The Effect of Spatial Resolution on Wall Shear Stress Measurements Acquired Using Radial Phase Contrast Magnetic Resonance Angiography in the Middle Cerebral Arteries of Healthy Volunteers
Restricted accessResearch articleFirst published online February, 2011
The Effect of Spatial Resolution on Wall Shear Stress Measurements Acquired Using Radial Phase Contrast Magnetic Resonance Angiography in the Middle Cerebral Arteries of Healthy Volunteers
We have recently implemented radial phase-contrast techniques that allow high resolution angiograms with velocity information to be acquired within clinically-useful imaging times. 10 healthy volunteers were scanned using PC-VIPR and PC-SOS, two high resolution phase-contrast techniques at spatial resolutions of 0.67×0.67×0.67 mm3 and 0.4×0.4×1 mm3 respectively. The velocity measurements from the two acquisitions were imported into a custom Matlab runtime environment that automatically calculated WSS values using Green's Theorem and B-spline interpolation. Time average axial WSS was 1.069 N/m2 (95% confidence interval: 0.8628< × < 1.276) in the left and right middle cerebral arteries of the 10 healthy volunteers (n=20) when scanned by PC-VIPR, and 1.670 N/m2 when scanned by PC-SOS (95% confidence interval: 1.395 < × < 1.946). This difference in means was statistically significant (p < 0.002). Previous investigators have found that higher spatial resolution results in higher WSS measurements because smaller voxel size results in fewer partial volume effects. This was true in our study as well. In this study, we found that PC-SOS has significantly higher spatial resolution than PC-VIPR and this followed in the WSS measurements. Higher in-plane spatial resolution allows WSS calculations to be performed more accurately because of increased precision near the vessel boundary.
MalekAAlperSIzumoS. Hemodynamic Shear Stress and Its Role in Atherosclerosis. JAMA1999; 282: 2035–2042.
2.
CunninghamKGotliebA. The role of shear stress in the pathogenesis of atherosclerosis. Laboratory Investigation,2005; 85: 9–23.
3.
HoiYMengHWoodwardSH. Effects of arterial geometry on aneurysm growth: three-dimensional computational fluid dynamics study. J Neurosurg2004; 101: 676–681.
4.
ChengCTempelDvan HaperenR. Atherosclerotic lesion size and vulnerability are determined by patterns of fluid shear stress. Circulation2006; 113: 2744–2753.
5.
AbbruzzeseTAGuzmanRJMartinRL. Matrix metalloproteinase inhibition limits arterial enlargement in a rodent arteriovenous fistula model. Surgery1998; 124: 328–335.
6.
StalderAFRusseMFFrydrychowiczA. Quantitative 2D and 3D phase contrast MRI: optimized analysis of blood flow and vessel wall parameters. Magn Reson Med2008; 60: 1218–1231.
7.
VelikinaJVJohnsonKMWuY. PC HYPR flow: a technique for rapid imaging of contrast dynamics. J Magn Reson Imaging2010; 31: 447–456.
8.
JohnsonKLumDTurskiP. Improved 3D phase contrast MRI with off-resonance corrected dual echo VIPR. Magn Reson Med2008; 60: 1329–36.
9.
KeithLKecskemetiSVelikinaJ. Simulation of relative temporal resolution of time-resolved MRA sequences. Magn Reson Med2008; 60: 398–404.
10.
ChangWLandgrafBFrydrychowiczA. Hemodynamics at the Carotid Terminus and Surrounding Segments assessed using Highly Accelerated High-Resolution Phase Contrast MR Velocimetry and Automated Spline Interpolation Presented at the 19th Symposium Neuroradiologicum, Bologna, Italy. 2010; p. 253.
11.
BrodskyEKLuAThorntonFJ. Using multiple half-echos to improve sampling efficiency and fat suppression in time-resolved MRA. Proc. ISMRM 11th Annu. Meeting. 2003; Toronto, Canada. p. 74.
ShojimaMOshimMTakagiK. Magnitude and Role of Wall Shear Stress on CerebralAneurysm Stroke. 2004; 35: 2500.
14.
