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一种使用扩散 MRI 估计脑区之间解剖连接的算法。

An algorithm to estimate anatomical connectivity between brain regions using diffusion MRI.

机构信息

Department of Robotics, Brain and Cognitive Sciences, Istituto Italiano di Tecnologia, Genova, Via Morego 30, Italy.

出版信息

Magn Reson Imaging. 2013 Apr;31(3):353-8. doi: 10.1016/j.mri.2012.10.001. Epub 2012 Dec 7.

Abstract

The study of anatomical connectivity is essential for interpreting functional MRI data and for establishing how brain areas are linked together into networks to support higher-order functions. Diffusion-weighted MR images (DWI) and tractography provide a unique noninvasive tool to explore the connectional architecture of the brain. The identification of anatomical circuits associated with a specific function can be better accomplished by the joint application of diffusion and functional MRI. In this article, we propose a simple algorithm to identify the set of pathways between two regions of interest. The method is based upon running deterministic tractography from all possible starting positions in the brain and selecting trajectories that intersect both regions. We compare results from single-fiber tractography using diffusion tensor imaging and from multi-fiber tractography using reduced-encoding persistent angular structure (PAS) MRI on standard DWI datasets from healthy human volunteers. Our results show that, in comparison with single-fiber tractography, the multi-fiber technique reveals additional putative routes of connection. We demonstrate highly consistent results of the proposed technique over a cohort of 16 healthy subjects.

摘要

解剖连通性的研究对于解释功能磁共振成像 (fMRI) 数据以及确定大脑区域如何连接成网络以支持更高阶的功能至关重要。弥散加权磁共振成像 (DWI) 和示踪技术提供了一种独特的无创工具,可用于探索大脑的连接结构。通过弥散和功能磁共振成像的联合应用,可以更好地识别与特定功能相关的解剖回路。在本文中,我们提出了一种简单的算法来识别两个感兴趣区域之间的通路集。该方法基于从大脑中的所有可能起始位置运行确定性示踪,并选择与两个区域相交的轨迹。我们比较了使用扩散张量成像进行单纤维示踪和使用基于减少编码的持久角结构 (PAS) MRI 进行多纤维示踪在来自健康人类志愿者的标准 DWI 数据集上的结果。我们的结果表明,与单纤维示踪相比,多纤维技术揭示了额外的潜在连接途径。我们在 16 名健康受试者的队列中证明了该技术的高度一致性结果。

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