Literature DB >> 26473395

The Computational Fluid Dynamics Rupture Challenge 2013--Phase II: Variability of Hemodynamic Simulations in Two Intracranial Aneurysms.

Philipp Berg, Christoph Roloff, Oliver Beuing, Samuel Voss, Shin-Ichiro Sugiyama, Nicolas Aristokleous, Andreas S Anayiotos, Neil Ashton, Alistair Revell, Neil W Bressloff, Alistair G Brown, Bong Jae Chung, Juan R Cebral, Gabriele Copelli, Wenyu Fu, Aike Qiao, Arjan J Geers, Simona Hodis, Dan Dragomir-Daescu, Emily Nordahl, Yildirim Bora Suzen, Muhammad Owais Khan, Kristian Valen-Sendstad, Kenichi Kono, Prahlad G Menon, Priti G Albal, Otto Mierka, Raphael Münster, Hernán G Morales, Odile Bonnefous, Jan Osman, Leonid Goubergrits, Jordi Pallares, Salvatore Cito, Alberto Passalacqua, Senol Piskin, Kerem Pekkan, Susana Ramalho, Nelson Marques, Stéphane Sanchi, Kristopher R Schumacher, Jess Sturgeon, Helena Švihlová, Jaroslav Hron, Gabriel Usera, Mariana Mendina, Jianping Xiang, Hui Meng, David A Steinman, Gábor Janiga.   

Abstract

With the increased availability of computational resources, the past decade has seen a rise in the use of computational fluid dynamics (CFD) for medical applications. There has been an increase in the application of CFD to attempt to predict the rupture of intracranial aneurysms, however, while many hemodynamic parameters can be obtained from these computations, to date, no consistent methodology for the prediction of the rupture has been identified. One particular challenge to CFD is that many factors contribute to its accuracy; the mesh resolution and spatial/temporal discretization can alone contribute to a variation in accuracy. This failure to identify the importance of these factors and identify a methodology for the prediction of ruptures has limited the acceptance of CFD among physicians for rupture prediction. The International CFD Rupture Challenge 2013 seeks to comment on the sensitivity of these various CFD assumptions to predict the rupture by undertaking a comparison of the rupture and blood-flow predictions from a wide range of independent participants utilizing a range of CFD approaches. Twenty-six groups from 15 countries took part in the challenge. Participants were provided with surface models of two intracranial aneurysms and asked to carry out the corresponding hemodynamics simulations, free to choose their own mesh, solver, and temporal discretization. They were requested to submit velocity and pressure predictions along the centerline and on specified planes. The first phase of the challenge, described in a separate paper, was aimed at predicting which of the two aneurysms had previously ruptured and where the rupture site was located. The second phase, described in this paper, aims to assess the variability of the solutions and the sensitivity to the modeling assumptions. Participants were free to choose boundary conditions in the first phase, whereas they were prescribed in the second phase but all other CFD modeling parameters were not prescribed. In order to compare the computational results of one representative group with experimental results, steady-flow measurements using particle image velocimetry (PIV) were carried out in a silicone model of one of the provided aneurysms. Approximately 80% of the participating groups generated similar results. Both velocity and pressure computations were in good agreement with each other for cycle-averaged and peak-systolic predictions. Most apparent "outliers" (results that stand out of the collective) were observed to have underestimated velocity levels compared to the majority of solutions, but nevertheless identified comparable flow structures. In only two cases, the results deviate by over 35% from the mean solution of all the participants. Results of steady CFD simulations of the representative group and PIV experiments were in good agreement. The study demonstrated that while a range of numerical schemes, mesh resolution, and solvers was used, similar flow predictions were observed in the majority of cases. To further validate the computational results, it is suggested that time-dependent measurements should be conducted in the future. However, it is recognized that this study does not include the biological aspects of the aneurysm, which needs to be considered to be able to more precisely identify the specific rupture risk of an intracranial aneurysm.

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Year:  2015        PMID: 26473395     DOI: 10.1115/1.4031794

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  14 in total

1.  Modeling hemodynamics in intracranial aneurysms: Comparing accuracy of CFD solvers based on finite element and finite volume schemes.

