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Evaluation of Artery Visualizations for Heart Disease Diagnosis
Dec. 2011 (vol. 17 no. 12)
pp. 2479-2488
Michelle Borkin, Harvard University
Krzysztof Gajos, Harvard University
Amanda Peters, Harvard University
Dimitrios Mitsouras, Brigham and Women's Hospital & Harvard Medical School
Simone Melchionna, IPCF-CNR, Consiglio Nazionale delle Ricerche
Frank Rybicki, Brigham and Women's Hospital & Harvard Medical School
Charles Feldman, Brigham and Women's Hospital & Harvard Medical School
Hanspeter Pfister, Harvard University
Heart disease is the number one killer in the United States, and finding indicators of the disease at an early stage is critical for treatment and prevention. In this paper we evaluate visualization techniques that enable the diagnosis of coronary artery disease. A key physical quantity of medical interest is endothelial shear stress (ESS). Low ESS has been associated with sites of lesion formation and rapid progression of disease in the coronary arteries. Having effective visualizations of a patient's ESS data is vital for the quick and thorough non-invasive evaluation by a cardiologist. We present a task taxonomy for hemodynamics based on a formative user study with domain experts. Based on the results of this study we developed HemoVis, an interactive visualization application for heart disease diagnosis that uses a novel 2D tree diagram representation of coronary artery trees. We present the results of a formal quantitative user study with domain experts that evaluates the effect of 2D versus 3D artery representations and of color maps on identifying regions of low ESS. We show statistically significant results demonstrating that our 2D visualizations are more accurate and efficient than 3D representations, and that a perceptually appropriate color map leads to fewer diagnostic mistakes than a rainbow color map.

[1] R. Amar, J. Eagan, and J. Stasko, Low-level components of analytic activity in information visualization. In Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization, pages 15–, Washington, DC, USA, 2005. IEEE Computer Society.
[2] N. Andrienko, G. Andrienko, and P. Gatalsky, Exploratory spatiotemporal visualization: an analytical review. Journal of Visual Languages & Computing, 14 (6): 503 – 541, 2003. Visual Data Mining.
[3] B. Bauer, P. Jolicoeur, and W. B. Cowan, Distractor heterogeneity versus linear separability in colour visual search. Perception, 25 (11): 1281 1293, 1996.
[4] J. Bertin, Semiology of Graphics: Diagrams, Networks, Maps. University of Wisconsin Press, 1983.
[5] D. Borland and R. T. II, Rainbow color map (still) considered harmful. IEEE Computer Graphics and Applications, pages 14 – 17, 2007.
[6] C. A. Brewer, Color use guidelines for data representation. In Proceedings of the Section on Statistical Graphics, American Statistical Association, pages 55 – 60, 1999.
[7] K. Bühler, P. Felkel, A. L. Cruz, and R. L. Cruz, Geometric methods for vessel visualization and quantification - a survey. In In Geometric Modelling for Scientific Visualization, pages 399 – 420. Springer-Verlag, 2002.
[8] Y. S. Chatzizisis, A. U. Coskun, M. Jonas, E. R. Edelman, C. L. Feldman, and P. H. Stone, Role of Endothelial Shear Stress in the Natural History of Coronary Atherosclerosis and Vascular Remodeling: Molecular, Cellular, and Vascular Behavior. J Am Coll Cardiol, 49 (25): 2379 – 2393, 2007.
[9] A. Cockburn and B. McKenzie, Evaluating the effectiveness of spatial memory in 2d and 3d physical and virtual environments. In Proceedings of the SIGCHI conference, CHI '02, pages 203 – 210, New York, NY, USA, 2002. ACM.
[10] A. V. Finn, M. Nakano, J. Narula, F. D. Kolodgie, and R. Virmani, Concept of vulnerable/unstable plaque. Arterioscler Thromb Vasc Biol, 30 (7): 1282 – 1292, 2010.
[11] A. Forsberg, J. Chen, and D. Laidlaw, Comparing 3d vector field visualization methods: A user study. IEEE Transactions on Visualization and Computer Graphics, 15 (6): 1219 – 1226, 2009.
[12] A. S. Forsberg, D. H. Laidlaw, A. van Dam, R. M. Kirby, G. E. Karniadakis, and J. L. Elion, Immersive virtual reality for visualizing flow through an artery. In VIS '00: Proceedings of the conference on Visualization '00, pages 457 – 460, Los Alamitos, CA, USA, 2000. IEEE Computer Society Press.
[13] H. K. Hahn, B. Preim, D. Selle, and H. O. Peitgen, Visualization and interaction techniques for the exploration of vascular structures. In VIS '01: Proceedings of the conference on Visualization '01, pages 395 – 402, Washington, DC, USA, 2001. IEEE Computer Society.
