Center of Functionally Integrative Neuroscience, Aarhus University Hospital, Nørrebrogade 44, Arhus C, Denmark.
Neuroimage. 2010 Jan 1;49(1):205-16. doi: 10.1016/j.neuroimage.2009.08.053. Epub 2009 Sep 2.
Due to its unique sensitivity to tissue microstructure, diffusion-weighted magnetic resonance imaging (MRI) has found many applications in clinical and fundamental science. With few exceptions, a more precise correspondence between physiological or biophysical properties and the obtained diffusion parameters remain uncertain due to lack of specificity. In this work, we address this problem by comparing diffusion parameters of a recently introduced model for water diffusion in brain matter to light microscopy and quantitative electron microscopy. Specifically, we compare diffusion model predictions of neurite density in rats to optical myelin staining intensity and stereological estimation of neurite volume fraction using electron microscopy. We find that the diffusion model describes data better and that its parameters show stronger correlation with optical and electron microscopy, and thus reflect myelinated neurite density better than the more frequently used diffusion tensor imaging (DTI) and cumulant expansion methods. Furthermore, the estimated neurite orientations capture dendritic architecture more faithfully than DTI diffusion ellipsoids.
由于其对组织微观结构的独特敏感性，扩散加权磁共振成像（MRI）在临床和基础科学中找到了许多应用。由于缺乏特异性，除了少数例外，生理或生物物理特性与获得的扩散参数之间更精确的对应关系仍然不确定。在这项工作中，我们通过将最近提出的用于脑物质中水分子扩散的扩散模型的扩散参数与光学显微镜和定量电子显微镜进行比较来解决这个问题。具体来说，我们将大鼠的神经突密度的扩散模型预测与光学髓鞘染色强度和电子显微镜的神经突体积分数的体视学估计进行比较。我们发现扩散模型能更好地描述数据，并且其参数与光学和电子显微镜的相关性更强，因此比更常用的扩散张量成像（DTI）和累积展开方法更能反映髓鞘化神经突的密度。此外，估计的神经突方向比 DTI 扩散椭圆更忠实地捕获树突结构。
