Bodammer N C, Kaufmann J, Kanowski M, Tempelmann C
Max-Planck Institute for Human Development, Berlin Germany.
Phys Med Biol. 2009 Feb 21;54(4):1009-33. doi: 10.1088/0031-9155/54/4/013. Epub 2009 Jan 16.
Diffusion tensor tractography (DTT) allows one to explore axonal connectivity patterns in neuronal tissue by linking local predominant diffusion directions determined by diffusion tensor imaging (DTI). The majority of existing tractography approaches use continuous coordinates for calculating single trajectories through the diffusion tensor field. The tractography algorithm we propose is characterized by (1) a trajectory propagation rule that uses voxel centres as vertices and (2) orientation probabilities for the calculated steps in a trajectory that are obtained from the diffusion tensors of either two or three voxels. These voxels include the last voxel of each previous step and one or two candidate successor voxels. The precision and the accuracy of the suggested method are explored with synthetic data. Results clearly favour probabilities based on two consecutive successor voxels. Evidence is also provided that in any voxel-centre-based tractography approach, there is a need for a probability correction that takes into account the geometry of the acquisition grid. Finally, we provide examples in which the proposed fibre-tracking method is applied to the human optical radiation, the cortico-spinal tracts and to connections between Broca's and Wernicke's area to demonstrate the performance of the proposed method on measured data.
扩散张量纤维束成像（DTT）通过连接由扩散张量成像（DTI）确定的局部主要扩散方向，使人能够探索神经元组织中的轴突连接模式。大多数现有的纤维束成像方法使用连续坐标来计算通过扩散张量场的单个轨迹。我们提出的纤维束成像算法的特点是：（1）一种轨迹传播规则，该规则使用体素中心作为顶点；（2）轨迹中计算步骤的方向概率，这些概率是从两个或三个体素的扩散张量中获得的。这些体素包括每个先前步骤的最后一个体素以及一个或两个候选后续体素。使用合成数据探索了所建议方法的精度和准确性。结果明显支持基于两个连续后续体素的概率。还提供了证据表明，在任何基于体素中心的纤维束成像方法中，都需要进行概率校正，该校正要考虑采集网格的几何形状。最后，我们提供了一些示例，其中将所提出的纤维追踪方法应用于人类视辐射、皮质脊髓束以及布洛卡区和韦尼克区之间的连接，以证明所提出方法在测量数据上的性能。
