HADAMARD-ENCODED BOLD FMRI FOR REDUCED SIGNAL DROPOUT

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 简介：BOLD fMRI在额眶和侧顶/颞区存在信号丢失， 空气和组织之间的磁化率差异引起体素内失相。通过减小切片厚度， 失相 的磁均匀区域中的信噪比（SNR）为代价， 脑（1）。在这里，我们介绍了一种新的解决方案：使用阿达玛编码，同时激发对子切片 随后使用UNFOLD（2）非相干地组合，以在不损失SNR的情况下获得丢失区域中的信号 均匀区域的效率。 方法：在动态采集中交替应用正弦和余弦调制的Hadamard脉冲（3）， 的 所需切片厚度的一半被同相和异相激励（图1）。假设有一个相移， 在子切片之间，由于可变性引起的梯度，所得到的复值时间序列包含 幅度分量，其中<$i是子片信号的幅度，并且符号随时间帧t交替 因为交替激励。对y（t）求平方并对其进行傅里叶变换，可以找到分量Y1， 以DC为中心的光谱对应于项 以及以奈奎斯特频率为中心的第二分量Y2 对应于 (Fig. 2）。应用展开滤波器H（w）以去除奈奎斯特分量，逆变换和 取平方根产生重构的时间序列，即两个时间序列的平方和的平方根。 子切片。 体素内失相分量的影响由此被去除。 Hadamard方法在螺旋进/出脉冲序列中实现（4）。采集60个2 mm厚的亚层 为 128个时间框架。从幅度重建图像获得对应于4 mm切片的时间序列， 使用两点矩形波串滤波器（）。在3 T下使用屏气任务获得功能数据，以引起激活 在 大部分大脑（5）。将这些扫描与类似的常规方法进行比较。 要了解卢卡斯中心正在进行的其他项目，请访问http://rsl.stanford.edu/ （卢卡斯年度报告） 和ISMRM 2011摘要）

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Introduction: BOLD fMRI suffers from signal dropout in frontal-orbital and lateral parietal/temporal regions from susceptibility differences between air and tissue induces intravoxel dephasing. By decreasing the slice thickness, dephasing is reduced and signal is regained, but at the expense of signal to noise ratio (SNR) in magnetically uniform regions of the brain (1). Here we introduce a novel solution: the use of Hadamard-encoding to simultaneously excite pairs of subslices that are subsequently combined incoherently using UNFOLD (2) to gain signal in dropout regions at no loss of SNR efficiency in uniform regions. Methods: Alternately applying sine- and cosine-modulated Hadamard pulses (3) in a dynamic acquisition, two sub-slices of half the desired slice thickness are excited in-phase and out-of-phase (Fig. 1). Assuming there is a phase shift of ¿ between subslices because of the susceptibility-induced gradients, the resulting complex-valued time series contains magnitude components , where ¿i are the magnitudes of the subslice signals, and the sign alternates with time frame t because of the alternating excitation. Squaring y(t) and taking its Fourier transform, one finds a component Y1 with spectrum centered at DC corresponding to the term and a second component Y2 centered at the Nyquist frequency corresponding to (Fig. 2). Applying an UNFOLD filter H(w) to remove the Nyquist component, inverse transforming and taking the square root yields a reconstructed timeseries , i.e. the square root of the sum of squares of the two subslices. The influence of the intravoxel dephasing component ¿ is thereby removed. The Hadamard method was implemented in a spiral-in/out pulse sequence (4). 60 2 mm thick subslices were acquired for 128 time frames. Timeseries corresponding to 4 mm slices were obtained from the magnitude reconstructed images as above using a two-point boxcar filter ( ). Functional data were obtained at 3T using a breath hold task to elicit activation in most of the brain (5). These scans were compared to a similar conventional method. To read about other projects ongoing at the Lucas Center, please visit http://rsl.stanford.edu/ (Lucas Annual Report and ISMRM 2011 Abstracts)