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: 10623234
• 负责人: NIKOLAOS MAKRIS
• 金额: $ 81.15万
• 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/10623234
• 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; Shapes; Source; System; Testing; Tissues; Tracer; Translating; Visual; autism spectrum disorder; comparative; connectome; deep learning; design; experimental study; human subject; improved; in vivo; inter-individual variation; millimeter; 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.

抽象的 在这个为期5年的R01项目中，标题为“绘制人脑的表面白质连接组 超高分辨率多对比扩散MRI，“我们建议创建人脑的第一个地图集 浅表白质（SWM）使用亚毫米超高分辨率MRI（DMRI）。 位于深层白质和皮质之间。 它与包括阿尔茨海默氏症，亨廷顿，癫痫，自闭症在内的大量疾病有关 谱系障碍，精神分裂症和双相情感障碍。 当前对人脑连接的描述中的代表性差不多。 形状的关联纤维捆绑包称为U纤维。 这些挑战的映射包括DMRI数据的空间分辨率不足 这可以防止使用当前拖拉术方法以及小尺寸，高曲率和 U-纤维的高个子间差异是额外的挑战 对人类神经解剖学的理解在很大程度上取决于猴子的侵入性示踪剂研究的结果，但是 猴子游泳的详细神经解剖学尚未进行系统的编译或分析。 我们建议解决迄今为止游泳的最多曲目描述的挑战。 我们的策略包括使用超高空间分辨率DMRI获取 Echo Times（TE），新型的DMRI Tractographhy方法，专为追踪U纤维，解剖学知情机器而设计 学会对U纤维进行细化，并从 猴子示踪剂研究。 猴子和人类大脑的SWM系统。 捕获未经预言的空间分辨率的人脑间变异性 支撑的可交付成果将是人类游泳和 猴子，这将使您的健康和疾病中的粪便公开释放所有图像数据 Tractographhy Atlasses，Monkey Connectivity Matriss，提取筋膜和所有软件作为开源。

项目成果

Accelerating joint relaxation-diffusion MRI by integrating time division multiplexing and simultaneous multi-slice (TDM-SMS) strategies.

• DOI: 10.1002/mrm.29160
• 发表时间: 2022-06
• 期刊: MAGNETIC RESONANCE IN MEDICINE
• 影响因子: 3.3
• 作者: Ji, Yang;Hoge, W. Scott;Gagoski, Borjan;Westin, Carl-Fredrik;Rathi, Yogesh;Ning, Lipeng
• 通讯作者: Ning, Lipeng