MRI Technology for Measurement of Functional and Structural Connectivity in Brain

描述（由申请人提供）：磁共振成像已经证明了在健康和疾病中对人类大脑的结构和功能连接进行非侵入性测绘的潜力。已经出现的主要方法包括扩散成像和静息状态功能连接映射。尽管这些方法具有经过验证的连接映射功能，但它们也面临限制其实用性的技术限制。扩散成像技术存在灵敏度低和数据编码效率低的问题。同样，在全脑连接映射过程中，静息状态功能连接在时间分辨率上受到空间编码的限制。在本研究项目中，我们假设通过多片编码和同步重聚焦采集可以大大提高这些方法中数据采集方案的效率。例如，通过将每个采集周期获得的图像切片数从1片增加到6片，我们既提高了数据采集的灵敏度，又大大缩短了成像时间。这一发展将有助于推动整个新兴扩散方法的发展，这些方法可以在传统的扩散张量图像上更详细地探测水的扩散，从而探测白质和灰质的连通性。同样，它将提高静息状态功能连接映射的时空分辨率和灵敏度。提高灵敏度和减少采集时间将为这些技术的常规临床和临床科学应用铺平道路。在项目的指导阶段，候选人将利用他的信号处理和优化理论专业知识来设计射频脉冲和重建算法，同时获得神经科学和MR物理学的知识来开发采集序列，以及处理和解释大脑连接数据。后期将结合本项目各组成部分进行实验，在临床相关时间框架内获得高信号体内数据，通过DTI、Q-ball、DSI进行静息状态功能连接图谱绘制和弥散成像。该项目符合候选人的长期职业目标，即建立一个高质量的MRI数据采集方法独立研究项目，该项目将充分利用软件算法开发，MR物理和基础神经科学之间的知识和相互作用。指导阶段将在MGH Martinos生物医学成像中心进行，候选人将利用先进的高场MRI设备和专业知识。此外，候选人将利用该中心附属机构（麻省理工学院和哈佛大学）的世界知名教育机会。他的职业发展计划包括MR物理和序列设计、扩散成像和脑连接组学方面的培训、专家咨询和神经科学课程；以及参加研讨会和科学会议。作为启动自己的独立研究项目的一部分，候选人将帮助指导一名将参与该项目的研究生。

DESCRIPTION (provided by applicant): Magnetic resonance imaging has demonstrated the potential for non-invasive mapping of the structural and functional connectivity of the human brain in health and disease. The primary methods that have emerged include diffusion imaging and resting-state functional connectivity mapping. Although these methods have validated capabilities for connectivity mapping, they also face technical limitations which constrain their utility. Diffusion imaging is hampered by low sensitivity and the inefficiency of encoding the diffusion data. Similarly, resting-state functional connectivity is limited in temporal resolution by spatial encoding during whole brain connectivity mapping. In this research project, we hypothesize that we can greatly improve the efficiency of the data acquisition schemes in these methods via multi-slice encoding and simultaneous refocusing acquisition. For example, by increasing the number of images slices obtained per acquisition period from 1 slice to up to 6, we both increase the sensitivity of the data acquisition and greatly reduce the imaging time. This development will help advance an entire class of emerging diffusion methodology which probe the water diffusion and thus white matter and grey matter connectivity in increasing detail over the traditional diffusion tensor image. Similarly, it will increase the spatial-temporal resolution and the sensitivity of resting-state functional connectivity mapping. Improving sensitivity and reduce acquisition time will pave way for routine clinical and clinical science applications of these technologies. During the mentored phase of the project, the candidate will draw on his signal processing and optimization theory expertise to design RF pulses and reconstruction algorithms, while gaining knowledge in neuroscience and MR physic to develop acquisition sequences, as well as process and interpret the brain connectivity data. In the later stage, by combining various components of this project, experiments will be carried out to obtain high signal in vivo data in clinically relevant time frame for resting-state functional connectivity mapping and diffusion imaging via DTI, Q-ball, and DSI. The project fits the candidate's long-term career goal of establishing a high-quality independent research program on data acquisition methodology in MRI that will fully utilizes the knowledge and the inter-play between software algorithm development, MR physic, and the underlying neuroscience. The mentored phase will be carried out at the MGH Martinos Center for Biomedical Imaging where the candidate will take advantage of the advanced high-field MRI facility and expertise. Furthermore, the candidate will make use of the world renowned educational opportunities at the Center's affiliated institutions (MIT and Harvard). His career development plan includes training in MR physics and sequence design, diffusion imaging and brain connectomics, consultations with experts and coursework in neuroscience; and participation in seminars and scientific meetings. As part of initiating his own independent research program, the candidate will help mentor a graduate student who will be involved in this project. PUBLIC HEALTH RELEVANCE: Diffusion imaging and resting-state fMRI are potent methods for visualizing pathology and mapping connectivity in the brain. This work will develop highly efficient data acquisition scheme to increase speed and sensitivity of these methods, thus making them more applicable for clinical use.