K Valen-Sendstad1, D A Steinman. 1. From the Biomedical Simulation Lab (K.V.-S., D.A.S.), Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada.
Abstract
BACKGROUND AND PURPOSE: Computational fluid dynamics has become a popular tool for studying intracranial aneurysm hemodynamics, demonstrating success for retrospectively discriminating rupture status; however, recent highly refined simulations suggest potential deficiencies in solution strategies normally used in the aneurysm computational fluid dynamics literature. The purpose of the present study was to determine the impact of this gap. MATERIALS AND METHODS: Pulsatile flow in 12 realistic MCA aneurysms was simulated by using both high-resolution and normal-resolution strategies. Velocity fields were compared at selected instants via domain-averaged error. We also compared wall shear stress fields and various reduced hemodynamic indices: cycle-averaged mean and maximum wall shear stress, oscillatory shear index, low shear area, viscous dissipation ratio, and kinetic energy ratio. RESULTS: Instantaneous differences in flow and wall shear stress patterns were appreciable, especially for bifurcation aneurysms. Linear regressions revealed strong correlations (R(2) > 0.9) between high-resolution and normal-resolution solutions for all indices except kinetic energy ratio (R(2) = 0.25) and oscillatory shear index (R(2) = 0.23); however, for most indices, the slopes were significantly <1, reflecting a pronounced underestimation by the normal-resolution simulations. Some high-resolution simulations were highly unstable, with fluctuating wall shear stresses reflected by the poor oscillatory shear index correlation. CONCLUSIONS: Typical computational fluid dynamics solution strategies may ultimately be adequate for augmenting rupture risk assessment on the basis of certain highly reduced indices; however, they cannot be relied on for predicting the magnitude and character of the complex biomechanical stimuli to which the aneurysm wall may be exposed. This impact of the computational fluid dynamics solution strategy is likely greater than that for other modeling assumptions or uncertainties.
BACKGROUND AND PURPOSE: Computational fluid dynamics has become a popular tool for studying intracranial aneurysm hemodynamics, demonstrating success for retrospectively discriminating rupture status; however, recent highly refined simulations suggest potential deficiencies in solution strategies normally used in the aneurysm computational fluid dynamics literature. The purpose of the present study was to determine the impact of this gap. MATERIALS AND METHODS: Pulsatile flow in 12 realistic MCA aneurysms was simulated by using both high-resolution and normal-resolution strategies. Velocity fields were compared at selected instants via domain-averaged error. We also compared wall shear stress fields and various reduced hemodynamic indices: cycle-averaged mean and maximum wall shear stress, oscillatory shear index, low shear area, viscous dissipation ratio, and kinetic energy ratio. RESULTS: Instantaneous differences in flow and wall shear stress patterns were appreciable, especially for bifurcation aneurysms. Linear regressions revealed strong correlations (R(2) > 0.9) between high-resolution and normal-resolution solutions for all indices except kinetic energy ratio (R(2) = 0.25) and oscillatory shear index (R(2) = 0.23); however, for most indices, the slopes were significantly <1, reflecting a pronounced underestimation by the normal-resolution simulations. Some high-resolution simulations were highly unstable, with fluctuating wall shear stresses reflected by the poor oscillatory shear index correlation. CONCLUSIONS: Typical computational fluid dynamics solution strategies may ultimately be adequate for augmenting rupture risk assessment on the basis of certain highly reduced indices; however, they cannot be relied on for predicting the magnitude and character of the complex biomechanical stimuli to which the aneurysm wall may be exposed. This impact of the computational fluid dynamics solution strategy is likely greater than that for other modeling assumptions or uncertainties.
Authors: David A Steinman; Yiemeng Hoi; Paul Fahy; Liam Morris; Michael T Walsh; Nicolas Aristokleous; Andreas S Anayiotos; Yannis Papaharilaou; Amirhossein Arzani; Shawn C Shadden; Philipp Berg; Gábor Janiga; Joris Bols; Patrick Segers; Neil W Bressloff; Merih Cibis; Frank H Gijsen; Salvatore Cito; Jordi Pallarés; Leonard D Browne; Jennifer A Costelloe; Adrian G Lynch; Joris Degroote; Jan Vierendeels; Wenyu Fu; Aike Qiao; Simona Hodis; David F Kallmes; Hardeep Kalsi; Quan Long; Vitaly O Kheyfets; Ender A Finol; Kenichi Kono; Adel M Malek; Alexandra Lauric; Prahlad G Menon; Kerem Pekkan; Mahdi Esmaily Moghadam; Alison L Marsden; Marie Oshima; Kengo Katagiri; Véronique Peiffer; Yumnah Mohamied; Spencer J Sherwin; Jens Schaller; Leonid Goubergrits; Gabriel Usera; Mariana Mendina; Kristian Valen-Sendstad; Damiaan F Habets; Jianping Xiang; Hui Meng; Yue Yu; George E Karniadakis; Nicholas Shaffer; Francis Loth Journal: J Biomech Eng Date: 2013-02 Impact factor: 2.097
Authors: Mohammadreza Khani; Lucas R Sass; Tao Xing; M Keith Sharp; Olivier Balédent; Bryn A Martin Journal: J Biomech Eng Date: 2018-08-01 Impact factor: 2.097
Authors: M J Gounis; I M J van der Bom; A K Wakhloo; S Zheng; J-Y Chueh; A L Kühn; A A Bogdanov Journal: AJNR Am J Neuroradiol Date: 2014-10-01 Impact factor: 3.825
Authors: Philipp Berg; Samuel Voß; Gábor Janiga; Sylvia Saalfeld; Aslak W Bergersen; Kristian Valen-Sendstad; Jan Bruening; Leonid Goubergrits; Andreas Spuler; Tin Lok Chiu; Anderson Chun On Tsang; Gabriele Copelli; Benjamin Csippa; György Paál; Gábor Závodszky; Felicitas J Detmer; Bong J Chung; Juan R Cebral; Soichiro Fujimura; Hiroyuki Takao; Christof Karmonik; Saba Elias; Nicole M Cancelliere; Mehdi Najafi; David A Steinman; Vitor M Pereira; Senol Piskin; Ender A Finol; Mariya Pravdivtseva; Prasanth Velvaluri; Hamidreza Rajabzadeh-Oghaz; Nikhil Paliwal; Hui Meng; Santhosh Seshadhri; Sreenivas Venguru; Masaaki Shojima; Sergey Sindeev; Sergey Frolov; Yi Qian; Yu-An Wu; Kent D Carlson; David F Kallmes; Dan Dragomir-Daescu; Oliver Beuing Journal: Int J Comput Assist Radiol Surg Date: 2019-05-03 Impact factor: 2.924