Skip to main content
SpringerLink
Log in

The Importance of Hemorheology and Patient Anatomy on the Hemodynamics in the Inferior Vena Cava

  • Published:
Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

Inferior vena cava (IVC) filters have been used for nearly half a century to prevent pulmonary embolism in at-risk patients. However, complications with IVC filters remain common. In this study, we investigate the importance of considering the hemorheological and morphological effects on IVC hemodynamics by simulating Newtonian and non-Newtonian blood flow in three IVC models with varying levels of geometric idealization. Partial occlusion by an IVC filter and a thrombus is also considered. More than 99% of the infrarenal IVC volume is found to contain flow in the nonlinear region of the shear rate–viscosity curve for blood (less than 100 s−1) in the unoccluded IVCs. Newtonian simulations performed using the asymptotic viscosity for blood over-predict the non-Newtonian Reynolds numbers by more than a factor of two and under-predict the mean wall shear stress (WSS) by 28–54%. Agreement with the non-Newtonian simulations is better using a characteristic viscosity, but local WSS errors are still large (up to 50%) in the partially occluded cases. Secondary flow patterns in the IVC also depend on the viscosity model and IVC morphological complexity. Non-Newtonian simulations required only a marginal increase in computational expense compared with the Newtonian simulations. We recommend that future studies of IVC hemodynamics consider the effects of hemorheology and IVC morphology when accurate predictions of WSS and secondary flow features are desired.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

References

  1. Aycock, K. I., R. L. Campbell, K. B. Manning, S. P. Sastry, S. M. Shontz, F. C. Lynch, and B. A. Craven. A computational method for predicting inferior vena cava filter performance on a patient-specific basis. J. Biomech. Eng. 136:1–13, 2014. Erratum, 137:1–2, 2015.

  2. Baaijens, J. P. W. Numerical analysis of steady generalized Newtonian blood flow in a 2D model of the carotid artery bifurcation. Biorheology 30:63–74, 1993.

    CAS  PubMed  Google Scholar 

  3. Ballyk, P. D., D. A. Steinman, and C. R. Ethier. Simulation of non-Newtonian blood flow in an end-to-side anastomosis. Biorheology 31:565–86, 1994.

    CAS  PubMed  Google Scholar 

  4. Basmadjian, D. Embolization: critical thrombus height, shear rates, and pulsatility. patency of blood vessels. J. Biomed. Mater. Res. 23:1315–1326, 1989.

    Article  CAS  PubMed  Google Scholar 

  5. Benard, N., R. Perrault, and D. Coisne. Computational approach to estimating the effects of blood properties on changes in intra-stent flow. Ann. Biomed. Eng. 34:1259–1271, 2006.

    Article  PubMed  Google Scholar 

  6. Bird, R. B., R. C. Armstrong, and O. Hassager. Dynamics of polymeric liquids. Vol. 1, Fluid mechanics, New York: Wiley, 1987.

  7. Chaikof, E. L., M. F. Fillinger, J. S. Matsumura, R. B. Rutherford, G. H. White, J. D. Blankensteijn, V. M. Bernhard, P. L. Harris, K. C. Kent, J. May, F. J. Veith, and C. K. Zarins. Identifying and grading factors that modify the outcome of endovascular aortic aneurysm repair. J. Vasc. Surg. 35:1061–1066, 2002.

    Article  PubMed  Google Scholar 

  8. Chen, J., X.-Y. Lu, and W. Wang. Non-Newtonian effects of blood flow on hemodynamics in distal vascular graft anastomoses. J. Biomech. 39:1983–95, 2006.

    Article  PubMed  Google Scholar 

  9. Cheng, C. P., R. J. Herfkens, and C. A. Taylor. Inferior vena caval hemodynamics quantified in vivo at rest and during cycling exercise using magnetic resonance imaging. Am. J. Physiol. Heart Circ. Physiol. 284:H1161–7, 2003.

