STEADY-STATE FREE PRECESSION DIFFUSION IMAGING USING 3D ROTATING SPIRALS

使用 3D 旋转螺旋进行稳态自由进动扩散成像

• 批准号: 8362916
• 负责人: JIAN ZHANG
• 金额: $ 1.95万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2012-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8362916
• 关键词: Algorithms; Calibration; Data; Diffusion; Diffusion Magnetic Resonance Imaging; Funding; Grant; Image; Location; Magnetic Resonance; Methods; Morphologic artifacts; Motion; National Center for Research Resources; Phase; Principal Investigator; Reporting; Research; Research Infrastructure; Resources; Sampling; Scanning; Signal Transduction; Source; Techniques; Technology; Translating; United States National Institutes of Health; Weight; Work; base; cost; reconstruction; research study

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Although signal in SSFP-DWI is composed of both spin echo and multiple stimulated echoes, experiments have shown that motion induced artifacts in SSFP-DWI can still be reduced by correcting navigated phase errors or averaging multiple DWI scans. In this work, we will present a SSFP 3D rotating spiral (3DRS) method for fast DWI and diffusion tensor imaging (DTI) acquisition, which is based on our previously reported 3D-SNAILS technique [1]. By combining SSFP-DWI and 3DRS readouts in this approach, high quality diffusion weighted volumes can be rapidly acquired with very high SNR efficiency and low sensitivity to motion artifacts. One key result of the proposed auto-calibrated kSPA algorithm is that the reconstruction kernel can be computed using calibration data acquired at any location. To accomplish that we only need to translate the surrounding sampling points to center at a set of grid points in the middle of the calibration region. We then repeat the reconstruction for each coil to form the final image similar to the GRAPPA algorithm.

该子项目是利用资源的众多研究子项目之一 由 NIH/NCRR 资助的中心拨款提供。子项目的主要支持 并且子项目的首席研究员可能是由其他来源提供的， 包括其他 NIH 来源。 子项目可能列出的总成本 代表子项目使用的中心基础设施的估计数量， NCRR 赠款不直接向子项目或子项目工作人员提供资金。 虽然SSFP-DWI中的信号由自旋回波和多重受激回波组成，但实验表明： SSFP-DWI 中运动引起的伪影仍然可以通过纠正导航相位误差或对多个 DWI 进行平均来减少 扫描。在这项工作中，我们将提出一种用于快速 DWI 和扩散张量成像的 SSFP 3D 旋转螺旋 (3DRS) 方法 (DTI) 采集，它基于我们之前报道的 3D-SNAILS 技术 [1]。通过结合 SSFP-DWI 和 3DRS 在这种方法中，可以以非常高的信噪比效率快速获取高质量的扩散加权体积 对运动伪影的敏感性低。所提出的自动校准 kSPA 算法的一个关键结果是 可以使用在任何位置获取的校准数据来计算重建内核。为了实现这一点，我们只需要 将周围的采样点平移到校准区域中间的一组网格点的中心。我们然后 对每个线圈重复重建，形成类似于 GRAPPA 算法的最终图像。