Suppr超能文献

基于扩散的人类听辐射束轨迹图谱。

Diffusion-based tractography atlas of the human acoustic radiation.

机构信息

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, USA.

Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto (TN), Italy.

出版信息

Sci Rep. 2019 Mar 11;9(1):4046. doi: 10.1038/s41598-019-40666-8.

Abstract

Diffusion MRI tractography allows in-vivo characterization of white matter architecture, including the localization and description of brain fibre bundles. However, some primary bundles are still only partially reconstructed, or not reconstructed at all. The acoustic radiation (AR) represents a primary sensory pathway that has been largely omitted in many tractography studies because its location and anatomical features make it challenging to reconstruct. In this study, we investigated the effects of acquisition and tractography parameters on the AR reconstruction using publicly available Human Connectome Project data. The aims of this study are: (i) using a subgroup of subjects and a reference AR for each subject, define an optimum set of parameters for AR reconstruction, and (ii) use the optimum parameters set on the full group to build a tractography-based atlas of the AR. Starting from the same data, the use of different acquisition and tractography parameters lead to very different AR reconstructions. Optimal results in terms of topographical accuracy and correspondence to the reference were obtained for probabilistic tractography, high b-values and default tractography parameters: these parameters were used to build an AR probabilistic tractography atlas. A significant left-hemispheric lateralization was found in the AR reconstruction of the 34 subjects.

摘要

弥散磁共振纤维束追踪技术可用于对活体的白质结构进行特征描述,包括对脑纤维束的定位和描述。然而,一些主要的纤维束仍未完全重建,或者根本没有重建。声辐射(AR)是一种主要的感觉通路,在许多纤维束追踪研究中都被大量忽略,因为它的位置和解剖特征使得其难以重建。在这项研究中,我们使用公开的人类连接组计划数据来研究采集和纤维束追踪参数对 AR 重建的影响。本研究的目的是:(i)使用子组的Subject 和每个 Subject 的参考 AR,定义 AR 重建的最佳参数集;(ii)使用完整组的最佳参数集构建 AR 的基于纤维追踪的图谱。从相同的数据开始,使用不同的采集和纤维束追踪参数会导致非常不同的 AR 重建。在概率纤维追踪、高 b 值和默认纤维追踪参数方面,我们获得了在地形准确性和与参考物的对应性方面的最佳结果:这些参数被用于构建 AR 概率纤维追踪图谱。在 34 名受试者的 AR 重建中发现了显著的左侧偏侧化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8711/6411970/5f75862f6b6e/41598_2019_40666_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验