High-Speed fMRI of Resting State Connectivity

静息态连接的高速功能磁共振成像

• 批准号: 8824403
• 负责人: Stefan Posse
• 金额: $ 26.38万
• 依托单位: UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8824403
• 关键词: Acceleration; Behavior; Brain; Brain Mapping; Brain Neoplasms; Brain region; Cardiac; Clinical; Clinical Research; Complement; Data; Diagnostic; Electrocorticogram; Exhibits; Frequencies; Functional Magnetic Resonance Imaging; Goals; Head Movements; Human; Image; Impairment; Individual; Lead; Lesion; Maps; Methodology; Methods; Modeling; Monitor; Morphologic artifacts; Motion; Neurons; Neurosciences Research; Patients; Physiological; Play; Research; Resolution; Rest; Role; Sampling; Scanning; Seeds; Sensitivity and Specificity; Side; Signal Transduction; Slice; Slide; Source; Speed; Time; base; cost; data acquisition; functional disability; improved; individualized medicine; interest; nervous system disorder; outcome forecast; public health relevance; reconstruction; regional difference; segregation; temporal measurement; time use; tool; treatment strategy

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.

描述（由申请人提供）：使用静息状态fMRI的功能性连接组学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。最近的研究已经证明了超过100个静息态网络（RSN），表现出相当大的时间和空间的非平稳性。现在有相当大的兴趣，在更高的频率（高达5赫兹）比传统的静息状态功能磁共振成像检测到的特征静息状态连接。然而，扫描内的连接性和头部运动伪影的非平稳性损害了在单个受试者中检测RSN的灵敏度。 在功能磁共振成像方法的进步，以提高数据采集率发挥了重要作用，在提高BOLD的灵敏度，以任务为基础的功能磁共振成像和映射的时间动态的大脑状态。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，如我们的初步数据所示，其在大脑皮层区域之间表现出脉动波形的相当大的区域差异。然而，高速功能磁共振成像遭受重建伪影在高加速率，并增加多回波采集分离BOLD和非BOLD信号源尚未被调查。本研究的长期目标是开发一种可靠和敏感的静息状态功能磁共振成像方法，用于神经系统疾病患者的功能脑区的术前映射。该提案的目的是整合同步多切片（SMS）EPI和多板回波容积成像（EVI），这已经成为主要的高速数据采集方法与多维压缩感知，以实现前所未有的时间和空间分辨率和BOLD灵敏度，而不牺牲图像质量。我们还将整合运动伪影的全面校正。该方法将在健康对照和脑肿瘤患者中使用时间动态统计分析方法进行验证，以灵敏地捕获静息状态波动的时间动态。这项研究的基本原理是，静息状态功能磁共振成像有可能取代基于任务的功能磁共振成像来绘制主要的大脑网络，这将降低成本，并使功能磁共振成像能够用于无法用基于任务的功能磁共振成像研究的患者群体。虽然静息状态fMRI在不同受试者中的功能定位与基于任务的fMRI一致，但仍需要提高静息状态fMRI在单个受试者水平上的可靠性。这项研究将建立超高速功能磁共振成像作为一个敏感的和定量的方法映射静息状态连接在临床和神经科学研究的个别科目。表征静息状态连接的时间动态将增强我们对静息时内在脑活动的理解，以改善诊断和指导治疗。这 将最终导致基于患者特异性功能性脑映射的改进的个体化治疗策略和预后。