Exploring the 3D geometry of the diffusion kurtosis tensor-Impact on the development of robust tractography procedures and novel biomarkers
Exploring the 3D geometry of the diffusion kurtosis tensor-Impact on the development of robust tractography procedures and novel biomarkers
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DOI：
10.1016/j.neuroimage.2015.02.004
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发表时间：
2015-05-01
期刊：
影响因子：
5.7
通讯作者：
Ferreira, Hugo Alexandre
中科院分区：
文献类型：
--
作者：
Henriques, Rafael Neto;Correia, Marta Morgado;Ferreira, Hugo Alexandre
扩散峰度成像（DKI）是一种扩散加权技术，它克服了常用扩散张量成像方法的局限性。该技术通过扩散峰度张量（KT）模拟水扩散的非高斯行为，该扩散峰度张量可用于提供组织异质性的指标和组织微观结构的空间结构的更好表征。在这项研究中，KT的几何形状阐明使用多房室模型，其中考虑到细胞内和细胞外介质之间的扩散异质性，以及每个模型参数和合成噪声的结果的敏感性生成的合成数据。此外，基于KT的最大值垂直于排列良好的纤维的方向分布的假设，提出了一种新的算法，用于直接从KT估计纤维方向，并与文献中先前提出的基于DKI的取向分布函数（ODF）估计提取的纤维方向进行比较。合成数据结果表明，对于以高交叉角交叉的纤维，直接从KT提取的方向估计比基于DKI的ODF估计方法（DKI-ODF）具有更小的误差。然而，所提出的方法表现出较小的角分辨率和较低的稳定性的模拟参数的变化。在真实的数据上，对这些KT纤维估计进行的纤维束成像表明，当使用5个b值进行扩散采集时，在分辨到达中央前皮质的外侧胼胝体纤维方面，比基于DKI的ODF具有更高的灵敏度。使用更快的采集方案，基于KT的纤维束成像没有显示出比DKI-ODF程序更好的性能。然而，它表明，直接KT纤维估计更适合计算广义版本的径向峰度图。(C)2015年，作者。爱思唯尔公司出版
Diffusion kurtosis imaging (DKI) is a diffusion-weighted technique which overcomes limitations of the commonly used diffusion tensor imaging approach. This technique models non-Gaussian behaviour of water diffusion by the diffusion kurtosis tensor (KT), which can be used to provide indices of tissue heterogeneity and a better characterisation of the spatial architecture of tissue microstructure. In this study, the geometry of the KT is elucidated using synthetic data generated from multi-compartmental models, where diffusion heterogeneity between intra-and extra-cellular media is taken into account, as well as the sensitivity of the results to each model parameter and to synthetic noise. Furthermore, based on the assumption that the maxima of the KT are distributed perpendicularly to the direction of well-aligned fibres, a novel algorithm for estimating fibre direction directly from the KT is proposed and compared to the fibre directions extracted from DKI-based orientation distribution function (ODF) estimates previously proposed in the literature. Synthetic data results showed that, for fibres crossing at high intersection angles, direction estimates extracted directly from the KT have smaller errors than the DKI-based ODF estimation approaches (DKI-ODF). Nevertheless, the proposed method showed smaller angular resolution and lower stability to changes of the simulation parameters. On real data, tractography performed on these KT fibre estimates suggests a higher sensitivity than the DKI-based ODF in resolving lateral corpus callosum fibres reaching the pre-central cortex when diffusion acquisition is performed with five b-values. Using faster acquisition schemes, KT-based tractography did not show improved performance over the DKI-ODF procedures. Nevertheless, it is shown that direct KT fibre estimates are more adequate for computing a generalised version of radial kurtosis maps. (C) 2015 The Authors. Published by Elsevier Inc.