Login / Signup

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

Kristian Valen-SendstadAslak W BergersenYuji ShimogonyaLeonid GoubergritsJan BrueningJordi PallaresSalvatore CitoSenol PiskinKerem PekkanArjan J GeersIgnacio LarrabideSaikiran RapakaViorel MihalefWenyu FuAike QiaoKartik JainSabine RollerKent-Andre MardalRamji KamakotiThomas SpirkaNeil AshtonAlistair RevellNicolas AristokleousJ Graeme HoustonMasanori TsujiFujimaro IshidaPrahlad G MenonLeonard D BrowneStephen BroderickMasaaki ShojimaSatoshi KoizumiMichael BarbourAlberto AlisedaHernán G MoralesThierry LefèvreSimona HodisYahia M Al-SmadiJustin S TranAlison L MarsdenSreeja VaippummadhomG Albert EinsteinAlistair G BrownKristian DebusKuniyasu NiizumaSherif RashadShin-Ichiro SugiyamaM Owais KhanAdam R UpdegroveShawn C ShaddenBart M W CornelissenCharles B L M MajoiePhilipp BergSylvia SaalfieldKenichi KonoDavid A Steinman
Published in: Cardiovascular engineering and technology (2018)
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.
Keyphrases
  • coronary artery
  • deep learning
  • abdominal aortic aneurysm
  • optic nerve
  • emergency department
  • adverse drug
  • machine learning
  • optical coherence tomography
  • electronic health record