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教程:扩散磁共振成像与结构连接组学指南

Tutorial: a guide to diffusion MRI and structural connectomics.

作者信息

Shamir Ittai, Assaf Yaniv

机构信息

Department of Neurobiology, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.

Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.

出版信息

Nat Protoc. 2025 Feb;20(2):317-335. doi: 10.1038/s41596-024-01052-5. Epub 2024 Sep 4.

Abstract

Diffusion magnetic resonance imaging (dMRI) is a versatile imaging technique that has gained popularity thanks to its sensitive ability to measure displacement of water molecules within a living tissue on a micrometer scale. Although dMRI has been around since the early 1990s, its applications are constantly evolving, primarily regarding the inference of structural connectomics from nerve fiber trajectories. However, these applications require expertise in image processing and statistics, and it can be difficult for a newcomer to choose an appropriate pipeline to fit their research needs, not least because dMRI is such a flexible methodology that dozens of acquisition and analysis pipelines have been developed over the years. This introductory guide is designed for graduate students and researchers in the neuroscience community who are interested in integrating this new methodology regardless of their background in neuroimaging and computational tools. The guide provides a brief overview of the basic dMRI methodologies but focuses on its applications in neuroplasticity and connectomics. The guide starts with dMRI experimental designs and a complete step-by-step pipeline for structural connectomics. The following section covers the basics of dMRI, including parameters and clinical applications (apparent diffusion coefficient, mean diffusivity, fractional anisotropy and microscopic fractional anisotropy), as well as different approaches and models. The final section focuses on structural connectomics, covering subjects from fiber tracking (techniques, evaluation and limitations) to structural networks (constructing, analyzing and visualizing a network).

摘要

扩散磁共振成像(dMRI)是一种用途广泛的成像技术,由于其能够在微米尺度上灵敏地测量活体组织内水分子的位移,因而受到广泛关注。尽管dMRI自20世纪90年代初就已出现,但其应用仍在不断发展,主要涉及从神经纤维轨迹推断结构连接组学。然而,这些应用需要图像处理和统计学方面的专业知识,新手可能很难选择合适的流程来满足其研究需求,尤其是因为dMRI是一种非常灵活的方法,多年来已经开发出了数十种采集和分析流程。本入门指南是为神经科学界的研究生和研究人员设计的,他们对整合这种新方法感兴趣,无论其在神经成像和计算工具方面的背景如何。该指南简要概述了基本的dMRI方法,但重点介绍了其在神经可塑性和连接组学中的应用。指南首先介绍dMRI实验设计以及用于结构连接组学的完整分步流程。下一部分涵盖dMRI的基础知识,包括参数和临床应用(表观扩散系数、平均扩散率、分数各向异性和微观分数各向异性),以及不同的方法和模型。最后一部分重点介绍结构连接组学,涵盖从纤维追踪(技术、评估和局限性)到结构网络(构建、分析和可视化网络)等主题。

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