ADVANCES IN DIFFUSION IMAGING USING PARALLEL IMAGING

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 我们正在继续努力，为斯坦福大学P41 RR09784高级磁共振技术中心的研究人员和合作者重新定义和改进DWI和扩散张量成像(DTI)的方法。敏感性编码(SENSE)是MRI中常规梯度编码的一个有价值的补充。它利用射频线圈阵列中各个单元中包含的一些空间信息来实现相当大的扫描时间的减少。因此，考虑到有效遍历k-空间的生理和技术限制，Sense是一个很有前途的概念。SENSE几乎可以用来加速任何传统的磁共振成像技术，而不会干扰磁共振成像中使用的典型对比机制，例如扩散加权成像(DWI)。尽管存在众所周知的问题，但在大多数情况下，EPI仍然是获取体内DWI数据的首选方法。随着最近在空间上更加均匀地扫描扩散特性以及在包含多个纤维束的体素中解析更多细节方面的成就，测量的数量已经大大增加，EPI作为快速数据采集工具的作用变得更加重要。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We are continuing our efforts to redefine and improve upon the methodology of DWI and diffusion tensor imaging (DTI) for the investigators and collaborators on the P41 RR09784 Center for Advanced MR Technology at Stanford effort. SENSitivity Encoding (SENSE) is a valuable complement to regular gradient encoding in MRI. It employs some of the spatial information contained in the individual elements in an RF coil array to achieve a considerable reduction of scanning time. For this reason, SENSE is a promising concept in view of physiological as well as technical limits to efficiently traverse k-space. SENSE can be used to accelerate virtually any conventional MRI technique without interfering with typical contrast mechanisms used in MRI, such as diffusion-weighted imaging (DWI). Despite well-known problems, in most cases EPI is still the method of choice for acquiring in-vivo DWI data. With recent achievements in scanning diffusion properties more uniformly in space and resolving more details in voxels that contain more than one fiber tract, the number of measurements has tremendously increased and the role of EPI as a vehicle for fast data acquisition has become even more important.