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A Rapid and Computationally Inexpensive Method to Virtually Implant Current and Next-Generation Stents into Subject-Specific Computational Fluid Dynamics Models

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Abstract

Computational modeling is often used to quantify hemodynamic alterations induced by stenting, but frequently uses simplified device or vascular representations. Based on a series of Boolean operations, we developed an efficient and robust method for assessing the influence of current and next-generation stents on local hemodynamics and vascular biomechanics quantified by computational fluid dynamics. Stent designs were parameterized to allow easy control over design features including the number, width and circumferential or longitudinal spacing of struts, as well as the implantation diameter and overall length. The approach allowed stents to be automatically regenerated for rapid analysis of the contribution of design features to resulting hemodynamic alterations. The applicability of the method was demonstrated with patient-specific models of a stented coronary artery bifurcation and basilar trunk aneurysm constructed from medical imaging data. In the coronary bifurcation, we analyzed the hemodynamic difference between closed-cell and open-cell stent geometries. We investigated the impact of decreased strut size in stents with a constant porosity for increasing flow stasis within the stented basilar aneurysm model. These examples demonstrate the current method can be used to investigate differences in stent performance in complex vascular beds for a variety of stenting procedures and clinical scenarios.

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References

  1. Antiga, L., and D. A. Steinman. Robust and objective decomposition and mapping of bifurcating vessels. IEEE Trans. Med. Imaging 23:704–713, 2004.

    Article  PubMed  Google Scholar 

  2. Appanaboyina, S., F. Mut, R. Löhner, C. M. Putman, and J. R. Cebral. Computational fluid dynamics of stented intracranial aneurysms using adaptive embedded unstructured grids. Int. J. Numer. Methods Fluid. 57:475–493, 2008.

    Article  CAS  Google Scholar 

  3. Baráth, K., F. Cassot, J. H. Fasel, M. Ohta, and D. A. Rüfenacht. Influence of stent properties on the alteration of cerebral intra-aneurysmal haemodynamics: flow quantification in elastic sidewall aneurysm models. Neurol. Res. 27(Suppl 1):S120–S128, 2005.

    Article  PubMed  Google Scholar 

  4. Benndorf, G., M. Ionescu, M. Valdivia y Alvarado, A. Biondi, J. Hipp, and R. Metcalfe. Anomalous hemodynamic effects of a self-expanding intracranial stent: comparing in vitro and ex vivo models using ultra-high resolution microct based cfd. J. Biomech. 43:740–748, 2010.

    Article  PubMed  Google Scholar 

  5. Berry, J. L., E. Manoach, C. Mekkaoui, P. H. Rolland, J. E. Moore, Jr., and A. Rachev. Hemodynamics and wall mechanics of a compliance matching stent: in vitro and in vivo analysis. J. Vasc. Interv. Radiol. 13:97–105, 2002.

    Article  PubMed  Google Scholar 

  6. Ebrahimi, N., B. Claus, C. Y. Lee, A. Biondi, and G. Benndorf. Stent conformity in curved vascular models with simulated aneurysm necks using flat-panel ct: an in vitro study. AJNR Am. J. Neuroradiol. 28:823–829, 2007.

    PubMed  CAS  Google Scholar 

  7. Figueroa, C. A., I. E. Vignon-Clementel, K. E. Jansen, T. J. R. Hughes, and C. A. Taylor. A coupled momentum method for modeling blood flow in three-dimensional deformable arteries. Comput. Methods Appl. Mech. Eng. 195:5685–5706, 2006.

    Article  Google Scholar 

  8. Finet, G., M. Gilard, B. Perrenot, G. Rioufol, P. Motreff, L. Gavit, and R. Prost. Fractal geometry of arterial coronary bifurcations: a quantitative coronary angiography and intravascular ultrasound analysis. EuroIntervention 3:490–498, 2007.

