Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge
- Autores
- Valen-Sendstad, Kristian; Bergersen, Aslak W.; Shimogonya, Yuji; Goubergrits, Leonid; Bruening, Jan; Pallares, Jordi; Cito, Salvatore; Piskin, Senol; Pekkan, Kerem; Geers, Arjan J.; Larrabide, Ignacio; Rapaka, Saikiran; Mihalef, Viorel; Fu, Wenyu; Qiao, Aike; Jain, Kartik; Roller, Sabine; Mardal, Kent-Andre; Kamakoti, Ramji; Spirka, Thomas; Ashton, Neil; Revell, Alistair; Aristokleous, Nicolas; Houston, J. Graeme; Tsuji, Masanori; Ishida, Fujimaro; Menon, Prahlad G.; Browne, Leonard D.; Broderick, Stephen; Shojima, Masaaki; Koizumi, Satoshi; Barbour, Michael; Aliseda, Alberto; Morales, Hernán G.; Lefèvre, Thierry; Hodis, Simona; Al-Smadi, Yahia M.; Tran, Justin S.; Marsden, Alison L.; Vaippummadhom, Sreeja; Einstein, G. Albert; Brown, Alistair G.; Debus, Kristian; Niizuma, Kuniyasu; Rashad, Sherif; Sugiyama, Shin-ichiro; Owais Khan, M.; Updegrove, Adam R.; Shadden, Shawn C.; Cornelissen, Bart M. W.; Majoie, Charles B. L. M.; Berg, Philipp; Saalfield, Sylvia; Kono, Kenichi; Steinman, David A.
- Año de publicación
- 2018
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- 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.
Fil: Valen-Sendstad, Kristian. Simula Research Laboratory and Center for Cardiological Innovation; Noruega
Fil: Bergersen, Aslak W.. University of Oslo; Noruega
Fil: Shimogonya, Yuji. Nihon University; Japón
Fil: Goubergrits, Leonid. Charite´ – Universita¨tsmedizin Berlin; Alemania
Fil: Bruening, Jan. Charité – Universitätsmedizin Berlin; Alemania
Fil: Pallares, Jordi. Universitat Rovira I Virgili; España
Fil: Cito, Salvatore. Universitat Rovira I Virgili; España
Fil: Piskin, Senol. University Of Texas At San Antonio.; Estados Unidos
Fil: Pekkan, Kerem. Koc University; Turquía
Fil: Geers, Arjan J.. Universitat Pompeu Fabra; España
Fil: Larrabide, Ignacio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Rapaka, Saikiran. Siemens Medical Solutions USA Inc; Estados Unidos
Fil: Mihalef, Viorel. Siemens Medical Solutions USA Inc; Estados Unidos
Fil: Fu, Wenyu. Beijing Union University; China
Fil: Qiao, Aike. Beijing University of Technology; China
Fil: Jain, Kartik. Simula Research Laboratory and Center for Cardiological Innovation; Noruega. University of Siegen; Alemania. University of Zürich; Suiza
Fil: Roller, Sabine. University of Siegen; Alemania
Fil: Mardal, Kent-Andre. Simula Research Laboratory and Center for Cardiological Innovation; Noruega. University of Oslo; Noruega
Fil: Kamakoti, Ramji. Dassault Systemes; Francia
Fil: Spirka, Thomas. Simpleware Software Solutions; Reino Unido
Fil: Ashton, Neil. University of Oxford; Reino Unido
Fil: Revell, Alistair. University of Manchester; Reino Unido
Fil: Aristokleous, Nicolas. University of Limerick; Irlanda
Fil: Houston, J. Graeme. University of Dundee; Reino Unido
Fil: Tsuji, Masanori. Mie Chuo Medical Center; Japón
Fil: Ishida, Fujimaro. Mie Chuo Medical Center; Japón
Fil: Menon, Prahlad G.. University of Pittsburgh; Estados Unidos
Fil: Browne, Leonard D.. University of Limerick; Irlanda
Fil: Broderick, Stephen. University of Limerick; Irlanda
Fil: Shojima, Masaaki. University of Tokyo; Japón
Fil: Koizumi, Satoshi. University of Tokyo; Japón
