Advertisement

Annals of Biomedical Engineering

, Volume 33, Issue 3, pp 257–269 | Cite as

Comparison of CFD and MRI Flow and Velocities in an In Vitro Large Artery Bypass Graft Model

  • Joy P. Ku
  • Christopher J. Elkins
  • Charles A. TaylorEmail author
Article

Abstract

Bypass graft failures have been attributed to various hemodynamic factors, including flow stasis and low shear stress. Ideally, surgeries would minimize the occurrence of these detrimental flow conditions, but surgeons cannot currently assess this. Numerical simulation techniques have been proposed as one method for predicting changes in flow distributions and patterns from surgical bypass procedures, but comparisons against experimental results are needed to assess their usefulness. Previous in vitro studies compared simulated results against experimentally obtained measurements, but they focused on peripheral arteries, which have lower Reynolds numbers than those found in the larger arteries. In this study, we compared simulation results against measurements obtained using magnetic resonance imaging (MRI) techniques for a phantom model of a stenotic vessel with a bypass graft under conditions suitable for surgical planning purposes and with inlet Reynolds numbers closer to those found in the larger arteries. Comparisons of flow rate and velocity profiles were performed at maximum and minimum flows at four locations and used simulation results that were temporally and spatially averaged, key postprocessing when comparing against phase contrast MRI measurements. The maximum error in the computed volumetric flow rates was 6% of the measured values, and excellent qualitative agreement was obtained for the through-plane velocity profiles in both magnitude and shape. The in-plane velocities also agreed reasonably well at most locations.