Authors:  Lorenzo Botti; Nikhil Paliwal; Pierangelo Conti; Luca Antiga; Hui Meng
Journal:  Int J Numer Method Biomed Eng       Date:  2018-07-20       Impact factor: 2.747

2.  Flow-splitting-based computation of outlet boundary conditions for improved cerebrovascular simulation in multiple intracranial aneurysms.

Authors:  Sylvia Saalfeld; Samuel Voß; Oliver Beuing; Bernhard Preim; Philipp Berg
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-07-30       Impact factor: 2.924

3.  Multiple intracranial aneurysms: a direct hemodynamic comparison between ruptured and unruptured vessel malformations.

Authors:  Philipp Berg; Oliver Beuing
Journal:  Int J Comput Assist Radiol Surg       Date:  2017-07-21       Impact factor: 2.924

4.  The Computational Fluid Dynamics Rupture Challenge 2013—Phase I: prediction of rupture status in intracranial aneurysms.

Authors:  G Janiga; P Berg; S Sugiyama; K Kono; D A Steinman
Journal:  AJNR Am J Neuroradiol       Date:  2014-12-11       Impact factor: 3.825

5.  Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH)-phase II: rupture risk assessment.

Authors:  Philipp Berg; Samuel Voß; Gábor Janiga; Sylvia Saalfeld; Aslak W Bergersen; Kristian Valen-Sendstad; Jan Bruening; Leonid Goubergrits; Andreas Spuler; Tin Lok Chiu; Anderson Chun On Tsang; Gabriele Copelli; Benjamin Csippa; György Paál; Gábor Závodszky; Felicitas J Detmer; Bong J Chung; Juan R Cebral; Soichiro Fujimura; Hiroyuki Takao; Christof Karmonik; Saba Elias; Nicole M Cancelliere; Mehdi Najafi; David A Steinman; Vitor M Pereira; Senol Piskin; Ender A Finol; Mariya Pravdivtseva; Prasanth Velvaluri; Hamidreza Rajabzadeh-Oghaz; Nikhil Paliwal; Hui Meng; Santhosh Seshadhri; Sreenivas Venguru; Masaaki Shojima; Sergey Sindeev; Sergey Frolov; Yi Qian; Yu-An Wu; Kent D Carlson; David F Kallmes; Dan Dragomir-Daescu; Oliver Beuing
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-05-03       Impact factor: 2.924

6.  Accounting for residence-time in blood rheology models: do we really need non-Newtonian blood flow modelling in large arteries?

Authors:  Amirhossein Arzani
Journal:  J R Soc Interface       Date:  2018-09-26       Impact factor: 4.118

7.  Multi-modality cerebral aneurysm haemodynamic analysis: in vivo 4D flow MRI, in vitro volumetric particle velocimetry and in silico computational fluid dynamics.

Authors:  Melissa C Brindise; Sean Rothenberger; Benjamin Dickerhoff; Susanne Schnell; Michael Markl; David Saloner; Vitaliy L Rayz; Pavlos P Vlachos
Journal:  J R Soc Interface       Date:  2019-09-11       Impact factor: 4.118

8.  Semi-automated analysis of 4D flow MRI to assess the hemodynamic impact of intracranial atherosclerotic disease.

Authors:  Alireza Vali; Maria Aristova; Parmede Vakil; Ramez Abdalla; Shyam Prabhakaran; Michael Markl; Sameer A Ansari; Susanne Schnell
Journal:  Magn Reson Med       Date:  2019-03-28       Impact factor: 4.668

9.  Fluid-Structure Simulations of a Ruptured Intracranial Aneurysm: Constant versus Patient-Specific Wall Thickness.

Authors:  S Voß; S Glaßer; T Hoffmann; O Beuing; S Weigand; K Jachau; B Preim; D Thévenin; G Janiga; P Berg
Journal:  Comput Math Methods Med       Date:  2016-09-18       Impact factor: 2.238

Review 10.  Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review.

Authors:  Sarah N Lipp; Elizabeth E Niedert; Hannah L Cebull; Tyler C Diorio; Jessica L Ma; Sean M Rothenberger; Kimberly A Stevens Boster; Craig J Goergen
Journal:  Front Physiol       Date:  2020-05-12       Impact factor: 4.566

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