The Mind Research Network, Albuquerque, New Mexico 87106, USA.
Hum Brain Mapp. 2012 Jan;33(1):50-62. doi: 10.1002/hbm.21192. Epub 2011 Mar 9.
The relationship between head motion and diffusion values such as fractional anisotropy (FA) and mean diffusivity (MD) is currently not well understood. Simulation studies suggest that head motion may introduce either a positive or negative bias, but this has not been quantified in clinical studies. Moreover, alternative measures for removing bias as result of head motion, such as the removal of problematic gradients, has been suggested but not carefully evaluated. The current study examined the impact of head motion on FA and MD across three common pipelines (tract-based spatial statistics, voxelwise, and region of interest analyses) and determined the impact of removing diffusion weighted images. Our findings from a large cohort of healthy controls indicate that while head motion was associated with a positive bias for both FA and MD, the effect was greater for MD. The positive bias was observed across all three analysis pipelines and was present following established protocols for data processing, suggesting that current techniques (i.e., correction of both image and gradient table) for removing motion bias are likely insufficient. However, the removal of images with gross artifacts did not fundamentally change the relationship between motion and DTI scalar values. In addition, Monte Carlo simulations suggested that the random removal of images increases the bias and reduces the precision of both FA and MD. Finally, we provide an example of how head motion can be quantified across different neuropsychiatric populations, which should be implemented as part of any diffusion tensor imaging quality assurance protocol.
头部运动与扩散值（如各向异性分数（FA）和平均扩散系数（MD））之间的关系目前尚未得到很好的理解。模拟研究表明，头部运动会引入正偏差或负偏差，但这在临床研究中尚未得到量化。此外，还提出了其他消除因头部运动而产生偏差的替代措施，例如去除有问题的梯度，但尚未仔细评估。本研究在三个常见管道（基于束的空间统计学、体素和感兴趣区域分析）中检查了头部运动对 FA 和 MD 的影响，并确定了去除扩散加权图像的影响。我们从大量健康对照组中的发现表明，尽管头部运动会对 FA 和 MD 产生正偏差，但 MD 的影响更大。这种正偏差在所有三个分析管道中均可见，并且在经过数据处理的既定方案后仍然存在，这表明当前用于消除运动偏差的技术（即图像和梯度表的校正）可能不足。然而，去除具有明显伪影的图像并不能从根本上改变运动与 DTI 标量值之间的关系。此外，蒙特卡罗模拟表明，随机去除图像会增加 FA 和 MD 的偏差并降低其精度。最后，我们提供了一个示例，说明了如何在不同的神经精神人群中量化头部运动，这应该作为任何扩散张量成像质量保证协议的一部分实施。
