Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia.
imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium.
J Alzheimers Dis. 2022;90(4):1771-1791. doi: 10.3233/JAD-220551.
Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM.
In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls.
By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons.
Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus.
This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.
大多数使用磁共振扩散加权成像(DW-MRI)研究阿尔茨海默病(AD)的研究都集中在使用扩散(峰度)张量模型对白质(WM)微观结构变化进行分析。尽管最近的研究已经解决了张量模型的一些局限性,例如对交叉纤维和脑脊液(CSF)的部分容积效应的表示,但重点仍然是在对 WM 进行建模和分析。
在这项工作中,我们提出了一种用于 DW-MRI 的大脑分析方法,该方法可以分离多个组织区室以及微观和宏观效应,以研究 AD 连续体和对照组之间的受试者群体之间的差异。
通过多壳 DW-MRI 的多组织约束球谐分解,用 WM 纤维方向分布函数以及 GM 和 CSF 对扩散信号的贡献来对脑组织结构进行建模。从这个多组织模型中,提取了一组捕捉组织扩散特性和形态的指标。通过固定、体素和张量形态计量学方法进行组间差异的询问,同时对多个比较进行强烈的 FWE 控制。
在包括胼胝体、扣带束、纵向束和皮质脊髓束在内的 WM 束中发现了与 AD 阶段相关的异常。确定了组织成分的变化,特别是在颞叶内侧和上纵束。
这种分析框架构成了一种综合方法,允许从单个 DW-MRI 数据集同时进行 WM、GM 和 CSF 的宏观和微观评估。