Fil: Barbour, Michael. University of Washington; Estados Unidos
Fil: Aliseda, Alberto. University of Washington; Estados Unidos
Fil: Morales, Hernán G.. Medisys - Philips Research Paris; Francia
Fil: Lefèvre, Thierry. Medisys - Philips Research Paris; Francia
Fil: Hodis, Simona. Texas A&M University - Kingsville; Estados Unidos
Fil: Al-Smadi, Yahia M.. Jordan University of Science and Technology; Jordania
Fil: Tran, Justin S.. Stanford University; Estados Unidos
Fil: Marsden, Alison L.. Stanford University; Estados Unidos
Fil: Vaippummadhom, Sreeja. EinNel Technlogies; India
Fil: Einstein, G. Albert. EinNel Technlogies; India
Fil: Brown, Alistair G.. Siemens PLM Software; Estados Unidos
Fil: Debus, Kristian. Siemens PLM Software; Estados Unidos
Fil: Niizuma, Kuniyasu. Tohoku University; Japón
Fil: Rashad, Sherif. Tohoku University; Japón
Fil: Sugiyama, Shin-ichiro. Kohnan Hospital; Japón
Fil: Owais Khan, M.. University of Toronto; Canadá
Fil: Updegrove, Adam R.. University of California at Berkeley; Estados Unidos
Fil: Shadden, Shawn C.. University of California at Berkeley; Estados Unidos
Fil: Cornelissen, Bart M. W.. Academic Medical Center; Países Bajos
Fil: Majoie, Charles B. L. M.. Academic Medical Center; Países Bajos
Fil: Berg, Philipp. University of Magdeburg; Alemania
Fil: Saalfield, Sylvia. University of Magdeburg; Alemania
Fil: Kono, Kenichi. Wakayama Rosai Hospital; Japón
Fil: Steinman, David A.. University of Toronto; Canadá - Materia
-
INTRACRANIAL ANEURYSM
PATIENT-SPECIFIC MODELLING
WALL SHEAR STRESS
RUPTURE RISK
UNCERTAINTY QUANTIFICATION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/112699
Ver los metadatos del registro completo
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Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD ChallengeValen-Sendstad, KristianBergersen, Aslak W.Shimogonya, YujiGoubergrits, LeonidBruening, JanPallares, JordiCito, SalvatorePiskin, SenolPekkan, KeremGeers, Arjan J.Larrabide, IgnacioRapaka, SaikiranMihalef, ViorelFu, WenyuQiao, AikeJain, KartikRoller, SabineMardal, Kent-AndreKamakoti, RamjiSpirka, ThomasAshton, NeilRevell, AlistairAristokleous, NicolasHouston, J. GraemeTsuji, MasanoriIshida, FujimaroMenon, Prahlad G.Browne, Leonard D.Broderick, StephenShojima, MasaakiKoizumi, SatoshiBarbour, MichaelAliseda, AlbertoMorales, Hernán G.Lefèvre, ThierryHodis, SimonaAl-Smadi, Yahia M.Tran, Justin S.Marsden, Alison L.Vaippummadhom, SreejaEinstein, G. AlbertBrown, Alistair G.Debus, KristianNiizuma, KuniyasuRashad, SherifSugiyama, Shin-ichiroOwais Khan, M.Updegrove, Adam R.Shadden, Shawn C.Cornelissen, Bart M. W.Majoie, Charles B. L. M.Berg, PhilippSaalfield, SylviaKono, KenichiSteinman, David A.INTRACRANIAL ANEURYSMPATIENT-SPECIFIC MODELLINGWALL SHEAR STRESSRUPTURE RISKUNCERTAINTY QUANTIFICATIONhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Purpose—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.Fil: Valen-Sendstad, Kristian. Simula Research Laboratory and Center for Cardiological Innovation; NoruegaFil: Bergersen, Aslak W.. University of Oslo; NoruegaFil: Shimogonya, Yuji. Nihon University; JapónFil: Goubergrits, Leonid. Charite´ – Universita¨tsmedizin Berlin; AlemaniaFil: Bruening, Jan. Charité – Universitätsmedizin Berlin; AlemaniaFil: