K-Space energy spectrum analysis for echo-planar imaging

描述（由申请人提供）：本项目的目标是提高回波平面成像（EPI）的质量和空间精度，以便从基于EPI的医学研究和临床诊断中获得准确的定量信息。EPI是最快的MR成像技术之一，并已广泛应用于各种需要高时间分辨率的动态研究，如功能MRI（fMRI），对比增强成像和基于MR的介入手术。然而，EPI数据质量通常会因各种伪影而降低，例如几何失真和磁化率信号丢失。此外，EPI对磁化场不均匀性的敏感性使其在基于EPI的纵向研究中不太可靠。先前已经报道了用于EPI质量改进和伪影减少的几种技术。然而，大多数先前报告的EPI伪影减少方法需要耗时的场映射扫描，因此可能并不总是实用的（例如，对于临床扫描和基于EPI的介入MRI程序）。在这里，我们建议使用一种新的k空间能量谱分析来量化（1）k空间能量分布，（2）磁化率场梯度，（3）空间相关回波时间值，以及（4）直接来自采集的EPI数据的伪影水平，而不需要额外的场映射过程或脉冲序列修改。使用所提出的方法可以有效地去除各种EPI伪影（例如失真和吉布涟漪伪影）。此外，开发的k空间能量谱分析将被应用于设计相位编码的3D并行EPI的最佳采集策略，具有改善的信噪比和减少的运动相关伪影。我们还计划应用所提出的方法来重新分析以前获得的fMRI数据，并回顾性地提高分组激活的纵向可重复性。在拟议项目中开发的方法将提供给MRI社区，以便其他研究小组可以使用开发的方法来改善他们未来基于EPI的定量研究或回顾性改善以前获得的EPI数据。

DESCRIPTION (provided by applicant): The goal of this project is to improve the quality and spatial accuracy of echo-planar imaging (EPI), so that accurate quantitative information can be derived from EPI based medical research and clinical diagnosis. EPI is one of the fastest MR imaging techniques, and has been popularly applied to various dynamic studies that require high temporal-resolution, such as functional MRI (fMRI), contrast-enhanced imaging, and MR based interventional procedures. However, EPI data quality is usually degraded by various artifacts, such as geometric distortions and susceptibility signal loss. Furthermore, the sensitivity of EPI to susceptibility field nhomogeneities makes it less reliable in EPI based longitudinal studies. Several techniques have been previously reported for EPI quality improvement and artifact reduction. However, most previously reported EPI artifact reduction methods require time-consuming field mapping scans, and therefore may not always be practical (e.g. for clinical scans and EPI based interventional MRI procedures). Here we propose to use a novel k-space energy spectrum analysis to quantify (1) the k-space energy distribution, (2) susceptibility field gradients, (3) the spatially-dependent echo time values, and (4) artifact levels directly from the acquired EPI data, without the need of additional field mapping procedure or pulse sequence modification. Various EPI artifacts (e.g. distortions and Gibb's ripple artifact) can be effectively removed using the proposed approach. Furthermore, the developed k-space energy spectrum analysis will be applied to design an optimal acquisition strategy for phase-encoded 3D parallel EPI, with an improved signal-to-noise ratio and reduced motion related artifact. We also plan to apply the proposed methods to re-analyze the previously acquired fMRI data, and retrospectively improve the longitudinal reproducibility of grouped activation. The methods developed in the proposed project will be made available to MRI community so that other research groups may use the developed methods to improve their future EPI based quantitative studies or to retrospectively improve the EPI data that were previously obtained.