Slice-timing effects and their correction in functional MRI.
Slice-timing effects and their correction in functional MRI.
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DOI：
10.1016/j.neuroimage.2011.06.078
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发表时间：
2011-09-15
期刊：
影响因子：
5.7
通讯作者：
Windischberger, Christian
中科院分区：
文献类型：
--
作者：
Sladky, Ronald;Friston, Karl J.;Troestl, Jasmin;Cunnington, Ross;Moser, Ewald;Windischberger, Christian
准确的计时对于功能性 MRI 数据分析至关重要。数据集通常使用重复的二维成像方法进行测量，导致切片之间存在时间偏移。为了补偿这种时序差异，切片时序校正（即时间数据插值）已被用作 fMRI 预处理步骤超过 15 年。然而，关于这种方法的有效性和适用性一直存在争论。本文首次详细分析了切片定时效应对不同功能磁共振成像范式和测量参数的模拟数据的影响，同时考虑了数据噪声和平滑效应。在这里，我们表明，根据重复时间和范式设计，切片定时效应可能会显着损害功能磁共振成像结果，而切片定时校正方法可以成功补偿这些影响，从而提高数据分析的稳健性。此外，我们的模拟数据结果得到了体内经验数据集的支持。我们的研究结果表明，切片定时校正应包含在功能磁共振成像预处理流程中。 ► 切片采集延迟会降低功能磁共振成像数据分析的灵敏度。 ► 预处理期间的切片定时校正可抑制估计器偏差。 ► 我们基于广泛模拟的研究结果得到了体内数据的支持。
Exact timing is essential for functional MRI data analysis. Datasets are commonly measured using repeated 2D imaging methods, resulting in a temporal offset between slices. To compensate for this timing difference, slice-timing correction (i.e. temporal data interpolation) has been used as an fMRI pre-processing step for more than fifteen years. However, there has been an ongoing debate about the effectiveness and applicability of this method. This paper presents the first elaborated analysis of the impact of the slice-timing effect on simulated data for different fMRI paradigms and measurement parameters, taking into account data noise and smoothing effects. Here we show, depending on repetition time and paradigm design, slice-timing effects can significantly impair fMRI results and slice-timing correction methods can successfully compensate for these effects and therefore increase the robustness of the data analysis. In addition, our results from simulated data were supported by empirical in vivo datasets. Our findings suggest that slice-timing correction should be included in the fMRI pre-processing pipeline. ► Slice acquisition delays can degrade sensitivity of fMRI data analysis. ► Slice-timing correction during pre-processing suppresses estimator bias. ► Our findings based on extensive simulations are supported by in vivo data.
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