Keyword

Computational fluid dynamics Finite element modeling Numerical simulations Magnetic resonance imaging PC-MRI surgical planning Phantom experiment 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Alley, M. T., R. Y. Shifrin, N. J. Pelc, and R. J. Herfkens. Ultrafast contrast-enhanced three-dimensional MR angiography: State of the art. Radiographics 18:273–285, 1998.Google Scholar
  2. 2.
    Bassiouny, H. S., S. White, S. Glagov, E. Choi, D. P. Giddens, and C. K. Zarins. Anastomotic intimal hyperplasia: Mechanical injury or flow induced. J. Vasc. Surg. 15:708–717, 1992.Google Scholar
  3. 3.
    Bertolotti, C., V. Deplano, J. Fuseri, and P. Dupouy. Numerical and experimental models of post-operative realistic flows in stenosed coronary bypasses. J. Biomech. 34:1049–1064, 2001.Google Scholar
  4. 4.
    Botnar, R., G. Rappitsch, M. B. Scheidegger, D. Leipsch, K. Perktold, and P. Boesiger. Hemodynamics in the carotid artery bifurcation: A comparison between numerical simulations and in vitro MRI measurements. J. Biomech. 33:137–144, 2000.Google Scholar
  5. 5.
    Brewster, D. C., A. J. LaSalle, J. G. Robison, E. C. Strayhorn, and R. C. Darling. Factors affecting patency of femoropopliteal bypass grafts. Surg. Gynecol. Obstet. 157:437–442, 1983.Google Scholar
  6. 6.
    Dardik, H., K. Wengerter, F. Qin, A. Pangilinan, F. Silvestri, F. Wolodiger, M. Kahn, B. Sussman, and I. M. Ibrahim. Comparative decades of experience with glutaraldehyde-tanned human umbilical cord vein graft for lower limb revascularization: An analysis of 1275 cases. J. Vasc. Surg. 35:64–71, 2002.Google Scholar
  7. 7.
    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: Proceedings of the International Society for Magnetic Resonance in Medicine Tenth Scientific Meeting and Exhibition Conference, Honolulu, Hawai’i, USA, 2002.Google Scholar
  8. 8.
    Elkins, C. J., J. K. Eaton, and R. B. Wicker. Rapid experimentation in complex internal flow passages using SLA and MRV. In: Proceedings of the 4th ASME/JSME Joint Fluids Engineering Conference Conference, Honolulu, Hawaii, 2003.Google Scholar
  9. 9.
    Erickson, C. A., J. B. Towne, G. R. Seabrook, J. A. Freischlag, and R. A. Cambria. Ongoing vascular laboratory surveillance is essential to maximize long-term in situ saphenous vein bypass patency. J. Vasc. Surg. 23:18–27, 1996.Google Scholar
  10. 10.
    Ethier, C. R., S. Prakash, D. A. Steinman, R. L. Leask, G. G. Couch, and M. Ojha. Steady flow separation patterns in a 45 degree junction. J. Fluid Mech. 411:1–38, 2000.Google Scholar
  11. 11.
    Ethier, C. R., D. A. Steinman, X. Zhang, S. R. Karpik, and M. Ojha. Flow waveform effects on end-to-side anastomotic flow patterns. J. Biomech. 31:609–617, 1998.Google Scholar
  12. 12.
    Friedman, M. H., O. J. Deters, F. F. Mark, C. B. Bargeron, and G. M. Hutchins. Arterial geometry affects hemodynamics. A potential risk factor for atherosclerosis. Atherosclerosis 46:225–231, 1983.Google Scholar
  13. 13.
    Gijsen, F. J. H., F. N. van de Vosse, and J. D. Janssen. The influence of the non-Newtonian properties of blood on the flow in large arteries: Steady flow in a carotid bifurcation model. J. Biomech. 32:601–608, 1999.Google Scholar
  14. 14.
    Hajjar, G. E., and W. J. Quinones-Baldrich. The polytetrafluoroethylene graft for infrainguinal revascularization: Long-term results. In: Long-term Results in Vascular Surgery, edited by J. S. T. Yao and W. H. Pearce. Norwalk, CT: Appleton & Lange, 1993, pp. 215–224.Google Scholar
  15. 15.
    Khalifa, A. M. A., and D. P. Giddens. Characterization and evolution of post-stenotic flow disturbances. J. Biomech. 14:279–296, 1981.Google Scholar
  16. 16.
    Ku, J. P., Numerical and Experimental Investigations of Blood Flow with Application to Vascular Bypass Surgery, in Electrical Engineering. Stanford, CA: Stanford University, 2004.Google Scholar
  17. 17.
    Ku, J. P., M. T. Draney, F. R. Arko, W. A. Lee, F. P. Chan, N. J. Pelc, C. K. Zarins, and C. A. Taylor. In vivo validation of numerical prediction of blood flow in arterial bypass grafts. Ann. Biomed. Eng. 30:743–752, 2002.Google Scholar
  18. 18.
    Lei, M., D. Giddens, S. Jones, F. Loth, and H. Bassiouny. Pulsatile flow in an end-to-side vascular graft model: Comparison of computations with experimental data. J. Biomech. Eng. 123:80–87, 2001.Google Scholar
  19. 19.
    McCauley, T. R., C. S. Pena, C. K. Holland, T. B. Price, and J. C. Gore. Validation of volume flow measurements with cine phase-contrast MR imaging for peripheral arterial waveforms. J. Magn. Reson. Imaging 5:663–668, 1995.Google Scholar
  20. 20.
    Milner, J. S., J. A. Moore, B. K. Rutt, and D. A. Steinman. Hemodynamics of human carotid artery bifurcations: Computational studies with models reconstructed from magnetic resonance imaging of normal subjects. J. Vasc. Surg. 28:143–156, 1998.Google Scholar
  21. 21.
    Nayler, G. L., D. N. Firmin, and D. B. Longmore. Blood flow imaging by cine magnetic resonance. J. Comput. Assist. Tomogr. 10:715–722, 1986.Google Scholar
