Fast Functional MRI with Sparse Sampling and Model-Based Reconstruction

具有稀疏采样和基于模型的重建的快速功能 MRI

• 批准号: 9228804
• 负责人: JEFFREY A FESSLER
• 金额: $ 32.63万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9228804
• 关键词: Acceleration; Address; Aging; Alzheimer' s Disease; Biological Markers; Brain; Brain imaging; Brain region; Cardiac; Complex; Cortical Column; Data; Development; Dimensions; Frequencies; Functional Magnetic Resonance Imaging; Future; Goals; Head; Image; Imaging Techniques; Information Networks; Language; Lead; Magnetic Resonance Imaging; Measures; Mental disorders; Methods; Modeling; Morphologic artifacts; Motion; Multiple Sclerosis; Neurosciences Research; Noise; Output; Pathway Analysis; Patients; Pattern; Physiological; Population Study; Predisposition; Process; RF coil; Resolution; Respiration; Rest; Sampling; Signal Transduction; Slice; Socioeconomic Status; Speed; Substance abuse problem; Surface; Techniques; Technology; Testing; Time; Variant; Work; base; cognitive neuroscience; cognitive process; heart rhythm; hemodynamics; image reconstruction; improved; magnetic field; nervous system disorder; neuroimaging; novel; physiologic model; public health relevance; reconstruction; relating to nervous system; respiratory; response; social; spatiotemporal; temporal measurement; tool; trend

Project Summary: Fast Functional MRI with Sparse Sampling and Model-Based Reconstruction 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 ultra-fast whole-brain fMRI acquisition approach that expands the spatiotemporal resolution envelope by roughly 3-fold. For example, new methods will allow 2mm isotropic resolution image with 250ms temporal resolution or 1.5mm isotropic resolution images with 500ms temporal resolution. Current state-of-the-art acquisition approaches for fMRI use the simultaneous multislice (SMS, and also known as multiband) method; these single-shot acquisitions use parallel imaging concepts and array coils to provide acceleration in the slice direction and possibly, the in-plane direction as well. Our approach is fundamentally different and uniquely powerful because: 1) it uses parallel imaging concepts for the slice and in-plane directions similar to multiband methods, while 2) also exploiting the temporal dimension that has a substantial data redundancy, and 3) incorporating novel image reconstruction methods based on low- rank (LR) spatiotemporal representations and “sparse” sampling patterns that extend farther out in k-space to improve spatial resolution. Together, these methods promise to enable new faster and more robust fMRI acquisition technology than is currently possible, while also improving spatial resolution. The project has three main aims: (1) Develop new low-rank and sparse (L+S) acquisition and reconstruction methods that model temporal basis functions using multi-coil array data, and account for magnetic field inhomogeneity; (2) Develop and evaluate methods to address several well-recognized issues associated with fMRI acquisition, notably physiological noise, head motion, and susceptibility-induced signal losses; and (3) Evaluate the low-rank and sparse acquisition approach and compare to state-of-the-art SMS (multiband) acquisition methods for task and resting state fMRI. The proposed technology will greatly improve spatiotemporal resolution for a given set of hardware (gradient and RF coils). Faster fMRI will allow improved physiological noise correction, improved statistical power and sensitivity for network analysis, and discovery of temporally ordered network processes. Higher spatial resolution will lead to less partial volume and susceptibility artifacts, improved surface-based analyses, and potentially layer-specific BOLD dynamics. These methods also may lead to fMRI that is more robust to head motion making it more useful for patient studies and studies of language.

项目摘要：具有稀疏采样和基于模型的重建的快速功能 MRI 使用 MRI 的功能性脑成像（功能性 MRI 或 fMRI）在过去 25 年中发展迅速，并且 广泛用于基础认知神经科学研究和术前计划。 用于开发神经和精神疾病的生物标志物以及基于人群的研究， 例如，正常和异常的发育和衰老在成像方面也取得了进展。 用于纠正伪影和分析功能活动的硬件和方法以及处理方法。 该项目的总体目标是开发一种新颖的超快速全脑功能磁共振成像采集方法 将时空分辨率范围扩大了大约 3 倍，例如，新方法将允许 2 毫米。 时间分辨率为 250ms 的各向同性分辨率图像或 500ms 的 1.5mm 各向同性分辨率图像 当前最先进的 fMRI 采集方法使用同步多层切片。 （SMS，也称为多波段）方法；这些单次采集使用并行成像概念和 阵列线圈提供切片方向的加速度，也可能提供面内方向的加速度。 该方法具有根本上的不同且独特强大，因为：1）它使用并行成像概念 切片和面内方向类似于多频带方法，同时 2) 还利用了时间维度 具有大量的数据冗余，并且3）结合了基于低值的新颖图像重建方法 秩（LR）时空表示和“稀疏”采样模式在 k 空间中延伸得更远 这些方法共同提高了空间分辨率，有望实现更快、更稳健的新功能磁共振成像。 采集技术比目前可能的多，同时还提高了空间分辨率。 该项目有三个主要目标：（1）开发新的低秩稀疏（L+S）采集和重建 使用多线圈阵列数据对时间基函数进行建模并考虑磁场的方法 (2) 开发和评估方法来解决与相关的几个公认的问题 fMRI 采集、显着的生理噪声、头部运动和磁化率引起的信号损失；以及 (3) 评估低秩和稀疏采集方法并与最先进的 SMS（多频段）进行比较 任务和静息状态功能磁共振成像的采集方法。 所提出的技术将极大地提高给定硬件集的时空分辨率（梯度 和射频线圈）。更快的功能磁共振成像将允许改进生理噪声校正、改进统计功率和 网络分析和发现时间顺序网络过程的空间敏感性更高。 分辨率将减少部分体积和磁化率伪影，改进基于表面的分析，以及 这些方法还可能导致对头部更稳健的功能磁共振成像。 运动使其对于患者研究和语言研究更加有用。