 33.
    Miller, Jr., F. J., W. J. Sharp, X. Fang, L. W. Oberley, T. D. Oberley, and N. L. Weintraub. Oxidative stress in human abdominal aortic aneurysms: a potential mediator of aneurysmal remodeling. Arterioscler. Thromb. Vasc. Biol. 22:560–565, 2002.CrossRefPubMedGoogle Scholar
  34. 34.
    Montain, S. J., S. M. Jilka, A. A. Ehsani, and J. M. Hagberg. Altered hemodynamics during exercise in older essential hypertensive subjects. Hypertension 12:479–484, 1988.PubMedGoogle Scholar
  35. 35.
    Moore, Jr., J. E., and D. N. Ku. Pulsatile velocity measurements in a model of the human abdominal aorta under resting conditions. J. Biomech. Eng. 116:337–346, 1994.CrossRefPubMedGoogle Scholar
  36. 36.
    Moore, Jr., J. E., C. Xu, S. Glagov, C. K. Zarins, and D. N. Ku. Fluid wall shear stress measurements in a model of the human abdominal aorta: oscillatory behavior and relationship to atherosclerosis. Atherosclerosis 110:225–240, 1994.CrossRefPubMedGoogle Scholar
  37. 37.
    Muller, J., O. Sahni, X. Li, K. E. Jansen, M. S. Shephard, and C. A. Taylor. Anisotropic adaptive finite element method for modelling blood flow. Comput. Meth. Biomech. Biomed. Eng. 8:295–305, 2005.Google Scholar
  38. 38.
    Myers, J., M. Prakash, V. Froelicher, D. Do, S. Partington, and J. E. Atwood. Exercise capacity and mortality among men referred for exercise testing. N. Engl. J. Med. 346:793–801, 2002.CrossRefPubMedGoogle Scholar
  39. 39.
    Nakahashi, T. K., K. Hoshina, P. S. Tsao, E. Sho, M. Sho, J. K. Karwowski, C. Yeh, R. B. Yang, J. N. Topper, and R. L. Dalman. Flow loading induces macrophage antioxidative gene expression in experimental aneurysms. Arterioscler. Thromb. Vasc. Biol. 22:2017–2022, 2002.CrossRefPubMedGoogle Scholar
  40. 40.
    Newman, K. M., J. Jean-Claude, H. Li, W. G. Ramey, and M. D. Tilson. Cytokines that activate proteolysis are increased in abdominal aortic aneurysms. Circulation 90:II224–II227, 1994.PubMedGoogle Scholar
  41. 41.
    Nichols, W. W., and M. F. O’Rourke. Mcdonald’s Blood Flow in Arteries (4th ed.). New York: Oxford University Press, 179 pp., 1998.Google Scholar
  42. 42.
    Peattie, R. A., T. J. Riehle, and E. I. Bluth. Pulsatile flow in fusiform models of abdominal aortic aneurysms: flow fields, velocity patterns and flow-induced wall stresses. J. Biomech. Eng. 126:438–446, 2004.CrossRefPubMedGoogle Scholar
  43. 43.
    Perktold, K., R. O. Peter, M. Resch, and G. Langs. Pulsatile non-newtonian blood flow in three-dimensional carotid bifurcation models: a numerical study of flow phenomena under different bifurcation angles. J. Biomed. Eng. 13:507–515, 1991.CrossRefPubMedGoogle Scholar
  44. 44.
    Perktold, K., and G. Rappitsch. Computer simulation of local blood flow and vessel mechanics in a compliant carotid artery bifurcation model. J. Biomech. 28:845–856, 1995.CrossRefPubMedGoogle Scholar
  45. 45.
    Rayz, V. L., L. Boussel, M. T. Lawton, G. Acevedo-Bolton, L. Ge, W. L. Young, R. T. Higashida, and D. Saloner. Numerical modeling of the flow in intracranial aneurysms: prediction of regions prone to thrombus formation. Ann. Biomed. Eng. 36:1793–1804, 2008.CrossRefPubMedGoogle Scholar
  46. 46.
    Sallam, A. M., and N. H. C. Hwang. Human red blood-cell hemolysis in a turbulent shear-flow—contribution of Reynolds shear stresses. Biorheology 21:783–797, 1984.PubMedGoogle Scholar
  47. 47.
    Salsac, A. V., S. R. Sparks, J. M. Chomaz, and J. C. Lasheras. Evolution of the wall shear stresses during the progressive enlargement of symmetric abdominal aortic aneurysms. J. Fluid Mech. 560:19–51, 2006.CrossRefGoogle Scholar
  48. 48.
    Salsac, A. V., S. R. Sparks, and J. C. Lasheras. Hemodynamic changes occurring during the progressive enlargement of abdominal aortic aneurysms. Ann. Vasc. Surg. 18:14–21, 2004.CrossRefPubMedGoogle Scholar
  49. 49.
    Santilli, J. D., and S. M. Santilli. Diagnosis and treatment of abdominal aortic aneurysms. Am. Fam. Physician 56:1081–1090, 1997.PubMedGoogle Scholar
  50. 50.
    Sergeev, S. I. Fluid oscillations in pipes at moderate Reynolds numbers. Fluid Dyn. 1:21–22, 1966.Google Scholar
  51. 51.
    Steele, B. N., M. S. Olufsen, and C. A. Taylor. Fractal network model for simulating abdominal and lower extremity blood flow during resting and exercise conditions. Comput. Meth. Biomech. Biomed. Eng. 10:39–51, 2007.CrossRefGoogle Scholar
  52. 52.
    Stergiopulos, N., P. Segers, and N. Westerhof. Use of pulse pressure method for estimating total arterial compliance in vivo. Am. J. Physiol. Heart Circul. Physiol. 276:H424–H428, 1999.Google Scholar
