Structural connectome construction using constrained spherical deconvolution in multi-shell diffusion-weighted magnetic resonance imaging.

IF 13.1 1区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Marlene Tahedl, J-Donald Tournier, Robert E Smith
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引用次数: 0

Abstract

Connectional neuroanatomical maps can be generated in vivo by using diffusion-weighted magnetic resonance imaging (dMRI) data, and their representation as structural connectome (SC) atlases adopts network-based brain analysis methods. We explain the generation of high-quality SCs of brain connectivity by using recent advances for reconstructing long-range white matter connections such as local fiber orientation estimation on multi-shell dMRI data with constrained spherical deconvolution, which yields both increased sensitivity to detecting crossing fibers compared with competing methods and the ability to separate signal contributions from different macroscopic tissues, and improvements to streamline tractography such as anatomically constrained tractography and spherical-deconvolution informed filtering of tractograms, which have increased the biological accuracy of SC creation. Here, we provide step-by-step instructions to creating SCs by using these methods. In addition, intermediate steps of our procedure can be adapted for related analyses, including region of interest-based tractography and quantification of local white matter properties. The associated software MRtrix3 implements the relevant tools for easy application of the protocol, with specific processing tasks deferred to components of the FSL software. The protocol is suitable for users with expertise in dMRI and neuroscience and requires between 2 h and 13 h to complete, depending on the available computational system.

基于约束球面反褶积的多壳扩散加权磁共振成像结构连接体构建。
利用弥散加权磁共振成像(diffusion weighted magnetic resonance imaging, dMRI)数据在体内生成连接神经解剖图谱,并采用基于网络的脑分析方法将其表示为结构连接组(structural connectome, SC)图谱。我们解释了高质量脑连接性SCs的产生,通过使用最近的进展来重建远程白质连接,如局部纤维方向估计多壳dMRI数据与约束球形反卷积,这产生了检测交叉纤维的灵敏度比竞争方法更高,并且能够分离来自不同宏观组织的信号贡献。以及流线束造影的改进,如解剖学约束束造影和束图的球形反卷积信息滤波,这增加了SC创建的生物学准确性。在这里,我们提供了使用这些方法创建sc的分步说明。此外,我们程序的中间步骤可以适用于相关分析,包括基于兴趣区域的束状图和局部白质特性的量化。相关软件MRtrix3实现了相关工具,方便了协议的应用,将特定的处理任务推迟到FSL软件的组件中。该协议适用于具有dMRI和神经科学专业知识的用户,需要2到13小时才能完成,具体取决于可用的计算系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nature Protocols
Nature Protocols 生物-生化研究方法
CiteScore
29.10
自引率
0.70%
发文量
128
审稿时长
4 months
期刊介绍: Nature Protocols focuses on publishing protocols used to address significant biological and biomedical science research questions, including methods grounded in physics and chemistry with practical applications to biological problems. The journal caters to a primary audience of research scientists and, as such, exclusively publishes protocols with research applications. Protocols primarily aimed at influencing patient management and treatment decisions are not featured. The specific techniques covered encompass a wide range, including but not limited to: Biochemistry, Cell biology, Cell culture, Chemical modification, Computational biology, Developmental biology, Epigenomics, Genetic analysis, Genetic modification, Genomics, Imaging, Immunology, Isolation, purification, and separation, Lipidomics, Metabolomics, Microbiology, Model organisms, Nanotechnology, Neuroscience, Nucleic-acid-based molecular biology, Pharmacology, Plant biology, Protein analysis, Proteomics, Spectroscopy, Structural biology, Synthetic chemistry, Tissue culture, Toxicology, and Virology.
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