Afzali Maryam, Pieciak Tomasz, Newman Sharlene, Garyfallidis Eleftherios, Özarslan Evren, Cheng Hu, Jones Derek K
Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom.
AGH University of Science and Technology, Kraków, Poland; LPI, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain.
J Neurosci Methods. 2021 Jan 1;347:108951. doi: 10.1016/j.jneumeth.2020.108951. Epub 2020 Oct 2.
Diffusion MRI is a non-invasive technique to study brain microstructure. Differences in the microstructural properties of tissue, including size and anisotropy, can be represented in the signal if the appropriate method of acquisition is used. However, to depict the underlying properties, special care must be taken when designing the acquisition protocol as any changes in the procedure might impact on quantitative measurements. This work reviews state-of-the-art methods for studying brain microstructure using diffusion MRI and their sensitivity to microstructural differences and various experimental factors. Microstructural properties of the tissue at a micrometer scale can be linked to the diffusion signal at a millimeter-scale using modeling. In this paper, we first give an introduction to diffusion MRI and different encoding schemes. Then, signal representation-based methods and multi-compartment models are explained briefly. The sensitivity of the diffusion MRI signal to the microstructural components and the effects of curvedness of axonal trajectories on the diffusion signal are reviewed. Factors that impact on the quality (accuracy and precision) of derived metrics are then reviewed, including the impact of random noise, and variations in the acquisition parameters (i.e., number of sampled signals, b-value and number of acquisition shells). Finally, yet importantly, typical approaches to deal with experimental factors are depicted, including unbiased measures and harmonization. We conclude the review with some future directions and recommendations on this topic.
扩散磁共振成像(Diffusion MRI)是一种用于研究脑微观结构的非侵入性技术。如果采用适当的采集方法,组织微观结构特性(包括大小和各向异性)的差异可以在信号中体现出来。然而,为了描绘潜在特性,在设计采集方案时必须格外小心,因为采集过程中的任何变化都可能影响定量测量。本文综述了使用扩散磁共振成像研究脑微观结构的最新方法,以及它们对微观结构差异和各种实验因素的敏感性。通过建模,可以将微米尺度下组织的微观结构特性与毫米尺度下的扩散信号联系起来。在本文中,我们首先介绍扩散磁共振成像和不同的编码方案。然后,简要解释基于信号表示的方法和多室模型。综述了扩散磁共振成像信号对微观结构成分的敏感性以及轴突轨迹曲率对扩散信号的影响。接着综述了影响导出指标质量(准确性和精确性)的因素,包括随机噪声的影响以及采集参数(即采样信号数量、b值和采集壳层数)的变化。最后但同样重要的是,描述了处理实验因素的典型方法,包括无偏测量和归一化。我们在综述结尾给出了关于该主题的一些未来方向和建议。