Blood Flow Clustering and Applications inVirtual Stenting of Intracranial Aneurysms

Oeltze, Steffen; Lehmann, Dirk J.; Kühn, Alexander; Janiga, Gábor; Theisel, Holger; Preim, Bernhard

doi:10.1109/tvcg.2013.2297914

Cited by 49 publications

(83 citation statements)

References 43 publications

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“…On demand, the groups are refined in a clustering step leading to a more detailed visualization, e.g., of flow further off the core line. We show that this two-step approach outperforms the direct clustering [32] in terms of speed and accuracy and illustrate our method by six (out of 17 investigated) case studies. We further contribute an expert evaluation of the visual summary, exploration techniques, and an automatic assembly of core line segments output by Sujudi and Haimes' algorithm [45] into continuous lines.…”

mentioning

confidence: 84%

“…The pipeline for cases (d-f), which differs in steps tailored to virtual stenting, is outlined in [32].…”

Section: Hemodynamic Data Generation Pipelinementioning

confidence: 99%

“…Most techniques decompose a blood flow field into regions of similar behavior based on integral curves [2,17,23,32]. Others employ local vectors [47] or aneurysm wall properties [14,18,30].…”

Section: Partition-based Visualization Of Blood Flowmentioning

confidence: 99%

“…Clustering approaches employ a data-driven strategy for grouping integral curves and are hence self-tuning with respect to differences in the flow across datasets. In [32], different integral curve properties and techniques for clustering streamlines were compared for analyzing the blood flow pattern in cerebral aneurysms. A spectral clustering approach [51] performed best and will hence, be applied in the refinement step of our approach.…”

Section: Partitioning Based On Integral Curve Propertiesmentioning

confidence: 99%

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Cluster Analysis of Vortical Flow in Simulations of Cerebral Aneurysm Hemodynamics

Oeltze-Jafra

Cebral

Janiga³

et al. 2016

IEEE Trans. Visual. Comput. Graphics

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Computational fluid dynamic (CFD) simulations of blood flow provide new insights into the hemodynamics of vascular pathologies such as cerebral aneurysms. Understanding the relations between hemodynamics and aneurysm initiation, progression, and risk of rupture is crucial in diagnosis and treatment. Recent studies link the existence of vortices in the blood flow pattern to aneurysm rupture and report observations of embedded vortices -a larger vortex encloses a smaller one flowing in the opposite direction -whose implications are unclear. We present a clustering-based approach for the visual analysis of vortical flow in simulated cerebral aneurysm hemodynamics. We show how embedded vortices develop at saddle-node bifurcations on vortex core lines and convey the participating flow at full manifestation of the vortex by a fast and smart grouping of streamlines and the visualization of group representatives. The grouping result may be refined based on spectral clustering generating a more detailed visualization of the flow pattern, especially further off the core lines. We aim at supporting CFD engineers researching the biological implications of embedded vortices.

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mentioning

confidence: 84%

“…The pipeline for cases (d-f), which differs in steps tailored to virtual stenting, is outlined in [32].…”

Section: Hemodynamic Data Generation Pipelinementioning

confidence: 99%

Section: Partition-based Visualization Of Blood Flowmentioning

confidence: 99%

Section: Partitioning Based On Integral Curve Propertiesmentioning

confidence: 99%

See 2 more Smart Citations

Cluster Analysis of Vortical Flow in Simulations of Cerebral Aneurysm Hemodynamics

Oeltze-Jafra

Cebral

Janiga³

et al. 2016

IEEE Trans. Visual. Comput. Graphics

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“…The tape-like structure provides a clear picture of how the representatives diverge and merge. Oeltze et al [26] proposed to cluster the streamlines and use the cluster representatives for a clear view. They conducted a qualitative study on using different similarity measures, including geometry-based similarities and attributebased similarities.…”

Section: Related Workmentioning

confidence: 99%

VesselMap: A web interface to explore multivariate vascular data

Tao

Huang

Qiu

et al. 2016

Computers & Graphics

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a b s t r a c tHemodynamics plays a key role in the pathological evolution of vascular diseases such as vascular stenosis, plaques and aneurysms. Augmented visualization of relevant hemodynamic and geometric data accelerates engineering designs of diagnostic and therapeutic methods for those vascular diseases. However, four dimensional (4D) hemodynamic data are intrinsically complex. Consequently, exploration of this information has not been streamlined, despite its importance. In this paper, we propose a web interface to explore multivariate hemodynamic data, thereby facilitating the visualization of spatial and temporal relationships among those hemodynamic parameters of interest. The main thrust of this web system is the proposed VesselMap methodology, a 2D representation of vessel structures that provides an overview of all query results without any visual occlusions. Furthermore, in this framework, quantilequantile plot was also used to compare spatial variations in parameter distributions, thereby greatly aiding in extracting local characteristics of hemodynamic parameters.Using "patient-specific" computational fluid dynamics (CFD) simulations, realistic flow velocity fields were obtained. Based on those CFD-simulated velocity fields, we performed an empirical evaluation to confirm the usefulness of our approach for biomedical engineering applications. We concluded that the proposed VesselMap methodology allowed users to rapidly interact with hemodynamic data of interest, enhancing efficacy of information retrieval.

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Image‐based modeling of blood flow in cerebral aneurysms treated with intrasaccular flow diverting devices

Mut

Chung

Chudyk³

et al. 2019

Numer Methods Biomed Eng

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Modeling the flow dynamics in cerebral aneurysms after the implantation of intrasaccular devices is important for understanding the relationship between flow conditions created immediately posttreatment and the subsequent outcomes. This information, ideally available a priori based on computational modeling prior to implantation, is valuable to identify which aneurysms will occlude immediately and which aneurysms will likely remain patent and would benefit from a different procedure or device.In this report, a methodology for modeling the hemodynamics in intracranial aneurysms treated with intrasaccular flow diverting devices is described. This approach combines an image-guided, virtual device deployment within patient-specific vascular models with an immersed boundary method on adaptive unstructured grids. A partial mesh refinement strategy that reduces the number of mesh elements near the aneurysm dome where the flow conditions are largely stagnant was compared with the full refinement strategy that refines the mesh everywhere around the device wires. The results indicate that using the partial mesh refinement approach is adequate for analyzing the posttreatment hemodynamics, at a reduced computational cost. The results obtained on a series of four cerebral aneurysms treated with different intrasaccular devices were in good qualitative agreement with angiographic observations. Promising results were obtained relating posttreatment flow conditions and outcomes of treatments with intrasaccular devices, which need to be confirmed on larger series. KEYWORDS cerebral aneurysms, computational hemodynamics, flow diversion, intrasaccular flow diverter

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Blood Flow Clustering and Applications inVirtual Stenting of Intracranial Aneurysms

Cited by 49 publications

References 43 publications

Cluster Analysis of Vortical Flow in Simulations of Cerebral Aneurysm Hemodynamics

Cluster Analysis of Vortical Flow in Simulations of Cerebral Aneurysm Hemodynamics

VesselMap: A web interface to explore multivariate vascular data

Image‐based modeling of blood flow in cerebral aneurysms treated with intrasaccular flow diverting devices

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