Comparative Blood Flow Visualization for Cerebral Aneurysm Treatment Assessment
A pathological vessel dilation in the brain, termed cerebral aneurysm, bears a high risk of rupture, and is associated with a high mortality. In recent years, incidental findings of unruptured aneurysms have become more frequent, mainly due to advances in medical imaging. The pathological condition...
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Published in | Computer graphics forum Vol. 33; no. 3; pp. 131 - 140 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Blackwell Publishing Ltd
01.06.2014
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Subjects | |
Online Access | Get full text |
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Summary: | A pathological vessel dilation in the brain, termed cerebral aneurysm, bears a high risk of rupture, and is associated with a high mortality. In recent years, incidental findings of unruptured aneurysms have become more frequent, mainly due to advances in medical imaging. The pathological condition is often treated with a stent that diverts the blood flow from the aneurysm sac back to the original vessel. Prior to treatment, neuroradiologists need to decide on the optimal stent configuration and judge the long‐term rupture risk, for which blood flow information is essential. Modern patient‐specific simulations can model the hemodynamics for various stent configurations, providing important indicators to support the decision‐making process. However, the necessary visual analysis of these data becomes tedious and time‐consuming, because of the abundance of information. We introduce a comprehensive comparative visualization that integrates morphology with blood flow indicators to facilitate treatment assessment. To deal with the visual complexity, we propose a details‐on‐demand approach, combining established medical visualization techniques with innovative glyphs inspired by information visualization concepts. In an evaluation we have obtained informal feedback from domain experts, gauging the value of our visualization. |
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Bibliography: | Supporting InformationSupporting Information istex:1AABF70E196C7EFDA3197DF0AE7E6C20998E7CA1 ArticleID:CGF12369 ark:/67375/WNG-6JMNNPVT-F SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-2 content type line 23 |
ISSN: | 0167-7055 1467-8659 |
DOI: | 10.1111/cgf.12369 |