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Simulation-based imaging (SBI) is a blood flow imaging technique thatoptimally fits a computational fluid dynamics (CFD) simulation tolow-resolution, noisy magnetic resonance (MR) flow data to produce ahigh-resolution velocity field. In this work, we study the effectivity of SBIin predicting wall shear stress (WSS) relative to standard magnetic resonanceimaging (MRI) postprocessing techniques using two synthetic numericalexperiments: flow through an idealized, two-dimensional stenotic vessel and amodel of an adult aorta. In particular, we study the sensitivity of these twoapproaches with respect to the Reynolds number of the underlying flow, theresolution of the MRI data, and the noise in the MRI data. We found that theSBI WSS reconstruction: 1) is insensitive to Reynolds number over the rangeconsidered (Re $\leq$ 1000), 2) improves as the amount of MRI data increasesand provides accurate reconstructions with as little as three MRI voxels perdiameter, and 3) degrades linearly as the noise in the data increases with aslope determined by the resolution of the MRI data. We also consider thesensitivity of SBI to the resolution of the CFD mesh and found there isflexibility in the mesh used for SBI, although the WSS reconstruction becomesmore sensitive to other parameters, particularly the resolution of the MRIdata, for coarser meshes. This indicates a fundamental trade-off between scantime (i.e., MRI data quality and resolution) and reconstruction time using SBI,which is inherently different than the trade-off between scan time andreconstruction quality observed in standard MRI postprocessing techniques.

Accurate quantification of blood flow wall shear stress using simulation-based imaging: a synthetic, comparative study