Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid-β-induced pathology

Abstract

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia in the elderly population. In this study, we used the APP/PS1 transgenic mouse model to explore the feasibility of using diffusion kurtosis imaging (DKI) as a tool for the early detection of microstructural changes in the brain due to amyloid-β (Aβ) plaque deposition. Methods: We longitudinally acquired DKI data of wild-type (WT) and APP/PS1 mice at 2, 4, 6 and 8 months of age, after which these mice were sacrificed for histological examination. Three additional cohorts of mice were also included at 2, 4 and 6 months of age to allow voxel-based co-registration between diffusion tensor and diffusion kurtosis metrics and immunohistochemistry. Results: Changes were observed in diffusion tensor (DT) and diffusion kurtosis (DK) metrics in many of the 23 regions of interest that were analysed. Mean and axial kurtosis were greatly increased owing to Aβ-induced pathological changes in the motor cortex of APP/PS1 mice at 4, 6 and 8 months of age. Additionally, fractional anisotropy (FA) was decreased in APP/PS1 mice at these respective ages. Linear discriminant analysis of the motor cortex data indicated that combining diffusion tensor and diffusion kurtosis metrics permits improved separation of WT from APP/PS1 mice compared with either diffusion tensor or diffusion kurtosis metrics alone. We observed that mean kurtosis and FA are the critical metrics for a correct genotype classification. Furthermore, using a newly developed platform to co-register the in vivo diffusion-weighted magnetic resonance imaging with multiple 3D histological stacks, we found high correlations between DK metrics and anti-Aβ (clone 4G8) antibody, glial fibrillary acidic protein, ionised calcium-binding adapter molecule 1 and myelin basic protein immunohistochemistry. Finally, we observed reduced FA in the septal nuclei of APP/PS1 mice at all ages investigated. The latter was at least partially also observed by voxel-based statistical parametric mapping, which showed significantly reduced FA in the septal nuclei, as well as in the corpus callosum, of 8-month-old APP/PS1 mice compared with WT mice. Conclusions: Our results indicate that DKI metrics hold tremendous potential for the early detection and longitudinal follow-up of Aβ-induced pathology.

Diffusion MRI detects longitudinal white matter changes in the 3xTg-AD mouse model of Alzheimer's disease

“…Previous dMRI studies have reported similar trends of decrease in diffusivity and increase in kurtosis in the brain using different mouse models of AD [35,36,45,46]. Our diffusion tensor (DT) metrics results are in general concordance with Sun et al [45], where reduced D ⊥ with age in the EC of the transgenic group (APPsw) is seen in the results.…”

“…DKI has been used in human studies to investigate tissue microstructural changes associated with aging [22][23][24][25] and AD [26,27], particularly for assessing WM abnormalities [28][29][30][31]. Furthermore, the extra diffusional kurtosis (DK) measures have a demonstrated sensitivity to brain pathology in a variety animal models [32][33][34], including AD mouse models [35,36].…”

The Barcelona Brain Health Initiative: A Cohort Study to Define and Promote Determinants of Brain Health

“…Second, a large number of sensitive baseline measures are fundamental to detect true effects of lifestyle interventions on cognitive decline and prevention of neurodegenerative diseases, and fully explain and understand the different age-related trajectories ( Nilsson and Lövdén, 2018 ).…”

Increased Neurite Orientation-Dispersion and Density in the TgCRND8 Mouse Model of Amyloidosis: Inverse Relation with Functional Connectome Clustering and Modulation by Interleukin-6

“…Interestingly, opposite changes in hippocampal MD, AD and RD was observed between 6-8 mo in the APP/PS1 mouse using a diffusion kurtosis image acquisition scheme (Praet et al, 2018).…”