Skip to main content
SpringerLink
Log in

Characterizing Intracranial Hemodynamics in Sickle Cell Anemia: Impact of Patient-Specific Viscosity

  • Original Article
  • Published:
Cardiovascular Engineering and Technology Aims and scope Submit manuscript

Abstract

Purpose

Pediatric and adult patients with sickle cell anemia (SCA) are at increased risk of stroke and cerebrovascular accident. In the general adult population, there is a relationship between arterial hemodynamics and pathology; however, this relationship in SCA patients remains to be elucidated. The aim of this work was to characterize circle of Willis hemodynamics in patients with SCA and quantify the impact of viscosity choice on pathophysiologically-relevant hemodynamics measures.

Methods

Based on measured vascular geometries, time-varying flow rates, and blood parameters, detailed patient-specific simulations of the circle of Willis were conducted for SCA patients (n = 6). Simulations quantified the impact of patient-specific and standard blood viscosities on wall shear stress (WSS).

Results

These results demonstrated that use of a standard blood viscosity introduces large errors into the estimation of pathophysiologically-relevant hemodynamic parameters. Standard viscosity models overpredicted peak WSS by 55% and 49% for steady and pulsatile flow, respectively. Moreover, these results demonstrated non-uniform, spatial patterns of positive and negative WSS errors related to viscosity, and standard viscosity simulations overpredicted the time-averaged WSS by 32% (standard deviation = 7.1%). Finally, differences in shear rate demonstrated that the viscosity choice alters the simulated near-wall flow field, impacting hemodynamics measures.

Conclusions

This work presents simulations of circle of Willis arterial flow in SCA patients and demonstrates the importance and feasibility of using a patient-specific viscosity in these simulations. Accurately characterizing cerebrovascular hemodynamics in SCA populations has potential for elucidating the pathophysiology of large-vessel occlusion, aneurysms, and tissue damage in these patients.

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

Abbreviations

ACA:

Anterior cerebral artery

BAS:

Basilar artery

CFD:

Computational fluid dynamics

CVA:

Cerebrovascular accident

HbSS:

Homozygous sickle cell anemia

Hgb S/A:

Hemoglobin S or A

ICA:

Internal carotid artery

ICAM:

Intercellular adhesion molecule

MCA:

Middle cerebral artery

MR(I):

Magnetic resonance (imaging)

OSI:

Oscillatory shear index

\(\overline{{{\text{OSI}}_{{{\text{P}}/{\text{S}}}} }}\) :

Spatially-averaged oscillatory shear index simulated using either patient-specific (P) or standard (S) viscosity

PC-MRI:

Phase contrast-MRI

PCA:

Posterior cerebral artery

SCA:

Sickle cell anemia

SD:

Standard deviation

TNF-α:

Tumor necrosis factor-α

VCAM:

Vascular cell adhesion molecule

WSS:

Wall shear stress

\({\text{WSS}}_{\text{Max}}\) :

Maximum wall shear stress value for steady flow or the maximum time-averaged wall shear stress value for pulsatile simulations

\(\overline{{{\text{WSS}}_{\text{P/S}} }}\) :

Spatially-averaged wall shear stress simulated using either patient-specific (P) or standard (S) viscosity under steady flow conditions

\(\overline{{{\text{WSS}}_{\text{Mean,P/S}} }}\) :

Time- and spatially-averaged wall shear stress using either patient-specific (P) or standard (S) viscosity under pulsatile flow conditions

WSSMean :

Time-averaged value of WSS from pulsatile flow simulations

\({\text{\% WSS}}_{\text{DIF}}\) :

The percent difference of time-averaged WSSMean between simulations using patient-specific viscosity and standard viscosity values

µ P :

Patient-specific viscosity value estimated from clinical hematocrit measurements (kg/m-s)

µ S :

Standard blood viscosity typically used for hemodynamics simulations (0.00368 kg/m-s)

References

  1. Adams, R. J., V. C. Mckie, L. Hsu, B. Files, E. Vichinsky, C. Pegelow, M. Abboud, D. Gallagher, A. Kutlar, F. T. Nichols, D. R. Bonds, D. Brambilla, G. Woods, N. Olivieri, C. Driscoll, S. Miller, W. Wang, A. Hurlett, C. Scher, B. Berman, E. Carl, A. M. Jones, E. S. Roach, E. Wright, R. A. Zimmerman, and M. Waclawiw. Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial Doppler ultrasonography. N. Engl. J. Med. 1998. https://doi.org/10.1056/NEJM199807023390102.

