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Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress : The 2015 International Aneurysm CFD Challenge

Valen-Sendstad, Kristian ; Bergersen, Aslak W. ; Shimogonya, Yuji ; Goubergrits, Leonid ; Bruening, Jan ; Pallares, Jordi ; Cito, Salvatore ; Piskin, Senol ; Pekkan, Kerem and Geers, Arjan J. , et al. (2018) In Cardiovascular Engineering and Technology 9(4). p.544-564
Abstract

Purpose: Image-based computational fluid dynamics (CFD) is widely used to predict intracranial aneurysm wall shear stress (WSS), particularly with the goal of improving rupture risk assessment. Nevertheless, concern has been expressed over the variability of predicted WSS and inconsistent associations with rupture. Previous challenges, and studies from individual groups, have focused on individual aspects of the image-based CFD pipeline. The aim of this Challenge was to quantify the total variability of the whole pipeline. Methods: 3D rotational angiography image volumes of five middle cerebral artery aneurysms were provided to participants, who were free to choose their segmentation methods, boundary conditions, and CFD solver and... (More)

Purpose: Image-based computational fluid dynamics (CFD) is widely used to predict intracranial aneurysm wall shear stress (WSS), particularly with the goal of improving rupture risk assessment. Nevertheless, concern has been expressed over the variability of predicted WSS and inconsistent associations with rupture. Previous challenges, and studies from individual groups, have focused on individual aspects of the image-based CFD pipeline. The aim of this Challenge was to quantify the total variability of the whole pipeline. Methods: 3D rotational angiography image volumes of five middle cerebral artery aneurysms were provided to participants, who were free to choose their segmentation methods, boundary conditions, and CFD solver and settings. Participants were asked to fill out a questionnaire about their solution strategies and experience with aneurysm CFD, and provide surface distributions of WSS magnitude, from which we objectively derived a variety of hemodynamic parameters. Results: A total of 28 datasets were submitted, from 26 teams with varying levels of self-assessed experience. Wide variability of segmentations, CFD model extents, and inflow rates resulted in interquartile ranges of sac average WSS up to 56%, which reduced to < 30% after normalizing by parent artery WSS. Sac-maximum WSS and low shear area were more variable, while rank-ordering of cases by low or high shear showed only modest consensus among teams. Experience was not a significant predictor of variability. Conclusions: Wide variability exists in the prediction of intracranial aneurysm WSS. While segmentation and CFD solver techniques may be difficult to standardize across groups, our findings suggest that some of the variability in image-based CFD could be reduced by establishing guidelines for model extents, inflow rates, and blood properties, and by encouraging the reporting of normalized hemodynamic parameters.

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publishing date
type
Contribution to journal
publication status
published
keywords
Intracranial aneurysm, Patient-specific modelling, Rupture risk, Uncertainty quantification, Wall shear stress
in
Cardiovascular Engineering and Technology
volume
9
issue
4
pages
544 - 564
publisher
Springer
external identifiers
  • scopus:85057737651
ISSN
1869-408X
DOI
10.1007/s13239-018-00374-2
language
English
LU publication?
no
id
d41e24d1-a517-4a23-a47d-7c94f556c3d2
date added to LUP
2019-05-14 09:23:00
date last changed
2022-04-25 23:38:58
@article{d41e24d1-a517-4a23-a47d-7c94f556c3d2,
  abstract     = {{<p>Purpose: Image-based computational fluid dynamics (CFD) is widely used to predict intracranial aneurysm wall shear stress (WSS), particularly with the goal of improving rupture risk assessment. Nevertheless, concern has been expressed over the variability of predicted WSS and inconsistent associations with rupture. Previous challenges, and studies from individual groups, have focused on individual aspects of the image-based CFD pipeline. The aim of this Challenge was to quantify the total variability of the whole pipeline. Methods: 3D rotational angiography image volumes of five middle cerebral artery aneurysms were provided to participants, who were free to choose their segmentation methods, boundary conditions, and CFD solver and settings. Participants were asked to fill out a questionnaire about their solution strategies and experience with aneurysm CFD, and provide surface distributions of WSS magnitude, from which we objectively derived a variety of hemodynamic parameters. Results: A total of 28 datasets were submitted, from 26 teams with varying levels of self-assessed experience. Wide variability of segmentations, CFD model extents, and inflow rates resulted in interquartile ranges of sac average WSS up to 56%, which reduced to &lt; 30% after normalizing by parent artery WSS. Sac-maximum WSS and low shear area were more variable, while rank-ordering of cases by low or high shear showed only modest consensus among teams. Experience was not a significant predictor of variability. Conclusions: Wide variability exists in the prediction of intracranial aneurysm WSS. While segmentation and CFD solver techniques may be difficult to standardize across groups, our findings suggest that some of the variability in image-based CFD could be reduced by establishing guidelines for model extents, inflow rates, and blood properties, and by encouraging the reporting of normalized hemodynamic parameters.</p>}},
  author       = {{Valen-Sendstad, Kristian and Bergersen, Aslak W. and Shimogonya, Yuji and Goubergrits, Leonid and Bruening, Jan and Pallares, Jordi and Cito, Salvatore and Piskin, Senol and Pekkan, Kerem and Geers, Arjan J. and Larrabide, Ignacio and Rapaka, Saikiran and Mihalef, Viorel and Fu, Wenyu and Qiao, Aike and Jain, Kartik and Roller, Sabine and Mardal, Kent Andre and Kamakoti, Ramji and Spirka, Thomas and Ashton, Neil and Revell, Alistair and Aristokleous, Nicolas and Houston, J. Graeme and Tsuji, Masanori and Ishida, Fujimaro and Menon, Prahlad G. and Browne, Leonard D. and Broderick, Stephen and Shojima, Masaaki and Koizumi, Satoshi and Barbour, Michael and Aliseda, Alberto and Morales, Hernán G. and Lefèvre, Thierry and Hodis, Simona and Al-Smadi, Yahia M. and Tran, Justin S. and Marsden, Alison L. and Vaippummadhom, Sreeja and Einstein, G. Albert and Brown, Alistair G. and Debus, Kristian and Niizuma, Kuniyasu and Rashad, Sherif and Sugiyama, Shin ichiro and Owais Khan, M. and Updegrove, Adam R. and Shadden, Shawn C. and Cornelissen, Bart M.W. and Majoie, Charles B.L.M. and Berg, Philipp and Saalfield, Sylvia and Kono, Kenichi and Steinman, David A.}},
  issn         = {{1869-408X}},
  keywords     = {{Intracranial aneurysm; Patient-specific modelling; Rupture risk; Uncertainty quantification; Wall shear stress}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{544--564}},
  publisher    = {{Springer}},
  series       = {{Cardiovascular Engineering and Technology}},
  title        = {{Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress : The 2015 International Aneurysm CFD Challenge}},
  url          = {{http://dx.doi.org/10.1007/s13239-018-00374-2}},
  doi          = {{10.1007/s13239-018-00374-2}},
  volume       = {{9}},
  year         = {{2018}},
}