Abstract
Wall Shear Stress (WSS) has been demonstrated to be a biomarker of the development of atherosclerosis. In vivo assessment of WSS is still challenging, but 4D Flow MRI represents a promising tool to provide 3D velocity data from which WSS can be calculated. In this study, a system based on Laser Doppler Velocimetry (LDV) was developed to validate new improvements of 4D Flow MRI acquisitions and derived WSS computing. A hydraulic circuit was manufactured to allow both 4D Flow MRI and LDV velocity measurements. WSS profiles were calculated with one 2D and one 3D method. Results indicated an excellent agreement between MRI and LDV velocity data, and thus the set-up enabled the evaluation of the improved performances of 3D with respect to the 2D-WSS computation method. To provide a concrete example of the efficacy of this method, the influence of the spatial resolution of MRI data on derived 3D-WSS profiles was investigated. This investigation showed that, with acquisition times compatible with standard clinical conditions, a refined MRI resolution does not improve WSS assessment, if the impact of noise is unreduced. This study represents a reliable basis to validate with LDV WSS calculation methods based on 4D Flow MRI.
Highlights
Atherosclerosis represents one of the most prevalent cardiovascular diseases
In Laser Doppler Velocimetry (LDV) campaigns, it is possible to reproduce the same experimental conditions of in vitro Phase-Contrast MRI (PC MRI) acquisitions in terms of geometry, flow rate, pressure, fluid viscosity, and density, providing accurate velocity profiles to serve as a reference for PC MRI data
The methods proposed by Stalder et al.[10] (2D-Wall Shear Stress (WSS)) and Potters et al.[11] (3D-WSS) were employed to assess WSS from PC MRI and LDV data-sets in the same location of the test section, in view to demonstrate the efficacy of this experimental system to validate PC MRI post-processing algorithms for WSS computation
Summary
Atherosclerosis represents one of the most prevalent cardiovascular diseases. It accounts for 21% of deaths worldwide and implies high social c osts[1]. The methods proposed by Stalder et al.[10] (2D-WSS) and Potters et al.[11] (3D-WSS) were employed to assess WSS from PC MRI and LDV data-sets in the same location of the test section, in view to demonstrate the efficacy of this experimental system to validate PC MRI post-processing algorithms for WSS computation.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
