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

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...

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Published in:Magnetic resonance in medicine 2022-05, Vol.87 (5), p.2495-2511
Main Authors: Roberts, Grant S., Loecher, Michael W., Spahic, Alma, Johnson, Kevin M., Turski, Patrick A., Eisenmenger, Laura B., Wieben, Oliver
Format: Article
Language:English
Subjects:
4D flow MRI
angiography
Blood
blood flow tracking
Blood Flow Velocity
Constraints
Displacement
displacement correction
Humans
Imaging, Three-Dimensional - methods
intracranial
Magnetic Resonance Angiography - methods
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Pathology
probabilistic streamlines
Probability theory
Spin dynamics
Spin labeling
Spin Labels
Stochasticity
Tracking
Variance analysis
Velocity
Velocity distribution
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Summary: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. Conclusion Virtual injections with improved streamlines from 4D‐flow MRI allow for flexible, robust, intracranial flow tracking.
ISSN:0740-3194
1522-2594
DOI:10.1002/mrm.29134