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

Kristian Valen-Sendstad; Aslak W. Bergersen; Yuji Shimogonya; Leonid Goubergrits; Jan Bruening; Jordi Pallares; Salvatore Cito; Senol Piskin; Kerem Pekkan; Arjan J. Geers; Ignacio Larrabide; Saikiran Rapaka; Viorel Mihalef; Wenyu Fu; Aike Qiao; Kartik Jain; Sabine Roller; Kent-Andre Mardal; Ramji Kamakoti; Thomas Spirka; Neil Ashton; Alistair Revell; Nicolas Aristokleous; J. Graeme Houston; Masanori Tsuji; Fujimaro Ishida; Prahlad G. Menon; Leonard D. Browne; Stephen Broderick; Masaaki Shojima; Satoshi Koizumi; Michael Barbour; Alberto Aliseda; Hernán G. Morales; Thierry Lefèvre; Simona Hodis; Yahia M. Al-Smadi; Justin S. Tran; Alison L. Marsden; Sreeja Vaippummadhom; G. Albert Einstein; Alistair G. Brown; Kristian Debus; Kuniyasu Niizuma; Sherif Rashad; Shin-ichiro Sugiyama; M. Owais Khan; Adam R. Updegrove; Shawn C. Shadden; Bart M. W. Cornelissen; Charles B. L. M. Majoie; Philipp Berg; Sylvia Saalfield; Kenichi Kono; David A. Steinman

doi:https://doi.org/10.1007/s13239-018-00374-2

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

Kristian Valen-Sendstad, Aslak W. Bergersen, Yuji Shimogonya, Leonid Goubergrits, Jan Bruening, Jordi Pallares, Salvatore Cito, Senol Piskin, Kerem Pekkan, Arjan J. Geers, Ignacio Larrabide, Saikiran Rapaka, Viorel Mihalef, Wenyu Fu, Aike Qiao, Kartik Jain, Sabine Roller, Kent-Andre Mardal, Ramji Kamakoti, Thomas SpirkaNeil Ashton, Alistair Revell, Nicolas Aristokleous, J. Graeme Houston, Masanori Tsuji, Fujimaro Ishida, Prahlad G. Menon, Leonard D. Browne, Stephen Broderick, Masaaki Shojima, Satoshi Koizumi, Michael Barbour, Alberto Aliseda, Hernán G. Morales, Thierry Lefèvre, Simona Hodis, Yahia M. Al-Smadi, Justin S. Tran, Alison L. Marsden, Sreeja Vaippummadhom, G. Albert Einstein, Alistair G. Brown, Kristian Debus, Kuniyasu Niizuma, Sherif Rashad, Shin-ichiro Sugiyama, M. Owais Khan, Adam R. Updegrove, Shawn C. Shadden, Bart M. W. Cornelissen, Charles B. L. M. Majoie, Philipp Berg, Sylvia Saalfield, Kenichi Kono, David A. Steinman

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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 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.

Original language	English
Pages (from-to)	544-564
Journal	Cardiovascular Engineering and Technology
Volume	9
Issue number	4
DOIs	https://doi.org/10.1007/s13239-018-00374-2
Publication status	Published - 2018

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Valen-Sendstad, K., Bergersen, A. W., Shimogonya, Y., Goubergrits, L., Bruening, J., Pallares, J., Cito, S., Piskin, S., Pekkan, K., Geers, A. J., Larrabide, I., Rapaka, S., Mihalef, V., Fu, W., Qiao, A., Jain, K., Roller, S., Mardal, K.-A., Kamakoti, R., ... Steinman, D. A. (2018). Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge. Cardiovascular Engineering and Technology, 9(4), 544-564. https://doi.org/10.1007/s13239-018-00374-2

@article{9ef743efaa9b4a0f9ba61e0c905c6cb2,

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

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 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.",

author = "Kristian Valen-Sendstad and Bergersen, {Aslak W.} and Yuji Shimogonya and Leonid Goubergrits and Jan Bruening and Jordi Pallares and Salvatore Cito and Senol Piskin and Kerem Pekkan and Geers, {Arjan J.} and Ignacio Larrabide and Saikiran Rapaka and Viorel Mihalef and Wenyu Fu and Aike Qiao and Kartik Jain and Sabine Roller and Kent-Andre Mardal and Ramji Kamakoti and Thomas Spirka and Neil Ashton and Alistair Revell and Nicolas Aristokleous and Houston, {J. Graeme} and Masanori Tsuji and Fujimaro Ishida and Menon, {Prahlad G.} and Browne, {Leonard D.} and Stephen Broderick and Masaaki Shojima and Satoshi Koizumi and Michael Barbour and Alberto Aliseda and Morales, {Hern{\'a}n G.} and Thierry Lef{\`e}vre and Simona Hodis and Al-Smadi, {Yahia M.} and Tran, {Justin S.} and Marsden, {Alison L.} and Sreeja Vaippummadhom and Einstein, {G. Albert} and Brown, {Alistair G.} and Kristian Debus and Kuniyasu Niizuma and Sherif Rashad and Shin-ichiro Sugiyama and {Owais Khan}, M. and Updegrove, {Adam R.} and Shadden, {Shawn C.} and Cornelissen, {Bart M. W.} and Majoie, {Charles B. L. M.} and Philipp Berg and Sylvia Saalfield and Kenichi Kono and Steinman, {David A.}",

year = "2018",

doi = "https://doi.org/10.1007/s13239-018-00374-2",

language = "English",

volume = "9",

pages = "544--564",

journal = "Cardiovascular Engineering and Technology",

issn = "1869-408X",

publisher = "Springer Publishing Company",

number = "4",

}

Valen-Sendstad, K, Bergersen, AW, Shimogonya, Y, Goubergrits, L, Bruening, J, Pallares, J, Cito, S, Piskin, S, Pekkan, K, Geers, AJ, Larrabide, I, Rapaka, S, Mihalef, V, Fu, W, Qiao, A, Jain, K, Roller, S, Mardal, K-A, Kamakoti, R, Spirka, T, Ashton, N, Revell, A, Aristokleous, N, Houston, JG, Tsuji, M, Ishida, F, Menon, PG, Browne, LD, Broderick, S, Shojima, M, Koizumi, S, Barbour, M, Aliseda, A, Morales, HG, Lefèvre, T, Hodis, S, Al-Smadi, YM, Tran, JS, Marsden, AL, Vaippummadhom, S, Einstein, GA, Brown, AG, Debus, K, Niizuma, K, Rashad, S, Sugiyama, S, Owais Khan, M, Updegrove, AR, Shadden, SC, Cornelissen, BMW , Majoie, CBLM, Berg, P, Saalfield, S, Kono, K & Steinman, DA 2018, 'Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge', Cardiovascular Engineering and Technology, vol. 9, no. 4, pp. 544-564. https://doi.org/10.1007/s13239-018-00374-2

TY - JOUR

T1 - Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: 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.

PY - 2018

Y1 - 2018

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.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85057737651&origin=inward

UR - https://www.ncbi.nlm.nih.gov/pubmed/30203115

U2 - https://doi.org/10.1007/s13239-018-00374-2

DO - https://doi.org/10.1007/s13239-018-00374-2

M3 - Article

C2 - 30203115

SN - 1869-408X

VL - 9

SP - 544

EP - 564

JO - Cardiovascular Engineering and Technology

JF - Cardiovascular Engineering and Technology

IS - 4

ER -

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

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