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Scientific Visualization pp 305–324Cite as

Visual Exploration of Simulated and Measured Blood Flow

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Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

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.

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References

  1. American Heart Association: Heart and stroke statistics (2010). http://www.americanheart.org/statistics

  2. Arheden, H.k., Saeed, M., Törnqvist, E., Lund, G., Wendland, M.F., Higgins, C.B., Ståhlberg, F.: Accuracy of segmented MR velocity mapping to measure small vessel pulsatile flow in a phantom simulating cardiac motion. J. Magn. Reson. Imaging 13(5), 722–728 (2001)

    Google Scholar 

  3. Bernstein, M.A., Ikezaki, Y.: Comparison of phase-difference and complex-difference processing in phase-contrast MR angiography. Magn. Reson. Imaging 1(2), 725–729 (1991). http://www3.interscience.wiley.com/journal/112146770/abstract

  4. Bernstein, M.A., Zhou, X.J., Polzin, J.A., King, K.F., Ganin, A., Pelc, N.J., Glover, G.H.: Concomitant gradient terms in phase contrast MR: analysis and correction. Magn. Reson. Med. 39(2), 300–308 (1998)

    Article  Google Scholar 

  5. Cebral, J.R., Castro, M.A., Appanaboyina, S., Putmann, C.M., Millan, D., Frangi, A.F.: Efficient pipeline for image-based patient-specific analysis of cebral aneurysm hemodynamics:technique and sensitivity. IEEE Trans. Med. Imaging 24(4), 457–467 (2005)

    Article  Google Scholar 

  6. Cebral, J.R., Putman, C.M., Alley, M.T., Hope, T., Bammer, R., Calamante, F.: Hemodynamics in normal cerebral arteries: qualitative comparison of 4d phase-contrast magnetic resonance and image-based computational fluid dynamics. J. Eng. Math. 64(4), 367–378 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  7. Chung, A.C.S., Noble, J.A., Summers, P.: Vascular segmentation of phase-contrast magnetic resonance angiograms based on statistical mixture modeling and local phase coherence. IEEE Trans. Med. Imaging 23(12), 1490–1507 (2004)

    Article  Google Scholar 

  8. Elmqvist, N., Tudoreanu, M.E., Tsigas, P.: Evaluating motion constraints for 3d wayfinding in immersive and desktop virtual environments. In: Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems, CHI ’08, pp. 1769–1778. ACM, New York, NY, USA (2008)

    Google Scholar 

  9. Everts, M.H., Bekker, H., Roerdink, J.B., Isenberg, T.: Depth-dependent halos: illustrative rendering of dense line data. IEEE Trans. Vis. Comput. Graph. 15, 1299–1306 (2009). http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.138

  10. Garcke, H.: Preu\(\beta \)er, T., Rumpf, M., Telea, A., Weikard, U., van Wijk, J.: A continuous clustering method for vector fields. In: Proceedings of the conference on Visualization ’00. VIS’00, pp. 351–358. IEEE Computer Society Press, Los Alamitos, CA, USA (2000)

    Google Scholar 

  11. Gasteiger, R., Neugebauer, M., Beuing, O., Preim, B.: The FLOWLENS: A Focus-and-Context Visualization Approach for Exploration of Blood Flow in Cerebral Aneurysms. IEEE Trans. Vis. Comput. Graph. 17, 2183–2192 (2011)

    Article  Google Scholar 

  12. Gasteiger, R., Neugebauer, M., Kubisch, C., Preim, B.: Adapted surface visualization of cerebral aneurysms with embedded blood flow information. In: Eurographics Workshop on Visual Computing for Biology and Medicine (EG VCBM), pp. 25–32 (2010)

    Google Scholar 

  13. Gatehouse, P., Keegan, J., Crowe, L., Masood, S., Mohiaddin, R., Kreitner, K.F., Firmin, D.: Applications of phase-contrast flow and velocity imaging in cardiovascular MRI. Eur. Radiol. 15, 2172–2184 (2005)

    Article  Google Scholar 

  14. Gatehouse, P.D., Rolf, M.P., Graves, M.J., Hofman, M.B., Totman, J.J., Werner, B., Quest, R.A., Liu, Y., Spiczak von, J., Dieringer, M., Firmin, D.N., Rossum van, A., Lombardi, M., Schwitter, J., Schulz-Menger, J., Kilner, P.J.: 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. J. Cardiovasc. Magn. Reson. 12(5) (2010)

