Visual Exploration of Simulated and Measured Blood Flow

Morphology of cardiovascular tissue is influenced by the unsteady behavior of the blood flow and vice versa. Therefore, the pathogenesis of several cardiovascular diseases is directly affected by the blood-flow dynamics. Understanding flow behavior is of vital importance to understand the cardiovascular system and potentially harbors a considerable value for both diagnosis and risk assessment. The analysis of hemodynamic characteristics involves qualitative and quantitative inspection of the blood-flow field. Visualization plays an important role in the qualitative exploration, as well as the definition of relevant quantitative measures and its validation. There are two main approaches to obtain information about the blood flow: simulation by computational fluid dynamics, and in-vivo measurements. Although research on blood flow simulation has been performed for decades, many open problems remain concerning accuracy and patient-specific solutions. Possibilities for real measurement of blood flow have recently increased considerably by new developments in magnetic resonance imaging which enable the acquisition of 3D quantitative measurements of blood-flow velocity fields. This chapter presents the visualization challenges for both simulation and real measurements of unsteady blood-flow fields.

[1]  Harald Garcke,et al.  A continuous clustering method for vector fields , 2000, Proceedings Visualization 2000. VIS 2000 (Cat. No.00CH37145).

[2]  Michael Markl,et al.  Time‐resolved three‐dimensional phase‐contrast MRI , 2003, Journal of magnetic resonance imaging : JMRI.

[3]  Wenbin Chen,et al.  Segmentation of discrete vector fields , 2006, IEEE Transactions on Visualization and Computer Graphics.

[4]  M. Cadioli,et al.  In Vivo Quantification of Helical Blood Flow in Human Aorta by Time-Resolved Three-Dimensional Cine Phase Contrast Magnetic Resonance Imaging , 2009, Annals of Biomedical Engineering.

[5]  Marcel Breeuwer,et al.  Exploration of 4D MRI Blood Flow using Stylistic Visualization , 2010, IEEE Transactions on Visualization and Computer Graphics.

[6]  Karin Markenroth,et al.  Phase Contrast MRI Segmentation Using Velocity and Intensity , 2005, Scale-Space.

[7]  J. Alison Noble,et al.  Vascular segmentation of phase contrast magnetic resonance angiograms based on statistical mixture modeling and local phase coherence , 2004, IEEE Transactions on Medical Imaging.

[8]  M. Komu,et al.  Effect of fasting and food intake on magnetization transfer of human liver tissue. , 1997, Magnetic resonance imaging.

[9]  Eric A. Wernert,et al.  Constrained 3D navigation with 2D controllers , 1997, Proceedings. Visualization '97 (Cat. No. 97CB36155).

[10]  J. Hogg.  Magnetic resonance imaging. , 1994, Journal of the Royal Naval Medical Service.

[11]  Robert S. Laramee,et al.  The State of the Art in Flow Visualization: Dense and Texture‐Based Techniques , 2004, Comput. Graph. Forum.

[12]  Tino Ebbers,et al.  Sequence optimization to reduce velocity offsets in cardiovascular magnetic resonance volume flow quantification - A multi-vendor study , 2011, Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance.

[13]  M. Alley,et al.  Hemodynamics in normal cerebral arteries: qualitative comparison of 4D phase-contrast magnetic resonance and image-based computational fluid dynamics , 2009, Journal of engineering mathematics.

[14]  Bernhard Preim,et al.  Adapted Surface Visualization of Cerebral Aneurysms with Embedded Blood Flow Information , 2010, VCBM.

[15]  N J Pelc,et al.  Concomitant gradient terms in phase contrast MR: Analysis and correction , 1998, Magnetic resonance in medicine.

[16]  Toshio Kobayashi,et al.  Fluid-structure interaction modeling of blood flow and cerebral aneurysm: Significance of artery and aneurysm shapes , 2009 .

[17]  G. Duckwiler,et al.  Sensitivity of patient-specific numerical simulation of cerebal aneurysm hemodynamics to inflow boundary conditions. , 2007, Journal of neurosurgery.

[18]  Francis K. H. Quek,et al.  A review of vessel extraction techniques and algorithms , 2004, CSUR.

[19]  Marcel Breeuwer,et al.  Interactive Virtual Probing of 4D MRI Blood-Flow , 2011, IEEE Transactions on Visualization and Computer Graphics.

[20]  Bernhard Preim,et al.  Automatic Generation of Context Visualizations for Cerebral Aneurysms from MRA Datasets , 2009 .

[21]  Tobias Isenberg,et al.  Depth-Dependent Halos: Illustrative Rendering of Dense Line Data , 2009, IEEE Transactions on Visualization and Computer Graphics.

[22]  Anders Heyden,et al.  Velocity Based Segmentation in Phase Contrast MRI Images , 2004, MICCAI.

[23]  Thomas Wischgoll,et al.  Biophysical model of the spatial heterogeneity of myocardial flow. , 2009, Biophysical journal.