    Article  Google Scholar 

  9. Finn, A. V., G. Nakazawa, M. Joner, F. D. Kolodgie, E. K. Mont, H. K. Gold, and R. Virmani. Vascular responses to drug eluting stents: importance of delayed healing. Arterioscler. Thromb. Vasc. Biol. 27:1500–1510, 2007.

    Article  PubMed  CAS  Google Scholar 

  10. Ford, M. D., N. Alperin, S. H. Lee, D. W. Holdsworth, and D. A. Steinman. Characterization of volumetric flow rate waveforms in the normal internal carotid and vertebral arteries. Physiol. Meas. 26:477–488, 2005.

    Article  PubMed  Google Scholar 

  11. Garasic, J. M., E. R. Edelman, J. C. Squire, P. Seifert, M. S. Williams, and C. Rogers. Stent and artery geometry determine intimal thickening independent of arterial injury. Circulation 101:812–818, 2000.

    PubMed  CAS  Google Scholar 

  12. He, X., and D. N. Ku. Pulsatile flow in the human left coronary artery bifurcation: average conditions. J. Biomech. Eng. 118:74–82, 1996.

    Article  PubMed  CAS  Google Scholar 

  13. Hoi, Y., H. Meng, S. H. Woodward, B. R. Bendok, R. A. Hanel, L. R. Guterman, and L. N. Hopkins. Effects of arterial geometry on aneurysm growth: three-dimensional computational fluid dynamics study. J. Neurosurg. 101:676–681, 2004.

    Article  PubMed  Google Scholar 

  14. Hsu, S. W., J. C. Chaloupka, J. A. Feekes, M. D. Cassell, and Y. F. Cheng. In vitro studies of the neuroform microstent using transparent human intracranial arteries. AJNR Am. J. Neuroradiol. 27:1135–1139, 2006.

    PubMed  Google Scholar 

  15. Iakovou, I., T. Schmidt, E. Bonizzoni, L. Ge, G. M. Sangiorgi, G. Stankovic, F. Airoldi, A. Chieffo, M. Montorfano, M. Carlino, I. Michev, N. Corvaja, C. Briguori, U. Gerckens, E. Grube, and A. Colombo. Incidence, predictors, and outcome of thrombosis after successful implantation of drug-eluting stents. JAMA 293:2126–2130, 2005.

    Article  PubMed  CAS  Google Scholar 

  16. Kang, W. C., K. J. Oh, S. H. Han, T. H. Ahn, and E. K. Shin. Progression of dissection due to residual dissection after intracoronary stenting for spontaneous coronary dissection at bifurcation site of lad and diagonal artery. Int. J. Cardiol. 125:e40–e43, 2008.

    Article  PubMed  Google Scholar 

  17. Kim, M., E. I. Levy, H. Meng, and L. N. Hopkins. Quantification of hemodynamic changes induced by virtual placement of multiple stents across a wide-necked basilar trunk aneurysm. Neurosurgery 61:1305–1312, 2007 (discussion 1312–1303).

    Article  PubMed  Google Scholar 

  18. Kim, M., D. B. Taulbee, M. Tremmel, and H. Meng. Comparison of two stents in modifying cerebral aneurysm hemodynamics. Ann. Biomed. Eng. 36:726–741, 2008.

    Article  PubMed  Google Scholar 

  19. LaDisa, Jr., J. F., D. A. Hettrick, L. E. Olson, I. Guler, E. R. Gross, T. T. Kress, J. R. Kersten, D. C. Warltier, and P. S. Pagel. Coronary stent implantation alters coronary artery hemodynamics and wall shear stress during maximal vasodilation. J. Appl. Physiol. 93:1939–1946, 2002.

    PubMed  Google Scholar 

  20. LaDisa, Jr., J. F., I. Guler, L. E. Olson, D. A. Hettrick, J. R. Kersten, D. C. Warltier, and P. S. Pagel. Three-dimensional computational fluid dynamics modeling of alterations in coronary wall shear stress produced by stent implantation. Ann. Biomed. Eng. 31:972–980, 2003.

