Children with sickle cell anemia (SCA) have a high incidence of strokes, and transcranial Doppler (TCD) identifies at-risk patients by measuring blood velocities in large intracerebral arteries; time-averaged mean velocities greater than 200 cm/s confer high stroke risk and warrant therapeutic intervention with blood transfusions. Our objective was to use computational fluid dynamics to alter fluid and artery wall properties, to simulate scenarios causative of significantly elevated arterial blood velocities. Two-dimensional simulations were created and increasing percent stenoses were created in silico, with their locations varied among middle cerebral artery (MCA), internal carotid artery (ICA), and anterior cerebral artery (ACA). Stenoses placed in the MCA, ICA, or ACA generated local increases in velocity, but not sufficient to reach magnitudes > 200 cm/s, even up to 75% stenosis. Three-dimensional reconstructions of the MCA, ICA, and ACA from children with SCA were generated from magnetic resonance angiograms. Using finite element method, blood flow was simulated with realistic velocity waveforms to the ICA inlet. Three-dimensional reconstructions revealed an uneven, internal arterial wall surface in children with SCA and higher mean velocities in the MCA up to 145 cm/s compared to non-SCA reconstructions. There were also greater areas of flow recirculation and larger regions of low wall shear stress. Taken together, these bumps on the internal wall of the cerebral arteries could create local flow disturbances that, in aggregate, could elevate blood velocities in SCA. Identifying cellular causes of these microstructures as adhered blood cells or luminal narrowing due to endothelial hyperplasia induced by disturbed flow would provide new targets to treat children with SCA. The preliminary qualitative results provided here point out the critical role of 3D reconstruction of patient-specific vascular geometries and provide qualitative insight to complex interplay between vascular geometry and rheological properties possibly altered by SCA.
HassellKL. Population estimates of sickle cell disease in the U.S. Am J Prev Med2010; 38: S512–21.
2.
HilleryCPanepintoJ. Pathophysiology of stroke in sickle cell disease. Microcirculation2004; 11: 195–208.
3.
DeBaunMRArmstrongFDMcKinstryRCWareREVichinskyEKirkhamFJ. Silent cerebral infarcts: a review on a prevalent and progressive cause of neurologic injury in sickle cell anemia. Blood2012; 119: 4587–96.
4.
AdamsRJBrambillaD. Optimizing primary stroke prevention in sickle cell anemia trial I. Discontinuing prophylactic transfusions used to prevent stroke in sickle cell disease. N Engl J Med2005; 353: 2769–78.
5.
AdamsRJMcKieVCHsuLFilesBVichinskyEPegelowCAbboudMGallagherDKutlarANicholsFTBondsDRBrambillaD. Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial Doppler ultrasonography. N Engl J Med1998; 339: 5–11.
6.
AdamsRJBrambillaDJGrangerSGallagherDVichinskyEAbboudMRPegelowCHWoodsGRohdeEMNicholsFTJonesALudenJPBowmanLHagnerSMoralesKHRoachES. Stroke and conversion to high risk in children screened with transcranial Doppler ultrasound during the STOP study. Blood2004; 103: 3689–94.
7.
HankinsJSFortnerGLMcCarvilleMBSmeltzerMPWangWCLiCSWareRE. The natural history of conditional transcranial Doppler flow velocities in children with sickle cell anaemia. Br J Haematol2008; 142: 94–9.
ChienSUsamiSBertlesJF. Abnormal rheology of oxygenated blood in sickle cell anemia. J Clin Invest1970; 49: 623–34.
10.
ChienSUsamiSDellenbackRJGregersenMI. Blood viscosity: influence of erythrocyte deformation. Science1967; 157: 827–9.
11.
ChienSUsamiSDellenbackRJGregersenMINanningaLBGuestMM. Blood viscosity: influence of erythrocyte aggregation. Science1967; 157: 829–31.
12.
WangWCPavlakisSGHeltonKJMcKinstryRCCasellaJFAdamsRJReesRCInvestigators BH. MRI abnormalities of the brain in one-year-old children with sickle cell anemia. Pediatr Blood Cancer2008; 51: 643–6.
