Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark.
Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Neuroimage. 2021 May 1;231:117849. doi: 10.1016/j.neuroimage.2021.117849. Epub 2021 Feb 12.
Information about tissue on the microscopic and mesoscopic scales can be accessed by modelling diffusion MRI signals, with the aim of extracting microstructure-specific biomarkers. The standard model (SM) of diffusion, currently the most broadly adopted microstructural model, describes diffusion in white matter (WM) tissues by two Gaussian components, one of which has zero radial diffusivity, to represent diffusion in intra- and extra-axonal water, respectively. Here, we reappraise these SM assumptions by collecting comprehensive double diffusion encoded (DDE) MRI data with both linear and planar encodings, which was recently shown to substantially enhance the ability to estimate SM parameters. We find however, that the SM is unable to account for data recorded in fixed rat spinal cord at an ultrahigh field of 16.4 T, suggesting that its underlying assumptions are violated in our experimental data. We offer three model extensions to mitigate this problem: first, we generalize the SM to accommodate finite radii (axons) by releasing the constraint of zero radial diffusivity in the intra-axonal compartment. Second, we include intracompartmental kurtosis to account for non-Gaussian behaviour. Third, we introduce an additional (third) compartment. The ability of these models to account for our experimental data are compared based on parameter feasibility and Bayesian information criterion. Our analysis identifies the three-compartment description as the optimal model. The third compartment exhibits slow diffusion with a minor but non-negligible signal fraction (∼12%). We demonstrate how failure to take the presence of such a compartment into account severely misguides inferences about WM microstructure. Our findings bear significance for microstructural modelling at large and can impact the interpretation of biomarkers extracted from the standard model of diffusion.
有关微观和介观尺度组织的信息可以通过建模扩散 MRI 信号来获取，目的是提取具有微观结构特异性的生物标志物。扩散的标准模型（SM）是目前最广泛采用的微观结构模型，它通过两个高斯分量来描述白质（WM）组织中的扩散，其中一个分量的径向扩散率为零，分别表示轴内和轴外水中的扩散。在这里，我们通过收集具有线性和平面编码的综合双扩散编码（DDE）MRI 数据来重新评估这些 SM 假设，最近的研究表明，这种方法可以大大提高估计 SM 参数的能力。然而，我们发现 SM 无法解释在 16.4T 超高场下固定大鼠脊髓记录的数据，这表明其基本假设在我们的实验数据中被违反了。我们提出了三种模型扩展来缓解这个问题：首先，我们通过释放轴内部分的零径向扩散率约束，将 SM 推广到能够适应有限半径（轴突）的情况。其次，我们包括内部分的峰度来解释非高斯行为。第三，我们引入了一个额外的（第三个）部分。这些模型对我们实验数据的解释能力是基于参数可行性和贝叶斯信息准则来比较的。我们的分析确定了三部分描述是最优模型。第三个部分表现出缓慢的扩散，具有较小但不可忽略的信号分数（约 12%）。我们展示了不考虑这种部分的存在如何严重误导对 WM 微观结构的推断。我们的发现对宏观的微观结构建模具有重要意义，并可能影响从扩散标准模型中提取的生物标志物的解释。
