Explorative Blood Flow Visualization using Dynamic Line Filtering based on Surface Features

Rupture risk assessment is a key to devise patient‐specific treatment plans of cerebral aneurysms. To understand and predict the development of aneurysms and other vascular diseases over time, both hemodynamic flow patterns and their effect on the vessel surface need to be analyzed. Flow structures close to the vessel wall often correlate directly with local changes in surface parameters, such as pressure or wall shear stress. Yet, in many existing applications, the analyses of flow and surface features are either somewhat detached from one another or only globally available. Especially for the identification of specific blood flow characteristics that cause local startling parameters on the vessel surface, like elevated pressure values, an interactive analysis tool is missing.

[1]  Roger Crawfis,et al.  View point evaluation and streamline filtering for flow visualization , 2011, 2011 IEEE Pacific Visualization Symposium.

[2]  D F Kallmes,et al.  Angioarchitectures and Hemodynamic Characteristics of Posterior Communicating Artery Aneurysms and Their Association with Rupture Status , 2017, American Journal of Neuroradiology.

[3]  Kai Lawonn,et al.  AmniVis – A System for Qualitative Exploration of Near‐Wall Hemodynamics in Cerebral Aneurysms , 2013, Comput. Graph. Forum.

[4]  Irene C van der Schaaf,et al.  Risk of Rupture of Unruptured Intracranial Aneurysms in Relation to Patient and Aneurysm Characteristics: An Updated Meta-Analysis , 2007, Stroke.

[5]  G. Janiga,et al.  Cerebral blood flow in a healthy Circle of Willis and two intracranial aneurysms: computational fluid dynamics versus four-dimensional phase-contrast magnetic resonance imaging. , 2014, Journal of biomechanical engineering.

[6]  Hans-Christian Hege,et al.  Visual Exploration of Nasal Airflow , 2009, IEEE Transactions on Visualization and Computer Graphics.

[7]  Bernhard Preim,et al.  Reconstruction of 3D Surface Meshes for Bood Flow Simulations of Intracranial Aneurysms , 2015, CURAC.

[8]  Silvia Born,et al.  Visual Analysis of Cardiac 4D MRI Blood Flow Using Line Predicates , 2013, IEEE Transactions on Visualization and Computer Graphics.

[9]  Rob J. van der Geest,et al.  A Framework for Fast Initial Exploration of PC-MRI Cardiac Flow , 2016, VCBM/MedViz.

[10]  Nicolas Thibieroz Order-Independent Transparency Using Per-Pixel Linked Lists , 2011 .

[11]  Philipp Berg,et al.  Multiple intracranial aneurysms: a direct hemodynamic comparison between ruptured and unruptured vessel malformations , 2017, International Journal of Computer Assisted Radiology and Surgery.

[12]  Kai Lawonn,et al.  Comparative Blood Flow Visualization for Cerebral Aneurysm Treatment Assessment , 2014, Comput. Graph. Forum.

[13]  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.

[14]  H Meng,et al.  CFD: Computational Fluid Dynamics or Confounding Factor Dissemination? The Role of Hemodynamics in Intracranial Aneurysm Rupture Risk Assessment , 2014, American Journal of Neuroradiology.

[15]  Kai Lawonn,et al.  Combined Visualization of Vessel Deformation and Hemodynamics in Cerebral Aneurysms , 2017, IEEE Transactions on Visualization and Computer Graphics.

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

[17]  B. Bendok,et al.  Unruptured intracranial aneurysms and the assessment of rupture risk based on anatomical and morphological factors: sifting through the sands of data. , 2009, Neurosurgical focus.

[18]  Bernhard Preim,et al.  Cluster Analysis of Vortical Flow in Simulations of Cerebral Aneurysm Hemodynamics , 2016, IEEE Transactions on Visualization and Computer Graphics.

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

[20]  Bernhard Preim,et al.  Ieee Transactions on Visualization and Computer Graphics 1 Blood Flow Clustering and Applications in Virtual Stenting of Intracranial Aneurysms , 2022 .

[21]  F. Hamzei-Sichani,et al.  Differences in Hemodynamics and Rupture Rate of Aneurysms at the Bifurcation of the Basilar and Internal Carotid Arteries , 2017, American Journal of Neuroradiology.

[22]  Bernhard Preim,et al.  Automatic Detection and Visualization of Qualitative Hemodynamic Characteristics in Cerebral Aneurysms , 2012, IEEE Transactions on Visualization and Computer Graphics.

[23]  Bernhard Preim,et al.  The Medical Exploration Toolkit – an efficient support for visual computing in surgical planning and training , 2008 .

[24]  Bernhard Preim,et al.  Semi-Automatic Vortex Extraction in 4D PC-MRI Cardiac Blood Flow Data using Line Predicates , 2013, IEEE Transactions on Visualization and Computer Graphics.

[25]  Bernhard Preim,et al.  Recommendations for accurate numerical blood flow simulations of stented intracranial aneurysms , 2013, Biomedizinische Technik. Biomedical engineering.

[26]  Gerik Scheuermann,et al.  Streamline Predicates , 2006, IEEE Transactions on Visualization and Computer Graphics.

[27]  D. Nichols,et al.  Unruptured intracranial aneurysms: natural history, clinical outcome, and risks of surgical and endovascular treatment , 2003, The Lancet.

[28]  Kai Lawonn,et al.  Occlusion-free Blood Flow Animation with Wall Thickness Visualization , 2016, IEEE Transactions on Visualization and Computer Graphics.