MRI and CFD studies of pulsatile flow in healthy and stenosed carotid bifurcation models
Introduction
Over the last few decades, research has demonstrated the influence of vessel geometry and haemodynamic forces on the development of vascular pathology (Ku et al., 1985; Glagov et al., 1988). In regions of disturbed blood flow, which are found around vessel bifurcations, there is an increased chance of atheroma deposition. The viscous drag of the blood on the vessel wall (wall shear stress; WSS) is believed to play a part in regulating arterial structure (Caro et al., 1971; Giddens et al., 1993; Gnasso et al., 1997; Malek et al., 1999), and is implicated in plaque development. The exact relationship between atheroma deposition and WSS remains uncertain, with low WSS, oscillating WSS, and WSS gradient all having been considered (Ku et al., 1985; Caro et al., 1971; Giddens et al., 1993).
There is considerable interest in the development of in vivo techniques that would allow accurate blood flow quantification and estimation of WSS, but they are not yet available for clinical use. The two most promising techniques are Doppler ultrasound and magnetic resonance imaging (MRI). Doppler ultrasound is a real time technique and does not suffer from data loss during turbulent flow. Current commercial systems are based on acquisition of two-dimensional (2D) image data in which only a single component of velocity is acquired. Acquisition of 2 or 3 velocity components requires multi-beam systems which are the subject of current research (Dunmire et al., 2000). Acquisition of real time three-dimensional (3D) information is also possible using 2D array systems (Light et al., 1998), but these are at an early stage of development. Ultrasound cannot be used on arteries that lie behind bony or air-filled structures. MRI is intrinsically 3D, but suffers from long acquisition times and signal loss in turbulent flow, which limits its use in diseased arteries. Both techniques have spatial resolutions that are only just high enough (0.5 mm) for in vivo studies of carotid arteries.
WSS estimation methods based on MRI have to date been mainly restricted to measurement of the axial component at a single plane (Oshinski et al., 1995; Oyre et al., 1998; Stokholm et al., 2000). Similarly, ultrasound methods have been based on estimation of axial WSS at a single location (Brands et al., 1995; Hoeks et al., 1995). Vector MRI information was obtained at the intersection of selected planes in the aorta by Suzuki et al. (1998). Time-resolved measurement of in vivo flow and WSS vectors remains a challenging goal. Therefore, the study of fluid dynamics is often carried out in physical or computational models (Zhao et al., 2000). For useful reviews, see Ku (1997) and Berger and Jou (2000). There have been very few experimental studies of pulsatile flow in carotid models, especially in stenosed models. Palmen et al. (1994) used hydrogen bubble visualisation, Gijsen et al. (1996) used laser Doppler anemometry, and Botnar et al. (2000) used MRI. We have previously reported on the estimation of WSS vectors throughout a flow region from MRI velocity measurements of steady (Köhler et al., 2001) and pulsatile (Papathanasopoulou et al., 2003) flow in phantoms.
An alternative approach has been to use MRI structural data and velocity measurements as the boundary conditions to solve the Navier–Stokes equations in a computational fluid dynamics (CFD) package, from which WSS can be calculated (Long et al., 2000; Steinman et al., 2002).
In the present work, we used a time-resolved 3D phase-contrast (PC) MRI sequence to acquire all three velocity components of pulsatile flow in models of a human carotid bifurcation with and without a 30% (diameter) axisymmetrical stenosis. We show velocity vectors at selected time frames, and WSS vectors calculated from the MRI measurements. These are compared qualitatively with the predictions of CFD calculations. The comparison of normal and stenosed phantoms under physiologically realistic flow conditions is novel, as is the qualitative comparison of MRI and CFD results for the stenosed phantom.
Section snippets
Data acquisition
MR scanning was performed on a 1.5 T GE Signa scanner (GE Medical, Milwaukee), using a 75 mm surface coil. The flow phantoms were anthropomorphically realistic models of a human carotid bifurcation with an axisymmetric 30% diameter (50% area) stenosis and a healthy carotid bifurcation (Shelley Medical Imaging Technologies, London, Ont., Canada). A computer-controlled pump (UHDC Flow System, Shelley) was used to generate a realistic carotid waveform, and pumped blood-mimicking fluid (Shelley)
Results
The flow waveform is shown in Fig. 1. It was measured from the axial velocity component in the common carotid vessel of the stenosed phantom, and has a mean of 7.4 ml/s, compared with a pump setting of 7.2 ml/s. Time points t1 (peak flow) and t2 (decelerating flow) are studied in more detail in Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7.
Fig. 2 shows maximum intensity projection (MIP) images generated from the phase contrast “reference” images, i.e. images without velocity sensitisation. An inverted
Discussion
Flow in the symmetrically stenosed phantom is shifted towards the outer (non-divider) wall of the ICA. There is a small flow separation zone immediately downstream of the stenosis on the outer wall of the ICA, and a larger one further downstream and on the inner wall (arrow, Fig. 2, Fig. 3).
This is quite different from flow in the normal phantom, in which most of the ICA flow follows the inner wall, and there is a single flow separation zone in the outer (bulb) region (arrowhead, Fig. 2, Fig. 3
Conclusions
We have demonstrated MRI measurement of fluid flow and subsequent estimation of WSS vectors during pulsatile flow in normal and stenosed carotid phantoms. The estimates were in qualitative agreement with CFD predictions except immediately downstream of the stenosis, where image segmentation was unsatisfactory.
Acknowledgements
This work was carried out at the SHEFC Brain Imaging Research Centre for Scotland, Edinburgh, and was funded in part by the EPSRC. The viscosity measurements were kindly made by Donald Easton of the Department of Haematology, Royal Infirmary of Edinburgh. Dr. Uwe Köhler developed the segmentation and WSS calculation software. Quan Long developed software for computational grid generation. Martin Connell provided support for computing and visualisation. Bob Gravett (Shelley Medical Imaging
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