Pallares, Jordi. Universitat Rovira I Virgili; EspañaFil: Cito, Salvatore. Universitat Rovira I Virgili; EspañaFil: Piskin, Senol. University Of Texas At San Antonio.; Estados UnidosFil: Pekkan, Kerem. Koc University; TurquíaFil: Geers, Arjan J.. Universitat Pompeu Fabra; EspañaFil: Larrabide, Ignacio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rapaka, Saikiran. Siemens Medical Solutions USA Inc; Estados UnidosFil: Mihalef, Viorel. Siemens Medical Solutions USA Inc; Estados UnidosFil: Fu, Wenyu. Beijing Union University; ChinaFil: Qiao, Aike. Beijing University of Technology; ChinaFil: Jain, Kartik. Simula Research Laboratory and Center for Cardiological Innovation; Noruega. University of Siegen; Alemania. University of Zürich; SuizaFil: Roller, Sabine. University of Siegen; AlemaniaFil: Mardal, Kent-Andre. Simula Research Laboratory and Center for Cardiological Innovation; Noruega. University of Oslo; NoruegaFil: Kamakoti, Ramji. Dassault Systemes; FranciaFil: Spirka, Thomas. Simpleware Software Solutions; Reino UnidoFil: Ashton, Neil. University of Oxford; Reino UnidoFil: Revell, Alistair. University of Manchester; Reino UnidoFil: Aristokleous, Nicolas. University of Limerick; IrlandaFil: Houston, J. Graeme. University of Dundee; Reino UnidoFil: Tsuji, Masanori. Mie Chuo Medical Center; JapónFil: Ishida, Fujimaro. Mie Chuo Medical Center; JapónFil: Menon, Prahlad G.. University of Pittsburgh; Estados UnidosFil: Browne, Leonard D.. University of Limerick; IrlandaFil: Broderick, Stephen. University of Limerick; IrlandaFil: Shojima, Masaaki. University of Tokyo; JapónFil: Koizumi, Satoshi. University of Tokyo; JapónFil: Barbour, Michael. University of Washington; Estados UnidosFil: Aliseda, Alberto. University of Washington; Estados UnidosFil: Morales, Hernán G.. Medisys - Philips Research Paris; FranciaFil: Lefèvre, Thierry. Medisys - Philips Research Paris; FranciaFil: Hodis, Simona. Texas A&M University - Kingsville; Estados UnidosFil: Al-Smadi, Yahia M.. Jordan University of Science and Technology; JordaniaFil: Tran, Justin S.. Stanford University; Estados UnidosFil: Marsden, Alison L.. Stanford University; Estados UnidosFil: Vaippummadhom, Sreeja. EinNel Technlogies; IndiaFil: Einstein, G. Albert. EinNel Technlogies; IndiaFil: Brown, Alistair G.. Siemens PLM Software; Estados UnidosFil: Debus, Kristian. Siemens PLM Software; Estados UnidosFil: Niizuma, Kuniyasu. Tohoku University; JapónFil: Rashad, Sherif. Tohoku University; JapónFil: Sugiyama, Shin-ichiro. Kohnan Hospital; JapónFil: Owais Khan, M.. University of Toronto; CanadáFil: Updegrove, Adam R.. University of California at Berkeley; Estados UnidosFil: Shadden, Shawn C.. University of California at Berkeley; Estados UnidosFil: Cornelissen, Bart M. W.. Academic Medical Center; Países BajosFil: Majoie, Charles B. L. M.. Academic Medical Center; Países BajosFil: Berg, Philipp. University of Magdeburg; AlemaniaFil: Saalfield, Sylvia. University of Magdeburg; AlemaniaFil: Kono, Kenichi. Wakayama Rosai Hospital; JapónFil: Steinman, David A.. University of Toronto; CanadáSpringer2018-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/112699Valen-Sendstad, Kristian; Bergersen, Aslak W.; Shimogonya, Yuji; Goubergrits, Leonid; Bruening, Jan; et