Attenuation of motion artifacts in fMRI using discrete reconstruction of irregular fMRI trajectories (DRIFT).
Attenuation of motion artifacts in fMRI using discrete reconstruction of irregular fMRI trajectories (DRIFT).
复制标题
使用不规则 fMRI 轨迹离散重建 (DRIFT) 来衰减 fMRI 中的运动伪影。
DOI：
10.1002/mrm.28723
复制
发表时间：
2021
影响因子：
3.3
通讯作者：
Razlighi,QolamrezaR
中科院分区：
文献类型：
--
作者：
Parker,DavidB;Spincemaille,Pascal;Razlighi,QolamrezaR
目的大量研究报告运动是功能磁共振成像中最有害的噪声和伪影来源。现有的运动校正方法不能完全解决运动问题。回溯性技术，如空间对齐，可以纠正体积间的错位，但不能解决体积污染和自旋历史伪影。预期运动校正可以防止自旋历史伪影，但目前还不能足够快地更新梯度以消除k空间填充伪影，这就需要一种混合方法来完全解决这些问题。理论和方法运动可以数学地表示为MR信号方程，以描述k空间中运动伪影的原点。从这些方程可以看出，不同的运动对信号有不同的影响。从这些方程出发，设计了一种新的运动校正算法，以直接在k空间中消除运动诱导的伪影，离散重建不规则的fMRI轨迹(漂移)。结果表明，虽然一些运动类型对MR信号的影响可以忽略不计，但其他运动类型即使在运动停止后也会产生灾难性和持久的伪影。在模拟中，漂移能够在没有旋转历史的情况下消除运动伪影。在体模扫描中，漂移会显著减弱fMRI数据中的运动伪影。结论无论是前瞻性运动校正方法还是回溯性运动校正方法都不能完全消除fMRI数据中的运动伪影。然而，漂移作为一种回溯性技术，当与预期运动校正相结合时，可以消除相当大一部分运动伪影。
PurposeNumerous studies report motion as the most detrimental source of noise and artifacts in fMRI. Current motion correction methods fail to completely address the motion problem. Retrospective techniques such as spatial realignment can correct for between‐volume misalignment but fail to address within volume contamination and spin‐history artifacts. Prospective motion correction can prevent spin‐history artifacts but currently cannot update the gradients fast enough to remove k‐space filling artifacts, calling for a hybrid approach to fully address these problems.Theory and methodsMotion can be mathematically formulated into the MR signal equation to describe the motion artifacts at their origin in k‐space. From these equations, it is demonstrated that different motions have different effects on the signal. A novel motion correction algorithm is designed from these equations to remove motion‐induced artifacts directly in k‐space, discrete reconstruction of irregular fMRI trajectory (DRIFT). This method is evaluated rigorously using fMRI simulations and data from a rotating phantom inside the scanner.ResultsThe results indicate that although some motion types have negligible effects on the MR signal, others produce catastrophic and lasting artifacts even after motion cessation. In simulation, DRIFT is able to remove motion artifacts in the absence of spin history. In a phantom scan, DRIFT significantly attenuates the motion artifacts in the fMRI data.ConclusionNeither prospective nor retrospective motion correction methods could completely remove the motion artifacts from the fMRI data. However, DRIFT, as a retrospective technique, when combined with prospective motion correction, can eliminate a significant portion of motion artifacts.