High-Speed fMRI of Resting State Connectivity

描述(由申请人提供)：使用静息状态功能磁共振成像的功能连接是一种快速扩展的无任务方法，预计将产生重大的临床影响。最近的研究表明，有100多个休眠状态网络(RSNs)表现出相当大的时间和空间非平稳。现在有相当大的兴趣在比传统静息状态fMRI可检测到的频率高得多的频率(高达5赫兹)下表征静息状态连通性。然而，连通性和头部运动伪影的扫描内非平稳性影响了单个受试者检测RSNs的灵敏度。提高数据采集率的fMRI方法的进步在提高基于任务的fMRI的BOLD敏感性和绘制脑状态的时间动态图方面发挥了重要作用。增加采样率改善了静息状态信号波动和心脏相关信号脉动的分离，正如我们的初步数据显示的那样，大脑皮质区域的脉动波形显示出相当大的区域差异。然而，高速功能磁共振成像在高加速时存在重建伪影，并且增加多回波采集来分离粗体和非粗体信号源还没有被研究过。这项研究的长期目标是开发一种可靠和灵敏的静息状态fMRI方法，用于术前对神经系统疾病患者的口才脑区进行标测。该方案的目标是将同时多层(SMS)EPI和多层回波体积成像(EVI)这两种主要的高速数据采集方法与多维压缩传感技术相结合，在不牺牲图像质量的情况下获得前所未有的时间和空间分辨率和大胆的灵敏度。我们还将集成一个全面的运动伪影校正功能。这一方法将在健康对照组和脑肿瘤患者中得到验证，使用时间动态统计分析方法灵敏地捕获静息状态波动的时间动力学。这项研究的基本原理是，静息状态的功能磁共振成像有可能取代基于任务的功能磁共振成像，用于绘制主要的大脑网络，这将降低成本，并使无法用基于任务的功能磁共振成像研究的患者组能够进行功能磁共振成像。虽然静息状态fMRI跨受试者组的功能定位已被证明与基于任务的fMRI是一致的，但在单个受试者水平上仍需要提高静息状态fMRI的可靠性。这项研究将建立超高速功能磁共振成像作为一种灵敏和定量的方法，用于在临床和神经科学研究中绘制个体受试者的静息状态连接。刻画静息状态连通性的时间动力学特征将增强我们对静息状态下内在脑活动的理解，从而改进诊断和指导治疗。这 最终将根据患者特定的脑功能图改进个性化治疗策略和预后。

DESCRIPTION (provided by applicant): Functional connectomics using resting state fMRI is a rapidly expanding task-free approach, which is expected to have significant clinical impact. Recent studies have demonstrated more than 100 resting state networks (RSNs), which exhibit considerable temporal and spatial non-stationary. There is now considerable interest in characterizing resting state connectivity at much higher frequencies (up to 5 Hz) than detectable with traditional resting state fMRI. However, intra-scan non-stationary of connectivity and head movement artifacts compromise the sensitivity of detecting RSNs in single subjects. Advances in fMRI methodology to increase data acquisition rates have played an important role in improving BOLD sensitivity for task-based fMRI and for mapping the temporal dynamics of brain-states. Increasing the sampling rate improves segregation of resting state signal fluctuation and cardiac-related signal pulsation, which as our preliminary data show exhibits considerable regional differences of the pulsation waveform across cortical brain regions. However, high-speed fMRI suffers from reconstruction artifacts at high acceleration rates, and adding multi-echo acquisition to separate BOLD and non-BOLD signal sources has not been investigated. The long-term goal of this research is to develop a reliable and sensitive resting state fMRI method for presurgical mapping of eloquent brain regions in patients with neurological disorders. The objective of this proposal is to integrate simultaneous multi-slice (SMS) EPI and multi-slab echo-volumar imaging (EVI), which have emerged as the principal high-speed data acquisition approaches with multi-dimensional compressed sensing, to achieve unprecedented temporal and spatial resolution and BOLD sensitivity without sacrificing image quality. We will additionally integrate a comprehensive correction of motion artifacts. This approach will be validated in healthy controls and patients with brain tumors using time-dynamic statistical analysis methods to sensitively capture the temporal dynamics of resting state fluctuations. The rationale of this research is that resting state fMRI has the potential to replac task-based fMRI for mapping major brain networks, which would reduce costs and enable fMRI in patient groups that cannot be studied with task-based fMRI. While functional localization of resting state fMRI across groups of subjects has been demonstrated to be consistent with task-based fMRI, there is a need to improve reliability of resting state fMRI at the single subject leve. This research will establish ultra-high-speed fMRI as a sensitive and quantitative approach for mapping resting state connectivity in individual subjects in clinical and neuroscience research. Characterizing the temporal dynamics of resting state connectivity will enhance our understanding of intrinsic brain activity at rest to improve diagnostics and to guide therapy. This will ultimately lead to improved individualized treatment strategies and prognosis based upon patient specific functional brain mapping.