    Google Scholar 

  15. Greil, G., Geva, T., Maier, S.E., Powell, A.J.: Effect of acquisition parameters on the accuracy of velocity encoded cine magnetic resonance imaging blood flow measurements. Magn. Reson. Imaging 15(1), 47–54 (2002). doi:10.1002/jmri.10029

    Article  Google Scholar 

  16. Hanson, A.J., Wernert, E.A.: Constrained 3d navigation with 2d controllers. In: Proceedings of the 8th Conference on Visualization ’97, VIS ’97, pp. 175–182. IEEE Computer Society Press (1997)

    Google Scholar 

  17. Huo, Y., Kaimovitz, B., Lanir, Y., Wischgoll, T., Hoffman, J.I., Kassab, G.S.: Biophysical model of spatial heterogeneity of myocardial flow. Biophys. J. 96(10), 4035–4043 (2009)

    Article  Google Scholar 

  18. Kanitsar, A., Fleischmann, D., Wegenkittl, R., Felkl, P., Gröller, E.: CPR: curved planar reformation. pp. 37–44. IEEE Computer Society (2002)

    Google Scholar 

  19. Kirbas, C., Quek, F.: A review of vessel extraction techniques and algorithms. ACM Comput. Surv. 36, 81–121 (2004)

    Article  Google Scholar 

  20. Krishnan, H., Garth, C., Guhring, J., Gulsun, M., Greiser, A., Joy, K.: Analysis of time-dependent flow-sensitive PC-MRI data. IEEE Trans. Vis. Comput. Graph. 99, 1 (2011). doi:10.1109/TVCG.2011.80

    Google Scholar 

  21. Kuhn, A., Lehmann, D.J., Gaststeiger, R., Neugebauer, M., Preim, B., Theisel, H.: A clustering-based visualization technique to emphasize meaningful regions of vector fields. In: Proceedings of Vision, Modeling, and Visualization (VMV 2011), pp. 191–198. Eurographics Assosciation (2011)

    Google Scholar 

  22. Langley, J., Zhao, Q.: Unwrapping magnetic resonance phase maps with chebyshev polynomials. J. Magn. Reson. Imaging 27(9), 1293–1301 (2009)

    Article  Google Scholar 

  23. Laramee, R.S., Hauser, H., Doleisch, H., Vrolijk, B., Post, F.H., Weiskopf, D.: The state of the art in flow visualization: dense and texture-based techniques. Comput. Graph. Forum 23(2), 203–221 (2004)

    Article  Google Scholar 

  24. Li, H., Chen, W., Shen, I.F.: Segmentation of discrete vector fields. IEEE Trans. Vis. Comput. Graph. 12, 289–300 (2006). http://doi.ieeecomputersociety.org/10.1109/TVCG.2006.54

  25. Lorensen, W.E., Cline, H.E.: Marching cubes: a high resolution 3d surface construction algorithm. In: Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques. SIGGRAPH ’87, pp. 163–169. ACM, New York, NY, USA (1987)

    Google Scholar 

  26. Lotz, J., Döker, R., Noeske, R., Schüttert, M., Felix, R., Galanski, M., Gutberlet, M., Meyer, G.P.: In vitro validation of phase-contrast flow measurements at 3 T in comparison to 1.5 T: precision, accuracy, and signal-to-noise ratios. J. Magn. Reson. Imaging 21(5), 604–610 (2005)

    Article  Google Scholar 

  27. Markl, M., Chan, F.P., Alley, M.T.: L. Wedding, K., Draney, M.T., Elkins, C.J., Parker, D.W., Taylor, C.A., Herfkens, R.J., Pelc, N.J.: Time resolved three dimensional phase contrast MRI. Magn. Reson. Imaging 506, 64 (2003)

    Google Scholar 

  28. Morbiducci, U., Ponzini, R., Rizzo, G., Cadioli, M., Esposito, A., De Cobelli, F., Del Maschio, A., Montevecchi, F., Redaelli, A.: In vivo: quantification of helical blood flow in human aorta by time-resolved three-dimensional cine phase contrast magnetic resonance imaging. Ann. Biomed. Eng. 37, 516–531 (2009)

    Article  Google Scholar 

  29. Neugebauer, M., Diehl, V., Skalej, M., Preim, B.: Geometric reconstruction of the ostium of cerebral aneurysms. In: Koch, R., Kolb, A., Rezk-Salama, C. (eds.) VMV 2010–Vision, Modeling, Visualization, pp. 307–314 (2010)

