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.
Wall shear stress (WSS) is a relevant hemodynamic indicator of the local stress applied on the endothelium surface. More specifically, its spatiotemporal distribution reveals crucial in the evolution of many pathologies such as aneurysm, stenosis, and atherosclerosis. This paper introduces a new solution, called PaLMA, to quantify the WSS from 4D Flow MRI data. It relies on a twostep local parametric model, to accurately describe the vessel wall and the velocity-vector field in the neighborhood of a given point of interest. Extensive validations have been performed on synthetic 4D Flow MRI data, including four datasets generated from patient specific computational fluid dynamics simulations on carotids. The validation tests are focused on the robustness with respect to noise and on the impact of the resolution level in the context of complex flow patterns. The WSS quantification performance reached by PaLMA is significantly higher than the reference one obtained using the smoothing B-spline method proposed by Potters et al. (2015) method, while the computation time is equivalent for both WSS quantification methods.
4D flow MRI is a promising tool in cardiovascular imaging. However, its lack of resolution can degrade some biomarkers' evaluation accuracy. The computational fluid dynamics (CFD) simulation is considered as the reference method to improve numerically the image resolution. However, CFD simulations are complex and time consuming, and matching their results with 4D Flow MRI data is very challenging. This paper aims to introduce a fast and efficient super-resolution (SR) approach thanks to the minimization of a L 2 -penalized criterion, which combines a weighted least-squares data fidelity term and Navier-Stokes equations. The algorithm has been validated on synthetic and phantom datasets and compared to state-of-the-art solutions. Moreover, a prospective study is conducted on the segmentationfree application of the proposed algorithm.
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