TY - JOUR
T1 - Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress
T2 - The 2015 International Aneurysm CFD Challenge
AU - Valen-Sendstad, Kristian
AU - Bergersen, Aslak W.
AU - Shimogonya, Yuji
AU - Goubergrits, Leonid
AU - Bruening, Jan
AU - Pallares, Jordi
AU - Cito, Salvatore
AU - Piskin, Senol
AU - Pekkan, Kerem
AU - Geers, Arjan J.
AU - Larrabide, Ignacio
AU - Rapaka, Saikiran
AU - Mihalef, Viorel
AU - Fu, Wenyu
AU - Qiao, Aike
AU - Jain, Kartik
AU - Roller, Sabine
AU - Mardal, Kent Andre
AU - Kamakoti, Ramji
AU - Spirka, Thomas
AU - Ashton, Neil
AU - Revell, Alistair
AU - Aristokleous, Nicolas
AU - Houston, J. Graeme
AU - Tsuji, Masanori
AU - Ishida, Fujimaro
AU - Menon, Prahlad G.
AU - Browne, Leonard D.
AU - Broderick, Stephen
AU - Shojima, Masaaki
AU - Koizumi, Satoshi
AU - Barbour, Michael
AU - Aliseda, Alberto
AU - Morales, Hernán G.
AU - Lefèvre, Thierry
AU - Hodis, Simona
AU - Al-Smadi, Yahia M.
AU - Tran, Justin S.
AU - Marsden, Alison L.
AU - Vaippummadhom, Sreeja
AU - Einstein, G. Albert
AU - Brown, Alistair G.
AU - Debus, Kristian
AU - Niizuma, Kuniyasu
AU - Rashad, Sherif
AU - Sugiyama, Shin ichiro
AU - Owais Khan, M.
AU - Updegrove, Adam R.
AU - Shadden, Shawn C.
AU - Cornelissen, Bart M.W.
AU - Majoie, Charles B.L.M.
AU - Berg, Philipp
AU - Saalfield, Sylvia
AU - Kono, Kenichi
AU - Steinman, David A.
N1 - Publisher Copyright:
© 2018, The Author(s).
PY - 2018/12/15
Y1 - 2018/12/15
N2 - 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.
AB - 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.
KW - Intracranial aneurysm
KW - Patient-specific modelling
KW - Rupture risk
KW - Uncertainty quantification
KW - Wall shear stress
UR - http://www.scopus.com/inward/record.url?scp=85057737651&partnerID=8YFLogxK
U2 - 10.1007/s13239-018-00374-2
DO - 10.1007/s13239-018-00374-2
M3 - Article
C2 - 30203115
AN - SCOPUS:85057737651
SN - 1869-408X
VL - 9
SP - 544
EP - 564
JO - Cardiovascular Engineering and Technology
JF - Cardiovascular Engineering and Technology
IS - 4
ER -
