Investigating the Prevalence of Complex Fiber Configurations in White Matter Tissue with Diffusion Magnetic Resonance Imaging
Investigating the Prevalence of Complex Fiber Configurations in White Matter Tissue with Diffusion Magnetic Resonance Imaging
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DOI：
10.1002/hbm.22099
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发表时间：
2013-11-01
影响因子：
4.8
通讯作者：
Sijbers, Jan
中科院分区：
文献类型：
--
作者：
Jeurissen, Ben;Leemans, Alexander;Sijbers, Jan
人们早就认识到，扩散张量模型是不合适的复杂的纤维结构的特点，导致张量衍生的措施，如主特征向量和分数各向异性是不可靠的或误导这些地区。然而，关于这一问题在实践中的影响仍有争议。最近一项使用贝叶斯自动相关检测（ARD）多室模型的研究表明，三分之一的白色物质（WM）体素包含交叉纤维，这个值虽然已经很重要，但可能被低估了。本研究的目的是提供更可靠的估计受影响的体素的比例，每个WM体素内的纤维方向的数量，以及对张量衍生分析的影响，使用大型，高质量的扩散加权数据集，重建参数专门为此任务进行了优化。使用了两种重建算法：约束球面反卷积（CSD）和先前研究中使用的ARD方法。我们估计包含交叉纤维的WM体素的比例近似为90%（使用CSD）和63%（使用ARD）。这两个值都比以前报道的要高得多，强烈表明扩散张量模型在绝大多数WM区域是不够的。这对依赖于该模型的下游处理应用，特别是纤维束成像，以及各向异性和径向/轴向扩散率测量的解释具有严重影响。《脑地图》34：2747-2766，2013年。(c)2012 Wiley Periodicals，Inc.
It has long been recognized that the diffusion tensor model is inappropriate to characterize complex fiber architecture, causing tensor-derived measures such as the primary eigenvector and fractional anisotropy to be unreliable or misleading in these regions. There is however still debate about the impact of this problem in practice. A recent study using a Bayesian automatic relevance detection (ARD) multicompartment model suggested that a third of white matter (WM) voxels contain crossing fibers, a value that, whilst already significant, is likely to be an underestimate. The aim of this study is to provide more robust estimates of the proportion of affected voxels, the number of fiber orientations within each WM voxel, and the impact on tensor-derived analyses, using large, high-quality diffusion-weighted data sets, with reconstruction parameters optimized specifically for this task. Two reconstruction algorithms were used: constrained spherical deconvolution (CSD), and the ARD method used in the previous study. We estimate the proportion of WM voxels containing crossing fibers to be approximate to 90% (using CSD) and 63% (using ARD). Both these values are much higher than previously reported, strongly suggesting that the diffusion tensor model is inadequate in the vast majority of WM regions. This has serious implications for downstream processing applications that depend on this model, particularly tractography, and the interpretation of anisotropy and radial/axial diffusivity measures. Hum Brain Mapp 34:2747-2766, 2013. (c) 2012 Wiley Periodicals, Inc.