@article{janiga_computational_2015,
	title = {The computational fluid dynamics rupture challenge 2013-phase {I}: prediction of rupture status in intracranial aneurysms},
	volume = {36},
	issn = {0195-6108},
	url = {http://dx.doi.org/10.3174/ajnr.A4157},
	doi = {10.3174/ajnr.a4157},
	abstract = {BACKGROUND AND PURPOSE: Rupture risk assessment for intracranial aneurysms remains challenging, and risk factors, including wall shear stress, are discussed controversially. The primary purpose of the presented challenge was to determine how consistently aneurysm rupture status and rupture site could be identified on the basis of computational fluid dynamics. MATERIALS AND METHODS: Two geometrically similar MCA aneurysms were selected, 1 ruptured, 1 unruptured. Participating computational fluid dynamics groups were blinded as to which case was ruptured. Participants were provided with digitally segmented lumen geometries and, for this phase of the challenge, were free to choose their own flow rates, blood rheologies, and so forth. Participants were asked to report which case had ruptured and the likely site of rupture. In parallel, lumen geometries were provided to a group of neurosurgeons for their predictions of rupture status and site. RESULTS: Of 26 participating computational fluid dynamics groups, 21 (81\%) correctly identified the ruptured case. Although the known rupture site was associated with low and oscillatory wall shear stress, most groups identified other sites, some of which also experienced low and oscillatory shear. Of the 43 participating neurosurgeons, 39 (91\%) identified the ruptured case. None correctly identified the rupture site. CONCLUSIONS: Geometric or hemodynamic considerations favor identification of rupture status; however, retrospective identification of the rupture site remains a challenge for both engineers and clinicians. A more precise understanding of the hemodynamic factors involved in aneurysm wall pathology is likely required for computational fluid dynamics to add value to current clinical decision-making regarding rupture risk.},
	number = {3},
	journal = {American Journal of Neuroradiology},
	author = {Janiga, Gabor and Berg, Philipp and Sugiyama, S and Kono, K and Steinman, DA},
	month = mar,
	year = {2015},
	pages = {530--536}
}