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基于线性时不变梯度模型的螺旋 fMRI 的可行性。

Feasibility of spiral fMRI based on an LTI gradient model.

机构信息

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom; Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.

Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland; Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.

出版信息

Neuroimage. 2021 Dec 15;245:118674. doi: 10.1016/j.neuroimage.2021.118674. Epub 2021 Oct 27.

Abstract

Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B inhomogeneity are more difficult to correct compared to EPI. Effective correction requires accurate knowledge of the traversed k-space trajectory. With the goal of making spiral fMRI more accessible, we have evaluated image reconstruction using trajectories predicted by the gradient impulse response function (GIRF), which can be determined in a one-time calibration step. GIRF-predicted reconstruction was tested for high-resolution (0.8 mm) fMRI at 7T. Image quality and functional results of the reconstructions using GIRF-prediction were compared to reconstructions using the nominal trajectory and concurrent field monitoring. The reconstructions using nominal spiral trajectories contain substantial artifacts and the activation maps contain misplaced activation. Image artifacts are substantially reduced when using the GIRF-predicted reconstruction, and the activation maps for the GIRF-predicted and monitored reconstructions largely overlap. The GIRF reconstruction provides a large increase in the spatial specificity of the activation compared to the nominal reconstruction. The GIRF-reconstruction generates image quality and fMRI results similar to using a concurrently monitored trajectory. The presented approach does not prolong or complicate the fMRI acquisition. Using GIRF-predicted trajectories has the potential to enable high-quality spiral fMRI in situations where concurrent trajectory monitoring is not available.

摘要

螺旋成像非常适合功能磁共振成像,但由于梯度不完美和 B 不均匀引起的伪影比 EPI 更难纠正,因此其应用受到限制。有效的校正需要准确了解所经过的 k 空间轨迹。为了使螺旋 fMRI 更易于使用,我们评估了使用梯度脉冲响应函数 (GIRF) 预测轨迹进行图像重建的效果,该方法可以在一次性校准步骤中确定。在 7T 下对高分辨率(0.8mm) fMRI 进行了 GIRF 预测重建的测试。将使用 GIRF 预测的重建与使用标称轨迹和同时场监测的重建的图像质量和功能结果进行了比较。使用标称螺旋轨迹的重建包含大量伪影,并且激活图包含错位激活。使用 GIRF 预测重建可以大大减少图像伪影,并且 GIRF 预测和监测重建的激活图大部分重叠。与标称重建相比,GIRF 重建大大提高了激活的空间特异性。GIRF 重建生成的图像质量和 fMRI 结果与使用同时监测的轨迹相似。所提出的方法不会延长或复杂化 fMRI 采集。在无法进行同时轨迹监测的情况下,使用 GIRF 预测的轨迹有可能实现高质量的螺旋 fMRI。

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