Abstract
Rationale and Objectives: Computational fluid dynamic (CFD) simulations are discussed with respect to their potential for quality assurance of flow quantification using commercial software for the evaluation of magnetic resonance phase contrast angiography (PCA) data. Materials and Methods: Magnetic resonance phase contrast angiography data was evaluated with the Nova software. CFD simulations were performed on that part of the vessel system where the flow behavior was unexpected or non-reliable. The CFD simulations were performed with in-house written software. Results: The numerical CFD calculations demonstrated that under reasonable boundary conditions, defined by the PCA velocity values, the flow behavior within the critical parts of the vessel system can be correctly reproduced. Conclusion: CFD simulations are an important extension to commercial flow quantification tools with regard to quality assurance.
Highlights
Magnetic resonance phase contrast angiography is an established technique to measure the velocity and the direction of flow [1]
Rationale and Objectives: Computational fluid dynamic (CFD) simulations are discussed with respect to their potential for quality assurance of flow quantification using commercial software for the evaluation of magnetic resonance phase contrast angiography (PCA) data
CFD simulations were performed on that part of the vessel system where the flow behavior was unexpected or non-reliable
Summary
Magnetic resonance phase contrast angiography is an established technique to measure the velocity and the direction of flow [1]. In each case the relative phase are not unique and the absolute velocity values are wrong. At this point the correct answer to the flow in the critical regions can only be derived on the base of physical models and computational flow dynamics (CFD). The idea is to selectively model the relevant vessel system and to include the known velocity values from the PCA measurements within the big vessels as boundary conditions. These velocity conditions are sufficient in most cases because the velocities tune in to the given pressure conditions. The intrinsic symmetry of the vessels can be used to reduce the dimensionality of the problem from three to two, which is necessary to use the software on commercial computers with limited working memory and CPU power—only the relative orientation of the vessels and their diameters (e.g. due to stenoses) have to be considered
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