  22. 22.
    Nevelsteen, A., R. Suy, W. Daenen, A. Boel, and G. Stalpaert. Aortofemoral grafting: Factors influencing late results. Surgery 88:642–653, 1980.Google Scholar
  23. 23.
    Palafox, G. N., R. B. Wicker, and C. J. Elkins. Rapid in-vitro physiologic flow experimentation using rapid prototyping and particle image velocimetry. In: Proceedings of the 2003 ASME Summer Bioengineering Meeting Conference, Key Biscayne, Florida, 2003.Google Scholar
  24. 24.
    Papaharilaou, Y., D. J. Doorly, and S. J. Sherwin. Assessing the accuracy of two-dimensional phase-contrast MRI measurements of complex unsteady flows. J. Magn. Reson. Imaging 14:714–723, 2001.Google Scholar
  25. 25.
    Pelc, N. J., F. G. Sommer, K. C. P. Li, T. J. Brosnan, R. J. Herfkens, and D. R. Enzmann. Quantitative magnetic resonance flow imaging. Magn. Reson. Q. 10:125–147, 1994.Google Scholar
  26. 26.
    Pelc, N. J., R. J. Herfkens, A. Shimakawa, and D. R. Enzmann. Phase contrast cine magnetic resonance imaging. Magn. Reson. Q. 7:229–254, 1991.Google Scholar
  27. 27.
    Perktold, K., M. Hofer, G. Rappitsch, M. Loew, B. D. Kuban, and M. H. Friedman. Validated computation of physiologic flow in a realistic coronary artery branch. J. Biomech. 31:217–228, 1998.Google Scholar
  28. 28.
    Popovic, J. 1999 National Hospital Discharge Survey: Annual Summary with Detailed Diagnosis and Procedure Data. Hyattsville, MD: National Center for Health Statistics, 2001.Google Scholar
  29. 29.
    Steinman, D. A., R. Frayne, X. D. Zhang, B. K. Rutt, and C. R. Ethier. MR measurement and numerical simulation of steady flow in an end-to-side anastomosis model. J. Biomech. 29:537–542, 1996.Google Scholar
  30. 30.
    Stept, L. L., W. R. Flinn, W. J. McCarthy III, S. T. Bartlett, J. J. Bergan, and J. S. T. Yao. Technical defects as a cause of early graft failure after femorodistal bypass. Arch. Surg. 122:599–604, 1987.Google Scholar
  31. 31.
    Stroud, J. S., S. A. Berger, and D. Saloner. Influence of stenosis morphology on flow through severely stenotic vessels: Implications for plaque rupture. J. Biomech. 33:443–455, 2000.Google Scholar
  32. 32.
    Summers, P., M. Drangova, A. Papadaki, D. W. Holdsworth, and B. K. Rutt. Multi-site comparison of accuracy, linearity and precision in MR flow measurements. In: Proceedings of the International Society for Magnetic Resonance in Medicine Ninth Scientific Meeting and Exhibition Conference, Glasgow, Scotland, UK, 2001.Google Scholar
  33. 33.
    Taylor, C. A., M. T. Draney, J. P. Ku, D. Parker, B. N. Steele, K. Wang, and C. K. Zarins. Predictive medicine: Computational techniques in therapeutic decision-making. Comput. Aided Surg. 4:231–247, 1999.Google Scholar
  34. 34.
    Taylor, C. A., T. J. R. Hughes, and C. K. Zarins. Finite element modeling of blood flow in arteries. Comput. Methods Appl. Mech. Eng. 158:155–196, 1998.Google Scholar
  35. 35.
    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. 26:1–14, 1998.Google Scholar
  36. 36.
    Walsh, D. B. Technical adequacy and graft thrombosis. In: Vascular Surgery, edited by R. B. Rutherford. Philadelphia, PA: W.B. Saunders, 2000, pp. 708–725.Google Scholar
  37. 37.
    Whitmore, R. L. Rheology of the Circulation. Oxford, England: Pergamon Press, 1968.Google Scholar
  38. 38.
    Whittemore, A. D., M. C. Donaldson, and J. A. Mannick. Ten-year patency of autogenous vein bypass grafts. In: Long-term Results in Vascular Surgery, edited by J. S. T. Yao and W. H. Pearce. Norwalk, CT: Appleton & Lange, 1993, pp. 243–246.Google Scholar
  39. 39.
    Wilson, N. M., Geometric Algorithms and Software Architecture for Computational Prototyping: Applications in Vascular Surgery and MEMS, in Mechanical Engineering. Stanford, CA: Stanford University, 2002.Google Scholar
  40. 40.
    Zarins, C. K., D. P. Giddens, B. K. Bharadvaj, V. S. Sottiurai, R. F. Mabon, and S. Glagov. Carotid bifurcation atherosclerosis: Quantitative correlation of plaque localization with flow velocity profiles and wall shear stress. Circ. Res. 53:502–514, 1983.Google Scholar
  41. 41.
    Zhao, S. Z., X. Y. Xu, P. Papathanasopoulou, and I. Marshall. Combined MRI measurement and CFD simulation of pulsatile flow in a carotid artery bifurcation phantom. In: Proceedings of the International Society for Magnetic Resonance in Medicine Tenth Scientific Meeting and Exhibition Conference, Honolulu, Hawaii, USA, 2002.Google Scholar

Copyright information

© Biomedical Engineering Society 2005

Authors and Affiliations

  • Joy P. Ku
    • 1
  • Christopher J. Elkins
    • 2
  • Charles A. Taylor
    • 2
    • 3
    • 4
    Email author
  1. 1.Department of Electrical EngineeringStanford UniversityStanford
  2. 2.Department of Mechanical EngineeringStanford UniversityStanford
  3. 3.Division of Vascular Surgery, Department of SurgeryStanford UniversityStanford
  4. 4.Surgery and Mechanical Engineering, Clark Center, E350, 318 Campus Drive, MC 5431Stanford UniversityStanford

Personalised recommendations