13.
AdamsRMckieVNicholsFCarlEZhangDLMckieKFigueroaRLitakerMThompsonWHessD. The use of transcranial ultrasonography to predict stroke in sickle-cell disease. New Engl J Med1992; 326: 605–10.
14.
AdamsRJNicholsFTFigueroaRMcKieVLottT. Transcranial Doppler correlation with cerebral angiography in sickle cell disease. Stroke1992; 23: 1073–7.
15.
AdamsRJNicholsFTAaslidRMckieVCMckieKCarlEStephensSThompsonWOMilnerPFigueroaR. Cerebral vessel stenosis in sickle-cell disease – criteria for detection by transcranial Doppler. Am J Pediat Hematol1990; 12: 277–82.
16.
TakeuchiSKarinoT. Flow patterns and distributions of fluid velocity and wall shear stress in the human internal carotid and middle cerebral arteries. World Neurosurg2010; 73: 174–85. discussion e27.
17.
SchoningMWalterJScheelP. Estimation of cerebral blood-flow through color duplex sonography of the carotid and vertebral arteries in healthy-adults. Stroke1994; 25: 17–22.
18.
RingelsteinEBKahlscheuerBNiggemeyerEOtisSM. Transcranial Doppler sonography: anatomical landmarks and normal velocity values. Ultrasound Med Biol1990; 16: 745–61.
19.
NeishASBlewsDESimmsCAMerrittRKSpinksAJ. Screening for stroke in sickle cell anemia: Comparison of transcranial Doppler Imaging and nonimaging US techniques. Radiology2002; 222: 709–14.
20.
KuDN. Blood flow in arteries. Ann Rev Fluid Mech1997; 29: 399–434.
21.
GiddensDPZarinsCKGlagovS. The role of fluid mechanics in the localization and detection of atherosclerosis. J Biomech Eng1993; 115: 588–94.
22.
Antiga L, Steinman D. The Vascular Modeling Toolkit (VMTK). 2009; www.vmtk.org.
23.
PiccinelliMVenezianiASteinmanDARemuzziAAntigaL. A framework for geometric analysis of vascular structures: application to cerebral aneurysms. IEEE Trans Med Imag2009; 28: 1141–55.
24.
MoghadamMEBazilevsYHsiaTYVignon-ClementelIEMarsdenAL. A comparison of outlet boundary treatments for prevention of backflow divergence with relevance to blood flow simulations. Computat Mech2011; 48: 277–91.
25.
VenezianiAVergaraC. An approximate method for solving incompressible Navier–Stokes problem with flow rate conditions. Comp Meth Appl Mech Engr2007; 196: 1685–700.
26.
PeiróJVenezianiA. Reduced models of the cardiovascular system. Cardiovasc Math2009; 1: 347–94.
27.
SchöberlJ. NETGEN An advancing front 2D/3D-mesh generator based on abstract rules. Comput Visualiz Sci1997; 1: 41–52.
28.
PlattMOAnkenyRFJoH. Laminar shear stress inhibits cathepsin L activity in endothelial cells. Arterioscler Thromb Vasc Biol2006; 26: 1784–90.
29.
PlattMOAnkenyRFShiGPWeissDVegaJDTaylorWRJoH. Expression of cathepsin K is regulated by shear stress in cultured endothelial cells and is increased in endothelium in human atherosclerosis. Am J Physiol Heart Circ Physiol2007; 292: H1479–86.
30.
PlattMOShockeyWA. Endothelial cells and cathepsins: biochemical and biomechanical regulation. Biochimie2016; 122: 314–23.
KuDNGiddensDPZarinsCKGlagovS. Pulsatile flow and atherosclerosis in the human carotid bifurcation. Positive correlation between plaque location and low oscillating shear stress. Arteriosclerosis1985; 5: 293–302.
33.
MalekAMAlperSLIzumoS. Hemodynamic shear stress and its role in atherosclerosis. JAMA1999; 282: 2035–42.
34.