    Article  PubMed  Google Scholar 

  21. LaDisa, Jr., J. F., L. E. Olson, I. Guler, D. A. Hettrick, S. H. Audi, J. R. Kersten, D. C. Warltier, and P. S. Pagel. Stent design properties and deployment ratio influence indexes of wall shear stress: a three-dimensional computational fluid dynamics investigation within a normal artery. J. Appl. Physiol. 97:424–430, 2004.

    Article  PubMed  Google Scholar 

  22. LaDisa, Jr., J. F., L. E. Olson, I. Guler, D. A. Hettrick, J. R. Kersten, D. C. Warltier, and P. S. Pagel. Circumferential vascular deformation after stent implantation alters wall shear stress evaluated using time-dependent 3d computational fluid dynamics models. J. Appl. Physiol. 98:947–957, 2005.

    Article  PubMed  Google Scholar 

  23. LaDisa, Jr., J. F., L. E. Olson, D. A. Hettrick, D. C. Warltier, J. R. Kersten, and P. S. Pagel. Axial stent strut angle influences wall shear stress after stent implantation: analysis using 3d computational fluid dynamics models of stent foreshortening. Biomed. Eng. Online 4:59, 2005.

    Article  PubMed  Google Scholar 

  24. LaDisa, Jr., J. F., L. E. Olson, R. C. Molthen, D. A. Hettrick, P. F. Pratt, M. D. Hardel, J. R. Kersten, D. C. Warltier, and P. S. Pagel. Alterations in wall shear stress predict sites of neointimal hyperplasia after stent implantation in rabbit iliac arteries. Am. J. Physiol. Heart 288:H2465–H2475, 2005.

    Article  CAS  Google Scholar 

  25. LaDisa, Jr, J. F., L. E. Olson, H. A. Douglas, D. C. Warltier, J. R. Kersten, and P. S. Pagel. Alterations in regional vascular geometry produced by theoretical stent implantation influence distributions of wall shear stress: Analysis of a curved coronary artery using 3d computational fluid dynamics modeling. Biomed. Eng. Online 5:40, 2006.

    Article  PubMed  Google Scholar 

  26. 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.

    PubMed  CAS  Google Scholar 

  27. Les, A. S., S. C. Shadden, C. A. Figueroa, J. M. Park, M. M. Tedesco, R. J. Herfkens, R. L. Dalman, and C. A. Taylor. Quantification of hemodynamics in abdominal aortic aneurysms during rest and exercise using magnetic resonance imaging and computational fluid dynamics. Ann. Biomed. Eng. 38:1288–1313, 2010.

    Article  PubMed  Google Scholar 

  28. Lieber, B. B., V. Livescu, L. N. Hopkins, and A. K. Wakhloo. Particle image velocimetry assessment of stent design influence on intra-aneurysmal flow. Ann. Biomed. Eng. 30:768–777, 2002.

    Article  PubMed  Google Scholar 

  29. Lloyd-Jones, D., R. Adams, M. Carnethon, G. De Simone, T. B. Ferguson, K. Flegal, E. Ford, K. Furie, A. Go, K. Greenlund, N. Haase, S. Hailpern, M. Ho, V. Howard, B. Kissela, S. Kittner, D. Lackland, L. Lisabeth, A. Marelli, M. McDermott, J. Meigs, D. Mozaffarian, G. Nichol, C. O’Donnell, V. Roger, W. Rosamond, R. Sacco, P. Sorlie, R. Stafford, J. Steinberger, T. Thom, S. Wasserthiel-Smoller, N. Wong, J. Wylie-Rosett, and Y. Hong. Heart disease and stroke statistics—2009 update: a report from the American heart association statistics committee and stroke statistics subcommittee. Circulation 119:480–486, 2009.

