School of Biomedical Engineering, The University of Sydney, Sydney, New South Wales, Australia.
Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia.
Magn Reson Med. 2023 Mar;89(3):1207-1220. doi: 10.1002/mrm.29496. Epub 2022 Oct 26.
Brain templates provide an essential standard space for statistical analysis of brain structure and function. Despite recent advances, diffusion MRI still lacks a template of fiber orientation distribution (FOD) and tractography that is unbiased for both white and gray matter. Therefore, we aim to build up a set of such templates for better white-matter analysis and joint structural and functional analysis.
We have developed a multimodal registration method to leverage the complementary information captured by T -weighted, T -weighted, and diffusion MRI, so that a coherent transformation is generated to register FODs into a common space and average them into a template. Consequently, the anatomically constrained fiber-tracking method was applied to the FOD template to generate a tractography template. Fiber-centered functional connectivity analysis was then performed as an example of the benefits of such an unbiased template.
Our FOD template preserves fine structural details in white matter and also, importantly, clear folding patterns in the cortex and good contrast in the subcortex. Quantitatively, our templates show better individual-template agreement at the whole-brain scale and segmentation scale. The tractography template aligns well with the gray matter, which led to fiber-centered functional connectivity showing high cross-group consistency.
We have proposed a novel methodology for building a tissue-unbiased FOD and anatomically constrained tractography template based on multimodal registration. Our templates provide a standard space and statistical platform for not only white-matter analysis but also joint structural and functional analysis, therefore filling an important gap in multimodal neuroimage analysis.
大脑模板为大脑结构和功能的统计分析提供了一个基本的标准空间。尽管最近取得了进展，但弥散磁共振成像仍然缺乏一个不受白质和灰质影响的纤维方向分布（FOD）和轨迹的模板。因此，我们旨在建立这样的模板集，以更好地进行白质分析和联合结构与功能分析。
我们开发了一种多模态配准方法，利用 T 加权、T 加权和弥散磁共振成像所捕获的互补信息，生成一个连贯的变换，将 FOD 配准到共同空间并将其平均到模板中。因此，应用基于解剖结构的纤维追踪方法到 FOD 模板中，生成轨迹模板。然后，进行纤维中心功能连接分析，作为这种无偏模板的优势的一个例子。
我们的 FOD 模板保留了白质的精细结构细节，并且重要的是，还保留了皮质的清晰折叠模式和皮质下结构的良好对比度。定量地，我们的模板在全脑和分割尺度上显示出更好的个体模板一致性。轨迹模板与灰质对齐良好，这导致纤维中心功能连接显示出较高的跨组一致性。
我们提出了一种基于多模态配准的构建无偏 FOD 和基于解剖结构的轨迹模板的新方法。我们的模板不仅为白质分析，也为联合结构和功能分析提供了一个标准空间和统计平台，因此填补了多模态神经影像分析中的一个重要空白。
