K-Space energy spectrum analysis for echo-planar imaging

项目描述（由申请人提供）：本项目旨在提高超声平面成像（echo-planar imaging， EPI）的质量和空间精度，从而为基于EPI的医学研究和临床诊断提供准确的定量信息。EPI是最快的MR成像技术之一，已被广泛应用于各种需要高时间分辨率的动态研究，如功能性MRI （fMRI）、对比增强成像和基于MR的介入程序。然而，EPI数据质量通常会受到各种人为因素的影响，如几何畸变和磁化率信号损失。此外，EPI对敏感性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。以前已经报道了几种用于EPI质量改进和减少工件的技术。然而，大多数先前报道的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，用于临床扫描和基于EPI的介入性MRI程序）。在这里，我们建议使用一种新的k空间能谱分析来量化(1)k空间能量分布，(2)磁化场梯度，(3)空间相关的回波时间值，以及(4)直接从获得的EPI数据中获得伪影水平，而无需额外的场映射程序或脉冲序列修改。使用所提出的方法可以有效地去除各种EPI伪影（例如失真和吉布波纹伪影）。此外，开发的k空间能谱分析将应用于设计相位编码3D并行EPI的最佳采集策略，该策略具有提高的信噪比和减少运动相关伪影。我们还计划应用所提出的方法来重新分析先前获得的fMRI数据，并回顾性地提高分组激活的纵向可重复性。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进他们未来基于EPI的定量研究或回顾性地改进先前获得的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.