Institute for Biomedical Engineering, ETH Zurich and University of Zurich, 8092 Zurich, Switzerland.
Institute for Biomedical Engineering, ETH Zurich and University of Zurich, 8092 Zurich, Switzerland; Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, 8032 Zurich, Switzerland.
Neuroimage. 2017 Jul 1;154:92-105. doi: 10.1016/j.neuroimage.2017.01.014. Epub 2017 Jan 9.
This work investigates the role of magnetic field fluctuations as a confound in fMRI. In standard fMRI experiments with single-shot EPI acquisition at 3 Tesla the uniform and gradient components of the magnetic field were recorded with NMR field sensors. By principal component analysis it is found that differences of field evolution between the EPI readouts are explainable by few components relating to slow and within-shot field dynamics of hardware and physiological origin. The impact of fluctuating field components is studied by selective data correction and assessment of its influence on image fluctuation and SFNR. Physiological field fluctuations, attributed to breathing, were found to be small relative to those of hardware origin. The dominant confounds were hardware-related and attributable to magnet drift and thermal changes. In raw image time series, field fluctuation caused significant SFNR loss, reflected by a 67% gain upon correction. Large part of this correction can be accomplished by traditional image realignment, which addresses slow and spatially uniform field changes. With realignment, explicit field correction increased the SFNR on the order of 6%. In conclusion, field fluctuations are a relevant confound in fMRI and can be addressed effectively by retrospective data correction. Based on the physics involved it is anticipated that the advantage of full field correction increases with field strength, with non-Cartesian readouts, and upon phase-sensitive BOLD analysis.
这项工作研究了磁场波动作为 fMRI 中的混杂因素的作用。在 3T 磁共振扫描仪上进行单次激发 EPI 采集的标准 fMRI 实验中，使用 NMR 磁场传感器记录了磁场的均匀和梯度分量。通过主成分分析发现，EPI 读出之间的磁场演化差异可以用少数几个与硬件和生理起源的慢场和单次场动力学相关的分量来解释。通过选择性数据校正研究了波动磁场分量的影响，并评估了其对图像波动和 SFNR 的影响。归因于呼吸的生理磁场波动相对于硬件起源的波动较小。主要混杂因素是与硬件相关的，归因于磁体漂移和热变化。在原始图像时间序列中，磁场波动导致 SFNR 显著损失，校正后增益为 67%。这种校正的大部分可以通过传统的图像配准来完成，图像配准可以解决慢场和空间均匀的场变化。通过配准，明确的场校正增加了 SFNR 的幅度约为 6%。总之，磁场波动是 fMRI 中的一个相关混杂因素，可以通过回顾性数据校正有效地解决。基于所涉及的物理原理，可以预期全磁场校正的优势随着场强的增加、非笛卡尔读出以及相位敏感的 BOLD 分析而增加。
