Towards quantitative evaluation of wall shear stress from 4D flow imaging

Abstract

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.

Navier-Stokes-Based Regularization for 4d Flow MRI Super-Resolution

“…Therefore, accurate quantification of biomarkers from such data becomes challenging. Indeed, the lack of resolution has a direct impact on the computation of spatial derivatives which are involved in the evaluation of biomarkers such as the wall shear stress [3,4]. Besides, this lack of resolution can have an additional effect through a coarse wall definition.…”

Accelerated sequences of 4D flow MRI using GRAPPA and compressed sensing: A comparison against conventional MRI and computational fluid dynamics

“…Additionally, significant underestimations of WSS are generally observed, partly because of partial volume effects and low spatiotemporal resolution 16 . Given the growing interests for evaluating the WSS clinically, substantial efforts are being undertaken to propose sophisticated reconstruction methods 5,17,18 . However, whereas little attention is generally paid to assess the quality of the input velocity measurements, it is a prerequisite step to properly reconstruct the WSS.…”

Segmentation-Free Super-Resolved 4D flow MRI Reconstruction Exploiting Navier-Stokes Equations and Spatial Regularization

“…Unfortunately, the reconstructed image has a limited spatial resolution [1,2] due to the need to make a trade-off between the signal-to-noise ratio and the acquisition time. Therefore, interpretation along with biomarkers' quantification turn into a complex problem as demonstrated for the wall shear stress [3,4]. Indeed, low resolution acquisitions imply a coarse estimation of spatial This work has been funded by Philips company through the GIE grant.…”