Patient-Specific Modeling and Multi-Scale Blood Simulation for Computational Hemodynamic Study on the Human Cerebrovascular System

Current Pharmaceutical Biotechnology

Volumn 13, Issue 11, 2012, Pages 2153-2165

  Oshima, Marie ^a   Torii, Ryo ^b   Tokuda, Shigefumi ^c   Yamada, Shigeki ^d   Koizumi, Akio ^d  

^a INSTITUTE OF INDUSTRIAL SCIENCE   (Japan)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c TOYOTA MOTOR CORPORATION   (Japan)

^d KYOTO UNIVERSITY   (Japan)

Author keywords

Cerebrovascular System; Multi Scale Simulation; Patient Specific Hemodynamic Computation; The Arterial Circle of Willis; Three Dimensional Vascular Modeling

Indexed keywords

ALGORITHM; ANEURYSM; ATHEROSCLEROSIS; BLOOD FLOW; BLOOD PRESSURE; BRAIN ARTERY; BRAIN BLOOD VESSEL; BRAIN CIRCULUS ARTERIOSUS; COMPUTER SIMULATION; FLOW RATE; FOURIER TRANSFORMATION; HEMODYNAMICS; HUMAN; IMPEDANCE; KINEMATICS; MATHEMATICAL MODEL; PREDICTION; REVIEW; SHEAR STRESS; VISCOSITY; WAVEFORM;

CEREBROVASCULAR CIRCULATION; CIRCLE OF WILLIS; COMPUTER SIMULATION; HEMODYNAMICS; HUMANS; MODELS, CARDIOVASCULAR;

EID: 84873446361     PISSN: 13892010     EISSN: 18734316     Source Type: Journal    
DOI: 10.2174/138920112802502105     Document Type: Review

References (65)

