Vanderbilt University Institute of Imaging Science, Nashville, TN, USA.
NMR Biomed. 2012 Jul;25(7):900-8. doi: 10.1002/nbm.1810. Epub 2012 Jan 16.
Diffusion tensor imaging (DTI) provides an indirect measure of tissue structure on a microscopic scale. To date, DTI is the only imaging method that provides such information in vivo, and has proven to be a valuable tool in both research and clinical settings. In this study, we investigated the relationship between white matter structure and diffusion parameters measured by DTI. We used micrographs from light microscopy of fixed, myelin-stained brain sections as a gold standard for direct comparison with data from DTI. Relationships between microscopic tissue properties observed with light microscopy (fiber orientation, density and coherence) and fiber properties observed by DTI (tensor orientation, diffusivities and fractional anisotropy) were investigated. Agreement between the major eigenvector of the tensor and myelinated fibers was excellent in voxels with high fiber coherence. In addition, increased fiber spread was strongly associated with increased radial diffusivity (p = 6 × 10(-6)) and decreased fractional anisotropy (p = 5 × 10(-8)), and was weakly associated with decreased axial diffusivity (p = 0.07). Increased fiber density was associated with increased fractional anisotropy (p = 0.03), and weakly associated with decreased radial diffusivity (p < 0.06), but not with axial diffusivity (p = 0.97). The mean diffusivity was largely independent of fiber spread (p = 0.24) and fiber density (p = 0.34).
弥散张量成像(DTI)提供了一种对微观组织结构的间接测量方法。到目前为止,DTI 是唯一一种可以在体内提供此类信息的成像方法,并且已被证明在研究和临床环境中都是一种很有价值的工具。在这项研究中,我们研究了白质结构与通过 DTI 测量的扩散参数之间的关系。我们使用固定的、用髓鞘染色的脑切片的光学显微镜图像作为与 DTI 数据直接比较的金标准。研究了光学显微镜观察到的微观组织特性(纤维方向、密度和相干性)与 DTI 观察到的纤维特性(张量方向、扩散率和各向异性分数)之间的关系。在具有高纤维相干性的体素中,张量的主要特征向量与有髓纤维之间的一致性非常好。此外,纤维扩散增加与径向扩散率增加(p = 6 × 10(-6))和各向异性分数降低(p = 5 × 10(-8))强烈相关,与轴向扩散率降低(p = 0.07)弱相关。纤维密度增加与各向异性分数增加(p = 0.03)相关,与径向扩散率降低(p < 0.06)弱相关,但与轴向扩散率无关(p = 0.97)。平均扩散率与纤维扩散(p = 0.24)和纤维密度(p = 0.34)的相关性不大。