APPLICATION OF A NOVEL QUANTITATIVE TRACTOGRAPHY-BASED ANALYSIS OF DIFFUSION TENSOR IMAGING TO EXAMINE FIBER BUNDLE LENGTH IN HUMAN CEREBRAL WHITE MATTER.
APPLICATION OF A NOVEL QUANTITATIVE TRACTOGRAPHY-BASED ANALYSIS OF DIFFUSION TENSOR IMAGING TO EXAMINE FIBER BUNDLE LENGTH IN HUMAN CEREBRAL WHITE MATTER.
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DOI：
10.21300/18.1.2016.21
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发表时间：
2016-04
影响因子：
0.5
通讯作者：
Paul RH
中科院分区：
文献类型：
--
作者：
Baker LM;Cabeen RP;Cooley S;Laidlaw DH;Paul RH
本文综述了弥散磁共振成像（dMRI）中基于长度的脑白色物质纤维束分析的基本方法和最新应用。扩散加权成像（DWI）是一种dMRI技术，它使用水的随机运动来探测大脑中的组织微观结构。扩散张量成像（DTI）是DWI的扩展，使用基于体素的标量度量或基于纤维束成像的分析来测量脑白色物质中水扩散的幅度和方向。最近，基于扩散张量成像（qtDTI）技术的定量纤维束成像已经被开发用于帮助量化白色物质纤维束的聚集结构解剖特性，包括束扩散的标量度量和更复杂的形态测量特性，诸如纤维束长度（FBL）。与传统的标量扩散度量不同，FBL反映了穿过大脑的白色物质通路的方向和曲率，并且对整个纤维束成像模型内的变化敏感。在本文中，我们讨论了这种方法的应用，提供了新的见解大脑的组织和功能。我们还讨论了通过更复杂的解剖模型和qtDTI新应用的潜在领域来改进方法的机会。
This paper reviews basic methods and recent applications of length-based fiber bundle analysis of cerebral white matter using diffusion magnetic resonance imaging (dMRI). Diffusion weighted imaging (DWI) is a dMRI technique that uses the random motion of water to probe tissue microstructure in the brain. Diffusion tensor imaging (DTI) is an extension of DWI that measures the magnitude and direction of water diffusion in cerebral white matter, using either voxel-based scalar metrics or tractography-based analyses. More recently, quantitative tractography based on diffusion tensor imaging (qtDTI) technology has been developed to help quantify aggregate structural anatomical properties of white matter fiber bundles, including both scalar metrics of bundle diffusion and more complex morphometric properties, such as fiber bundle length (FBL). Unlike traditional scalar diffusion metrics, FBL reflects the direction and curvature of white matter pathways coursing through the brain and is sensitive to changes within the entire tractography model. In this paper, we discuss applications of this approach to date that have provided new insights into brain organization and function. We also discuss opportunities for improving the methodology through more complex anatomical models and potential areas of new application for qtDTI.