1. Hendrikse, J.; Van Raamt, A.F.; Van der Graaf, Y.; Mali, W.P.T.M.; van der Grond, J. Distribution of cerebral blood flow in the circle of Willis. Radiology, 2005, 235, 184-189.
2. Stock, K.W.; Wetzel, S.G.; Lyrer, P.A.; Radu, E.W. Quantification of blood flow in the middle cerebral artery with phase-contrast MR imaging. Neuroradiology, 2000, 10, 1795-1800.
3. Tanaka, H.; Fujita, N.; Enoki, T.; Matsumoto, K.; Watanabe, Y.; Murase, K.; Nakamura, H. 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. Am. J. Neuroradiol., 2006, 27, 1770-17775.
4. Nixon, A.M.; Gunel, M.; Sumpio, B.E. The critical role of hemodynamics in the development of cerebral vascular disease. J. Neurosurg., 2010, 112, 1240-1253.
5. Malek, A.M.; Alper, S.L.; Izumo S. Hemodynamic shear stress and its role in atherosclerosis. J. Am. Med. Assoc., 1999, 282, 2035-2042.
6. Lee, S.W.; Antiga, L.; Spence, D.; Stinman, D. A geometry of the carotid bifurcation predicts its exposure to disturbed flow. Stroke, 2008, 39, 2341-2327.
7. Ujiie, H.; Tachibana, H.; Hiramatsu, O.; Hazel, A.; Matsumoto, T.; Ogasawara, Y.; Nakajima, H.; Hori, T.; Takakura, K.; Kajiya T. Effects of size and shape (aspect ratio) on the hemodynamics of saccular aneurysms: a possible index for surgical treatment of intracranial aneurysms. Neurosurgery, 1999, 45, 119-130.
8. Shojima, M.; Oshima, M.; Takagi, K.; Torii, R.; Hayakawa, M.; Katada, K.; Morita, A.; Kirino, T. Magnitude and role of wall shear stress on cerebral aneurysm: Computational fluid dynamic study of 20 middle cerebral artery aneurysms. Stroke, 2004, 35, 2500-2505.
9. Bacigaluppi, S.; Passerini, T.; Sangalli, L.; Secchi, P.; Vatini, S.; Vele, S.; Veneziani, A. Analysis of cerebral vascular morphologies for assessing rupture risk in cerebral aneurysms. J. Biomech., 2008, 41, S9.
10. Taylor, C.A.; Draney, M.T.; Ku, J.P.; Parker, D.; Steele, B.N.; Wang, K.; Zarins, C.K. Predictive medicine: Computational techniques in therapeutic decision-making. Comput. Aided Surg., 1999, 4, 231-247.
11. Zarins, C.K.; Taylor, C.A. Endovascular devise design in the future: transformation from trial and error to computational design. J. Endovasc. Ther., 2009, 16 112-121.
12. Lee, S.W.; Steinman, D.A. On the relative importance of rheology for image-based CFD models of the carotid bifurcation. J. Biomech. Eng., 2007, 129, 273-278.
13. Lee, S.W.; Lee, Fisher, P.F.; Bassiouny, H.S.; F. Loth. Direct numerical simulation of transitional flow in a stenosed carotid bifurcation. J. Biomech., 2008, 41, 2551-2561.
14. Cerbral, J.R.;Castro M.A.; Burgess, J.E.; Pergolizzi, R.S.; Sheridan, M.J.; Putman C.M. Charcaterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational heymodynaimcs models. Am. J. Neuroradiol., 2005, 26, 2550-2559.
15. Cebral, J.R.; Pergolizzi; and Putman C.M. Computational fluid dynamics modeling of intracranial aneurysms: qualitative comparison with cerebral angiography, Acad. Radiol., 2007, 14, 804-813.
16. Hoi, Y.S.; Woodward, S.H.; Kim, M.; Taulbee, D.B.; Meng, H. Validtion of CFD simulations of cerebral aneurysms with implication of geometric variations, J. Biomech. Eng., 2006, 128, 844-851.
17. Rays, V.L.; Boussel, L.; Lawton T.; Acevedo-Bolton, G.; Ge, L.; Young, W.L.; Higashida, T.; Saloner, D. Numerical modeling of the flow in intracranial aneurysms: prediction of region prone to thromosus formation, Ann. Biomed. Eng., 2008, 36, 1793-1804.
18. Torii, R.; Oshima, M.; Kobayashi, T.; Takagi, K. The hemodynamic study of the cerebral artery using numerical simulations based on medical imaging data. J. Visual., 2001, 4, 277-284.
19. Oshima, M.; Torii, R.; Kobayashi, T.; Taniguchi, N.; Takagi, K. Finite element simulation of blood flow in the cerebral artery. Comput. Methods Appl. Mech. Eng., 2001, 191, 661-671
20. Otto, F. Die Grundform des Arteriellen Pulses. Zeitung fur Biologie, 1899, 37, 483-586.
21. Passerini, T; Luca, M; Formaggia, L; Quarteroni, A.; Veneziani, A. A 3D/1D geometrical multiscale model of cerebral vasculature. J. Eng. Math., 2009, 64, 319-330.