    Article  CAS  PubMed  Google Scholar 

  10. Cherry, E. M. and J. K. Eaton. Shear thinning effects on blood flow in straight and curved tubes. Phys. Fluids 25:073104, 2013.

  11. Chien, S. Shear dependence of effective cell volume as a determinant of blood viscosity. Science 168:977–979, 1970.

    Article  CAS  PubMed  Google Scholar 

  12. Cho, Y. I. and K. R. Kensey. Effects of the non-Newtonian viscosity of blood on flows in a diseased arterial vessel. part 1: steady flows.Biorheology 28:241–62, 1991.

    CAS  PubMed  Google Scholar 

  13. Cipolla, J., N. S. Weger, R. Sharma, S. P. Schrag, B. Sarani, M. Truitt, M. Lorenzo, C. A. Sims, P. K. Kim, D. Torigian, B. Temple-Lykens, C. P. Sicoutris, and S. P. Stawicki. Complications of vena cava filters: a comprehensive clinical review. OPUS 12 Scientist 2:11–24, 2008.

    Google Scholar 

  14. Clark, W. D., B. A. Eslahpazir, I. R. Argueta-Morales, A. J. Kassab, E. A. Divo, and W. M. DeCampli. Comparison between bench-top and computational modelling of cerebral thromboembolism in ventricular assist device circulation. Cardiovasc. Eng. Technol. 6:242–255, 2015.

    Article  PubMed  Google Scholar 

  15. Couch, G. G., H. Kim, and M. Ojha. In vitro assessment of the hemodynamic effects of a partial occlusion in a vena cava filter. J. Vasc. Surg. 25:663–72, 1997.

    Article  CAS  PubMed  Google Scholar 

  16. Dowell, J. D., J. C. Castle, M. Schickel, U. K. Andersson, R. Zielinski, E. McLoney, G. Guy, X. Yang, and S. Ghadiali. Celect inferior vena cava wall strut perforation begets additional strut perforation. J. Vasc. Interv. Radiol. 26:1510–1518.e3, 2015.

  17. Fortuny, G., J. Herrero, D. Puigjaner, C. Olivé, F. Marimon, J. Garcia-Bennett, and D. Rodríguez. Effect of anticoagulant treatment in deep vein thrombosis: a patient-specific computational fluid dynamics study. J. Biomech. 48:2047–2053, 2015.

    Article  PubMed  Google Scholar 

  18. Fraser, K. H. and T. Zhang. Computational fluid dynamics analysis of thrombosis potential in left ventricular assist device drainage cannulae. ASAIO J. 56:157–163, 2010.

    Article  PubMed  PubMed Central  Google Scholar 

  19. García, A., S. Lerga, E. Peña, M. Malve, A. Laborda, M. A. De Gregorio, and M. A. Martínez. Evaluation of migration forces of a retrievable filter: experimental setup and finite element study. Med. Eng. Phys. 34:1167–1176, 2012.

    Article  PubMed  Google Scholar 

  20. Gasser, T. C., R. W. Ogden, and G. A. Holzapfel. Hyperelastic modelling of arterial layers with distributed collagen fibre orientations. J. R. Soc. Interface 3:15–35, 2006.

    Article  PubMed  Google Scholar 

  21. Gijsen, F. J., E. Allanic, F. N. van de Vosse, and J. D. Janssen. The influence of the non-Newtonian properties of blood on the flow in large arteries: unsteady flow in a 90° curved tube. J. Biomech. 32:705–13, 1999.

    Article  CAS  PubMed  Google Scholar 

  22. Goldsmith, H. and V. Turitto. Rheological aspects of thrombosis and haemostasis: basic principles and applications. Thromb. Haemost. 55:415–35, 1986.

    CAS  PubMed  Google Scholar 

  23. Grassi, J. Inferior vena cava filters: analysis of five currently available devices. Am. J. Roentgenol. 156:813–21, 1991.

    Article  CAS  Google Scholar 

  24. Hernández, Q. and E. Peña. Failure properties of vena cava tissue due to deep penetration during filter insertion. Biomech. Model Mechanobiol. 2015. doi:10.1007/s10237-015-0728-3.

