Flow-based method demonstrates improved accuracy for calculating wall shear stress in arterial flows from 4D flow MRI data. (January 2023)

• Record Type: Journal Article
• Authors: Hurd, Elliott R.; Iffrig, Elizabeth; Jiang, David; Oshinski, John N.; Timmins, Lucas H.
• Is Part Of: Journal of biomechanics. Volume 146(2023)
• Publication Date: 2023-01
• Subjects: Biomechanics -- Cardiac MRI -- Fluid–structure interaction -- Hemodynamics -- Phase-contrast magnetic resonance imaging; Animal mechanics -- Periodicals; Biomechanics -- Periodicals; Biomechanics -- Periodicals; Mécanique animale -- Périodiques; Biomécanique -- Périodiques; Electronic journals; 571.4305
• DOI: 10.1016/j.jbiomech.2022.111413
• Languages: English
• ISSNs: 0021-9290

Abstract

Abstract: Four-dimensional flow magnetic resonance imaging (i.e., 4D flow MRI) has become a valuable tool for the in vivo assessment of blood flow within large vessels and cardiac chambers. As wall shear stress (WSS) has been correlated with the development and progression of cardiovascular disease, focus has been directed at developing techniques to quantify WSS directly from 4D flow MRI data. The goal of this study was to compare the accuracy of two such techniques – termed the velocity and flow-based methods – in the setting of simplified and complex flow scenarios. Synthetic MR data were created from exact solutions to the Navier-Stokes equations for the steady and pulsatile flow of an incompressible, Newtonian fluid through a rigid cylinder. In addition, synthetic MR data were created from the predicted velocity fields derived from a fluid–structure interaction (FSI) model of pulsatile flow through a thick-walled, multi-layered model of the carotid bifurcation. Compared to the analytical solutions for steady and pulsatile flow, the flow-based method demonstrated greater accuracy than the velocity-based method in calculating WSS across all changes in fluid velocity/flow rate, tube radius, and image signal-to-noise ( p < 0.001). Furthermore, the velocity-based method was more sensitive to boundary segmentation than the flow-based method. When compared to results from the FSI model, the flow-based method demonstrated greater accuracy than the velocity-based method with average differences in time-averaged WSS of 0.31 ± 1.03 Pa and 0.45 ± 1.03 Pa, respectively ( p <0.005). These results have implications on the utility, accuracy, and clinical translational of methods to determine WSS from 4D flow MRI.