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.

摘要

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