    Article  PubMed  Google Scholar 

  2. Aleluia, M. M., T. C. C. Fonseca, R. Q. Souza, F. I. Neves, C. C. da Guarda, R. P. Santiago, B. L. A. Cunha, C. V. B. Figueiredo, S. S. Santana, S. S. da Paz, J. R. D. Ferreira, B. A. V. Cerqueira, and M. S. Gonçalves. Comparative study of sickle cell anemia and hemoglobin SC disease: clinical characterization, laboratory biomarkers and genetic profiles. BMC Hematol. 17:15, 2017. https://doi.org/10.1186/s12878-017-0087-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Alemu, Y., and D. Bluestein. Flow-induced platelet activation and damage accumulation in a mechanical heart valve: numerical studies. Artif. Org. 31:677–688, 2007.

    Article  Google Scholar 

  4. Alnæs, M. S., J. Isaksen, K.-A. Mardal, B. Romner, M. K. Morgan, and T. Ingebrigtsen. Computation of hemodynamics in the Circle of Willis. Stroke 38:2500–2505, 2007.

    Article  Google Scholar 

  5. Ando, J., H. Tsuboi, R. Korenaga, Y. Takada, N. Toyama-Sorimachi, M. Miyasaka, and A. Kamiya. Shear stress inhibits adhesion of cultured mouse endothelial cells to lymphocytes by downregulating VCAM-1 expression. Am. J. Physiol. 267:C679–C687, 1994. https://doi.org/10.1152/ajpcell.1994.267.3.c679.

    Article  CAS  PubMed  Google Scholar 

  6. Belhassen, L., G. Pelle, S. Sediame, D. Bachir, C. Carville, C. Bucherer, C. Lacombe, F. Gallacteros, and S. Adnot. Endothelial dysfunction in patients with sickle cell disease is related to selective impairment of shear stress-mediated vasodilation. Blood 97:1584–1589, 2001.

    Article  CAS  Google Scholar 

  7. Bharadvaj, B. K., R. F. Mabon, and D. P. Giddens. Steady flow in a model of the human carotid bifurcation. Part I-Flow visualization. J Biomech. 15:349–362, 1982. https://doi.org/10.1016/0021-9290(82)90057-4.

    Article  CAS  PubMed  Google Scholar 

  8. Birkeland, P., K. Gardner, R. Kesse-Adu, J. Davies, J. Lauritsen, F. R. Poulsen, C. M. Tolias, and S. L. Thein. Intracranial aneurysms in sickle-cell disease are associated with the hemoglobin SS genotype but not with moyamoya syndrome. Stroke 47:1710–1713, 2016. https://doi.org/10.1161/STROKEAHA.116.012664.

    Article  PubMed  Google Scholar 

  9. Bisschops, R. H. C., Y. Van Der Graaf, W. P. T. M. Mali, and J. Van Der Grond. High total cerebral blood flow is associated with a decrease of white matter lesions. J. Neurol. 251:1481–1485, 2004. https://doi.org/10.1007/s00415-004-0569-y.

    Article  CAS  PubMed  Google Scholar 

  10. Biswas, D., D. M. Casey, D. C. Crowder, D. A. Steinman, Y. H. Yun, and F. Loth. Characterization of transition to turbulence for blood in a straight pipe under steady flow conditions. J. Biomech. Eng. 138:2016.

    Article  Google Scholar 

  11. Campbell, I. C., J. Ries, S. S. Dhawan, A. A. Quyyumi, W. R. Taylor, and J. N. Oshinski. Effect of inlet velocity profiles on patient-specific computational fluid dynamics simulations of the carotid bifurcation. J. Biomech. Eng. 134:2012. https://doi.org/10.1115/1.4006681.