ZarinsCKGiddensDPBharadvajBKSottiuraiVSMabonRFGlagovS. Carotid bifurcation atherosclerosis. Quantitative correlation of plaque localization with flow velocity profiles and wall shear stress. Circ Res1983; 53: 502–14.
35.
RielaARRoachES. Etiology of stroke in children. J Child Neurol1993; 8: 201–20.
36.
BorosLThomasCWeinerWJ. Large cerebral vessel disease in sickle-cell anemia. J Neurol Neurosurg Psych1976; 39: 1236–9.
37.
MerkelKHHGinsbergPLParkerJCDonovanpostMJ. Cerebrovascular disease in sickle-cell anemia – clinical, pathological and radiological correlation. Stroke1978; 9: 45–52.
38.
FasanoRMMeierERHulbertML. Cerebral vasculopathy in children with sickle cell anemia. Blood Cell Mol Dis2015; 54: 17–25.
39.
BelcherJDMarkerPHWeberJPHebbelRPVercellottiGM. Activated monocytes in sickle cell disease: potential role in the activation of vascular endothelium and vaso-occlusion. Blood2000; 96: 2451–9.
40.
SwitzerJAHessDCNicholsFTAdamsRJ. Pathophysiology and treatment of stroke in sickle-cell disease: present and future. Lancet Neurol2006; 5: 501–12.
41.
BarabinoGAPlattMOKaulDK. Sickle cell biomechanics. Annu Rev Biomed Eng2010; 12: 345–67.
42.
LeeSWAntigaLSpenceJDSteinmanDA. Geometry of the carotid bifurcation predicts its exposure to disturbed flow. Stroke2008; 39: 2341–7.
43.
ProhovnikIHurlet-JensenAAdamsRDe VivoDPavlakisSG. Hemodynamic etiology of elevated flow velocity and stroke in sickle-cell disease. J Cereb Blood Flow Metab2009; 29: 803–10.
44.
AaslidRMarkwalderTMNornesH. Noninvasive transcranial Doppler ultrasound recording of flow velocity in basal cerebral arteries. J Neurosurg1982; 57: 769–74.
45.
BeliznaCLoufraniLGhaliALaharyAPrimardELouvelJPHenrionDLevesqueHIfrahN. Arterial stiffness and stroke in sickle cell disease. Stroke2012; 43: 1129–30.
46.
ValadiNSilvaGSBowmanLSRamsinghDVicariPFilhoACMassaroARKutlarANicholsFTAdamsRJ. Transcranial Doppler ultrasonography in adults with sickle cell disease. Neurology2006; 67: 572–4.
47.
Yang H, Veneziani A. Variational estimation of cardiac conductivities by a data assimilation procedure. 2013; Technical Report TR-2013-007, Math&CS, Emory University, to appear in Inverse Problems.
48.
BertagnaLVenezianiA. A model reduction approach for the variational estimation ovascular compliance by solving an inverse fluid–structure interaction problem. Inverse Problem2014; 30: 055006–055006.
49.
BertagnaLD’EliaMPeregoMVenezianiA. Data assimilation in cardiovascular fluid–structure interaction problems: an introduction. Fluid–Struct Interact Biomed Appl2014; 10: 395–481.
50.
KaulDKFabryMEWindischPBaezSNagelRL. Erythrocytes in sickle-cell-anemia are heterogeneous in their rheological and hemodynamic characteristics. J Clin Invest1983; 72: 22–31.
51.
BernaudinFVerlhacSArnaudCKamdemAVasileMKasbiFHauIMadhiFFourmauxCBiscardiSEpaudRPondarreC. Chronic and acute anemia and extracranial internal carotid stenosis are risk factors for silent cerebral infarcts in sickle cell anemia. Blood2015; 125: 1653–61.
52.
PiccinelliMBacigaluppiSBoccardiEEne-IordacheBRemuzziAVenezianiAAntigaL. Geometry of the internal carotid artery and recurrent patterns in location, orientation, and rupture status of lateral aneurysms: an image-based computational study. Neurosurgery2011; 68: 1270–85. discussion 85.