22. Olufsen, M.S.; Peskin, C.S.; Kim, W.Y.; Pedersen, E.M.; Nadim, A.; Larsen, J. Numerical simulation and experimental validation of blood flow in arteries with structured-tree outflow conditions. Ann. Biomed. Eng., 2000, 28, 1281-1299.
23. Olufsen, M.S. Strcutured tree outflow condtion for blood flow in larger systemic arteries. Am. J. Physiol., 1999, 276, 257-268.
24. Blanco, P.J.; Feijoo, R.A.; Urquiza, S.A. A unified variational approach for coupling 3D-1D models and its blood flow applications. Comput. Methods Appl. Mech. Eng., 2007, 196, 4391-4410.
25. Blanco P.J.; Pivello M.R.; Urquiza S.A.; Feijoo R.A. On the potentialities of 3D-1D coupled models in hemodynamics simulations. J. Biomech., 2009, 11, 919-930.
26. Vignon-Clementel, I.E.; Figueroa, C. A.; Jansen, K.E.; Taylor, C.A. Outflow boundary conditions for three-dimensional finite element modeling of blood flow and pressure in arteries. Comput. Methods Appl. Mech. Eng., 2006, 195, 3776-3796.
27. Liang, F.; Takagi, S.; Himeno, R.; Liu, H. Multi-scale modeling of the human cardiovascular system with application to aortic valvular and arterial stenoses. Med. Biol. Eng. Comput., 2009, 47, 743-755.
28. Kim, H. J; Vignon-Clementel, I.E.; Figueroa, C.A.; LaDisa J.F.; Jansen K.E.; Feinstein, J.A.; Taylor C.A. On coupling a lumped parameter heart model and a three-dimensional finite element aorta model. Ann. Biomed. Eng., 2009, 37, 2153-2169.
29. Blanco, P.J.; Urquiza, S.A.; Feijoo, R.A. Assessing the influence of heart rate in local hemodynamics through coupled 3D-1D-0D models. International J. Numer. Methods Biomed. Eng. 2010, 26, 890-903.
30. Morbiducci, U.; Callo, D.; Massai D.; Consolo. F.; Ponzini, R., Antiga, L., Bignardi, C., Deriu, M. A., Redaelli, A., Outflow conditions for image-based hemodynamic models of the carotid bifurcation: implications for indicators of abnormal flow. J. Biomech., 2010, 9, 91005.
31. Urquiza, S.A.; Blanco, P.J.; Venere, M.J.; Feijoo, R.A. Multidimensional modeling for the carotid artery blood flow. Comput. Methods Appl. Mech. Eng. 2006, 195, 4002-4017.
32. Migliavacca, F; Balossino, R; Pennati, G; Durbini, G; Hsia, T-Y; de Leval, R. T; Bove, E.L. Multiscale modeling in biofluidynamics: application to reconstructive pediatric cariac surgery. J. Biomech., 2006, 39, 1010-1020.
33. Vignon-Clementel, I.E.; Figueroa, C.A.; Jansen, K.E.; Taylor C.A. Outflow boundary conditions for 3D simulations of non-periodic blood flow and pressure fields in deformable arteries. Comput. Methods Biomech. Biomed. Eng., 2010, 13, (5), 625-640.
34. Nobile. F. Coupling strategies for the numerical simulation of blood flow in deformable arteries by 3D and 1D models. Math. Comput. Model. 2009, 49, 2152-2160.
35. Brisman, J.L.; Song, J.K.; Newell, D.W. Cerebral aneurysms. Eng. J. Med., 2006, 355, 928-939.
36. Long, Q.; Xu, X.Y.; Collins, M.W.; Bourne, M.; Griffith, T.M., Magnetic resonance image processing and structured grid generation of a human abdominal bifurcation. Comput. Methods Prog. Biomed., 1998, 36, 249-259.
37. Lrensen, W.E.; Cline, H.E. Marching cubes: a high resolution 3D surface construction algorithm. Comput. Graph., 1987, 21, 163-170.
38. Wang K.C.; Dutton, R.W.; Taylor, C.A. Improving geometric model construction for blood flow modeling. IEEE Eng. Med. Biol., 1999, 18, 33-39.
39. Zhang, Y.; Bazilevs, Y.; Goswmi, S.; Bajaj, C.L.; Hughes, T.J.R. Patient-specific vascular NURMS modeling for isogeometirc analysis of blood flow. Comput. Methods Appl. Mech. Eng., 2007, 196, 2943-2959.
40. Torii, R.; Oshima, M.; An integrated geometric modeling framework for patrinet-specific computational hemodynamic study on wide-ranged vascuolar network, Comput. Methods Biomech. Miomed. Eng., in Press (available online, doi: 10.1080/10255842.2011.554407)
41. Saito, T.; Toriwaki, J. Reverse distance transformation and skeletons based upon the Euclidean metric for n-dimensional digital binary picture. IEICE Trans. Info. Syst., 1994, E77D, 1005-1016.
