Fluid dynamic simulation of rat brain vessels, geometrically reconstructed from MR-angiography and validated using phase contrast angiography

The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also for deeper analysis of hemodynamic functional data, such as fMRI. Such vessel geometries can be obtained by different MR angiographic measur...

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Published inPhysica medica Vol. 27; no. 3; pp. 169 - 176
Main Authors Lehmpfuhl, Monika Carola, Hess, Andreas, Gaudnek, M. André, Sibila, Michael
Format Journal Article
LanguageEnglish
Published Italy Elsevier Ltd 01.07.2011
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ISSN1120-1797
1724-191X
1724-191X
DOI10.1016/j.ejmp.2010.07.002

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Abstract The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also for deeper analysis of hemodynamic functional data, such as fMRI. Such vessel geometries can be obtained by different MR angiographic measurements. It is shown that simulations using computational fluid dynamics (CFD) can be used to validate the vessel geometry, automatically reconstructed from time of flight (TOF) angiograms or phase contrast angiography (PC-MRA) data. CFD simulations are based on PC-MRA data, since these data contain additionally rheological information (phases) besides merely amplitudes as is the case for TOF measurements. Parts of the rat brain vessel system are carefully modeled consisting of a main tube and second order branches. By analyzing velocity changes up and downstream of bifurcations, it is shown that CFD can be used to help detecting missing vessels in the TOF based reconstruction. It is demonstrated by artificially deleting a branch from the reconstruction and compared the flow in both resulting CFD simulations. Finally the simulations help to understand the effects of secondary branches on the flow in the main tube. The aim of this study is to compare the measured (PCA) flow data with the CFD simulation results, based on the vessel geometry gained from the PCA image using an in house reconstruction algorithm. If a more accurate simulation method is found and if in principal the simulation matches the PCA data, it might be possible to deduct that in cases where the measured data varies from the CFD simulation, the reconstruction is not complete, i.e. branches are missing or wrong branches were reconstructed.
AbstractList The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also for deeper analysis of hemodynamic functional data, such as fMRI. Such vessel geometries can be obtained by different MR angiographic measurements. It is shown that simulations using computational fluid dynamics (CFD) can be used to validate the vessel geometry, automatically reconstructed from time of flight (TOF) angiograms or phase contrast angiography (PC-MRA) data. CFD simulations are based on PC-MRA data, since these data contain additionally rheological information (phases) besides merely amplitudes as is the case for TOF measurements. Parts of the rat brain vessel system are carefully modeled consisting of a main tube and second order branches. By analyzing velocity changes up and downstream of bifurcations, it is shown that CFD can be used to help detecting missing vessels in the TOF based reconstruction. It is demonstrated by artificially deleting a branch from the reconstruction and compared the flow in both resulting CFD simulations. Finally the simulations help to understand the effects of secondary branches on the flow in the main tube. The aim of this study is to compare the measured (PCA) flow data with the CFD simulation results, based on the vessel geometry gained from the PCA image using an in house reconstruction algorithm. If a more accurate simulation method is found and if in principal the simulation matches the PCA data, it might be possible to deduct that in cases where the measured data varies from the CFD simulation, the reconstruction is not complete, i.e. branches are missing or wrong branches were reconstructed.
Abstract The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also for deeper analysis of hemodynamic functional data, such as fMRI. Such vessel geometries can be obtained by different MR angiographic measurements. It is shown that simulations using computational fluid dynamics (CFD) can be used to validate the vessel geometry, automatically reconstructed from time of flight (TOF) angiograms or phase contrast angiography (PC-MRA) data. CFD simulations are based on PC-MRA data, since these data contain additionally rheological information (phases) besides merely amplitudes as is the case for TOF measurements. Parts of the rat brain vessel system are carefully modeled consisting of a main tube and second order branches. By analyzing velocity changes up and downstream of bifurcations, it is shown that CFD can be used to help detecting missing vessels in the TOF based reconstruction. It is demonstrated by artificially deleting a branch from the reconstruction and compared the flow in both resulting CFD simulations. Finally the simulations help to understand the effects of secondary branches on the flow in the main tube. The aim of this study is to compare the measured (PCA) flow data with the CFD simulation results, based on the vessel geometry gained from the PCA image using an in house reconstruction algorithm. If a more accurate simulation method is found and if in principal the simulation matches the PCA data, it might be possible to deduct that in cases where the measured data varies from the CFD simulation, the reconstruction is not complete, i.e. branches are missing or wrong branches were reconstructed.
