Tournier J-Donald, Yeh Chun-Hung, Calamante Fernando, Cho Kuan-Hung, Connelly Alan, Lin Ching-Po
Brain Research Institute, Melbourne, Australia.
Neuroimage. 2008 Aug 15;42(2):617-25. doi: 10.1016/j.neuroimage.2008.05.002. Epub 2008 May 9.
Diffusion-weighted imaging can potentially be used to infer the connectivity of the human brain in vivo using fibre-tracking techniques, and is therefore of great interest to neuroscientists and clinicians. A key requirement for fibre tracking is the accurate estimation of white matter fibre orientations within each imaging voxel. The diffusion tensor model, which is widely used for this purpose, has been shown to be inadequate in crossing fibre regions. A number of approaches have recently been proposed to address this issue, based on high angular resolution diffusion-weighted imaging (HARDI) data. In this study, an experimental model of crossing fibres, consisting of water-filled plastic capillaries, is used to thoroughly assess three such techniques: constrained spherical deconvolution (CSD), super-resolved CSD (super-CSD) and Q-ball imaging (QBI). HARDI data were acquired over a range of crossing angles and b-values, from which fibre orientations were computed using each technique. All techniques were capable of resolving the two fibre populations down to a crossing angle of 45 degrees , and down to 30 degrees for super-CSD. A bias was observed in the fibre orientations estimated by QBI for crossing angles other than 90 degrees, consistent with previous simulation results. Finally, for a 45 degrees crossing, the minimum b-value required to resolve the fibre orientations was 4000 s/mm(2) for QBI, 2000 s/mm(2) for CSD, and 1000 s/mm(2) for super-CSD. The quality of estimation of fibre orientations may profoundly affect fibre tracking attempts, and the results presented provide important additional information regarding performance characteristics of well-known methods.
扩散加权成像有可能通过纤维追踪技术在体内推断人类大脑的连通性，因此受到神经科学家和临床医生的极大关注。纤维追踪的一个关键要求是准确估计每个成像体素内的白质纤维方向。为此广泛使用的扩散张量模型已被证明在交叉纤维区域是不充分的。最近基于高角分辨率扩散加权成像（HARDI）数据提出了许多方法来解决这个问题。在本研究中，使用由充满水的塑料毛细管组成的交叉纤维实验模型来全面评估三种此类技术：约束球形反卷积（CSD）、超分辨CSD（super-CSD）和Q球成像（QBI）。在一系列交叉角度和b值上采集HARDI数据，并使用每种技术从中计算纤维方向。所有技术都能够分辨出两个纤维群，对于CSD和super-CSD，分辨能力分别达到45度和30度的交叉角度。对于QBI估计的纤维方向，在90度以外的交叉角度观察到偏差，这与先前的模拟结果一致。最后，对于45度交叉，分辨纤维方向所需的最小b值对于QBI为4000 s/mm²，对于CSD为2000 s/mm²，对于super-CSD为1000 s/mm²。纤维方向估计的质量可能会深刻影响纤维追踪尝试，并且所呈现的结果提供了有关知名方法性能特征的重要补充信息。
