Development and application of cognitive neuroimaging tools for quantitative white matter analyses

扩散张量成像（DTI）、磁化转移成像（MTI）和髓磷脂水成像（MWI）等定量白质成像方法比传统MRI方法对脑微结构的变化更敏感。然而，尽管 MRI 硬件取得了进步（例如，更高的磁场强度和更多的接收器通道），改进的数据采集方案（例如，3D 脉冲序列和并行成像技术），以及 DTI、MTI 和 MWI 采集参数的细化，用于量化受试者间差异和/或白质结构纵向变化的数据分析方法仍然相对静态。******特别是，人类白质 MRI 数据的分析传统上采用两种方法之一。体素分析具有高空间分辨率的优点，因此能够检测微小的局部白质变化。然而，如果白质的大小或位置因人而异，则这种方法在跨受试者分析中会受到很大影响，因此不太适合对患有创伤性脑损伤或多发性硬化症等白质疾病的患者进行分组分析。另一方面，感兴趣区域 (ROI) 分析从较大的预先确定的大脑区域中提取数据，从而允许受试者之间的病变大小和位置存在微小差异（即，只要它们位于所选 ROI 内的某个位置），但代价是对微小局部变化的敏感性。然而，这些 ROI 方法还需要先验假设选择哪个大脑区域（或一组或多个区域）以及每个 ROI 应该有多大，从而导致固有的敏感性与特异性的权衡。******为了解决其中的一些限制，我的小组将追求以下三个相互关联的研究目标：******1。使用功能磁共振成像引导的 DTI 创建一组功能定义的白质图谱；***2。开发新颖的基于束的分析方法来测量白质投资回报率；和***3。使用上述图集和基于束的分析方法，结合功能磁共振成像和认知测试，研究结构连接、功能连接和认知表现之间的关系。 *****生物医学工程和生理学研究生项目将总共培养 4 名研究生（即第一个目标为 2 名硕士生，第二和第三目标各为 1 名博士生）。 ******最后，通过这项研究获得的知识将进一步阐明大脑结构、大脑功能和认知表现之间的复杂关系；由于由此产生的大脑图谱和分析软件可能在整个系统和认知神经科学领域具有广泛的应用，我们计划免费分发这些工具，以便加拿大和国外的其他神经影像研究人员可以使用它们。**

Quantitative white matter imaging methods such as diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), and myelin water imaging (MWI) are more sensitive than conventional MRI methods to changes in brain microstructure. However, despite advances in MRI hardware (e.g., higher magnetic field strengths and more receiver channels), improved data acquisition schemes (e.g., 3D pulse sequences and parallel imaging techniques), and the refinement of DTI, MTI and MWI acquisition parameters, data analysis approaches to quantify inter-subject differences and/or longitudinal changes in white matter structure have remained relatively static.******In particular, analyses of human white matter MRI data have traditionally taken one of two approaches. Voxel-wise analyses have the advantage of high spatial resolution and are therefore able to detect small, localized white matter changes. However, this approach suffers greatly in cross-subject analyses if sizes or locations of the white matter changes vary from one individual to the next, and are therefore not well-suited for group-wise analysis of patients with traumatic brain injuries or white matter disorders such as Multiple Sclerosis. On the other hand, region-of-interest (ROI) analyses extract data from larger pre-determined brain areas, thereby allowing for small differences in lesion sizes and locations across subjects (i.e., as long as they are somewhere within the chosen ROI) at the expense of sensitivity to small, localized changes. However, these ROI approaches also require a priori assumptions about which brain region (or set or regions) to choose and how large each ROI should be, leading to inherent sensitivity vs. specificity trade-offs.******In order to address several of these limitations, my group will pursue the following three interrelated research objectives:******1. Creating a set of functionally-defined white matter atlases using fMRI-guided DTI;***2. Developing novel tract-based analysis methods to measure along white matter ROIs; and***3. Using the aforementioned atlases and tract-based analysis methods in conjunction with fMRI and cognitive testing to study relationships between structural connectivity, functional connectivity and cognitive performance.******In total, 4 graduate students will be trained through the Biomedical Engineering and Physiology Graduate Programs (i.e., 2 MSc students for the first objective, and 1 PhD student each for the second and third objectives). ******Finally, the knowledge gained through this research will further elucidate the complex relationships between brain structure, brain function and cognitive performance; and since the resulting brain atlases and analysis software are likely to have wide-ranging applications throughout systems and cognitive neuroscience, we plan to freely distribute these tools so that they can be used by other neuroimaging researchers within Canada and abroad.**