Singh, PK, Marzo, A, Coley, SC et al. (9 more authors) (2009) The Role of Computational Fluid Dynamics in the Management of Unruptured Intracranial Aneurysms: A Clinicians' View. Computational Intelligence and Neuroscience, 2009. 760364. ISSN 1687-5265
Abstract
Objective. The importance of hemodynamics in the etiopathogenesis of intracranial aneurysms (IAs) is widely accepted. Computational fluid dynamics (CFD) is being used increasingly for hemodynamic predictions. However, alogn with the continuing development and validation of these tools, it is imperative to collect the opinion of the clinicians. Methods. A workshop on CFD was conducted during the European Society of Minimally Invasive Neurological Therapy (ESMINT) Teaching Course, Lisbon, Portugal. 36 delegates, mostly clinicians, performed supervised CFD analysis for an IA, using the @neuFuse software developed within the European project @neurIST. Feedback on the workshop was collected and analyzed. The performance was assessed on a scale of 1 to 4 and, compared with experts' performance. Results. Current dilemmas in the management of unruptured IAs remained the most important motivating factor to attend the workshop and majority of participants showed interest in participating in a multicentric trial. The participants achieved an average score of 2.52 (range 0–4) which was 63% (range 0–100%) of an expert user. Conclusions. Although participants showed a manifest interest in CFD, there was a clear lack of awareness concerning the role of hemodynamics in the etiopathogenesis of IAs and the use of CFD in this context. More efforts therefore are required to enhance understanding of the clinicians in the subject.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2009 Pankaj K. Singh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Sep 2021 12:49 |
Last Modified: | 25 Jun 2023 22:45 |
Status: | Published |
Publisher: | Hindawi |
Identification Number: | 10.1155/2009/760364 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177886 |