Parker Geoffrey J M, Alexander Daniel C
Imaging Science and Biomedical Engineering, University of Manchester, Stopford Building, Oxford Road, Manchester M13 9PT, UK.
Philos Trans R Soc Lond B Biol Sci. 2005 May 29;360(1457):893-902. doi: 10.1098/rstb.2005.1639.
Recently developed methods to extract the persistent angular structure (PAS) of axonal fibre bundles from diffusion-weighted magnetic resonance imaging (MRI) data are applied to drive probabilistic fibre tracking, designed to provide estimates of anatomical cerebral connectivity. The behaviour of the PAS function in the presence of realistic data noise is modelled for a range of single and multiple fibre configurations. This allows probability density functions (PDFs) to be generated that are parametrized according to the anisotropy of individual fibre populations. The PDFs are incorporated in a probabilistic fibre-tracking method to allow the estimation of whole-brain maps of anatomical connection probability. These methods are applied in two exemplar experiments in the corticospinal tract to show that it is possible to connect the entire primary motor cortex (M1) when tracing from the cerebral peduncles, and that the reverse experiment of tracking from M1 successfully identifies high probability connection via the pyramidal tracts. Using the extracted PAS in probabilistic fibre tracking allows higher specificity and sensitivity than previously reported fibre tracking using diffusion-weighted MRI in the corticospinal tract.
最近开发的从扩散加权磁共振成像（MRI）数据中提取轴突纤维束的持久角结构（PAS）的方法被应用于驱动概率纤维追踪，旨在提供大脑解剖连接性的估计。针对一系列单纤维和多纤维配置，对存在实际数据噪声时PAS函数的行为进行了建模。这使得能够生成根据单个纤维群体的各向异性进行参数化的概率密度函数（PDF）。这些PDF被纳入一种概率纤维追踪方法中，以估计全脑解剖连接概率图。这些方法在皮质脊髓束的两个示例实验中得到应用，结果表明，从大脑脚进行追踪时能够连接整个初级运动皮层（M1），并且从M1进行追踪的反向实验成功地通过锥体束识别出高概率连接。在概率纤维追踪中使用提取的PAS比之前报道的在皮质脊髓束中使用扩散加权MRI进行纤维追踪具有更高的特异性和敏感性。
