- Workshop presentation
- Open Access
Pressure gradients calculated from PC-MRI, SPIV and CFD velocity data in a phantom model: comparison with catheter-based pressure measurement
© Khodarahmi et al; licensee BioMed Central Ltd. 2012
- Published: 1 February 2012
- Stereoscopic Particle Image Velocimetry
- Velocity Encode
- Phase Contrast Sequence
- Inlet Reynolds Number
- Software Package Fluent
Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis and is defined as any pathologic process causing obstruction to blood flow in the arteries outside the heart; mainly the arteries supplying the lower extremities. Phase-contrast MRI (PC-MRI) provides a powerful and non-invasive method to acquire spatially registered blood velocity. The velocity field, then, can be used to derive other clinically useful hemodynamic parameters, such as blood pressure gradients.
Computational Fluid Dynamics (CFD) simulation of the same flow was performed on the same geometry using the CFD software package Fluent 12.1 based on a finite volume scheme.
The Poisson equation was also solved using the CFD velocities, regridded to a rectangular mesh of the same grid resolution as PC-MRI. The pressure distribution obtained directly from the Fluent software is also shown for comparison. As shown in figure 2, good agreement exits between pressures calculated from different methods.
Pressure gradients calculated from PC-MRI data is comparable with those obtained from other experimental and numerical methods. Direct pressure measurement using two simultaneous catheters placed proximal and distal to the stenosis is currently under investigation and will be added as the ground truth to the discussed methods.
This work was supported in part by the National Science Foundation under Grant 0730467 and by an innovative grant from the Clinical and Translational Research Program of the University of Louisville.
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.