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Characterization of BOLD activation in multi-echo fMRI data using fuzzy cluster analysis and a comparison with quantitative modeling.

机译:使用模糊聚类分析以及与定量建模的比较,对多回波功能磁共振成像数据中的BOLD激活进行表征。

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摘要

A combination of multiple gradient-echo imaging and exploratory data analysis (EDA), i.e. fuzzy cluster analysis (FCA), is proposed for separation and characterization of BOLD activation in single-shot spiral functional magnetic resonance imaging (fMRI) experiments at 3 T. Differentiation of functional activation using FCA is performed by clustering pixel signal changes (DeltaS) as a function of echo time (TE). Further vascular classification is supported by the localization of activation and the comparison with a single-exponential decay model. In some subjects, an additional indication for large vessels within a voxel was found as oscillation of the fMRI signal difference vs echo time (TE). Such large vessels may be separated from small vessel activation and, therefore, our proposed procedure might prove useful if a more specific functional localization is desired in fMRI. In addition to the signal change DeltaS, DeltaT(2)*/T(2)* is significantly different between activated regions. Averaged over all eight subjects DeltaT(2)* is 1.7 +/- 0.2 ms in ROIs with the highest signal change characterized as containing large vessels, whereas in ROIs corresponding to microvascular environment average DeltaT(2)* values are 0.8 +/- 0.1 ms. Copyright 2001 John Wiley & Sons, Ltd.
机译:提出了将多重梯度回波成像和探索性数据分析(EDA)(即模糊聚类分析(FCA))相结合的方法,用于在3 T下单次螺旋功能磁共振成像(fMRI)实验中对BOLD激活进行分离和表征。通过将像素信号变化(DeltaS)作为回波时间(TE)的函数进行聚类,可以执行使用FCA进行功能激活的区分。激活的定位以及与单指数衰减模型的比较支持进一步的血管分类。在某些受试者中,还发现fMRI信号差相对于回声时间(TE)的振荡是对体素内大血管的另一种指征。这样的大血管可能会与小血管激活分开,因此,如果在fMRI中需要更具体的功能定位,我们提出的方法可能会证明是有用的。除了信号变化DeltaS之外,激活区域之间的DeltaT(2)* / T(2)*也显着不同。在八个信号最大的ROI中,DeltaT(2)*在具有最大信号变化的ROI中平均为1.7 +/- 0.2 ms,而在与微血管环境相对应的ROI中,平均DeltaT(2)*值为0.8 +/- 0.1多发性硬化症。版权所有2001 John Wiley&Sons,Ltd.

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