Mapping the superficial white matter connectome of the human brain using ultra high resolution multi-contrast diffusion MRI

摘要 在这个为期5年的R 01项目中，该项目题为“利用大脑皮层绘制人脑表面白色物质连接体”。 超高分辨率多对比度扩散MRI，“我们建议创建人类大脑的第一个图谱， 表面白色物质（SWM）使用亚毫米超高分辨率扩散MRI（dMRI）。SWM是 位于深层白色物质和皮层之间。它在神经发育和衰老中起着重要作用， 它与许多疾病有关，包括阿尔茨海默氏症、亨廷顿舞蹈症、癫痫症、自闭症 谱系障碍、精神分裂症和双相情感障碍。尽管SWM在健康和疾病方面具有重要意义， 在目前对人脑连接体的描述中，这种现象被严重低估。SWM包含短，u- 形状的联合纤维束称为U-纤维。迄今为止，多重挑战阻碍了全面 人类大脑SWM的映射。这些挑战包括dMRI数据的空间分辨率不足， 其防止使用当前纤维束成像方法的U纤维追踪，以及小尺寸、高曲率， U形纤维的受试者间变异性高。另一个挑战是缺乏地面实况信息。我们 对人类神经解剖学的理解在很大程度上依赖于对猴子进行的侵入性示踪研究的结果， 猴子SWM的详细神经解剖学尚未被系统地汇编或分析。 我们建议应对这些挑战，以创建迄今为止最全面的SWM描述。 我们的策略包括使用超高空间分辨率dMRI采集（~700µm各向同性或更好）， 回波时间（TE），设计用于追踪u纤维的新型dMRI纤维束成像方法，解剖学信息机器 学习包裹u-纤维，以及SWM连接矩阵的专家神经解剖学生成， 猴子示踪研究。此外，我们将开发一个新的本体框架来组织和命名 猴子和人类大脑的SWM系统。总体而言，这些步骤将实现稳健的体内追踪， 以前所未有的空间分辨率捕获人脑SWM的受试者间变化。我们 拟议的可交付成果将是第一个全面的，解剖学策划的人体SWM地图集， 猴子，这将使SWM在健康和疾病方面的研究成为可能。我们将公开所有图像数据， tractography地图集，猴子连接矩阵，提取的分册，以及所有开源软件。

Abstract In this 5-year R01 project entitled “Mapping the superficial white matter connectome of the human brain using ultra high resolution multi-contrast diffusion MRI,” we propose to create the first atlas of the human brain’s superficial white matter (SWM) using sub-millimeter ultra high resolution diffusion MRI (dMRI). The SWM is located between the deep white matter and the cortex. It plays an important role in neurodevelopment and aging, and it has been implicated in a large number of diseases including Alzheimer’s, Huntington’s, epilepsy, autism spectrum disorder, schizophrenia, and bipolar disorder. Despite its significance in health and disease, the SWM is vastly underrepresented in current descriptions of the human brain connectome. The SWM contains short, u- shaped association fiber bundles called u-fibers. Multiple challenges have thus far prevented comprehensive mapping of the human brain’s SWM. These challenges include the inadequate spatial resolution of dMRI data, which prevents u-fiber tracing using current tractography methods, as well as the small size, high curvature, and high inter-subject variability of the u-fibers. An additional challenge is the lack of ground truth information. Our understanding of human neuroanatomy relies heavily on the results of invasive tracer studies in monkeys, but the detailed neuroanatomy of the SWM in monkeys has not yet been systematically compiled or analyzed. We propose to address these challenges to create the most comprehensive description of the SWM to date. Our strategy includes using ultra high spatial resolution dMRI acquisitions (~700µm isotropic or better) at multiple echo times (TE), novel dMRI tractography methods designed for tracing u-fibers, anatomically informed machine learning to parcellate the u-fibers, and expert neuroanatomical generation of the SWM connectivity matrix from monkey tracer studies. Furthermore, we will develop a novel ontological framework to organize and name the SWM systems of the monkey and human brains. Overall, these steps will enable robust in-vivo tracing and capturing of inter-subject variability of the SWM of the human brain at an unprecedented spatial resolution. Our proposed deliverables will be the first comprehensive, anatomically curated atlases of the SWM in human and monkey, which will enable the study of the SWM in health and disease. We will publicly release all image data, tractography atlases, monkey connectivity matrices, extracted fascicles, and all software as open source.