WuYChangWJohnsonK. Fast whole brain 4D Contrast Enhanced MR angiography with velocity encoding using undersampled radial acquisition and highly constrained projection reconstruction (HYPRFlow): Image quality assessment in volunteer subjects. Am J Neuroradiol, (epub ahead of print March 2010) DOI 10.3174/ajnr.A2048.
15.
ChangWLandgrafBKecskemetiS. Velocity Measurements in the Middle Cerebral Arteries of Healthy Volunteers Using 3D-Radial PC HYPRFlow: Comparison With Transcranial Doppler Ultrasound and 2D-PC Am J Neuroradiol (ePub ahead of print) DOI 10.3174/ajnr.A2240. Am J Neuroradiol (Jan)2011; 32: 54–59.
16.
ChangWLandgrafBJohnsonKAssessment of Velocity and Wall Shear Stress in Areas of Complex Flow Using High-Resolution Phase Contrast MRA: Initial Clinical Experience, Presented at the Annual Meeting of the Radiological Society of North America, Chicago, IL. 2010.
17.
AlastrueyJParkerKPeiroJ. Modelling the circle of Willis to assess the effects of anatomic variations and occlusions on cerebral flows. J. Biomech. 200740: 1794–1805.
18.
AlnaesMIsaksenJMardelK. Computation of hemodynamics in the circle of Willis. Stroke2007; 38: 2500–5.
19.
CassotFZagzouleMMarc-VergnesJ. Hemodynamic role of the circle of Willis in stenoses of internal carotid arteries: an analytical solution to a linear model. J. Biomech. 2000; 33: N395–40.5.
20.
CebralJCastroMSotoO, Blood flow models of the circle of Willis from magnetic resonance data. J. Eng. Math. 2003; 47: 369–86.
21.
FerrandezADavidTBamfordJ. Computational models of blood flow in the circle of Willis. Comp. Methods Biomech. Biomed. Eng.2000; 4: 1–26.
22.
BammerRHopeTAskoyM. Time-resolved 3D quantitative flow MRI of the major intracranial vessels: initial experience and comparative evaluation at 1.5T and 3.0T in combination with parallel imaging. Magn. Reson. Med.2007; 57: 127–140.
23.
WetzelSMeckelSFrydrychowiczA. In vivo assessment and visualization of intracranial arterial hemodynamics with flow sensitized 4D MR imaging at 3T. Am J Neuroradiol2007; 28: 433–438.
CebralJCastroMAppanaboyinaS. Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity. IEEE Trans. Med. Imaging2005; 24: 457–67.
26.
HassanTEzuraMTimofeevE. Computational simulation of therapeutic parent artery occlusion to treat giant vertebrobasilar aneurysm. Am. J. Neuroradiol. 200425:63–68.
27.
JouL.QuickCYoungW.. Computational approach to quantifying hemodynamic forces in giant cerebral aneurysms. Am. J. Neuroradiol. 2003; 24: 1804–10.
28.
KerberCHeilmanC. Flow in experimental berry aneurysms: method and model. Am. J. Neuroradiol. 1983; 4: 374–77.
29.
ValenciaASolisF, Blood flow dynamics and arterial wall interaction in a saccular aneurysm model of the basilar artery. Comput. Struct. 2006; 84: 1326–37.
30.
CebralJCastroMBurgessJ. Characterization of cerebral aneurysm for assessing risk of rupture using patient-specific computational hemodynamics models. Am. J. Neuroradiol. 2005; 26: 2550–59.
31.
CebralJCastroMSotoO. Pilot clinical evaluation of aneurysm rupture using image-based computational fluid dynamics models. Proc. SPIE Med. Imaging. 2005; 5746: 245–56.
32.
TateshimaSMurayamaYVillablancaJ. In vitro measurement of fluid-induced wall shear stress in unruptured cerebral aneurysms harboring blebs. Stroke. 2003; 34: 187–92.
33.
EbbersT. 4D Flow Processing and Visualization, Presented at the Flow and Motion Quantification Workshop, 18th meeting of the International Society of Magnetic Resonance in Medicine, Stockholm, Sweden. 2010.
34.
JohnsonKMarklM. Improved SNR in phase contrast velocimetry with five-point balanced flow encoding. Magn. Res. Med.2010; 60: 1169–1177.