    Article  PubMed  Google Scholar 

  12. Caro, C. G., T. Pedley, R. C. Schroter, and W. A. Seed. The Mechanics of the Circulation. New York: Oxford University Press, 1978.

    Google Scholar 

  13. Cebral, J. R., F. Mut, J. Weir, and C. Putman. Quantitative characterization of the hemodynamic environment in ruptured and unruptured brain aneurysms. Am. J. Neuroradiol. 32:145–151, 2011. https://doi.org/10.3174/ajnr.A2419.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Cebral, J. R., C. M. Putman, M. T. Alley, T. Hope, R. Bammer, and F. Calamante. Hemodynamics in normal cerebral arteries: qualitative comparison of 4D phase-contrast magnetic resonance and image-based computational fluid dynamics. J. Eng. Math. 64:367–378, 2009.

    Article  Google Scholar 

  15. Chappell, D. C., S. E. Varner, R. M. Nerem, R. M. Medford, and R. W. Alexander. Oscillatory shear stress stimulates adhesion molecule expression in cultured human endothelium. Circ. Res. 82:532–539, 1998. https://doi.org/10.1161/01.RES.82.5.532.

    Article  CAS  PubMed  Google Scholar 

  16. Chien, S., S. Usami, and J. F. Bertles. Abnormal rheology of oxygenated blood in sickle cell anemia. J. Clin. Invest. 49:623–634, 1970. https://doi.org/10.1172/JCI106273.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Chnafa, C., P. Bouillot, O. Brina, B. M. A. Delattre, M. I. Vargas, K. O. Lovblad, V. M. Pereira, and D. A. Steinman. Vessel calibre and flow splitting relationships at the internal carotid artery terminal bifurcation. Physiol. Meas. 38:2044–2057, 2017.

    Article  CAS  Google Scholar 

  18. Cignoni, P., M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, and G. Ranzuglia. MeshLab: An open-source mesh processing tool. 6th Eurographics Italian Chapter Conference 2008 - Proceedings. 2008; pp. 129–136.

  19. Dampier, C., B. N. Y. Setty, B. Eggleston, D. Brodecki, P. O’Neal, and M. Stuart. Vaso-occlusion in children with sickle cell disease: clinical characteristics and biologic correlates. J. Pediatr. Hematol. Oncol. 26:785–790, 2004. https://doi.org/10.1016/s0084-3954(07)70057-x.

    Article  PubMed  Google Scholar 

  20. Das, A., J. P. Wansapura, W. M. Gottliebson, and R. K. Banerjee. Methodology for implementing patient-specific spatial boundary condition during a cardiac cycle from phase-contrast MRI for hemodynamic assessment. Med. Image Anal. 19:121–136, 2015. https://doi.org/10.1016/j.media.2014.09.001.

    Article  PubMed  Google Scholar 

  21. Detmer, F. J., B. J. Chung, F. Mut, M. Pritz, M. Slawski, F. Hamzei-Sichani, D. Kallmes, C. Putman, C. Jimenez, and J. R. Cebral. Development of a statistical model for discrimination of rupture status in posterior communicating artery aneurysms. Acta Neurochir. (Wien). 160:1643–1652, 2018. https://doi.org/10.1007/s00701-018-3595-8.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Detterich, J., T. Alexy, M. Rabai, R. Wenby, A. Dongelyan, T. Coates, J. Wood, and H. Meiselman. Low-shear red blood cell oxygen transport effectiveness is adversely affected by transfusion and further worsened by deoxygenation in sickle cell disease patients on chronic transfusion therapy. Transfusion 53:297–305, 2013. https://doi.org/10.1111/j.1537-2995.2012.03822.x.

    Article  CAS  PubMed  Google Scholar 

  23. Fields, M. E., K. P. Guilliams, D. K. Ragan, M. M. Binkley, C. Eldeniz, Y. Chen, M. L. Hulbert, R. C. McKinstry, J. S. Shimony, K. D. Vo, A. Doctor, H. An, A. L. Ford, and J. M. Lee. Regional oxygen extraction predicts border zone vulnerability to stroke in sickle cell disease. Neurology 90:e1134–e1142, 2018. https://doi.org/10.1212/WNL.0000000000005194.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Gao, L., Y. Hoi, D. D. Swartz, J. Kolega, A. Siddiqui, and H. Meng. Nascent aneurysm formation at the basilar terminus induced by hemodynamics. Stroke 39:2085–2090, 2008. https://doi.org/10.1161/STROKEAHA.107.509422.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Glagov, S., C. Zarins, D. P. Giddens, and D. N. Ku. Hemodynamics and atherosclerosis. Insights and perspectives gained from studies of human arteries. Arch. Pathol. Lab. Med. 112:1019–1031, 1988.