The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also for deeper analysis of hemodynamic functional data, such as fMRI. Such vessel geometries can be obtained by different MR angiographic measurements. It is shown that simulations using computational fluid dynamics (CFD) can be used to validate the vessel geometry, automatically reconstructed from time of flight (TOF) angiograms or phase contrast angiography (PC-MRA) data. CFD simulations are based on PC-MRA data, since these data contain additionally rheological information (phases) besides merely amplitudes as is the case for TOF measurements. Parts of the rat brain vessel system are carefully modeled consisting of a main tube and second order branches. By analyzing velocity changes up and downstream of bifurcations, it is shown that CFD can be used to help detecting missing vessels in the TOF based reconstruction. It is demonstrated by artificially deleting a branch from the reconstruction and compared the flow in both resulting CFD simulations. Finally the simulations help to understand the effects of secondary branches on the flow in the main tube. The aim of this study is to compare the measured (PCA) flow data with the CFD simulation results, based on the vessel geometry gained from the PCA image using an in house reconstruction algorithm. If a more accurate simulation method is found and if in principal the simulation matches the PCA data, it might be possible to deduct that in cases where the measured data varies from the CFD simulation, the reconstruction is not complete, i.e. branches are missing or wrong branches were reconstructed.The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also for deeper analysis of hemodynamic functional data, such as fMRI. Such vessel geometries can be obtained by different MR angiographic measurements. It is shown that simulations using computational fluid dynamics (CFD) can be used to validate the vessel geometry, automatically reconstructed from time of flight (TOF) angiograms or phase contrast angiography (PC-MRA) data. CFD simulations are based on PC-MRA data, since these data contain additionally rheological information (phases) besides merely amplitudes as is the case for TOF measurements. Parts of the rat brain vessel system are carefully modeled consisting of a main tube and second order branches. By analyzing velocity changes up and downstream of bifurcations, it is shown that CFD can be used to help detecting missing vessels in the TOF based reconstruction. It is demonstrated by artificially deleting a branch from the reconstruction and compared the flow in both resulting CFD simulations. Finally the simulations help to understand the effects of secondary branches on the flow in the main tube. The aim of this study is to compare the measured (PCA) flow data with the CFD simulation results, based on the vessel geometry gained from the PCA image using an in house reconstruction algorithm. If a more accurate simulation method is found and if in principal the simulation matches the PCA data, it might be possible to deduct that in cases where the measured data varies from the CFD simulation, the reconstruction is not complete, i.e. branches are missing or wrong branches were reconstructed.
The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also for deeper analysis of hemodynamic functional data, such as fMRI. Such vessel geometries can be obtained by different MR angiographic measurements. It is shown that simulations using computational fluid dynamics (CFD) can be used to validate the vessel geometry, automatically reconstructed from time of flight (TOF) angiograms or phase contrast angiography (PC-MRA) data. CFD simulations are based on PC-MRA data, since these data contain additionally rheological information (phases) besides merely amplitudes as is the case for TOF measurements. Parts of the rat brain vessel system are carefully modeled consisting of a main tube and second order branches. By analyzing velocity changes up and downstream of bifurcations, it is shown that CFD can be used to help detecting missing vessels in the TOF based reconstruction. It is demonstrated by artificially deleting a branch from the reconstruction and compared the flow in both resulting CFD simulations. Finally the simulations help to understand the effects of secondary branches on the flow in the main tube. The aim of this study is to compare the measured (PCA) flow data with the CFD simulation results, based on the vessel geometry gained from the PCA image using an in house reconstruction algorithm. If a more accurate simulation method is found and if in principal the simulation matches the PCA data, it might be possible to deduct that in cases where the measured data varies from the CFD simulation, the reconstruction is not complete, i.e. branches are missing or wrong branches were reconstructed.
Author Gaudnek, M. André
Hess, Andreas
Lehmpfuhl, Monika Carola
Sibila, Michael
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Issue 3
Keywords CFD
Vessel reconstruction
PC-MRA
Blood flow visualization
Blood flow simulation
Non-conformal meshing
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Snippet The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis), but also...
Abstract The exact knowledge of the blood vessel geometry plays an important role, not only in clinical applications (stroke diagnosis, detection of stenosis),...
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SubjectTerms Algorithms
Animals
Blood flow simulation
Blood Flow Velocity
Blood flow visualization
Brain - blood supply
Brain - metabolism
Brain - pathology
Cerebrovascular Circulation
CFD
Computer Simulation
Hydrodynamics
Image Processing, Computer-Assisted
Magnetic Resonance Angiography - instrumentation
Magnetic Resonance Angiography - methods
Magnetic Resonance Imaging - instrumentation
Magnetic Resonance Imaging - methods
Models, Animal
Non-conformal meshing
PC-MRA
Radiology
Rats
Reproducibility of Results
Vessel reconstruction
Title Fluid dynamic simulation of rat brain vessels, geometrically reconstructed from MR-angiography and validated using phase contrast angiography
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https://dx.doi.org/10.1016/j.ejmp.2010.07.002
https://www.ncbi.nlm.nih.gov/pubmed/20696607
https://www.proquest.com/docview/872524287
Volume 27
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