Variability of Computational Fluid Dynamics Solutions for Pressure and Flow in a Giant Aneurysm: The ASME 2012 Summer Bioengineering Conference CFD Challenge

Abstract

Stimulated by a recent controversy regarding pressure drops predicted in a giant aneurysm with a proximal stenosis, the present study sought to assess variability in the prediction of pressures and flow by a wide variety of research groups. In phase I, lumen geometry, flow rates, and fluid properties were specified, leaving each research group to choose their solver, discretization, and solution strategies. Variability was assessed by having each group interpolate their results onto a standardized mesh and centerline. For phase II, a physical model of the geometry was constructed, from which pressure and flow rates were measured. Groups repeated their simulations using a geometry reconstructed from a micro-computed tomography (CT) scan of the physical model with the measured flow rates and fluid properties. Phase I results from 25 groups demonstrated remarkable consistency in the pressure patterns, with the majority predicting peak systolic pressure drops within 8% of each other. Aneurysm sac flow patterns were more variable with only a few groups reporting peak systolic flow instabilities owing to their use of high temporal resolutions. Variability for phase II was comparable, and the median predicted pressure drops were within a few millimeters of mercury of the measured values but only after accounting for submillimeter errors in the reconstruction of the life-sized flow model from micro-CT. In summary, pressure can be predicted with consistency by CFD across a wide range of solvers and solution strategies, but this may not hold true for specific flow patterns or derived quantities. Future challenges are needed and should focus on hemodynamic quantities thought to be of clinical interest.

Mind the Gap: Impact of Computational Fluid Dynamics Solution Strategy on Prediction of Intracranial Aneurysm Hemodynamics and Rupture Status Indicators

“…To minimize the likelihood of overestimating the impact of solution strategy, we consciously chose the highest of the mesh and, separately, temporal resolutions reported by the 3 largest clinical studies to date [2][3][4] ; a cursory inspection of other aneurysm CFD studies recently published in the clinical literature [34][35][36][37][38][39] suggests that the resolutions of our NR simulations are, if anything, on the high side. Nevertheless, as noted by a recent aneurysm CFD Challenge, 20 it is difficult to compare node spacing, element types, and sizes from one study to another; there are simply not enough details provided about the solver parameters and cell distributions to exactly reproduce what other groups are using. Nevertheless, our NR simulations are likely finer than those of most of the above-mentioned studies, particularly because we concentrated our elements in the vicinity of the aneurysm rather than assuming a uniform mesh density throughout the domain.…”

“…2 On the other hand, recent case studies using tens of thousands of time-steps per cardiac cycle and tens of millions of tetrahedral elements (or the equivalent) have reported the presence of highly unstable and possibly turbulent flows, [15][16][17][18] consistent with clinical observations 19 but seemingly at odds with most published aneurysm CFD studies. The impact of the solution strategy was also evident in a recent CFD Challenge, 20 which highlighted, for the same aneurysm case, a wide variety of aneurysm inflow patterns contributed by 25 groups, most using a range of NR strategies. Nevertheless, discrimination of aneurysm rupture status tends to rely on hemodynamic indices that reduce complex velocity and WSS fields to a single number or category via integration over the cardiac cycle and/or aneurysm dome, with the potential for ameliorating differences in velocity and WSS fields predicted by HRversus-NR strategies.…”

A comparison of hemodynamic metrics and intraluminal thrombus burden in a common iliac artery aneurysm

“…With this in mind, we approximated the blood flow as laminar and considered the blood to be an incompressible fluid with a density of 1050 kg/m 3 . The walls of the arteries were characterised by no-slip, rigid wall boundary conditions [5,6,32,35,54,55] and the viscosity was modelled using a non-Newtonian approximation (Carreau-Yasuda, as implemented by Biasetti et al [44]; [56]). By using a non-Newtonian model, as opposed Newtonian, we can capture the macro-scale shear-thinning of the blood, allowing a one-way Lagrangian particle transport model to provide a good prediction of individual blood-cell trajectories within the continuous phase (blood).…”

“…In the past decades, computational fluid dynamics (CFD) has emerged as a powerful and popular tool for the study of blood flow dynamics of aneurysms and other cardiovascular disease [5][6][7][8]. With appropriate boundary conditions and model assumptions, CFD can simulate the blood flow through any vessel of the body using patient-specific geometries, typically derived from computed tomography (CT).…”

Generalized versus Patient-Specific Inflow Boundary Conditions in Computational Fluid Dynamics Simulations of Cerebral Aneurysmal Hemodynamics

“…34 The generalized inflow velocity profile was defined by predetermined Womersley profiles for fully developed pulsatile flow. 35,36 The flow was scaled so that the total generalized inflow equaled the measured inflow rate as determined by PC-MR imaging. Zero pressure boundary conditions were prescribed at all outlets.…”