  53. 53.
    Tang, B. T., C. P. Cheng, M. T. Draney, N. M. Wilson, P. S. Tsao, R. J. Herfkens, and C. A. Taylor. Abdominal aortic hemodynamics in young healthy adults at rest and during lower limb exercise: quantification using image-based computer modeling. Am. J. Physiol. Heart Circul. Physiol. 291:H668–H676, 2006.CrossRefGoogle Scholar
  54. 54.
    Taylor, C. A., C. P. Cheng, L. A. Espinosa, B. T. Tang, D. Parker, and R. J. Herfkens. In vivo quantification of blood flow and wall shear stress in the human abdominal aorta during lower limb exercise. Ann. Biomed. Eng. 30:402–408, 2002.CrossRefPubMedGoogle Scholar
  55. 55.
    Taylor, C. A., and M. T. Draney. Experimental and computational methods in cardiovascular fluid mechanics. Annu. Rev. Fluid Mech. 36:197–231, 2004.CrossRefGoogle Scholar
  56. 56.
    Taylor, C. A., T. J. R. Hughes, and C. K. Zarins. Finite element modeling of three-dimensional pulsatile flow in the abdominal aorta: relevance to atherosclerosis. Ann. Biomed. Eng. 26:975–987, 1998.CrossRefPubMedGoogle Scholar
  57. 57.
    Taylor, C. A., and D. A. Steinman. Image-based modeling of blood flow and vessel wall dynamics: applications, methods and future directions. Ann. Biomed. Eng., 2010. doi:10.1007/s10439-010-9901-0.
  58. 58.
    Taylor, T. W., and T. Yamaguchi. Three-dimensional simulation of blood flow in an abdominal aortic aneurysm—steady and unsteady flow cases. J. Biomech. Eng. 116:89–97, 1994.CrossRefPubMedGoogle Scholar
  59. 59.
    Thompson, R. W., D. R. Holmes, R. A. Mertens, S. Liao, M. D. Botney, R. P. Mecham, H. G. Welgus, and W. C. Parks. Production and localization of 92-kilodalton gelatinase in abdominal aortic aneurysms. An elastolytic metalloproteinase expressed by aneurysm-infiltrating macrophages. J. Clin. Invest. 96:318–326, 1995.CrossRefPubMedGoogle Scholar
  60. 60.
    van der Molen, A. J. Nephrogenic systemic fibrosis and the role of gadolinium contrast media. J. Med. Imaging Radiat. Oncol. 52:339–350, 2008.CrossRefPubMedGoogle Scholar
  61. 61.
    Vignon-Clementel, I. E., C. A. Figueroa, K. C. Jansen, and C. A. Taylor. Outflow boundary conditions for three-dimensional finite element modeling of blood flow and pressure in arteries. Comput. Meth. Appl. Mech. Eng. 195:3776–3796, 2006.Google Scholar
  62. 62.
    Vignon-Clementel, I. E., C. A. Figueroa, K. E. Jensen, and C. A. Taylor. Outflow boundary conditions for three-dimensional simulations of non-periodic blood flow and pressure fields in deformable arteries. Comput. Meth. Biomech. Biomed. Eng., 2009 (in press).Google Scholar
  63. 63.
    Vollmar, J. F., E. Paes, P. Pauschinger, E. Henze, and A. Friesch. Aortic aneurysms as late sequelae of above-knee amputation. Lancet 2:834–835, 1989.CrossRefPubMedGoogle Scholar
  64. 64.
    Whiting, C. H., and K. C. Jansen. A stabilized finite element method for the incompressible Navier–Stokes equations using a hierarchical basis. Int. J. Numer. Meth. Fluid 35:93–116, 2001.CrossRefGoogle Scholar
  65. 65.
    Wilson, N., K. Wang, R. W. Dutton, and C. A. Taylor. A software framework for creating patient specific geometric models from medical imaging data for simulation based medical planning of vascular surgery. Lect. Notes Comput. Sci. 2208:449–456, 2001.CrossRefGoogle Scholar
  66. 66.
    Womersley, J. R. Method for the calculation of velocity, rate of flow and viscous drag in arteries when the pressure gradient is known. J. Physiol. 127:553–563, 1955.PubMedGoogle Scholar
  67. 67.
    Yeung, J. J., H. J. Kim, T. A. Abbruzzese, I. E. Vignon-Clementel, M. T. Draney-Blomme, K. K. Yeung, I. Perkash, R. J. Herfkens, C. A. Taylor, and R. L. Dalman. Aortoiliac hemodynamic and morphologic adaptation to chronic spinal cord injury. J. Vasc. Surg. 44:1254–1265, 2006.CrossRefPubMedGoogle Scholar

Copyright information

© Biomedical Engineering Society 2010

Authors and Affiliations

  • Andrea S. Les
    • 1
  • Shawn C. Shadden
    • 2
  • C. Alberto Figueroa
    • 1
  • Jinha M. Park
    • 3
  • Maureen M. Tedesco
    • 4
  • Robert J. Herfkens
    • 5
  • Ronald L. Dalman
    • 4
  • Charles A. Taylor
    • 1
    • 6
  1. 1.Department of BioengineeringStanford UniversityStanfordUSA
  2. 2.Department of Mechanical and Aerospace EngineeringIllinois Institute of TechnologyChicagoUSA
  3. 3.Department of RadiologyUniversity of Southern CaliforniaLos AngelesUSA
  4. 4.Division of Vascular SurgeryStanford UniversityStanfordUSA
  5. 5.Department of RadiologyStanford UniversityStanfordUSA
  6. 6.James H. Clark CenterStanfordUSA

Personalised recommendations