Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis
Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis
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DOI：
10.1016/j.media.2006.07.003
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发表时间：
2006-10-01
影响因子：
10.9
通讯作者：
Gerig, Guido
中科院分区：
文献类型：
--
作者：
Corouge, Isabelle;Fletcher, P. Thomas;Gerig, Guido
定量扩散张量成像（DTI）已成为研究白色物质性质和人脑纤维束几何结构的主要成像手段。临床研究主要集中在局部统计的分数各向异性（FA）和平均扩散率（MD）来自张量。现有的分析技术没有充分考虑到测量是张量，因此需要适当的插值和张量的统计，以及感兴趣的区域是具有复杂空间几何形状的纤维束。我们提出了一个新的框架，定量牵引为导向的DTI分析，系统地包括张量插值和平均，使用非线性黎曼对称空间。一种新的测量张量各向异性，称为测地线各向异性（GA）的应用和FA相比。因此，感兴趣的束由归因于在横截面内计算的张量统计（平均值和方差）的内侧脊柱的几何形状表示。我们的方法的可行性证明了一个单一的数据集的各种纤维束。一项基于同一受试者的六次重复扫描的验证研究评估了这种新的DTI数据分析框架的可重复性。(C)2006 Elsevier B.V.保留所有权利。
Quantitative diffusion tensor imaging (DTI) has become the major imaging modality to study properties of white matter and the geometry of fiber tracts of the human brain. Clinical studies mostly focus on regional statistics of fractional anisotropy (FA) and mean diffusivity (MD) derived from tensors. Existing analysis techniques do not sufficiently take into account that the measurements are tensors, and thus require proper interpolation and statistics of tensors, and that regions of interest are fiber tracts with complex spatial geometry. We propose a new framework for quantitative tract-oriented DTI analysis that systematically includes tensor interpolation and averaging, using nonlinear Riemannian symmetric space. A new measure of tensor anisotropy, called geodesic anisotropy (GA) is applied and compared with FA. As a result, tracts of interest are represented by the geometry of the medial spine attributed with tensor statistics (average and variance) calculated within cross-sections. Feasibility of our approach is demonstrated on various fiber tracts of a single data set. A validation study, based on six repeated scans of the same subject, assesses the reproducibility of this new DTI data analysis framework. (C) 2006 Elsevier B.V. All rights reserved.