    PubMed  Google Scholar 

  25. Itatani, K., K. Miyaji, T. Tomoyasu, Y. Nakahata, K. Ohara, S. Takamoto, and M. Ishii. Optimal conduit size of the extracardiac fontan operation based on energy loss and flow stagnation. Ann. Thorac. Surg. 88:565–72; discussion 572–3, 2009.

  26. Johnston, B. M., P. R. Johnston, S. Corney, and D. Kilpatrick. Non-Newtonian blood flow in human right coronary arteries: transient simulations. J. Biomech. 39:1116–28, 2006.

    Article  PubMed  Google Scholar 

  27. Kundu, P. K. and I. M. Cohen. Fluid mechanics, San Diego: Academic Press, 2008.

    Google Scholar 

  28. Kuy, S. R., A. Dua, C. J. Lee, B. Patel, S. S. Desai, A. Dua, A. Szabo, and P. J. Patel. National trends in utilization of inferior vena cava filters in the united states, 2000–2009. J. Vasc. Surg. Venous Lymphat. Disord. 2:15–20, 2014.

    Article  PubMed  Google Scholar 

  29. Kwack, J. A. and A. Masud. A stabilized mixed finite element method for shear-rate dependent non-Newtonian fluids: 3D benchmark problems and application to blood flow in bifurcating arteries. Comput. Mech. 53(4):751–776 2013.

  30. Lee, S.-W. and D. A. Steinman. On the relative importance of rheology for image-based CFD models of the carotid bifurcation. J. Biomech. Eng. 129:273–278, 2007.

    Article  PubMed  Google Scholar 

  31. Mann, D. E. and J. M. Tarbell. Flow of non-Newtonian blood analog fluids in rigid curved and straight artery models. Biorheology 27:711–733, 1990.

    CAS  PubMed  Google Scholar 

  32. Marrero, V. L., J. A. Tichy, O. Sahni, and K. E. Jansen. Numerical study of purely viscous non-Newtonian flow in an abdominal aortic aneurysm. J. Biomech. Eng. 136:1–10, 2014.

    Article  Google Scholar 

  33. Mejia, J., R. Mongrain, and O. F. Bertrand. Accurate prediction of wall shear stress in a stented artery: Newtonian versus non-Newtonian models. J. Biomech. Eng. 133:074501, 2011.

    Article  PubMed  Google Scholar 

  34. Moiseyev, G. and P. Z. Bar-Yoseph. Computational modeling of thrombosis as a tool in the design and optimization of vascular implants. J. Biomech. 46:248–52, 2013.

    Article  PubMed  Google Scholar 

  35. Mukherjee, D., J. Padilla, and S. C. Shadden. Numerical investigation of fluid-particle interactions for embolic stroke. Theor. Comput. Fluid Dyn. 30:23–29, 2016.

    Article  Google Scholar 

  36. Oguzkurt, L., U. Ozkan, S. Ulusan, Z. Koc, and F. Tercan. Compression of the left common iliac vein in asymptomatic subjects and patients with left iliofemoral deep vein thrombosis. J. Vasc. Interv. Radiol. 19:366–370, 2008.

    Article  PubMed  Google Scholar 

  37. Papaioannou, T. G. and C. Stefanadis. Vascular wall shear stress: basic principles and methods. Hellenic J. Cardiol. 46:9–15, 2005.

    PubMed  Google Scholar 

  38. Rahbar, E., D. Mori, and J. E. Moore. Three-dimensional analysis of flow disturbances caused by clots in inferior vena cava filters. J. Vasc. Interv. Radiol. 22:835–42, 2011.

    Article  PubMed  Google Scholar 

  39. Singer, M. A., W. D. Henshaw, and S. L. Wang. Computational modeling of blood flow in the trapease inferior vena cava filter. J. Vasc. Interv. Radiol. 20:799–805, 2009.