    Article  PubMed  Google Scholar 

  30. Lonyai, A., A. M. Dubin, J. A. Feinstein, C. A. Taylor, and S. C. Shadden. New insights into pacemaker lead-induced venous occlusion: simulation-based investigation of alterations in venous biomechanics. Cardiovasc. Eng. 10:84–90, 2010.

    Article  PubMed  Google Scholar 

  31. Meng, H., Z. Wang, M. Kim, R. D. Ecker, and L. N. Hopkins. Saccular aneurysms on straight and curved vessels are subject to different hemodynamics: implications of intravascular stenting. AJNR Am. J. Neuroradiol. 27:1861–1865, 2006.

    PubMed  CAS  Google Scholar 

  32. Meng, H., E. Metaxa, L. Gao, N. Liaw, S. K. Natarajan, D. D. Swartz, A. H. Siddiqui, J. Kolega, and J. Mocco. Progressive aneurysm development following hemodynamic insult. J. Neurosurg., 2010. doi:10.3171/2010.9.JNS10368.

  33. Molyneux, A., R. Kerr, I. Stratton, P. Sandercock, M. Clarke, J. Shrimpton, and R. Holman. International subarachnoid aneurysm trial (isat) of neurosurgical clipping versus endovascular coiling in 2143 patients with ruptured intracranial aneurysms: a randomized trial. J. Stroke Cerebrovasc. Dis. 11:304–314, 2002.

    Article  PubMed  Google Scholar 

  34. Mortier, P., M. De Beule, D. Van Loo, B. Masschaele, P. Verdonck, and B. Verhegghe. Automated generation of a finite element stent model. Med. Biol. Eng. Comput. 46:1169–1173, 2008.

    Article  PubMed  Google Scholar 

  35. Mortier, P., G. A. Holzapfel, M. De Beule, D. Van Loo, Y. Taeymans, P. Segers, P. Verdonck, and B. Verhegghe. A novel simulation strategy for stent insertion and deployment in curved coronary bifurcations: comparison of three drug-eluting stents. Ann. Biomed. Eng. 38:88–99, 2010.

    Article  PubMed  Google Scholar 

  36. Murphy, J., and F. Boyle. Assessment of the effects of increasing levels of physiological realism in the computational fluid dynamics analyses of implanted coronary stents. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2008:5906–5909, 2008.

    PubMed  CAS  Google Scholar 

  37. Myers, J. G., J. A. Moore, M. Ojha, K. W. Johnston, and C. R. Ethier. Factors influencing blood flow patterns in the human right coronary artery. Ann. Biomed. Eng. 29:109–120, 2001.

    Article  PubMed  CAS  Google Scholar 

  38. O’Rourke, M. F., and M. E. Safar. Relationship between aortic stiffening and microvascular disease in brain and kidney: cause and logic of therapy. Hypertension 46:200–204, 2005.

    Article  PubMed  Google Scholar 

  39. Perry, R., C. G. De Pasquale, D. P. Chew, L. Brown, P. E. Aylward, and M. X. Joseph. Changes in left anterior descending coronary artery wall thickness detected by high resolution transthoracic echocardiography. Am. J. Cardiol. 101:937–940, 2008.

    PubMed  Google Scholar 

  40. Pflederer, T., J. Ludwig, D. Ropers, W. G. Daniel, and S. Achenbach. Measurement of coronary artery bifurcation angles by multidetector computed tomography. Invest. Radiol. 41:793–798, 2006.

    Article  PubMed  Google Scholar 

  41. Radaelli, A. G., L. Augsburger, J. R. Cebral, M. Ohta, D. A. Rufenacht, R. Balossino, G. Benndorf, D. R. Hose, A. Marzo, R. Metcalfe, P. Mortier, F. Mut, P. Reymond, L. Socci, B. Verhegghe, and A. F. Frangi. Reproducibility of haemodynamical simulations in a subject-specific stented aneurysm model—a report on the virtual intracranial stenting challenge 2007. J. Biomech. 41:2069–2081, 2008.

