@article{15111,
  keywords = {Intracranial aneurysm, Patient-specific modeling, Wall shear stress, Rupture risk, Uncertainty quantification},
  author = {Kristian Valen-Sendstad and Aslak Bergersen and Yuji Shimogonya and Leonid Goubergrits and Jan Bruening and Jordi Pallares and Salvatore Cito and Senol Piskin and Kerem Pekkan and Arjan Geers 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 Graeme Houston and Masanori Tsuji and Fujimaro Ishida and Prahlad Menon and Leonard Browne and Stephen Broderick and Masaaki Shojima and Satoshi Koizumi and Michael Barbour and Alberto Aliseda and Hern{\'a}n Morales and Thierry Lef{\`e}vre and Simona Hodis and Yahia Al-Smadi and Justin Tran and Alison Marsden and Sreeja Vaippummadhom and Albert Einstein and Alistair Brown and Kristian Debus and Kuniyasu Niizuma and Sherif Rashad and Shin-ichiro Sugiyama and Owais Khan and Adam Updegrove and Shawn Shadden and Bart Cornelissen and Charles Majoie and Philipp Ber and Sylvia Saalfield and Kenichi Kono and David Steinmam},
  title = {Real-World Variability in the Prediction of Intracranial Aneurysm Wall Shear Stress: The 2015 International Aneurysm CFD Challenge},
  abstract = {PurposeImage-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.Methods3D 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.ResultsA 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.ConclusionsWide 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.},
  year = {2018},
  journal = {Cardiovascular Engineering and Technology},
  volume = {9},
  pages = {544{\textendash}564},
  month = {10/2018},
  publisher = {Springer},
  address = {US},
  issn = {1869-408X},
  url = {https://goo.gl/mG9u9t},
  doi = {10.1007/s13239-018-00374-2},
}