    Google Scholar 

  26. Guilliams, K. P., M. E. Fields, D. K. Ragan, Y. Chen, C. Eldeniz, M. L. Hulbert, M. M. Binkley, J. N. Rhodes, J. S. Shimony, R. C. McKinstry, K. D. Vo, H. An, J. M. Lee, and A. L. Ford. Large-vessel vasculopathy in children with sickle cell disease: a magnetic resonance imaging study of infarct topography and focal atrophy. Pediatr. Neurol. 69:49–57, 2017. https://doi.org/10.1016/j.pediatrneurol.2016.11.005.

    Article  PubMed  Google Scholar 

  27. Hassell, K. L. Population estimates of sickle cell disease in the U.S. Am. J. Prev. Med. 38(4):S523–21, 2010.

    Article  Google Scholar 

  28. He, X., and D. N. Ku. Pulsatile flow in the human left coronary artery bifurcation: average conditions. J Biomech Eng. 118:74–82, 1996. https://doi.org/10.1115/1.2795948.

    Article  CAS  PubMed  Google Scholar 

  29. Hutchison, J. S., R. Ichord, A. M. Guerguerian, and G. DeVeber. Cerebrovascular disorders. Semin. Pediatr. Neurol. 11:139–146, 2004. https://doi.org/10.1016/j.spen.2004.04.004.

    Article  PubMed  Google Scholar 

  30. Jutukonda, M. R., C. A. Lee, N. J. Patel, L. T. Davis, S. J. Waddle, M. C. Gindville, S. Pruthi, A. A. Kassim, M. R. DeBaun, M. J. Donahue, and L. C. Jordan. Differential cerebral hemometabolic responses to blood transfusion in adults and children with sickle cell anemia. J. Magn. Reson. Imaging. 49(2):466–477, 2019.

    Article  Google Scholar 

  31. Kamiya, A., and T. Togawa. Adaptive regulation of wall shear stress to flow change in the canine carotid artery. Am. J. Physiol. 239:H14–H21, 1980. https://doi.org/10.1152/ajpheart.1980.239.1.h14.

    Article  CAS  PubMed  Google Scholar 

  32. Kassim, A. A., S. Pruthi, M. Day, M. Rodeghier, M. C. Gindville, M. A. Brodsky, M. R. Debaun, and L. C. Jordan. Silent cerebral infarcts and cerebral aneurysms are prevalent in adults with sickle cell anemia. Blood 127:2038–2040, 2016. https://doi.org/10.1182/blood-2016-01-694562.

    Article  CAS  PubMed  Google Scholar 

  33. Ku, D. N., D. P. Giddens, C. K. Zarins, and S. Glagov. Pulsatile flow and atherosclerosis in the human carotid bifurcation: positive correlation between plaque location and low and oscillating shear stress. Arteriosclerosis. 5:293–302, 1985.

    Article  CAS  Google Scholar 

  34. Mannino, R. G., D. R. Myers, B. Ahn, Y. Wang, M. Rollins, H. Gole, A. S. Lin, R. E. Guldberg, D. P. Giddens, L. H. Timmins, and W. A. Lam. Do-it-yourself in vitro vasculature that recapitulates in vivo geometries for investigating endothelial-blood cell interactions. Sci. Rep. 5:12401, 2015. https://doi.org/10.1038/srep12401.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Marshall, I., P. Papathanasopoulou, and K. Wartolowska. Carotid flow rates and flow division at the bifurcation in healthy volunteers. Physiol. Meas. 25:691–697, 2004.

    Article  Google Scholar 

  36. 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(1):P143–156, 1998. https://doi.org/10.1016/S0741-5214(98)70210-1.