    Article  PubMed  CAS  Google Scholar 

  42. Rayz, V. L., L. Boussel, L. Ge, J. R. Leach, A. J. Martin, M. T. Lawton, C. McCulloch, and D. Saloner. Flow residence time and regions of intraluminal thrombus deposition in intracranial aneurysms. Ann. Biomed. Eng. 38:3058–3069, 2010.

    Article  PubMed  CAS  Google Scholar 

  43. Richter, Y., and E. R. Edelman. Cardiology is flow. Circulation 113:2679–2682, 2006.

    Article  PubMed  Google Scholar 

  44. Rogers, C., and E. R. Edelman. Endovascular stent design dictates experimental restenosis and thrombosis. Circulation 91:2995–3001, 1995.

    PubMed  CAS  Google Scholar 

  45. Ryan, J., and D. J. Cohen. Are drug-eluting stents cost-effective? It depends on whom you ask. Circulation 114:1736–1743, 2006.

    Article  PubMed  Google Scholar 

  46. Sedat, J., Y. Chau, L. Mondot, J. Vargas, J. Szapiro, and M. Lonjon. Endovascular occlusion of intracranial wide-necked aneurysms with stenting (neuroform) and coiling: mid-term and long-term results. Neuroradiology 51:401–409, 2009.

    Article  PubMed  Google Scholar 

  47. Steinman, D. A., and C. A. Taylor. Flow imaging and computing: large artery hemodynamics. Ann. Biomed. Eng. 33:1704–1709, 2005.

    Article  PubMed  Google Scholar 

  48. Stergiopulos, N., D. F. Young, and T. R. Rogge. Computer simulation of arterial flow with applications to arterial and aortic stenoses. J. Biomech. 25:1477–1488, 1992.

    Article  PubMed  CAS  Google Scholar 

  49. Stergiopulos, N., P. Segers, and N. Westerhof. Use of pulse pressure method for estimating total arterial compliance in vivo. Am. J. Physiol. 276:H424–H428, 1999.

    PubMed  CAS  Google Scholar 

  50. Tanaka, H., N. Fujita, T. Enoki, K. Matsumoto, Y. Watanabe, K. Murase, and H. Nakamura. Relationship between variations in the circle of Willis and flow rates in internal carotid and basilar arteries determined by means of magnetic resonance imaging with semiautomated lumen segmentation: reference data from 125 healthy volunteers. AJNR Am. J. Neuroradiol. 27:1770–1775, 2006.

    PubMed  CAS  Google Scholar 

  51. 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 Circ. Physiol. 291:H668–H676, 2006.

    Article  PubMed  CAS  Google Scholar 

  52. Taylor, C. A., and D. A. Steinman. Image-based modeling of blood flow and vessel wall dynamics: applications, methods and future directions: Sixth International Bio-Fluid Mechanics Symposium and Workshop, March 28–30, 2008 Pasadena, California. Ann. Biomed. Eng. 38:1188–1203, 2010.

    Article  PubMed  Google Scholar 

  53. Van Belle, E., F. O. Tio, T. Couffinhal, L. Maillard, J. Pesseri, and J. M. Isner. Stent endothelialization: time course, impact of local catheter delivery, feasibility of recombinant protein administration, and response to cytokine expedition. Circulation 95:438–448, 1997.

    PubMed  Google Scholar 

  54. Van Huis, G. A., P. Sipkema, and N. Westerhof. Coronary input impedance during cardiac cycle as determined by impulse response method. Am. J. Physiol. 253:H317–H324, 1987.

    PubMed  Google Scholar 

  55. Vignon-Clementel, I. E., C. A. Figueroa, K. E. Jansen, and C. A. Taylor. Outflow boundary conditions for three-dimensional finite element modeling of blood flow and pressure in arteries. Comput. Methods Appl. Mech. Eng. 195:3776–3796, 2006.