[14] C. Healey, Choosing effective colours for data visualization. Visualiza-tion'96. Proceedings., pages 263 – 270, 1996.
[15] A. Kanitsar, D. Fleischmann, R. Wegenkittl, P. Felkel, and M. E. Gröller, Cpr: curved planar reformation. In VIS '02: Proceedings of the conference on Visualization '02, pages 37 – 44, Washington, DC, USA, 2002. IEEE Computer Society.
[16] G. Kindlmann, E. Reinhard, and S. Creem, Face-based luminance matching for perceptual colormap generation.—, 2002.
[17] A. Kjellin, L. Pettersson, S. Seipel, and M. Lind, Evaluating 2d and 3d visualizations of spatiotemporal information. ACM Transactions on Applied Perception (TAP), 7 (3): 1 – 23, 2010.
[18] R. Kosara, C. G. Healey, V. Interrante, D. H. Laidlaw, and C. Ware, User studies: Why, how, and when? IEEE Computer Graphics and Applications, 23: 20 – 25, 2003.
[19] E. L. Koua, A. Maceachren, and M. J. Kraak, Evaluating the usability of visualization methods in an exploratory geovisualization environment. International Journal of Geographical Information Science, 20: 425 – 448(24), April 2006.
[20] A. Kuß, M. Gensel, B. Meyer, V. Dercksen, and S. Prohaska, Effective techniques to visualize filamentsurface relationships. Computer Graphics Forum, 29 (3): 1003 – 1012, 2010.
[21] D. Laidlaw, R. Kirby, C. Jackson, J. Davidson, T. Miller, M. D. Silva, W. Warren, and M. Tarr, Comparing 2d vector field visualization methods: A user study. IEEE Transactions on Visualization and Computer Graphics, pages 59 – 70, 2005.
[22] H. Levkowitz and G. T. Herman, Color scales for image data. IEEE Computer Graphics and Applications, 12: 72 – 80, 1992.
[23] A. Light and P. J. Bartlein, The End of the Rainbow? Color Schemes for Improved Data Graphics. EOS Transactions, 85: 385 – 391, Oct. 2004.
[24] D. Lloyd-Jones and e. al. Heart Disease and Stroke Statistics–2009 Update: A Report From the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation, 119 (3): e21 – 181, 2009.
[25] J. Martin, E. S. II, R. J. M. II, Z. Liu, and S. Cai, Results of a user study on 2d hurricane visualization. Computer Graphics Forum, 27 (3): 991 – 998, 2008.
[26] S. Melchionna, M. Bernaschi, S. Succi, E. Kaxiras, F. J. Rybicki, D. Mitsouras, A. U. Coskun, and C. L. Feldman, Hydrokinetic approach to large-scale cardiovascular blood flow. Computer Physics Communications, 181 (3): 462 – 472, 2010.
[27] K. Moreland, Diverging color maps for scientific visualization. Advances in Visual Computing, pages 92 – 103, 2009.
[28] K. Museth, T. Müller, and A. Ynnerman, Model-free surface visualization of vascular trees. IEEE/Eurographics Symposium on Visualization, 2008.
[29] D. J. Peuquet, It's about time: A conceptual framework for the representation of temporal dynamics in geographic information systems. Annals of the Association of American Geographers, 84 (3): 441 – 461, 1994.
[30] C. Plaisant, The challenge of information visualization evaluation. In Proceedings of the working conference on Advanced visual interfaces, AVI '04, pages 109 – 116, New York, NY, USA, 2004. ACM.
[31] B. Preim and S. Oeltze, 3d visualization of vasculature: An overview, 2008.
[32] P. Rheingans, Color, change, and control for quantitative data display. Proceedings of the 3rd conference on Visualization'92, pages 252 – 259, 1992.
[33] P. Rheingans, Task-based color scale design (proceedings paper). spie.org, Jan 2000.
[34] F. Ritter, C. Hansen, V. Dicken, O. Konrad, B. Preim, and H. Peitgen, Real-time illustration of vascular structures. IEEE Transactions on Visualization and Computer Graphics, pages 877 – 884, 2006.
[35] B. Rogowitz and A. Kalvin, The which blair project: A quick visual method for evaluating perceptual color maps. Proceedings of the conference on Visualization'01, pages 183 – 190, 2001.
[36] B. Rogowitz, A. Kalvin, A. Cohen, and T. Watson, Invited paper: Which trajectories through which perceptually uniform color spaces produce appropriate colors scales for interval data?(gamut mapping i)(report. IS&T Color Imaging Conference Proceedings, Jan 2000.
