High SNR Functional Brain Imaging using Oscillating Steady State MRI

项目总结：使用振荡稳态磁共振成像的高信噪比脑功能成像 在过去的25年里，使用核磁共振(FMRI)的脑功能成像技术得到了迅速的发展。 广泛用于基础认知神经科学研究和术前计划。它正日益成为 用于开发神经和精神疾病的生物标记物，并用于基于人群的研究， 例如，正常和异常的发育和衰老。成像技术也取得了一些进展。 硬件和方法以及处理方法，以纠正伪影并分析功能活动。 这个项目的首要目标是开发一种新的全脑fmri采集方法，以改进 与目前领先的方法相比，信噪比提高了2到3倍。这样的提振大致相当于 从3T到7T的SNR收益，但没有额外的成本。我们的目标是提供 快速、高信噪比、亚毫米分辨率的图像，具有非常好的时间分辨率。我们的方法是 根本不同的是，几乎所有的标准fMRI方法都使用了一种新发现的来源 基于重复使用磁化的振荡稳态方法的fMRI信号， 提高了信号强度。该信号具有与标准功能磁共振成像相似的对比权重 方法：研究方法。振荡是非常可重现的，这将允许使用基于模型的重建，例如 示例低等级(LR)方法。一种新的基于黄金角度的LR张量捕获方法 提出了旋转变密度采集，在初步数据中显示了17倍的速度和很低的速度 错误率。总之，这些方法有望显著提高fMRI的信噪比(SNR 并允许更高的空间分辨率。 该项目有四个主要目标：(1)分析和模拟OSS信号的自旋物理，以阐明 该信号的性质，并获得最优敏感和稳健的捕获参数，(2)开发最优 OSS功能磁共振成像采集中的图像采集和重建方法。收购与重建 战略必须与开放源码软件方法联系在一起，并且是唯一的，(3)开发和评估方法以 解决与功能磁共振成像采集相关的几个公认问题，特别是生理噪声和头部 运动，以及(4)将OSS功能磁共振成像方法与最先进的同步多层螺旋CT进行比较 (短信息)采集方法在幻影和人类受试者中使用任务和静息状态功能磁共振成像。 对于给定的硬件集(Main)，所提出的技术将极大地提高信噪比和空间分辨率 磁场强度、射频线圈阵列)。较高的SNR将允许在单个受试者中进行更健壮的fMRI， 虽然空间分辨率很重要，因为大脑的功能单位(皮质柱)是1-2 mm和 同样，功能上不同的层是亚毫米级的，与输入和输出层的距离约为 1 mm。由于该方法不依赖于任何独特的硬件，因此该方法可以广泛且快速地实现 传播到神经成像界。

Project Summary: High SNR Functional Brain Imaging using Oscillating Steady State MRI Functional brain imaging using MRI (functional MRI or fMRI) has grown rapidly over the past 25 years and is widely used for basic cognitive neuroscience research and for presurgical planning. It is increasingly being used for developing biomarkers for neurological and psychiatric disorders and for population based studies of, for example, normal and abnormal development and aging. There have also been developments in imaging hardware and methods as well as processing methods to correct for artifacts and analyze functional activity. The overarching goal of this project is to develop a novel whole-brain fMRI acquisition approach that improves the SNR by 2- to 3-fold in comparison to the current leading methods. Such a boost is roughly equivalent to the SNR gain one achieves in going from 3T to 7T, but without the additional costs. Our goal is to provide rapid, high SNR, sub-millimeter resolution images with very good temporal resolution. Our approach is fundamentally different that nearly all standard fMRI methods in that is uses a newly discovered source of signal for fMRI that is based on an oscillating steady state approach which reuses magnetization and thus, improves the signal strength. This signal is shown to have contrast weighting that is similar to standard fMRI methods. The oscillations are very reproducible, which will allow the use of model based reconstructions, for example low-rank (LR) methods. A novel LR tensor and acquisition approach based on with a golden-angle rotated variable density acquisition is proposed that, in preliminary data, show a 17-fold speed-up with very low error rates. Together, these methods promise to dramatically improve the signal-to-noise ratio (SNR) of fMRI and allow for higher spatial resolution. The project has four main aims: (1) Analyze and simulate the spin physics of the OSS signal to elucidate the nature of this signal and obtain optimally sensitive and robust acquisition parameters, (2) Develop optimal image acquisition and reconstruction methods for OSS fMRI acquisition. The acquisition and reconstruction strategies are necessarily linked and are unique to the OSS approach, (3) Develop and evaluate methods to address several well-recognized issues associated with fMRI acquisition, notably physiological noise and head motion, and (4) Evaluate the OSS fMRI approach in comparison to state-of-the-art simultaneous multislice (SMS) acquisition methods in phantoms and in human subjects using both task and resting state fMRI. The proposed technology will greatly improve the SNR and spatial resolution for a given set of hardware (main magnetic field strength, RF coils arrays). Higher SNR will allow for more robust fMRI in individual subject, while spatial resolution is important as the functional units (cortical columns) of the brain are 1-2mm and similarly, functionally distinct layers are sub-mm with the distances from input and output layers being about 1mm. Since the methods do not relay on any unique hardware, the method can be widely and quickly disseminated to the neuroimaging community.