Brigham and Women's Hospital, Harvard Medical School, Boston, USA.
Department of Computer Science, University of Verona, Verona, Italy.
Neuroimage. 2022 Apr 1;249:118870. doi: 10.1016/j.neuroimage.2021.118870. Epub 2022 Jan 1.
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.
扩散磁共振成像(dMRI)纤维束示踪是一种高级的成像技术,能够在体重建大脑白质的宏观连接。它为使用连接度量或组织微观结构对大脑的结构连接进行定量映射提供了重要工具。在过去的二十年中,使用 dMRI 纤维束示踪研究大脑连接在神经影像学研究领域中发挥了重要作用。在本文中,我们提供了一个高级概述,说明如何使用纤维束示踪来实现大脑结构连接的定量分析,包括在健康和疾病中的应用。我们重点介绍两种定量分析纤维束示踪的方法,包括:1)束特异性分析,指的是通常是基于假设的研究,研究特定的解剖纤维束;2)连接组学分析,指的是更基于数据的研究,通常研究整个大脑的结构连接。我们首先回顾了定量分析纤维束示踪中三个主要处理步骤所涉及的方法学,包括纤维束示踪校正、分割和量化的方法。对于每个步骤,我们旨在描述方法学选择、它们的流行程度以及潜在的优缺点。然后,我们回顾了使用定量纤维束示踪方法研究大脑白质的研究,重点介绍了神经发育、衰老、神经退行性疾病、精神障碍和神经外科方面的应用。我们得出的结论是,虽然在方法学技术和应用范围方面已经取得了相当大的进展,但在定量分析纤维束示踪方面仍然没有关于“最佳”方法学的共识,研究人员在研究和临床应用中解释结果时应保持谨慎。