al.; Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge; Springer; Cardiovascular Engineering and Technology; -; 9; 9-2018; 544-5641869-408XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://link.springer.com/10.1007/s13239-018-00374-2info:eu-repo/semantics/altIdentifier/doi/10.1007/s13239-018-00374-2info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:46:37Zoai:ri.conicet.gov.ar:11336/112699instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:46:38.173CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge |
| title |
Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge |
| spellingShingle |
Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge Valen-Sendstad, Kristian INTRACRANIAL ANEURYSM PATIENT-SPECIFIC MODELLING WALL SHEAR STRESS RUPTURE RISK UNCERTAINTY QUANTIFICATION |
| title_short |
Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge |
| title_full |
Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge |
| title_fullStr |
Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge |
| title_full_unstemmed |
Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge |
| title_sort |
Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge |
| dc.creator.none.fl_str_mv |
Valen-Sendstad, Kristian Bergersen, Aslak W. Shimogonya, Yuji Goubergrits, Leonid Bruening, Jan Pallares, Jordi Cito, Salvatore Piskin, Senol Pekkan, Kerem Geers, Arjan J. Larrabide, Ignacio Rapaka, Saikiran Mihalef, Viorel Fu, Wenyu Qiao, Aike Jain, Kartik Roller, Sabine Mardal, Kent-Andre Kamakoti, Ramji Spirka, Thomas Ashton, Neil Revell, Alistair Aristokleous, Nicolas Houston, J. Graeme Tsuji, Masanori Ishida, Fujimaro Menon, Prahlad G. Browne, Leonard D. Broderick, Stephen Shojima, Masaaki Koizumi, Satoshi Barbour, Michael Aliseda, Alberto Morales, Hernán G. Lefèvre, Thierry Hodis, Simona Al-Smadi, Yahia M. Tran, Justin S. Marsden, Alison L. Vaippummadhom, Sreeja Einstein, G. Albert Brown, Alistair G. Debus, Kristian Niizuma, Kuniyasu Rashad, Sherif Sugiyama, Shin-ichiro Owais Khan, M. Updegrove, Adam R. Shadden, Shawn C. Cornelissen, Bart M. W. Majoie, Charles B. L. M. Berg, Philipp Saalfield, Sylvia Kono, Kenichi Steinman, David A. |
| author |
Valen-Sendstad, Kristian |
| author_facet |
Valen-Sendstad, Kristian Bergersen, Aslak W. Shimogonya, Yuji Goubergrits, Leonid Bruening, Jan Pallares, Jordi Cito, Salvatore Piskin, Senol Pekkan, Kerem Geers, Arjan J. Larrabide, Ignacio Rapaka, Saikiran Mihalef, Viorel Fu, Wenyu Qiao, Aike Jain, Kartik Roller, Sabine Mardal, Kent-Andre Kamakoti, Ramji Spirka, Thomas Ashton, Neil Revell, Alistair Aristokleous, Nicolas Houston, J. Graeme Tsuji, Masanori Ishida, Fujimaro Menon, Prahlad G. Browne, Leonard D. Broderick, Stephen Shojima, Masaaki Koizumi, Satoshi Barbour, Michael Aliseda, Alberto Morales, Hernán G. Lefèvre, Thierry Hodis, Simona Al-Smadi, Yahia M. Tran, Justin S. Marsden, Alison L. Vaippummadhom, Sreeja Einstein, G. Albert Brown, Alistair G. Debus, Kristian Niizuma, Kuniyasu Rashad, Sherif Sugiyama, Shin-ichiro Owais Khan, M. Updegrove, Adam R. Shadden, Shawn C. Cornelissen, Bart M. W. Majoie, Charles B. L. M. Berg, Philipp Saalfield, Sylvia Kono, Kenichi Steinman, David A. |
| author_role |
author |
| author2 |
