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。子弹和调查员（PI）可能已经从其他NIH来源获得了主要资金，因此可以在其他清晰的条目中代表。列出的机构适用于该中心，这不一定是调查员的机构。引言对运动伪像的校正仍然是MR中最重要的主题之一。尤其是在不合作患者的情况下，例如儿童和患有医疗状况的患者，可防止他们保持静止，准确的确定和纠正运动成为良好的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入内和输出序列，以进行回顾性运动校正，该校正旨在在平面内刚体运动的情况下去除运动相关的伪影，其中仅包括翻译和旋转运动。为这项研究设计的螺旋进出序列可用于获取每个交通的低分辨率导航器数据，而在扫描时间内没有额外的惩罚。修改后的感官重建过程使用导航数据来找到运动参数并消除k空间中底面采样的影响。 材料和方法根据[1]中描述的算法，为本研究设计了自旋回波旋转螺旋序列和外脉冲序列。由于梯度系统的局限性，螺旋轨迹大多以较高的速率限制区域开始，并在一定时间后切换到幅度有限的区域，该区域由扫描参数确定。在用于本研究的螺旋入内和外部轨迹的情况下，轨迹上的螺旋式轨迹用于获得每个交叉点的完全采样的低分辨率图像，而螺旋出的部分构成了最终高分辨率图像的交汇处之一。该脉冲序列的一个优点是，部分螺旋在180o度脉冲之后使用的静止时间，直至回声时间TE，这在T2加权的情况下没有引入扫描时间的罚款。低分辨率导航器数据的矩阵大小可以在操作员扫描之前进行交互调整。使用高性能梯度系统（Gmax = 50mt/m，SR = 150 mt/m/s）和8通道头阵列（MRI设备），使用1.5T扫描仪（GE Signa LX，11.0）对两名正常志愿者进行了测试。在扫描过程中，每10秒钟，志愿者每10秒就将头部移动大约10-20度，以模拟平面内刚体运动。所有人类研究均由我们机构审查委员会批准。脉冲序列使用的其他参数如下：TR/TE = 4000/56 ms，切片厚度/GAP = 5/0 mm，12片，FOV = 24 cm，矩阵尺寸= 256，Interleaves = 32，Nex = 1，Neyx = 1，Nevigator Matrix size size = 32和BW = 125 kHz。从扫描中获得的数据被送入运动校正算法，该算法使用导航器图像完成共同注册并获得旋转和翻译的量。在确定运动参数后，通过对抗k-空间轨迹并将线性相应用到k空间数据来纠正运动参数，K空间轨迹，K空间数据和线圈敏感性。这种运动校正引入了K空间中的一些差距，并导致图像域中的混叠。具有每个线圈通道的通用感官算法的修改版本，用于每个线圈，用于删除和混叠和重建图像。 结果显示了运动校正的结果。通过应用运动校正算法可显着去除刚体运动引起的伪影。修改后的感觉算法通过填充K-Space轨迹的反转而导致的K空间中的空隙来改善最终图像质量。从意义上的迭代中，初始图像和最终图像之间的差异很明显。这项研究中使用的螺旋轨迹可以更好地利用旋转校正后整个K空间的恒定底采样因子，从而更好地利用感官重建。如果其他轨迹（例如EPI），单个交流的旋转会在k空间中留下较大且任意间隔的间隔，而k空间无法通过意义上的纠正。有效的还原因子REFF用作k空间底采样的量度，并定义为两个螺旋臂与原始K空间采样密度之间的最大距离之比。对于运动损坏的数据集，REFF为1.65，这是一个可以通过感觉纠正的合理价值。显示了所有32个交错的导航图像，并显示了运动校正图像。由于运动，受试者会暴露于每个交织的不同组合线圈灵敏度。这导致导航图像具有略有不同的强度变化，这可能会影响注册。 致谢这项工作部分得到了NIH（1R01EB002771），斯坦福大学高级MR技术中心（P41RR09784），Lucas Foundation and Oak Foundation的支持。 参考文献[1] Glover GH，MRM，42：412-415（1999）。 [2] Atkinson D等人，MRM，42：963-969（1999）[3] Pruessmann等人，MRM，46：638-651（2001年）