iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium.
iMinds-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium.
Med Image Anal. 2015 Aug;24(1):269-281. doi: 10.1016/j.media.2015.01.001. Epub 2015 Jan 14.
Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a noninvasive imaging method, which can be used to investigate neural tracts in the white matter (WM) of the brain. However, the voxel sizes used in DW-MRI are relatively large, making DW-MRI prone to significant partial volume effects (PVE). These PVEs can be caused both by complex (e.g. crossing) WM fiber configurations and non-WM tissue, such as gray matter (GM) and cerebrospinal fluid. High angular resolution diffusion imaging methods have been developed to correctly characterize complex WM fiber configurations, but significant non-WM PVEs are also present in a large proportion of WM voxels. In constrained spherical deconvolution (CSD), the full fiber orientation distribution function (fODF) is deconvolved from clinically feasible DW data using a response function (RF) representing the signal of a single coherently oriented population of fibers. Non-WM PVEs cause a loss of precision in the detected fiber orientations and an emergence of false peaks in CSD, more prominently in voxels with GM PVEs. We propose a method, informed CSD (iCSD), to improve the estimation of fODFs under non-WM PVEs by modifying the RF to account for non-WM PVEs locally. In practice, the RF is modified based on tissue fractions estimated from high-resolution anatomical data. Results from simulation and in-vivo bootstrapping experiments demonstrate a significant improvement in the precision of the identified fiber orientations and in the number of false peaks detected under GM PVEs. Probabilistic whole brain tractography shows fiber density is increased in the major WM tracts and decreased in subcortical GM regions. The iCSD method significantly improves the fiber orientation estimation at the WM-GM interface, which is especially important in connectomics, where the connectivity between GM regions is analyzed.
弥散加权（DW）磁共振成像（MRI）是一种非侵入性成像方法，可用于研究大脑白质（WM）中的神经束。然而，DW-MRI 使用的体素尺寸相对较大，使得 DW-MRI 容易受到明显的部分容积效应（PVE）的影响。这些 PVEs 既可以由复杂的（例如交叉）WM 纤维结构引起，也可以由非 WM 组织引起，如灰质（GM）和脑脊液。高角分辨率扩散成像方法已被开发用于正确描述复杂的 WM 纤维结构，但在很大一部分 WM 体素中也存在显著的非 WM PVE。在约束球解卷积（CSD）中，使用代表单个相干定向纤维群体信号的响应函数（RF），从临床可行的 DW 数据中解卷积全纤维方向分布函数（fODF）。非 WM PVE 导致检测到的纤维方向精度降低，并在 CSD 中出现虚假峰值，在具有 GM PVE 的体素中更为明显。我们提出了一种方法，即信息约束球解卷积（iCSD），通过修改 RF 来局部考虑非 WM PVE，从而改善非 WM PVE 下的 fODF 估计。在实践中，根据高分辨率解剖数据估计的组织分数来修改 RF。来自模拟和体内自举实验的结果表明，在 GM PVE 下，识别纤维方向的精度和检测到的虚假峰值数量都有显著提高。概率全脑束追踪显示，主要 WM 束中的纤维密度增加，皮质下 GM 区域的纤维密度降低。iCSD 方法显著改善了 WM-GM 界面的纤维方向估计，这在连接组学中尤为重要，在连接组学中分析 GM 区域之间的连接。