Bergersen, Aslak W. Shimogonya, Yuji Goubergrits, Leonid Bruening, Jan Pallares, Jordi Cito, Salvatore Piskin, Senol Pekkan, Kerem Geers, Arjan J. Larrabide, Ignacio Rapaka, Saikiran Mihalef, Viorel Fu, Wenyu Qiao, Aike Jain, Kartik Roller, Sabine Mardal, Kent-Andre Kamakoti, Ramji Spirka, Thomas Ashton, Neil Revell, Alistair Aristokleous, Nicolas Houston, J. Graeme Tsuji, Masanori Ishida, Fujimaro Menon, Prahlad G. Browne, Leonard D. Broderick, Stephen Shojima, Masaaki Koizumi, Satoshi Barbour, Michael Aliseda, Alberto Morales, Hernán G. Lefèvre, Thierry Hodis, Simona Al-Smadi, Yahia M. Tran, Justin S. Marsden, Alison L. Vaippummadhom, Sreeja Einstein, G. Albert Brown, Alistair G. Debus, Kristian Niizuma, Kuniyasu Rashad, Sherif Sugiyama, Shin-ichiro Owais Khan, M. Updegrove, Adam R. Shadden, Shawn C. Cornelissen, Bart M. W. Majoie, Charles B. L. M. Berg, Philipp Saalfield, Sylvia Kono, Kenichi Steinman, David A. |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
INTRACRANIAL ANEURYSM PATIENT-SPECIFIC MODELLING WALL SHEAR STRESS RUPTURE RISK UNCERTAINTY QUANTIFICATION |
| topic |
INTRACRANIAL ANEURYSM PATIENT-SPECIFIC MODELLING WALL SHEAR STRESS RUPTURE RISK UNCERTAINTY QUANTIFICATION |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
| dc.description.none.fl_txt_mv |
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. Fil: Valen-Sendstad, Kristian. Simula Research Laboratory and Center for Cardiological Innovation; Noruega Fil: Bergersen, Aslak W.. University of Oslo; Noruega Fil: Shimogonya, Yuji. Nihon University; Japón Fil: Goubergrits, Leonid. Charite´ – Universita¨tsmedizin Berlin; Alemania Fil: Bruening, Jan. Charité – Universitätsmedizin Berlin; Alemania Fil: Pallares, Jordi. Universitat Rovira I Virgili; España Fil: Cito, Salvatore. Universitat Rovira I Virgili; España Fil: Piskin, Senol. University Of Texas At San Antonio.; Estados Unidos Fil: Pekkan, Kerem. Koc University; Turquía Fil: Geers, Arjan J.. Universitat Pompeu Fabra; España Fil: Larrabide, Ignacio. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Rapaka, Saikiran. Siemens Medical Solutions USA Inc; Estados Unidos Fil: Mihalef, Viorel. Siemens Medical Solutions USA Inc; Estados Unidos Fil: Fu, Wenyu. Beijing Union University; China Fil: Qiao, Aike. Beijing University of Technology; China Fil: Jain, Kartik. Simula Research Laboratory and Center for Cardiological Innovation; Noruega. University of Siegen; Alemania. University of Zürich; Suiza Fil: Roller, Sabine. University of Siegen; Alemania Fil: Mardal, Kent-Andre. Simula Research Laboratory and Center for Cardiological Innovation; Noruega. University of Oslo; Noruega Fil: Kamakoti, Ramji. Dassault Systemes; Francia Fil: Spirka, Thomas. Simpleware Software Solutions; Reino Unido Fil: Ashton, Neil. University of Oxford; Reino Unido Fil: Revell, Alistair. University of Manchester; Reino Unido Fil: Aristokleous, Nicolas. University of Limerick; Irlanda Fil: Houston, J. Graeme. University of Dundee; Reino Unido Fil: Tsuji, Masanori. Mie Chuo Medical Center; Japón Fil: Ishida, Fujimaro. Mie Chuo Medical Center; Japón Fil: Menon, Prahlad G.. University of Pittsburgh; Estados Unidos Fil: Browne, Leonard D.. University of Limerick; Irlanda Fil: Broderick, Stephen. University of