    Article  Google Scholar 

  37. Moore, 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. https://doi.org/10.1016/0021-9150(94)90207-0.

    Article  CAS  PubMed  Google Scholar 

  38. Moser, F. G., S. T. Miller, J. A. Bello, C. H. Pegelow, R. A. Zimmerman, W. C. Wang, K. Ohene-Frempong, A. Schwartz, E. P. Vichinsky, D. Gallagher, and T. R. Kinney. The spectrum of brain MR abnormalities in sickle-cell disease: a report from the cooperative study of sickle cell disease. Am. J. Neuroradiol. 17:965–972, 1996.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Nabavizadeh, S. A., A. Vossough, R. N. Ichord, J. Kwiatkowski, B. A. Pukenas, M. J. Smith, P. B. Storm, E. L. Zager, and R. W. Hurst. Intracranial aneurysms in sickle cell anemia: clinical and imaging findings. J. Neurointerv. Surg. 8:434–440, 2016. https://doi.org/10.1136/neurintsurg-2014-011572.

    Article  PubMed  Google Scholar 

  40. Needleman, J. P., B. N. Setty, L. Varlotta, C. Dampier, and J. L. Allen. Measurement of hemglobin saturation by oxygen in children and adolescents with sickle cell disease. Pediatr. Polmonol. 28(6):423–428, 1999.

    Article  CAS  Google Scholar 

  41. Ohene-Frempong, K., S. J. Weiner, L. A. Sleeper, S. T. Miller, S. Embury, J. W. Moohr, D. L. Wethers, C. H. Pegelow, and F. M. Gill. Cerebrovascular accidents in sickle cell disease: rates and risk factors. Blood 91:288–294, 1998. https://doi.org/10.1182/blood.V91.1.288.

    Article  CAS  PubMed  Google Scholar 

  42. Ohtsuka, A., J. Ando, R. Korenaga, A. Kamiya, N. Toyama-Sorimachi, and M. Miyasaka. The effect of flow on the expression of vascular adhesion molecule-1 by cultured mouse endothelial cells. Biochem. Biophys. Res. Commun. 193(1):303–310, 1993. https://doi.org/10.1006/bbrc.1993.1624.

    Article  CAS  PubMed  Google Scholar 

  43. Pedley, T. The Fluid Mechanics of Large Blood Vessels. Cambridge: Cambridge University Press, 1980.

    Book  Google Scholar 

  44. Prohovnik, I., A. Hurlet-Jensen, R. Adams, D. De Vivo, and S. G. Pavlakis. Hemodynamic etiology of elevated flow velocity and stroke in sickle-cell disease. J. Cereb. Blood Flow Metab. 29:803–810, 2009. https://doi.org/10.1038/jcbfm.2009.6.

    Article  PubMed  Google Scholar 

  45. Rees, D. C., T. N. Williams, and M. T. Gladwin. Sickle-cell disease. Lancet 376(9757):2018–2031, 2010.

    Article  CAS  Google Scholar 

  46. Rivera, C. P., A. Veneziani, R. E. Ware, and M. O. Platt. Original research: sickle cell anemia and pediatric strokes: computational fluid dynamics analysis in the middle cerebral artery. Exp. Biol. Med. 241:755–765, 2016. https://doi.org/10.1177/1535370216636722.

    Article  CAS  Google Scholar 

  47. Roach, M. R., S. Scott, and G. G. Ferguson. The hemodynamic importance of the geometry of bifurcations in the circle of Willis (Glass Model Studies). Stroke 3:255–267, 1972.

    Article  CAS  Google Scholar 

  48. Rothman, S. M., K. H. Fulling, and J. S. Nelson. Sickle cell anemia and central nervous system infarction: a neuropathological study. Ann. Neurol. 20:684–690, 1986.

    Article  CAS  Google Scholar 

  49. Sadasivan, C., D. J. Fiorella, H. H. Woo, and B. B. Lieber. Physical factors effecting cerebral aneurysm pathophysiology. Ann. Biomed. Eng. 41:1347–1365, 2013. https://doi.org/10.1007/s10439-013-0800-z.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Schmalzer, E. A., J. O. Lee, A. K. Brown, and S. Usami. Viscosity of mixtures of sickle and normal red cells at varying hematocrit levels: implications for transfusion. Transfusion 27:228–233, 1987. https://doi.org/10.1046/j.1537-2995.1987.27387235626.x.

