A SPIRAL IN & OUT PULSE SEQUENCE DESIGN FOR RETROSPECTIVE CORRECTION SENSE

螺旋式进入

• 批准号: 7358818
• 负责人: MURAT AKSOY
• 金额: $ 1.87万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-06-01 至 2007-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7358818
• 关键词: SPIRAL; OUT; PULSE; SEQUENCE; DESIGN

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. Introduction Correction of motion artifacts still remains to be one of the most essential topics in MR. Especially in the case of uncooperative patients such as children and patients suffering from a medical condition that prevents them from staying stationary, accurate determination and correction of motion becomes a must for good image quality. In this study, we propose a spin-echo spiral in & out sequence for retrospective motion correction that is aimed to remove motion related artifacts in the case of in-planar rigid body motion, which includes only translational and rotational motion. The spiral in & out sequence designed for this study can be used to get low resolution navigator data for each interleave with no extra penalty in scan time. The modified SENSE reconstruction procedure uses that navigator data to find the motion parameters and eliminates the effects of undersampling in k-space. Materials and Methods A spin echo Archimedian spiral in & out pulse sequence is designed for this study according to the algorithm described in [1]. Due to the gradient system limitations, a spiral trajectory mostly starts off in slew rate limited region and switches to amplitude limited region after a certain time which is determined by the scan parameters. In the case of the spiral in & out trajectory used for this study, a spiral in trajectory is used to get a fully sampled low resolution image for each interleave, and the spiral out part constitutes one of the interleaves of the final high resolution image. One advantage of this pulse sequence is that the spiral in portion makes use of the dead time after the 180o degree pulse up to the echo time TE and this introduces no penalty for scan time in case of T2 weighting. The matrix size of the low resolution navigator data can be adjusted interactively before scan by the operator. This sequence has been tested on two normal volunteers using a 1.5T scanner (GE Signa LX, 11.0) with a high performance gradient system (Gmax = 50mT/m, SR = 150 mT/m/s) and an 8 channel head array (MRI Devices). The volunteers were asked to move their head inside the head coil by approximately 10-20 degrees for every 10 seconds during the scan to simulate in-planar rigid body motion. All human studies were approved by the review board of our institution. Other parameters used for the pulse sequence are as follows: TR/TE = 4000/56 ms, slice thickness/gap = 5/0 mm, 12 slices, FOV = 24 cm, matrix size = 256, interleaves = 32, NEX = 1, navigator matrix size = 32 and BW = 125 kHz. The data obtained from the scans were fed into a motion correction algorithm that uses the navigator images to accomplish co-registration and to obtain the amount of rotation and translation. After the determination of motion parameters, k-space trajectory, k-space data and the coil sensitivities are corrected accordingly by counter-rotating the k-space trajectories and applying a linear phase to k-space data. This motion correction introduces some gaps in k-space and causes aliasing in image domain. A modified version of the generalized SENSE algorithm that has a channel for each coil and for each interleave is used to remove aliasing and reconstruct the image. Results The results of motion correction are shown. The artifacts resulting from rigid body motion are significantly removed by the application of motion correction algorithm. The modified SENSE algorithm provides improvement in the final image quality by filling in the gaps in k-space resulting from the counter-rotation of k- space trajectories. This is apparent from the difference between the initial image and final image in the SENSE iteration. The spiral trajectory used in this study allows for better utilization of SENSE reconstruction due to the constant undersampling factor throughout k-space after rotation correction. In case of other trajectories like EPI, rotation of individual interleaf leaves large and arbitrarily spaced gaps in k-space which cannot be corrected by SENSE. An effective reduction factor, Reff, is used as a measure of the k-space undersampling and is defined as the ratio of the maximum distance between two spiral arms to the original k-space sampling density. For the motion corrupted data sets, Reff is 1.65, which is a reasonable value that can be corrected with SENSE. The navigator images obtained for all 32 interleaves and the motion corrected images are shown. Because of the motion, the subject is exposed to different combined coil sensitivity for each interleave. This results in navigator images having a slightly different intensity variation which might affect the registration. Acknowledgements This work was supported in part by the NIH (1R01EB002771), the Center of Advanced MR Technology at Stanford (P41RR09784), Lucas Foundation and Oak Foundation. References [1] Glover GH, MRM, 42:412-415 (1999). [2] Atkinson D, et al., MRM, 42:963-969 (1999) [3] Pruessmann et al, MRM, 46:638-651 (2001

