Boujraf Saïd
Department of Biophysics and Clinical MRI Methods, Faculty of Medicine and Pharmacy, University of Fez, Fez, Morocco.
J Med Signals Sens. 2014 Apr;4(2):85-93.
Diffusion weighted imaging uses the signal loss associated with the random thermal motion of water molecules in the presence of magnetic field gradients to derive a number of parameters that reflect the translational mobility of the water molecules in tissues. With a suitable experimental set-up, it is possible to calculate all the elements of the local diffusion tensor (DT) and derived parameters describing the behavior of the water molecules in each voxel. One of the emerging applications of the information obtained is an interpretation of the diffusion anisotropy in terms of the architecture of the underlying tissue. These interpretations can only be made provided the experimental data which are sufficiently accurate. However, the DT results are susceptible to two systematic error sources: On one hand, the presence of signal noise can lead to artificial divergence of the diffusivities. In contrast, the use of a simplified model for the interaction of the protons with the diffusion weighting and imaging field gradients (b matrix calculation), common in the clinical setting, also leads to deviation in the derived diffusion characteristics. In this paper, we study the importance of these two sources of error on the basis of experimental data obtained on a clinical magnetic resonance imaging system for an isotropic phantom using a state of the art single-shot echo planar imaging sequence. Our results show that optimal diffusion imaging require combining a correct calculation of the b-matrix and a sufficiently large signal to noise ratio.
扩散加权成像利用在磁场梯度存在下与水分子随机热运动相关的信号损失来推导一些反映水分子在组织中平移运动性的参数。通过合适的实验设置，可以计算局部扩散张量（DT）的所有元素以及描述每个体素中水分子行为的派生参数。所获得信息的一个新兴应用是根据基础组织的结构来解释扩散各向异性。只有在实验数据足够准确的情况下才能进行这些解释。然而，DT结果易受两个系统误差源的影响：一方面，信号噪声的存在会导致扩散率出现人为偏差。相比之下，在临床环境中常用的对质子与扩散加权和成像场梯度相互作用的简化模型（b矩阵计算）也会导致派生扩散特征出现偏差。在本文中，我们基于在临床磁共振成像系统上使用先进的单次激发回波平面成像序列对各向同性体模获得的实验数据，研究这两个误差源的重要性。我们的结果表明，最佳扩散成像需要结合b矩阵的正确计算和足够大的信噪比。
