Virtual injections using 4D flow MRI with displacement corrections and constrained probabilistic streamlines

Abstract

Purpose: Streamlines from 4D-flow MRI have been used clinically for intracranial blood-flow tracking. However, deterministic and stochastic errors degrade streamline quality. The purpose of this study is to integrate displacement corrections, probabilistic streamlines, and novel fluid constraints to improve selective blood-flow tracking and emulate "virtual bolus injections." Methods: Both displacement artifacts (deterministic) and velocity noise (stochastic) inherently occur during phase-contrast MRI acquisitions. Here, two displacement correction methods, single-step and iterative, were tested in silico with simulated displacements and were compared with ground-truth velocity fields.Next, the effects of combining displacement corrections and constrained probabilistic streamlines were performed in 10 healthy volunteers using time-averaged 4D-flow data. Measures of streamline length and depth into vasculature were then compared with streamlines generated with no corrections and displacement correction alone using one-way repeated-measures analysis of variance and Friedman's tests. Finally, virtual injections with improved streamlines were generated for three intracranial pathology cases. Results:Iterative displacement correction outperformed the single-step method in silico. In volunteers, the combination of displacement corrections and constrained probabilistic streamlines allowed for significant improvements in streamline length and increased the number of streamlines entering the circle of Willis relative to streamlines with no corrections and displacement correction alone. In the pathology cases, virtual injections with improved streamlines were qualitatively similar to dynamic arterial spin labeling images and allowed for forward/ reverse selective flow tracking to characterize cerebrovascular malformations.

Toward accurate and fast velocity quantification with 3D ultrashort TE phase‐contrast imaging

“…These artifacts have already been reported in the early development stages of PC MRI 22,23 but have received limited attention since the introduction of 4D flow MRI. However, they become of concern if spatial accuracy is of importance, for example, when (1) comparing MRI velocity fields with other spatially resolved measures such as particle image velocimetry, 17,18 (2) merging data sets such as computational fluid dynamics and PC MRI for improved velocity fields data 25 or segmentations obtained from MR angiography or cardiac anatomy datasets with PC MRI for improved vessel boundary detections, 26 or (3) calculating streamlines along torturous vessel paths 27 . In addition, spatially sensitive measures such as WSS have been shown to be affected 28 …”