HADAMARD-ENCODED BOLD FMRI FOR REDUCED SIGNAL DROPOUT

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 简介：BOLD功能磁共振成像在额眶和外侧顶叶/颞区患有信号缺失。 空气和组织之间的敏感性差异导致体素内去相。通过减小切片厚度， 退相 降低并恢复信号，但代价是在磁均一区域中的信噪比(SNR 脑(1)。在这里，我们介绍了一种新的解决方案：使用Hadamard编码来同时激发子切片对 随后使用展开(2)进行非相干组合，以在不损失SNR的情况下获得丢弃区域中的信号 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阿达玛脉冲(3)，两个子切片 的 所需切片厚度的一半是同相和异相激发的(图1)。假设存在相移？ 由于磁化率引起的梯度，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，并且符号与时间帧t交替 因为交变激励。对y(T)平方并进行傅立叶变换，就可以得到一个分量y1，其中 以对应于项的DC为中心的频谱和以奈奎斯特频率为中心的第二分量Y2 对应于(图2)。应用展开滤光片H(W)来去除奈奎斯特分量、逆变换和 取平方根得到重建的时间序列，即两者的平方和的平方根 小切片。 从而消除了体素内去相分量的影响。 Hadamard方法是在螺旋输入/输出脉冲序列(4)中实现的。取60个2 mm厚的切片 为 128个时间范围。从量级重建图像中获得对应于4 mm切片的时间序列如下 上面使用的是两点箱车滤镜()。在3T时使用屏气任务获得功能数据以引发激活 在……里面 大脑皮层(5)。这些扫描与类似的常规方法进行了比较。 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年摘要)

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)