    Google Scholar 

  30. Neugebauer, M., Gasteiger, R., Beuing, O., Diehl, V., Skalej, M., Preim, B.: Map displays for the analysis of scalar data on cerebral aneurysm surfaces. Comput. Graph. Forum (EuroVis) 28(3), 895–902 (2009)

    Article  Google Scholar 

  31. Neugebauer, M., Gasteiger, R., Diehl, V., Beuing, O., Preim, B.: Automatic generation of context visualizations for cerebral aneurysms from MRA datasets. Int. J. Comput. Assist. Radiol. Surg. (CARS) 4(Supplement 1), 112–113 (2009)

    Google Scholar 

  32. Nixon, A.M., Gunel, M., Sumpio, B.E.: The critical role of hemodynamics in the development of cerebral vascular disease. Neurosurgery 112(6), 1240–1253 (2010)

    Article  Google Scholar 

  33. Oeltze, S., Preim, B.: Visualization of vasculature with convolution surfaces: method, validation and evaluation. IEEE Trans. Med. Imaging 24(4), 540–548 (2005)

    Article  Google Scholar 

  34. Pelc, N.J., Herfkens, R.J., Shimakawa, A., Enzmann, D.R.: Phase contrast cine magnetic resonance imaging. Magn. Reson. Q. 7, 229–254 (1991)

    Google Scholar 

  35. Persson, M., Solem, J.E., Markenroth, K., Svensson, J., Heyden, A.: Phase contrast MRI segmentation using velocity and intensity. Scale Space PDE Methods Comput. Vis. 3459, 119–130 (2005)

    Article  Google Scholar 

  36. Post, F.H., Vrolijk, B., Hauser, H., Laramee, R.S., Doleisch, H.: The state of the art in flow visualisation: feature extraction and tracking. Comput. Graph. Forum 22(4), 775–792 (2003)

    Article  Google Scholar 

  37. Pruessmann, K., Boesiger, P., Kozerke, S., Dydak, U. (Gyrotools): GTFlow. http://www.gyrotools.com/products/gt-flow.html (last visited)

  38. Rolf, M.P., Hofman, M.B.M., Gatehouse, P.D., Markenroth-Bloch, K., Heymans, M.W., Ebbers, T., Graves, M.J., Totman, J.J., Werner, B., van Rossum, A.C., Kilner, P.J., Heethaar, R.M.: Sequence optimization to reduce velocity offsets in cardiovascular magnetic resonance volume flow quantification - a multi-vendor study. J. Cardiovasc. Magn. Reson. 13(1), 18 (2011)

    Article  Google Scholar 

  39. Schlick, C.: A customizable reflectance model for everyday rendering. In: Proceedings of Fourth Eurographics Workshop on Rendering, pp. 73–83 (1993)

    Google Scholar 

  40. Solem, J.E., Persson, M., Heyden, A.: Velocity based segmentation in phase-contrast MRI images. In: Medical Image Computing and Computer-Assisted Intervention, pp. 459–466 (2004)

    Google Scholar 

  41. Soni, B., Thompson, D., Machiraju, R.: Visualizing particle/flow structure interactions in the small bronchial tubes. IEEE Trans. Vis. Comput. Graph. 14, 1412–1427 (2008). http://doi.ieeecomputersociety.org/10.1109/TVCG.2008.183

  42. Tappenbeck, A., Preim, B., Dicken, V.: Distance-based transfer function design: specification methods and applications. In: Proceedings of Simulation und Visualisierung, pp. 259–274 (2006)

    Google Scholar 

  43. Telea, A., van Wijk, J.J.: Simplified representation of vector fields. In: Proceedings of the Conference on Visualization ’99: Celebrating Ten Years. VIS ’99, pp. 35–42. IEEE Computer Society Press, Los Alamitos, CA, USA (1999)

    Google Scholar 

  44. Torii, R., Oshima, M., Kobayashi, T., Takagi, K., Tezduyar, T.E.: Fluid-structure interaction modeling of blood flow and cerebral aneurysm: significance of artery and aneurysm shapes. Comput. Methods Appl. Mech. Eng. 198(45–46), 3613–3621 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  45. van Pelt, R., Nguyen, H., Haar Romeny, B., Vilanova, A.: Automated segmentation of blood flow regions in large thoracic arteries using 3D-cine PC-MRI measurements. Int. J. Comput. Assist. Radiol. Surg. 1–8 (2011)

