使用带位移校正和约束概率流线的 4D 流 MRI 进行虚拟注射。
Virtual injections using 4D flow MRI with displacement corrections and constrained probabilistic streamlines.
机构信息
Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Department of Radiology, Stanford University, Stanford, California, USA.
出版信息
Magn Reson Med. 2022 May;87(5):2495-2511. doi: 10.1002/mrm.29134. Epub 2021 Dec 31.
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.
目的
4D-flow MRI 中的流线已在临床上用于颅内血流追踪。然而，确定性和随机性误差会降低流线质量。本研究的目的是整合位移校正、概率流线和新的流体约束条件，以改善选择性血流追踪并模拟“虚拟团注注射”。
方法
在相位对比 MRI 采集过程中，固有地会出现位移伪影（确定性）和速度噪声（随机性）。在这里，我们在模拟位移中测试了两种位移校正方法（单步和迭代），并将其与真实速度场进行了比较。接下来，我们在 10 名健康志愿者中使用时间平均 4D-flow 数据，对结合位移校正和约束概率流线的效果进行了研究。然后，使用单向重复测量方差分析和 Friedman 检验，将没有校正、只有位移校正和结合校正的三种方法生成的流线的长度和进入血管的深度进行比较。最后，对三个颅内病变病例生成了改进后的流线的虚拟注射。
结果
在模拟中，迭代位移校正优于单步方法。在志愿者中，与没有校正和只有位移校正的流线相比，位移校正和约束概率流线的结合可以显著提高流线的长度，并增加进入 Willis 环的流线数量。在病变病例中，改进后的流线的虚拟注射在定性上类似于动态动脉自旋标记图像，并且允许进行正向/反向选择性血流追踪，以表征脑血管畸形。
结论
从 4D-flow MRI 生成的改进后的流线虚拟注射允许灵活、稳健的颅内血流追踪。
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