[37] B. Rogowitz and L. Treinish, Data visualization: the end of the rainbow. Spectrum, IEEE, 35 (12): 52 – 59, 1998.
[38] B. Rogowitz, L. Treinish, and S. Bryson, How not to lie with visualization. Computers in Physics, 10 (3): 268 – 273, 1996.
[39] T. Ropinski, S. Hermann, R. Reich, M. Schafers, and K. Hinrichs, Multimodal vessel visualization of mouse aorta pet/ct scans. IEEE Transactions on Visualization and Computer Graphics, 15 (6): 1515 – 1522, 2009.
[40] F. J. Rybicki, S. Melchionna, D. Mitsouras, A. U. Coskun, A. G. Whit-More, M. Steigner, L. Nallamshetty, F. G. Welt, M. Bernaschi, M. Borkin, J. Sircar, E. Kaxiras, S. Succi, P. H. Stone, and C. L. Feldman, Prediction of coronary artery plaque progression and potential rupture from 320 detector row prospectively ecg-gated single heart beat ct angiography: Lattice boltzmann evaluation of endothelial shear stress. The International Journal of Cardiovascular Imaging, 25 (2): 289 – 299, 2009.
[41] J. P. Shaffer, Multiple hypothesis-testing. ANNUAL REVIEW OF PSYCHOLOGY, 46: 561 – 584, 1995.
[42] B. Shneiderman, Why not make interfaces better than 3d reality? Computer Graphics and Applications, IEEE, 23 (6): 12 – 15, 2003.
[43] P. H. Stone, S. Saito, S. Takahashi, Y. Makita, S. Nakamura, T. Kawasaki, A. Takahashi, T. Katsuki, S. Nakamura, A. Namiki, A. Hirohata, T. Matsumura, S. Yamazaki, H. Yokoi, S. Tanaka, S. Ohtsuji, F. Yoshimachi, J. Honye, D. Harwood, M. Papafaklis, M. Reitman, A. U. Coskun, and C. L. Feldman, The prediction trial: In-vivo assessment of coronary endothelial shear stress, arterial remodeling, and plaque morphology to predict coronary atherosclerosis progression and rupture in man. In Journal of the American College of Cardiology 2011, 2011.
[44] M. Straka, M. Cervenansky, A. LaCruz, A. Kochl, M. Sramek, E. Groller, and D. Fleischmann, The vesselglyph: Focus & context visualization in ct-angiography. In VIS '04: Proceedings of the conference on Visualization '04, pages 385 – 392, Washington, DC, USA, 2004. IEEE Computer Society.
[45] M. Termeer, J. O. Bescós, M. Breeuwer, A. Vilanova, F. Gerritsen, and M. E. Gröller, Covicad: Comprehensive visualization of coronary artery disease. IEEE Transactions on Visualization and Computer Graphics (accepted for publication), 13 (6):
[46] C. Tominski, G. Fuchs, and H. Schumann, Task-driven color coding. pages 373 – 380, Jul 2008.
[47] M. Tory, A. Kirkpatrick, and M. Atkins, Visualization task performance with 2d, 3d, and combination displays. IEEE Transactions on Visualization and Computer Graphics, pages 2 – 13, 2006.
[48] M. Tory, D. Sprague, F. Wu, W. So, and T. Munzner, Spatialization design: Comparing points and landscapes. IEEE Transactions on Visualization and Computer Graphics, pages 1262 – 1269, 2007.
[49] C. Ware, Color sequences for univariate maps: Theory, experiments and principles. IEEE Computer Graphics and Applications, pages 41 – 49, 1988.
[50] C. Ware, Designing with a 2 1/2-d attitude. Information Design Journal, 10 (3): 258 – 65, 2001.
[51] L. Zhu, S. Haker, and A. Tannenbaum, Conformal flattening maps for the visualization of vessels. SPIE Medical Imaging, 4681: 742748, 2002.
[52] L. Zhu, S. Haker, and A. Tannenbaum, Flattening maps for the visualization of multibranched vessels. IEEE Transactions on Medical Imaging, 24 (2): 191 – 198, 2005.

Index Terms:
Quantitative evaluation, qualitative evaluation, biomedical and medical visualization.
Citation:
Michelle Borkin, Krzysztof Gajos, Amanda Peters, Dimitrios Mitsouras, Simone Melchionna, Frank Rybicki, Charles Feldman, Hanspeter Pfister, "Evaluation of Artery Visualizations for Heart Disease Diagnosis," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 12, pp. 2479-2488, Dec. 2011, doi:10.1109/TVCG.2011.192
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