42. Insight Toolkit. Available at: http://www.itk.org/(Accessed on August 31, 2011).
43. Vasuclar Modeling Toolkit. Available at: http://www.vmtk.org/(Accessed on August 31, 2011).
44. Media Integration Standard Toolkit. Available at: http://mist.suenaga.cse.nagoya-u.ac.jp/document/(Accessed on August 31, 2011).
45. Lee, S.W.; Antiga, L.; Spence, J.D.; Steinman, D.A. Geometry of the carotid bifurcation predict its exposure to disturbed flow. Stroke, 2008, 39, 2341-2169.
46. Brooks, D.E.; Goodwin, J.W.; Seaman, G.V. Interactions among erythrocytes under shear. J. Appl. Physiol., 1970, 28, 172-177.
47. Development projects at the center for research on innovative simulation software. Available at: http://www.ciss.iis.utokyo. ac.jp/english/project/rss/example.html, (Accessed on August 31, 2011).
48. Tokuda, S. Computational study on initiation and growth of cardiovascular diseases. Ph.D. Thesis, Department of Mechanical Engineering, the University of Tokyo, Japan, 2008.
49. Tokuda, S.; Sugiyama, S.; Unemura, T.; Oshima, M. Modeling of multi-scale outflow boundary conditions for cerebral vascular flow simulation, Trans. JSME, 2008, 74, 871-878.
50. Zamir, M. Nonsymmetrical bifurcations in arterial branching. J. Gen Physiol., 1978, 72, 837-845.
51. Pries, A.R.; Recomb, T.W.: GeBner, T.; Sperandio, M.B.; Gross J.F.; Gaehtgens, P. Resistance to blood flow in microvessels in vivo. Circ. Res., 1994, 75, 904-915.
52. Freitas, R.A. Nanomedicine, volume I: Basic Capabilities, Landes Biosicence: Austin, TX, U.S.A., 1999.
53. Barbee, J.H.; Cokelet, G.R. The Fahraeus effect. Microvasc. Res., 1971, 3, 6-16.
54. Barbee, J.H.; Cokelet, G.R. Prediction of blood flow in tubes with diameters as small as 29m. Microvasc. Res., 1971, 3, 17-21.
55. Womersley, J.R. Method for the calculation of velocity, rate flow, and viscous drag in arteries when the pressure gradient is known. J. Physiol., 1955, 127, 553-563.
56. Scheel, P.; Ruge, C.; Schoning, M. Flow velocity and flow volume measurements in the extracranial carotid and vertebral arteries in healthy adults: Reference data and the effects of age. Ultrasound Med. Biol., 2000, 26, 1261-1266.
57. Hendrikse, J.; Hartkamp, M.J.; Hillen, B.; Mali, W.P.T.M.; van der Grond, J. Collateral ability of the circle of Willis in patients with unilateral internal carotid artery occlusion: border zone infarcts and clinical symptoms. Stroke, 2001, 32, 2768-2773.
58. Liebeskind, D. S. Collateral circulation. Stroke, 2003, 34, 2279-2284.
59. Gobin, Y.P.; Cloughesy T. F.; Chow K.I.; Duckwiler, G.R.; Sayre, J.W.; Milanese, K.; Vinuela, F. Intraarterial chemotherapy for brain tumor by using a spatial dose fractional algorithm and pulsatile delivery. Radiology, 2001, 218, 724-732.
60. Horikoshi, T.; Akiyama, I.; Yamagata, Z.; Sugita, M.; Nukui, H. Magnetic resonance angiographic evidence of sex-linked variations in the circle of Willis and the occurrence of cerebral aneurysms. J. Neurosurg., 2002, 96, 697-70.
61. Kapoor, K.; Singh, B.; Dewan, L.I. Variations in the configuration of the circle of Willis, Anat. Sci. Int., 2008, 83(2), pp.96-106.
62. Torii, R.; Oshima, M.; Kobayashi, T.; Takagi, K.; Tezduyar, T.E. Role of 0D peripheral vascular model in fluid-structure interaction modeling of aneurysms. Comput. Mech., 2010, 46, pp.43-52.
63. Liang, F.L.; Takagi, S.; Himeno, R.; Liu, H. Biomechanical characterization of ventricular-arterial coupling during aging: a multiscale model study. J. Biomech., 2009, 42, 692-704.
64. Ford, M.D.; Nikolov, H.N.; Milner, J.S.; Lownie, S.P.; Demont, E.M.; Kalata, W.; Loth, F.;Holdsworth, D.W.; Steinman, D. A. PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models. J. Biomech. Eng., 2008, 130, 021015.
65. Lee, S.W.; Smith, D.S.; Loth, F.; Fischer, P.F.; Bassiouny, H.S. Numerical and experimental simulation of transition flow in a blood vessel junction. Numer. Heat Transf., Appl., 2007, 51, 1-22.