Dynamic Magnetic Resonance Inverse Imaging of the Human Brain

描述（由申请人提供）：磁共振成像（MRI）已被广泛用于动态生理过程的非侵入性测量，例如与相对缓慢的血流动力学反应相关的神经元激活，时间分辨率为秒。由于RF技术的优点，特别是多通道RF阵列系统，MRI可以以最少的相位编码步骤直接获得嵌入在RF线圈阵列中的空间信息。由于最小梯度切换，这潜在地实现了数据采集期间的数量级加速度或最小声学噪声。在本授权中，我们提出了动态逆成像（InI）来实现毫秒级的时间分辨率。InI是基于大N阵列线圈技术、对比度准备和数据采集中的修改脉冲序列以及受脑电图（EEG）和脑磁图（MEG）启发的图像重建算法来实现的，以生成对MR测量动态的时间分辨统计推断。在本提案中，我们寻求MR InI在RF阵列线圈和序列开发以及数据重建和分析上的开发和优化。我们将探索动态MR InI在拟议试点研究中的两个主要应用中的应用，包括（1）极高时间BOLD血流动力学时间曲线的表征和（2）由于InI中使用的最小梯度切换而减少动态MRI采集期间的声学噪声。

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.