    Article  Google Scholar 

  56. Wang, W. Q., D. K. Liang, D. Z. Yang, and M. Qi. Analysis of the transient expansion behavior and design optimization of coronary stents by finite element method. J. Biomech. 39:21–32, 2006.

    Article  PubMed  Google Scholar 

  57. Wanke, I., A. Doerfler, B. Schoch, D. Stolke, and M. Forsting. Treatment of wide-necked intracranial aneurysms with a self-expanding stent system: initial clinical experience. AJNR Am. J. Neuroradiol. 24:1192–1199, 2003.

    PubMed  Google Scholar 

  58. Wentzel, J. J., D. M. Whelan, W. J. van der Giessen, H. M. van Beusekom, I. Andhyiswara, P. W. Serruys, C. J. Slager, and R. Krams. Coronary stent implantation changes 3-d vessel geometry and 3-d shear stress distribution. J. Biomech. 33:1287–1295, 2000.

    Article  PubMed  CAS  Google Scholar 

  59. Westerhof, N., N. Stergiopulos, and M. I. M. Noble. Snapshots of Hemodynamics: An Aid for Clinical Research and Graduate Education. New York, NY: Springer, 2005, 192 pp.

  60. Williams, A. R., B. K. Koo, T. J. Gundert, P. J. Fitzgerald, and J. F. LaDisa, Jr. Local hemodynamic changes caused by main branch stent implantation and subsequent virtual side branch balloon angioplasty in a representative coronary bifurcation. J. Appl. Physiol. 109:532–540, 2010.

    Article  PubMed  Google Scholar 

  61. Wu, W., W. Q. Wang, D. Z. Yang, and M. Qi. Stent expansion in curved vessel and their interactions: a finite element analysis. J. Biomech. 40:2580–2585, 2007.

    Article  PubMed  Google Scholar 

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Acknowledgments

This work is supported by a Translational Opportunity Grant of the Pilot and Collaborative Clinical and Translational Research Grants program from the Clinical and Translational Science Institute of Southeastern Wisconsin and computational support for this work was made possible by NSF grants CTS-0521602 and OCI-0923037. Dr. Bon-Kwon Koo is the recipient of a research grant from the CardioVascular Research Foundation (CVRF), Korea. The authors recognize Nathan Wilson Ph.D. of Open Source Medical Software Corporation for technical assistance.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Marquette University, 1515 West Wisconsin Ave, Room 206, Milwaukee, WI, 53233, USA

    Timothy J. Gundert, Andrew R. Williams & John F. LaDisa Jr.

  2. Mechanical, Materials and Aerospace Engineering, Illinois Institute of Technology, 10 W. 32nd St, Chicago, IL, 60616, USA

    Shawn C. Shadden

  3. Seoul National University College of Medicine, Seoul, Korea

    Bon-Kwon Koo

  4. Department of Pediatrics (Cardiology), Lucile Packard Children’s Hospital and Stanford University School of Medicine, 750 Welch Road, Suite 305, Palo Alto, CA, 94304, USA

    Jeffrey A. Feinstein

  5. Department of Bioengineering, Lucile Packard Children’s Hospital and Stanford University School of Medicine, 750 Welch Road, Suite 305, Palo Alto, CA, 94304, USA

    Jeffrey A. Feinstein

  6. Department of Medicine, Division of Cardiovascular Medicine, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA

    John F. LaDisa Jr.

  7. Department of Pediatrics, Division of Pediatrics, Children’s Hospital and the Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA

    John F. LaDisa Jr.

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  1. Timothy J. Gundert
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Associate Editor Kerry Hourigan oversaw the review of this article.

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Gundert, T.J., Shadden, S.C., Williams, A.R. et al. A Rapid and Computationally Inexpensive Method to Virtually Implant Current and Next-Generation Stents into Subject-Specific Computational Fluid Dynamics Models. Ann Biomed Eng 39, 1423–1437 (2011). https://doi.org/10.1007/s10439-010-0238-5

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