Limerick; Irlanda Fil: Shojima, Masaaki. University of Tokyo; Japón Fil: Koizumi, Satoshi. University of Tokyo; Japón Fil: Barbour, Michael. University of Washington; Estados Unidos Fil: Aliseda, Alberto. University of Washington; Estados Unidos Fil: Morales, Hernán G.. Medisys - Philips Research Paris; Francia Fil: Lefèvre, Thierry. Medisys - Philips Research Paris; Francia Fil: Hodis, Simona. Texas A&M University - Kingsville; Estados Unidos Fil: Al-Smadi, Yahia M.. Jordan University of Science and Technology; Jordania Fil: Tran, Justin S.. Stanford University; Estados Unidos Fil: Marsden, Alison L.. Stanford University; Estados Unidos Fil: Vaippummadhom, Sreeja. EinNel Technlogies; India Fil: Einstein, G. Albert. EinNel Technlogies; India Fil: Brown, Alistair G.. Siemens PLM Software; Estados Unidos Fil: Debus, Kristian. Siemens PLM Software; Estados Unidos Fil: Niizuma, Kuniyasu. Tohoku University; Japón Fil: Rashad, Sherif. Tohoku University; Japón Fil: Sugiyama, Shin-ichiro. Kohnan Hospital; Japón Fil: Owais Khan, M.. University of Toronto; Canadá Fil: Updegrove, Adam R.. University of California at Berkeley; Estados Unidos Fil: Shadden, Shawn C.. University of California at Berkeley; Estados Unidos Fil: Cornelissen, Bart M. W.. Academic Medical Center; Países Bajos Fil: Majoie, Charles B. L. M.. Academic Medical Center; Países Bajos Fil: Berg, Philipp. University of Magdeburg; Alemania Fil: Saalfield, Sylvia. University of Magdeburg; Alemania Fil: Kono, Kenichi. Wakayama Rosai Hospital; Japón Fil: Steinman, David A.. University of Toronto; Canadá |
| description |
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. |
| publishDate |
2018 |
| dc.date.none.fl_str_mv |
2018-09 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/112699 Valen-Sendstad, Kristian; Bergersen, Aslak W.; Shimogonya, Yuji; Goubergrits, Leonid; Bruening, Jan; et al.; Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge; Springer; Cardiovascular Engineering and Technology; -; 9; 9-2018; 544-564 1869-408X CONICET Digital CONICET |
| url |
http://hdl.handle.net/11336/112699 |
| identifier_str_mv |
Valen-Sendstad, Kristian; Bergersen, Aslak W.; Shimogonya, Yuji; Goubergrits, Leonid; Bruening, Jan; et al.; Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge; Springer; Cardiovascular Engineering and Technology; -; 9; 9-2018; 544-564 1869-408X CONICET Digital CONICET |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://link.springer.com/10.1007/s13239-018-00374-2 info:eu-repo/semantics/altIdentifier/doi/10.1007/s13239-018-00374-2 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/2.5/ar/ |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
https://creativecommons.org/licenses/by/2.5/ar/ |
| dc.format.none.fl_str_mv |
application/pdf application/pdf |
| dc.publisher.none.fl_str_mv |
Springer |
| publisher.none.fl_str_mv |
Springer |
| dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
| reponame_str |
CONICET Digital (CONICET) |
| collection |
CONICET Digital (CONICET) |
| instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
| repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
| repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
| _version_ |
1844614508325109760 |
| score |
13.070432 |