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Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking

机译:使用光学跟踪对功能性MRI进行3D回波平面成像数据的前瞻性运动校正

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摘要

We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2 × 2 × 3 factorial design with the following factors: PMC on or off; 3.0 mm or 1.5 mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5 mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p < 0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies.
机译:我们评估了基于光学相机的预期运动校正(PMC)系统在改善3D回波平面成像功能MRI数据质量方面的性能。在fMRI扫描期间,使用光学相机和外部标记器动态跟踪对象的头部运动。通过使用运动信息动态更新序列的RF激励和梯度波形来执行PMC,从而重新调整视场以匹配对象的头部运动。在5名健康志愿者上进行的无任务fMRI实验遵循2×2×3析因设计,并具有以下因素:PMC开启或关闭;各向同性分辨率为3.0毫米或1.5毫米;并且没有,缓慢或快速的头部运动。还以1.5毫米的分辨率对其中一名志愿者进行了视觉和运动功能性MRI实验,比较了PMC开启与PMC开启与否以及头部缓慢移动的情况。制定了度量标准来量化相对于k空间数据采集的运动量。运动量化度量标准将非常丰富的相机跟踪数据折叠为每个图像体积的一个标量值,该标量值可以强烈预测运动引起的伪像。 PMC系统不会在无运动条件下引入多余的伪像,并且相对于标准采集,低/高分辨率和慢/快的头部运动的所有组合将时间序列的时间信噪比提高了30%至40%。没有预期的更正。在两个基于任务的实验中,激活的体素的数量(p <0.001,未校正)在无运动情况下是可比较的,在慢动作情况下,PMC开启与PMC关闭的情况下激活的体素分别增加了78%和330%。 PMC系统是一种强大的解决方案,可以降低3D EPI多镜头序列的运动敏感性,从而克服其在fMRI研究中广泛使用的主要障碍之一。

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