Literature DB >> 24834416

Magnetic resonance imaging as a tool to assess reliability in simulating hemodynamics in cerebral aneurysms with a dedicated computational fluid dynamics prototype: preliminary results.

Christof Karmonik1, Y Jonathan Zhang1, Orlando Diaz1, Richard Klucznik1, Sasan Partovi1, Robert G Grossman1, Gavin W Britz1.   

Abstract

PURPOSE: As an example of enhancing information in clinical image data by computational methods, simulating hemodynamics in cerebral aneurysms by means of computational fluid dynamics (CFD) is currently a topic of active research. Challenges consist in translating this engineering technology into clinical research, validating the simulations and addressing a potential clinical value of the results. In this preliminary study, we demonstrate the use of phase contrast magnetic resonance imaging (pcMRI) for assessing the reliability of CFD results.
MATERIALS AND METHODS: For six cerebral aneurysms where intra-aneurysmal velocity information was available by 2D pcMRI, steady CFD simulations with constant inflow were performed using a dedicated CFD prototype system. Major features of the velocity patterns derived from pcMRI were compared to those obtained with the CFD.
RESULTS: Good qualitative agreement between measured (2D pcMRI) and simulated (CFD) features of the intra-aneurysmal velocity patterns were obtained. These findings are discussed in the broader framework of the expectations towards CFD simulations in a clinical research setting.
CONCLUSIONS: Computational simulations reproduce major features of measured velocity patterns in cerebral aneurysms. Looking forward, these simulations need to be refined towards specific applications in clinical research.

Entities:  

Keywords:  Cerebral aneurysms; aneurysm rupture; computational fluid dynamics (CFD)

Year:  2014        PMID: 24834416      PMCID: PMC3996232          DOI: 10.3978/j.issn.2223-3652.2014.02.07

Source DB:  PubMed          Journal:  Cardiovasc Diagn Ther        ISSN: 2223-3652


  34 in total

1.  Point: CFD--computational fluid dynamics or confounding factor dissemination.

Authors:  D F Kallmes
Journal:  AJNR Am J Neuroradiol       Date:  2012-01-19       Impact factor: 3.825

2.  Aneurysm rupture following treatment with flow-diverting stents: computational hemodynamics analysis of treatment.

Authors:  J R Cebral; F Mut; M Raschi; E Scrivano; R Ceratto; P Lylyk; C M Putman
Journal:  AJNR Am J Neuroradiol       Date:  2010-11-11       Impact factor: 3.825

3.  Computational fluid dynamics modeling of intracranial aneurysms: effects of parent artery segmentation on intra-aneurysmal hemodynamics.

Authors:  M A Castro; C M Putman; J R Cebral
Journal:  AJNR Am J Neuroradiol       Date:  2006-09       Impact factor: 3.825

4.  Aneurysm volume-to-ostium area ratio: a parameter useful for discriminating the rupture status of intracranial aneurysms.

Authors:  Ryuta Yasuda; Charles M Strother; Waro Taki; Kazuhiko Shinki; Kevin Royalty; Kari Pulfer; Christof Karmonik
Journal:  Neurosurgery       Date:  2011-02       Impact factor: 4.654

5.  Virtual angiography for visualization and validation of computational models of aneurysm hemodynamics.

Authors:  Matthew D Ford; Gordan R Stuhne; Hristo N Nikolov; Damiaan F Habets; Stephen P Lownie; David W Holdsworth; David A Steinman
Journal:  IEEE Trans Med Imaging       Date:  2005-12       Impact factor: 10.048

6.  Computational hemodynamics analysis of intracranial aneurysms treated with flow diverters: correlation with clinical outcomes.

Authors:  W Chong; Y Zhang; Y Qian; L Lai; G Parker; K Mitchell
Journal:  AJNR Am J Neuroradiol       Date:  2013-11-28       Impact factor: 3.825

7.  Effects of arterial geometry on aneurysm growth: three-dimensional computational fluid dynamics study.

Authors:  Yiemeng Hoi; Hui Meng; Scott H Woodward; Bernard R Bendok; Ricardo A Hanel; Lee R Guterman; L Nelson Hopkins
Journal:  J Neurosurg       Date:  2004-10       Impact factor: 5.115

8.  Image-based computational simulation of flow dynamics in a giant intracranial aneurysm.

Authors:  David A Steinman; Jaques S Milner; Chris J Norley; Stephen P Lownie; David W Holdsworth
Journal:  AJNR Am J Neuroradiol       Date:  2003-04       Impact factor: 3.825

9.  Flow diversion treatment: intra-aneurismal blood flow velocity and WSS reduction are parameters to predict aneurysm thrombosis.

Authors:  Zsolt Kulcsár; Luca Augsburger; Philippe Reymond; Vitor M Pereira; Sven Hirsch; Ajit S Mallik; John Millar; Stephan G Wetzel; Isabel Wanke; Daniel A Rüfenacht
Journal:  Acta Neurochir (Wien)       Date:  2012-08-29       Impact factor: 2.216

10.  Unruptured intracranial aneurysms conservatively followed with serial CT angiography: could morphology and growth predict rupture?

Authors:  William A Mehan; Javier M Romero; Joshua A Hirsch; David J Sabbag; Ramon G Gonzalez; Jeremy J Heit; Pamela W Schaefer
Journal:  J Neurointerv Surg       Date:  2013-11-25       Impact factor: 5.836

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  3 in total

1.  Reconstructing patient-specific cerebral aneurysm vasculature for in vitro investigations and treatment efficacy assessments.

Authors:  Venkat Keshav Chivukula; Michael R Levitt; Alicia Clark; Michael C Barbour; Kurt Sansom; Luke Johnson; Cory M Kelly; Christian Geindreau; Sabine Rolland du Roscoat; Louis J Kim; Alberto Aliseda
Journal:  J Clin Neurosci       Date:  2018-11-22       Impact factor: 1.961

2.  Patient-Specific Computational Fluid Dynamics in Ruptured Posterior Communicating Aneurysms Using Measured Non-Newtonian Viscosity : A Preliminary Study.

Authors:  Ui Yun Lee; Jinmu Jung; Hyo Sung Kwak; Dong Hwan Lee; Gyung Ho Chung; Jung Soo Park; Eun Jeong Koh
Journal:  J Korean Neurosurg Soc       Date:  2019-02-27

3.  Depiction of Cerebral Aneurysm Wall by Computational Fluid Dynamics (CFD) and Preoperative Illustration.

Authors:  Riki Tanaka; Boon Seng Liew; Yasuhiro Yamada; Kento Sasaki; Kyosuke Miyatani; Fuminari Komatsu; Tsukasa Kawase; Yoko Kato; Yuichi Hirose
Journal:  Asian J Neurosurg       Date:  2022-06-13
  3 in total

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