[24]  R. Mohiaddin,et al.  Applications of phase-contrast flow and velocity imaging in cardiovascular MRI , 2005, European Radiology.

[25]  Qun Zhao,et al.  Unwrapping magnetic resonance phase maps with Chebyshev polynomials. , 2009, Magnetic resonance imaging.

[26]  Bernhard Preim,et al.  Visualization of vasculature with convolution surfaces: method, validation and evaluation , 2005, IEEE Transactions on Medical Imaging.

[27]  Alejandro F. Frangi,et al.  Efficient pipeline for image-based patient-specific analysis of cerebral aneurysm hemodynamics: technique and sensitivity , 2005, IEEE Transactions on Medical Imaging.

[28]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[29]  Stephan E Maier,et al.  Effect of acquisition parameters on the accuracy of velocity encoded cine magnetic resonance imaging blood flow measurements , 2002, Journal of magnetic resonance imaging : JMRI.

[30]  Bernhard Preim,et al.  Map Displays for the Analysis of Scalar Data on Cerebral Aneurysm Surfaces , 2009, Comput. Graph. Forum.

[31]  Bernhard Preim,et al.  The FLOWLENS: A Focus-and-Context Visualization Approach for Exploration of Blood Flow in Cerebral Aneurysms , 2011, IEEE Transactions on Visualization and Computer Graphics.

[32]  D N Firmin,et al.  Dynamic range extension of cine velocity measurements using motion registered spatiotemporal phase unwrapping , 1996, Journal of magnetic resonance imaging : JMRI.

[33]  Bernhard Preim,et al.  A Clustering-based Visualization Technique to Emphasize Meaningful Regions of Vector Fields , 2011, VMV.

[34]  Christophe Schlick,et al.  A Customizable Reflectance Model for Everyday Rendering , 1993 .

[35]  Armin Kanitsar,et al.  CPR - curved planar reformation , 2002, IEEE Visualization, 2002. VIS 2002..

[36]  Thomas Wischgoll,et al.  Validation of Image-Based Method for Extraction of Coronary Morphometry , 2008, Annals of Biomedical Engineering.

[37]  F Ståhlberg,et al.  Accuracy of segmented MR velocity mapping to measure small vessel pulsatile flow in a phantom simulating cardiac motion , 2001, Journal of magnetic resonance imaging : JMRI.

[38]  Matthias Gutberlet,et al.  In vitro validation of phase‐contrast flow measurements at 3 T in comparison to 1.5 T: Precision, accuracy, and signal‐to‐noise ratios , 2005, Journal of magnetic resonance imaging : JMRI.

[39]  Kenneth I. Joy,et al.  Analysis of Time-Dependent Flow-Sensitive PC-MRI Data , 2012, IEEE Transactions on Visualization and Computer Graphics.

[40]  A. van Rossum,et al.  Flow measurement by cardiovascular magnetic resonance: a multi-centre multi-vendor study of background phase offset errors that can compromise the accuracy of derived regurgitant or shunt flow measurements , 2010, Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance.

[41]  Bernhard Preim,et al.  Distance-based transfer function design: Specification Methods and Applications , 2006, SimVis.

[42]  Ivan Viola,et al.  Importance-driven feature enhancement in volume visualization , 2005, IEEE Transactions on Visualization and Computer Graphics.

[43]  Huy Nguyen,et al.  Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements , 2012, International Journal of Computer Assisted Radiology and Surgery.

[44]  Raghu Machiraju,et al.  Visualizing Particle/Flow Structure Interactions in the Small Bronchial Tubes , 2008, IEEE Transactions on Visualization and Computer Graphics.

[45]  Alexandru Telea,et al.  Simplified representation of vector fields , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[46]  M. Gunel,et al.  The critical role of hemodynamics in the development of cerebral vascular disease. , 2010, Journal of neurosurgery.

[47]  Niklas Elmqvist,et al.  Evaluating motion constraints for 3D wayfinding in immersive and desktop virtual environments , 2008, CHI.

[48]  M. Bernstein,et al.  Comparison of phase‐difference and complex‐difference processing in phase‐contrast MR angiography , 1991, Journal of magnetic resonance imaging : JMRI.

[49]  Kwan-Liu Ma,et al.  Parallel hierarchical visualization of large time-varying 3D vector fields , 2007, Proceedings of the 2007 ACM/IEEE Conference on Supercomputing (SC '07).

[50]  Robert S. Laramee,et al.  The State of the Art in Flow Visualisation: Feature Extraction and Tracking , 2003, Comput. Graph. Forum.

[51]  R. Herfkens,et al.  Phase contrast cine magnetic resonance imaging. , 1991, Magnetic resonance quarterly.

[52]  Paul A. Bottomley,et al.  19F magnetic resonance imaging , 1977 .

[53]  Bernhard Preim,et al.  Geometric Reconstruction of the Ostium of Cerebral Aneurysms , 2010, VMV.