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

使用超高分辨率多重对比扩散 MRI 绘制人脑浅层白质连接组图

• 批准号: 10182286
• 负责人: NIKOLAOS MAKRIS
• 金额: $ 85.88万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10182286
• 关键词: Address; Aging; Algorithms; Alzheimer' s Disease; Anatomy; Architecture; Atlases; Auditory area; Bipolar Disorder; Brain; Brain Diseases; Brain Mapping; Communities; Complex; Computer software; Data; Data Set; Databases; Diffusion Magnetic Resonance Imaging; Disease; Epilepsy; Fascicle; Fiber; Generations; Goals; Health; Human; Huntington Disease; Image; Individual; Iron; Literature; Location; Machine Learning; Magnetic Resonance Imaging; Maps; Methods; Monkeys; Morphology; Myelin; Names; Neuroanatomy; Ontology; Play; Relaxation; Resolution; Role; Schizophrenia; Source; System; Testing; Time; Tissues; Tracer; Translating; Visual; autism spectrum disorder; base; comparative; connectome; deep learning; design; experimental study; human subject; improved; in vivo; inter-individual variation; neurodevelopment; novel; novel strategies; open source; prevent; tractography; ultra high resolution; white matter

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.

摘要 在这项为期5年的R01项目中，题为《使用 超高分辨率多对比度扩散磁共振成像，“我们计划创建首个人脑图谱。 浅层白质(SWM)采用亚毫米超高分辨率扩散磁共振成像(DMRI)。SWM是 位于深层白质和皮质之间。它在神经发育和衰老方面发挥着重要作用， 它与许多疾病有关，包括阿尔茨海默氏症、亨廷顿氏症、癫痫、自闭症 谱系障碍、精神分裂症和双相情感障碍。尽管它在健康和疾病方面具有重要意义，但SWM 在目前对人脑连接体的描述中被极大地低估了。SWM包含简短的u- 定形缔合纤维束，称为u-纤维。到目前为止，多重挑战阻碍了全面 绘制人脑的SWM图。这些挑战包括dMRI数据的空间分辨率不足， 这阻止了使用当前光刻方法的u纤维跟踪，以及小尺寸、高曲率和 U纤维在受试者之间的变异性很高。另一个挑战是缺乏基本的真相信息。我们的 对人类神经解剖学的理解在很大程度上依赖于猴子侵入性示踪剂研究的结果，但 关于猴子SWM的详细神经解剖学还没有被系统地汇编或分析。 我们建议应对这些挑战，以创建迄今为止对SWM的最全面描述。 我们的战略包括使用超高空间分辨率dMRI采集(~700微米各向同性或更好)在多个 回声时间(TE)，用于追踪U纤维的新的dMRI纤维束成像方法，解剖信息机 学习分离u纤维，并从神经解剖学专家生成SWM连接矩阵 猴子追踪研究。此外，我们将开发一个新的本体框架来组织和命名 猴子和人脑的SWM系统。总体而言，这些步骤将实现强大的体内示踪和 以前所未有的空间分辨率捕捉人脑SWM的受试者间变异性。我们的 拟议的交付成果将是第一个全面的、解剖学上精选的人体和 这将使SWM在健康和疾病方面的研究成为可能。我们将公开发布所有图像数据， 地图集、猴子连接矩阵、提取的分束和所有软件都是开源的。