该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得主要资金，因此可以在其他CRISP条目中表示。所列机构为中心，不一定是研究者所在机构。引言运动伪影的校正仍然是MR中最重要的主题之一。特别是在不合作的患者（如儿童和患有阻止其保持静止的医疗状况的患者）的情况下，准确确定和校正运动成为良好图像质量的必要条件。在这项研究中，我们提出了一个自旋回波螺旋进出序列的回顾性运动校正，旨在消除运动相关的文物的情况下，在平面刚体运动，其中只包括平移和旋转运动。为这项研究设计的螺旋进出序列可用于获得每个交织的低分辨率导航数据，而不会增加扫描时间。修改的SENSE重建过程使用该导航器数据来找到运动参数并消除k空间中的欠采样的影响。 材料与方法根据文献[1]中的算法设计了自旋回波阿基米德螺旋进出脉冲序列。由于梯度系统的限制，螺旋轨迹主要在转换速率受限区域中开始，并且在由扫描参数确定的特定时间之后切换到幅度受限区域。在用于本研究的螺旋进出轨迹的情况下，螺旋进出轨迹用于针对每个交织获得完全采样的低分辨率图像，并且螺旋出部分构成最终高分辨率图像的交织之一。该脉冲序列的一个优点是，螺旋部分利用了180度脉冲之后直到回波时间TE的死区时间，并且这在T2加权的情况下不引入扫描时间的损失。低分辨率导航器数据的矩阵大小可以在扫描之前由操作员交互地调整。已使用1.5T扫描仪（GE Signa LX，11.0）和高性能梯度系统（Gmax = 50 mT/m，SR = 150 mT/m/s）和8通道头部阵列（MRI器械）在两名正常志愿者身上测试了该序列。要求志愿者在扫描期间每10秒将其头部在头部线圈内移动约10-20度，以模拟平面内刚体运动。所有的人体研究都得到了我们机构审查委员会的批准。用于脉冲序列的其他参数如下：TR/TE = 4000/56 ms，切片厚度/间隙= 5/0 mm，12个切片，FOV = 24 cm，矩阵大小= 256，交错= 32，NEX = 1，导航矩阵大小= 32和BW = 125 kHz。从扫描中获得的数据被送入运动校正算法，该算法使用导航图像来完成配准并获得旋转和平移的量。在确定运动参数之后，通过反向旋转k空间轨迹并将线性相位应用于k空间数据来相应地校正k空间轨迹、k空间数据和线圈灵敏度。这种运动校正在k空间中引入了一些间隙，并导致图像域中的混叠。广义SENSE算法的修改版本具有用于每个线圈和用于每个交错的通道，用于去除混叠并重建图像。 结果给出了运动校正的结果。通过运动校正算法的应用，由刚体运动引起的伪影被显著地去除。经修改的SENSE算法通过填充由k空间轨迹的反向旋转引起的k空间中的间隙来提供最终图像质量的改进。这从SENSE迭代中的初始图像和最终图像之间的差异是明显的。本研究中使用的螺旋轨迹允许更好地利用SENSE重建，这是由于旋转校正后整个k空间中的恒定欠采样因子。在像EPI的其他轨迹的情况下，单独的隔片的旋转在k空间中留下了不能由SENSE校正的大的且任意间隔的间隙。一个有效的减少因子，Reff，被用来作为一个衡量的k空间欠采样，并被定义为两个螺旋臂之间的最大距离的原始k空间采样密度的比率。对于运动损坏的数据集，Reff为1.65，这是可以用SENSE校正的合理值。示出了针对所有32个交错获得的导航器图像和运动校正图像。由于运动，受试者对于每个交错暴露于不同的组合线圈灵敏度。这导致导航器图像具有可能影响配准的略微不同的强度变化。 致谢这项工作得到了NIH（1 R 01 EB 002771）、斯坦福大学先进MR技术中心（P41 RR 09784）、卢卡斯基金会和橡树基金会的部分支持。 参考文献[1]格洛弗GH，MRM，42：412-415（1999）。[2]Atkinson D等人，Pruessmann等人，MRM，46：638-651（2001