    Article  CAS  PubMed  Google Scholar 

  51. Sheriff, J., D. Bluestein, G. Girdhar, and J. Jesty. High-shear stress sensitizes platelets to subsequent low-shear conditions. Ann. Biomed. Eng. 38:1442–1450, 2010. https://doi.org/10.1007/s10439-010-9936-2.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Steen, R. G., X. Xiong, J. W. Langston, and K. J. Helton. Brain injury in children with sickle cell disease: prevalence and etiology. Ann. Neurol. 54(5):564–572, 2003.

    Article  Google Scholar 

  53. Steen, R. G., X. Xiong, R. K. Mulhern, J. W. Langston, and W. C. Wang. Subtle brain abnormalities in children with sickle cell disease: relationship to blood hematocrit. Ann. Neurol. 45:279–286, 1999.

    Article  CAS  Google Scholar 

  54. Steinberg, M. H. Management of sickle cell disease. N. Engl. J. Med. 340:1021–1030, 1999. https://doi.org/10.1056/NEJM199904013401307.

    Article  CAS  PubMed  Google Scholar 

  55. Steinman, D. A., and V. M. Pereira. How patient specific are patient-specific computational models of cerebral aneurysms? An overview of sources of error and variability. Neuosurg. Focus. 47(1):E14, 2019.

    Article  Google Scholar 

  56. Strouse, J. J., L. C. Jordan, S. Lanzkron, and J. F. Casella. The excess burden of stroke in hospitalized adults with sickle cell disease. Am. J. Hematol. 84(9):548–552, 2009.

    Article  Google Scholar 

  57. Tang, D., C. Yang, S. Kobayashi, and D. N. Ku. Effect of a lipid pool on stress/strain distributions in stenotic arteries: 3-D fluid-structure interactions (FSI) models. J. Biomech. Eng. 126:363–370, 2004.

    Article  Google Scholar 

  58. 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. https://doi.org/10.1007/s10439-010-9901-0.

    Article  PubMed  Google Scholar 

  59. Timmins, L. H., D. S. Molony, P. Eshtehardi, M. C. McDaniel, J. N. Oshinski, D. P. Giddens, and H. Samady. Oscillatory wall shear stress is a dominant flow characteristic affecting lesion progression patterns and plaque vulnerability in patients with coronary artery disease. J. R. Soc. Interface 14:20160972, 2017. https://doi.org/10.1098/rsif.2016.0972.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Tropea, B. I., S. Glagov, and C. K. Zarins. Hemodynamics and atherosclerosis. In: Basic science in vascular disease, edited by A. N. Sidawy, B. E. Sumpio, and R. B. depalma. Armonk: Futura Publishing Company Inc, 1997, pp. 107–126.

    Google Scholar 

  61. Václavů, L., Z. A. V. Baldew, S. Gevers, H. J. M. M. Mutsaerts, K. Fijnvandraat, M. H. Cnossen, C. B. Majoie, J. C. Wood, E. VanBavel, B. J. Biemond, P. van Ooij, and A. J. Nederveen. Intracranial 4D flow magnetic resonance imaging reveals altered haemodynamics in sickle cell disease. Br. J. Haematol. 180:432–442, 2018. https://doi.org/10.1111/bjh.15043.

    Article  PubMed  Google Scholar 

  62. Valen-Sendstad, K., K.-A. Mardal, M. Mortensen, B. A. P. Reif, and H. P. Langtangen. Direct numerical simulation of transitional flow in a patient-specific intracranial aneurysm. J. Biomech. 44:2826–2832, 2011.

    Article  Google Scholar 

  63. Wagner, M. C., J. R. Eckman, and T. M. Wick. Sickle cell adhesion depends on hemodynamics and endothelial activation. J. Lab. Clin. Med. 144:260–267, 2004. https://doi.org/10.1016/j.lab.2004.08.004.