    Article  PubMed  Google Scholar 

  40. Singer, M. A. and S. L. Wang. Modeling blood flow in a tilted inferior vena cava filter: does tilt adversely affect hemodynamics? J. Vasc. Interv. Radiol. 22:229–35, 2011.

    Article  PubMed  Google Scholar 

  41. Smouse, B. and A. Johar. Is market growth of vena cava filters justified? Endovasc. Today 9:74–77, 2010.

    Google Scholar 

  42. Stein, P. D., F. Kayali, and R. E. Olson. Twenty-one-year trends in the use of inferior vena cava filters. Arch. Intern. Med. 164:1541–1545, 2004.

    Article  PubMed  Google Scholar 

  43. Stewart, S. F. C., R. A. Robinson, R. A. Nelson, and R. A. Malinauskas. Effects of thrombosed vena cava filters on blood flow: flow visualization and numerical modeling. Ann. Biomed. Eng. 36:1764–81, 2008.

    Article  PubMed  Google Scholar 

  44. Surovtsova, I. Effects of compliance mismatch on blood flow in an artery with endovascular prosthesis. J. Biomech. 38:2078–2086, 2005.

    Article  PubMed  Google Scholar 

  45. Swaminathan, T. N., H. H. Hu, and A. A. Patel. Numerical analysis of the hemodynamics and embolus capture of a Greenfield vena cava filter. J. Biomech. Eng. 128:360–70, 2006.

    Article  CAS  PubMed  Google Scholar 

  46. Thurston, G. B. Frequency and shear rate dependence of viscoelasticity of human blood. Biorheology 10:375–381, 1973.

    CAS  PubMed  Google Scholar 

  47. Torii, R., M. Oshima, T. Kobayashi, K. Takagi, and T. E. Tezduyar. Fluid-structure interaction modeling of blood flow and cerebral aneurysm: significance of artery and aneurysm shapes. Comput. Methods Appl. Mech. Eng. 198:3613–3621, 2009.

    Article  Google Scholar 

  48. Trias, M., A. Arbona, J. Massó, B. Miñano, and C. Bona. FDA’s nozzle numerical simulation challenge: non-Newtonian fluid effects and blood damage. PloS One 9:e92638, 2014.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Vahidi, B. and N. Fatouraee. Large deforming buoyant embolus passing through a stenotic common carotid artery: a computational simulation. J. Biomech. 45:1312–22, 2012.

    Article  PubMed  Google Scholar 

  50. Wang, S. L. and M. A. Singer. Toward an optimal position for inferior vena cava filters: computational modeling of the impact of renal vein inflow with celect and trapease filters. J. Vasc. Interv. Radiol. 21:367–74, 2010.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors thank Elaheh Rahbar, Daisuke Mori, and James E. Moore Jr. for generously providing the geometry for the patient-averaged IVC model. This research was supported by the Walker Assistantship program at the Penn State Applied Research Laboratory.

Author information

Authors and Affiliations

  1. Applied Research Laboratory, The Pennsylvania State University, University Park, PA, USA

    Kenneth I. Aycock & Robert L. Campbell

  2. Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, USA

    Kenneth I. Aycock & Keefe B. Manning

  3. Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA, USA

    Robert L. Campbell

  4. Department of Surgery, Penn State Hershey Medical Center, Hershey, PA, USA

    Frank C. Lynch & Keefe B. Manning

  5. Division of Applied Mechanics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD, USA

    Brent A. Craven

Authors
  1. Kenneth I. Aycock
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Robert L. Campbell
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Frank C. Lynch
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Keefe B. Manning
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Brent A. Craven
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Keefe B. Manning.

Additional information

Associate Editor Andreas Anayiotos oversaw the review of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aycock, K.I., Campbell, R.L., Lynch, F.C. et al. The Importance of Hemorheology and Patient Anatomy on the Hemodynamics in the Inferior Vena Cava. Ann Biomed Eng 44, 3568–3582 (2016). https://doi.org/10.1007/s10439-016-1663-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10439-016-1663-x

Keywords

Search

Navigation