    Google Scholar 

  46. van Pelt, R.: Oliván Bescós, J., Breeuwer, M., Clough, R.E., Gröller, M.E., ter Haar Romenij, B., Vilanova, A.: Exploration of 4D MRI blood flow using stylistic visualization. IEEE Trans. Vis. Comput. Graph. 16(6), 1339–1347 (2010). doi:10.1109/TVCG.2010.153

  47. van Pelt, R.: Oliván Bescós, J., Breeuwer, M., Clough, R., Gröller, M., ter Haar Romeny, B., Vilanova, A.: Interactive virtual probing of 4d mri blood flow. IEEE Trans. Vis. Comput. Graph. 17, 2153–2162 (2011)

    Google Scholar 

  48. Venkataraman, S. (NVidia): 4D visualization of cardiac flow. In: GPU Technology Conference (2010). http://www.nvidia.com/content/GTC-2010/pdfs/2009_GTC2010.pdf

  49. Venugopal, P., Valentino, D., Schmitt, H., Villablanca, J.P., Viñuela, F., Duckwiler, G.: Sensitivity of patient-specific numerical simulation of cerebal aneurysm hemodynamics to inflow boundary conditions. J. Neurosurg. 106(6), 1051–1060 (2007)

    Article  Google Scholar 

  50. Viola, I., Kanitsar, A., Groller, M.E.: Importance-driven feature enhancement in volume visualization. IEEE Trans. Vis. Comput. Graph. 11, 408–418 (2005)

    Article  Google Scholar 

  51. Vlaardingerbroek, M.T., den Boer, J.A.: Magnetic Resonance Imaging. Springer, Berlin (1999)

    Book  Google Scholar 

  52. Wischgoll, T., Choy, J.S., Ritman, E., Kassab, G.S.: Validation of image-based extraction method for morphometry of coronary arteries. Ann. Biomed. Eng. 36(3), 356–368 (2008)

    Article  Google Scholar 

  53. World Health Organization: Cardiovascular diseases (CVDs) (2011). http://www.who.int/mediacentre/factsheets/fs317/

  54. Yang, G.Z., Burger, P., Kilner, P.J., Karwatowski, S.P., Firmin, D.N.: Dynamic range extension of cine velocity measurements using motion-registered spatiotemporal phase unwrapping. J. Magn. Reson. Imaging 6(3), 495–502 (1996)

    Article  Google Scholar 

  55. Yu, H., Wang, C., Ma, K.L.: Parallel hierarchical visualization of large time-varying 3d vector fields. In: Proceedings of the 2007 ACM/IEEE Conference on Supercomputing, SC ’07, pp. 24:1–24:12. ACM, New York, NY, USA (2007)

    Google Scholar 

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Authors and Affiliations

  1. Computer Graphics and Visualization, EEMCS - Delft University of Technology, Room : HB 11.270 Building 36 - Mekelweg 4, 2628 CD Delft, Postbox 5, 2600 AA Delft, The Netherlands

    A. Vilanova & Roy van Pelt

  2. Institut Für Simulation Und Graphik, Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany

    Bernhard Preim, Rocco Gasteiger & Mathias Neugebauer

  3. Computer Science and Engineering, Wright State University, Dayton, USA

    Thomas Wischgoll

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  1. A. Vilanova
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  2. Bernhard Preim
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  3. Roy van Pelt
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  4. Rocco Gasteiger
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  5. Mathias Neugebauer
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  6. Thomas Wischgoll
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Correspondence to A. Vilanova .

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Editors and Affiliations

  1. School of Computing Scientific Computing and Imaging Institu, University of Utah, Salt Lake City, Utah, USA

    Charles D. Hansen

  2. e-Research Centre, University of Oxford, Oxford, United Kingdom

    Min Chen

  3. School of Computing Scientific Computing and Imaging Institu, University of Utah, Salt Lake City, Utah, USA

    Christopher R. Johnson

  4. Department of Computer Science, Stony Brook University, New York, New York, USA

    Arie E. Kaufman

  5. Fachbereich Informatik, Technische Universität Kaiserslautern, Kaiserslautern, Germany

    Hans Hagen

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Vilanova, A., Preim, B., Pelt, R.v., Gasteiger, R., Neugebauer, M., Wischgoll, T. (2014). Visual Exploration of Simulated and Measured Blood Flow. In: Hansen, C., Chen, M., Johnson, C., Kaufman, A., Hagen, H. (eds) Scientific Visualization. Mathematics and Visualization. Springer, London. https://doi.org/10.1007/978-1-4471-6497-5_25

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