    Article  CAS  PubMed  Google Scholar 

  64. Wake-Buck, A. K., J. C. Gatenby, and J. C. Gore. Hemodynamic characteristics of the vertebrobasilar system analyzed using MRI-based models. PLoS ONE 7(12):2012. https://doi.org/10.1371/journal.pone.0051346.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Wastnedge, E., D. Waters, S. Patel, K. Morrison, M. Y. Goh, D. Adeloye, and I. Rudan. The global burden of sickle cell disease in children under five years of age: a systematic review and meta-analysis. J. Glob. Health 8:021103, 2018. https://doi.org/10.7189/jogh.08.021103.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Wick, T. M., and J. R. Eckman. Molecular basis of sickle cell-endothelial cell interactions. Curr. Opin Hematol. 3:118–124, 1996. https://doi.org/10.1097/00062752-199603020-00003.

    Article  CAS  PubMed  Google Scholar 

  67. Yushkevich, P. A., J. Piven, H. C. Hazlett, R. G. Smith, S. Ho, J. C. Gee, and G. Gerig. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 31:1116–1128, 2006. https://doi.org/10.1016/j.neuroimage.2006.01.015.

    Article  PubMed  Google Scholar 

  68. Zarins, C. K., M. A. Zatina, D. P. Giddens, D. N. Ku, and S. Glagov. Shear stress regulation of artery lumen diameter in experimental atherogenesis. J. Vasc. Surg. 5(3):P413–420, 1987. https://doi.org/10.1016/0741-5214(87)90048-6.

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by grants from the American Heart Association (10POST3450046), the National Institutes of Health (5T32 EB001628-07), and the National Center for Advancing Translational Sciences Vanderbilt CTSA award (UL1 TR002243). We are grateful to the Vanderbilt University Institute of Imaging Science (VUIIS) and the Human Imaging Core for providing imaging research resources used in this study.

Funding

American Heart Association (10POST3450046); National Institutes of Health (5T32 EB001628-07); and the National Center for Advancing Translational Sciences Vanderbilt CTSA award (UL1 TR002243).

Data Availability

Upon request, subject to IRB approval.

Conflict of interest

The authors have no conflicts of interest to declare.

Human Studies

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5)

Informed Consent

Informed consent was obtained from all patients included in the study.

Author information

Author notes

  1. Jacob M. Bumpus

    Present address: Northgate Technologies, Inc, Elgin, IL, USA

Authors and Affiliations

  1. Department of Bioengineering, University of Washington, Seattle, WA, USA

    Sara B. Keller

  2. Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA

    Jacob M. Bumpus, John C. Gore & Amanda K. W. Buck

  3. Department of Radiology, University of Washington, Seattle, WA, USA

    J. Christopher Gatenby

  4. Center for Cancer and Blood Disorders, Pediatric Specialists of Virginia, Fairfax, VA, USA

    Elizabeth Yang

  5. Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

    Adetola A. Kassim

  6. Department of Pediatrics, Emory University and Aflac Cancer and Blood Disorders Center, Children’s Healthcare of Atlanta, Atlanta, GA, USA

    Carlton Dampier

  7. Vanderbilt University Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA

    John C. Gore & Amanda K. W. Buck

  8. Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, USA

    John C. Gore

  9. Vanderbilt University Medical Center, 1161 21st Avenue South, Medical Center North, AA-1105, Nashville, TN, 37232-2310, USA

    Amanda K. W. Buck

Authors
  1. Sara B. Keller
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jacob M. Bumpus
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. Christopher Gatenby
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Elizabeth Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Adetola A. Kassim
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Carlton Dampier
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. John C. Gore
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Amanda K. W. Buck
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amanda K. W. Buck.

Additional information

Associate Editor Ajit P. Yoganathan oversaw the review of this article.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Electronic supplementary material 1 (PDF 187 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Keller, S.B., Bumpus, J.M., Gatenby, J.C. et al. Characterizing Intracranial Hemodynamics in Sickle Cell Anemia: Impact of Patient-Specific Viscosity. Cardiovasc Eng Tech 13, 104–119 (2022). https://doi.org/10.1007/s13239-021-00559-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13239-021-00559-2

Keywords

Search

Navigation