关键词: diffusion magnetic resonance imaging tractography tractometry vision white matter

Mesh : Humans White Matter / diagnostic imaging Visual Pathways / diagnostic imaging Diffusion Tensor Imaging / methods Brain / diagnostic imaging Diffusion Magnetic Resonance Imaging / methods Image Processing, Computer-Assisted / methods Vision Disorders / diagnostic imaging physiopathology

来  源:   DOI:10.2463/mrms.rev.2024-0007   PDF(Pubmed)

Abstract:
Diffusion-weighted MRI (dMRI) provides a unique non-invasive view of human brain tissue properties. The present review article focuses on tractometry analysis methods that use dMRI to assess the properties of brain tissue within the long-range connections comprising brain networks. We focus specifically on the major white matter tracts that convey visual information. These connections are particularly important because vision provides rich information from the environment that supports a large range of daily life activities. Many of the diseases of the visual system are associated with advanced aging, and tractometry of the visual system is particularly important in the modern aging society. We provide an overview of the tractometry analysis pipeline, which includes a primer on dMRI data acquisition, voxelwise model fitting, tractography, recognition of white matter tracts, and calculation of tract tissue property profiles. We then review dMRI-based methods for analyzing visual white matter tracts: the optic nerve, optic tract, optic radiation, forceps major, and vertical occipital fasciculus. For each tract, we review background anatomical knowledge together with recent findings in tractometry studies on these tracts and their properties in relation to visual function and disease. Overall, we find that measurements of the brain\'s visual white matter are sensitive to a range of disorders and correlate with perceptual abilities. We highlight new and promising analysis methods, as well as some of the current barriers to progress toward integration of these methods into clinical practice. These barriers, such as variability in measurements between protocols and instruments, are targets for future development.
摘要:
扩散加权MRI(dMRI)提供了人类脑组织特性的独特非侵入性视图。本综述文章重点介绍了使用dMRI来评估包含脑网络的远程连接中脑组织的特性的示差分析方法。我们特别关注传达视觉信息的主要白质束。这些联系特别重要,因为视觉从支持大量日常生活活动的环境中提供了丰富的信息。视觉系统的许多疾病与晚期衰老有关,视觉系统的示踪测量在现代老龄化社会中尤为重要。我们提供了示差分析管道的概述,其中包括dMRI数据采集的入门,体素模型拟合,纤维束造影,白质束的识别,和计算管道组织属性概况。然后,我们回顾了基于dMRI的视觉白质束分析方法:视神经,视神经束,光学辐射,镊子少校,和垂直枕骨束。对于每个管道,我们回顾了背景解剖学知识,以及对这些束及其与视觉功能和疾病有关的特性的示踪术研究的最新发现。总的来说,我们发现,大脑视觉白质的测量对一系列疾病敏感,并与感知能力相关。我们强调新的和有前途的分析方法,以及目前将这些方法整合到临床实践中的一些障碍。这些障碍,例如协议和仪器之间测量的可变性,是未来发展的目标。
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