Dynamic Magnetic Resonance Inverse Imaging of the Human Brain

描述(申请人提供)：磁共振成像(MRI)已被很好地用于动态生理过程的非侵入性测量，例如在时间分辨率为秒的情况下，神经元激活与相对较慢的血流动力学反应相耦合。由于射频技术的优势，特别是多通道射频阵列系统，磁共振成像可以直接获得嵌入到射频线圈阵列中的空间信息，并且只需最少的相位编码步骤。由于最小的梯度切换，这可能会在数据采集期间实现数量级的加速或最小的声学噪声。在这项授权中，我们提出了动态逆成像(INI)来实现毫秒的时间分辨率。INI基于大N阵列线圈技术、对比度准备和数据采集中的改进脉冲序列以及受脑电(EEG)和磁脑图(MEG)启发的图像重建算法来实现，以生成关于MR测量动态的时间分辨统计推断。在该方案中，我们寻求在射频阵列线圈和序列开发方面的MR INI的开发和优化，以及数据重建和分析。我们将探索动态MR INI在拟议的先导研究中的两个主要应用，包括(1)表征极高的时间BOLD血流动力学时间曲线和(2)由于INI中使用的最小梯度切换而减少动态MRI采集过程中的噪声。

DESCRIPTION (provided by applicant): Magnetic Resonance Imaging (MRI) has been well established for non-invasive measurement of dynamic physiological process, such as neuronal activation coupled to relatively slow hemodynamic responses at temporal resolution of seconds. Due to the advantages of RF technology, particularly multiple channel RF array systems, MRI can obtain spatial information embedded in the RF coil array directly with minimal phase encoding steps. This potentially enables order- of-magnitude acceleration or minimal acoustic noise during data acquisitions because of minimal gradient switching. In this grant, we propose the dynamic inverse imaging (InI) to achieve millisecond temporal resolution. InI is implemented based on the large-N array coil technology, modified pulse sequence in contrast preparation and data acquisition, as well as image reconstruction algorithms inspired by electroencephalography (EEG) and magnetoencephagraphy (MEG) in to order to generate time-resolved statistical inference on dynamics of the MR measurements. In this proposal, we seek the development and optimization of MR InI on RF array coil and sequence development, as well as data reconstruction and analysis. We will explore the application of dynamic MR InI to two major applications in the proposed pilot studies, including (1) characterization of extremely high temporal BOLD hemodynamic time curves and (2) reduction of acoustic noise during dynamic MRI acquisitions due to minimal gradient switching used in InI.