Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA.
Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA; Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, USA.
Neuroimage. 2020 Aug 1;216:116861. doi: 10.1016/j.neuroimage.2020.116861. Epub 2020 Apr 16.
Over the recent years, significant advances in Spin-Echo (SE) Echo-Planar (EP) Diffusion MRI (dMRI) have enabled improved fiber tracking conspicuity in the human brain. At the same time, pushing the spatial resolution and using higher b-values inherently expose the acquired images to further eddy-current-induced distortion and blurring. Recently developed data-driven correction techniques, capable of significantly mitigating these defects, are included in the reconstruction pipelines developed for the Human Connectome Project (HCP) driven by the NIH BRAIN initiative. In this case, however, corrections are derived from the original diffusion-weighted (DW) magnitude images affected by distortion and blurring. Considering the complexity of k-space deviations in the presence of time varying high spatial order eddy currents, distortion and blurring may not be fully reversed when relying on magnitude DW images only. An alternative approach, consisting of iteratively reconstructing DW images based on the actual magnetic field spatiotemporal evolution measured with a magnetic field monitoring camera, has been successfully implemented at 3T in single band dMRI (Wilm et al., 2017, 2015). In this study, we aim to demonstrate the efficacy of this eddy current correction method in the challenging context of HCP-style multiband (MB = 2) dMRI protocol. The magnetic field evolution was measured during the EP-dMRI readout echo train with a field monitoring camera equipped with 16 F NMR probes. The time variation of 0, 1 and 2 order spherical field harmonics were used to reconstruct DW images. Individual DW images reconstructed with and without field correction were compared. The impact of eddy current correction was evaluated by comparing the corresponding direction-averaged DW images and fractional anisotropy (FA) maps. F field monitoring data confirmed the existence of significant field deviations induced by the diffusion-encoding gradients, with variations depending on diffusion gradient amplitude and direction. In DW images reconstructed with the field correction, residual aliasing artifacts were reduced or eliminated, and when high b-values were applied, better gray/white matter delineation and sharper gyri contours were observed, indicating reduced signal blurring. The improvement in image quality further contributed to sharper contours and better gray/white matter delineation in mean DW images and FA maps. In conclusion, we demonstrate that up-to-2-order-eddy-current-induced field perturbation in multiband, in-plane accelerated HCP-style dMRI acquisition at 7T can be corrected by integrating the measured field evolution in image reconstruction.
近年来,自旋回波(SE)回波平面(EP)扩散磁共振成像(dMRI)的显著进步使得人类大脑中的纤维跟踪变得更加明显。与此同时,提高空间分辨率并使用更高的 b 值会使采集到的图像进一步受到涡流引起的变形和模糊的影响。最近开发的数据驱动校正技术能够显著减轻这些缺陷,这些技术被包括在 NIH BRAIN 倡议推动的人类连接组计划(HCP)的重建管道中。然而,在这种情况下,校正来自于受变形和模糊影响的原始扩散加权(DW)幅度图像。考虑到存在时变高空间阶数涡流时的 k 空间偏差的复杂性,仅依靠 DW 幅度图像可能无法完全反转变形和模糊。一种替代方法,包括基于磁场监测相机测量的实际磁场时空演化,迭代重建 DW 图像,已在 3T 单频带 dMRI 中成功实施(Wilm 等人,2017 年,2015 年)。在这项研究中,我们旨在证明这种涡流校正方法在 HCP 风格的多频带(MB=2)dMRI 协议的挑战性背景下的有效性。在 EP-dMRI 读出回波链期间,使用配备 16 个 F NMR 探头的磁场监测相机测量磁场演变。使用 0、1 和 2 阶球谐磁场谐波来重建 DW 图像。比较了有和没有磁场校正的单个 DW 图像。通过比较相应的方向平均 DW 图像和分数各向异性(FA)图来评估涡流校正的影响。F 场监测数据证实了扩散编码梯度引起的磁场偏差的存在,其变化取决于扩散梯度幅度和方向。在使用磁场校正重建的 DW 图像中,残留的混叠伪影减少或消除,当应用高 b 值时,可以观察到更好的灰白质区分和更清晰的脑回轮廓,表明信号模糊减少。图像质量的提高进一步有助于在平均 DW 图像和 FA 图中更清晰的轮廓和更好的灰白质区分。总之,我们证明了在 7T 时,多频带、平面内加速 HCP 风格的 dMRI 采集中,高达 2 阶的涡流引起的磁场扰动可以通过在图像重建中整合测量的磁场演化来校正。