Please use this identifier to cite or link to this item:
Title: Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid-beta-induced pathology
Authors: Praet, Jelle
Manyakov, Nikolay V.
MUCHENE, Leacky 
Mai, Zhenhua
Terzopoulos, Vasilis
de Backer, Steve
Torremans, An
Guns, Pieter-Jan
Van De Casteele, Tom
Bottelbergs, Astrid
Van Broeck, Bianca
Sijbers, Jan
Smeets, Dirk
Pemberton, Darrel J.
Schmidt, Mark E.
Van der Linden, Annemie
Verhoye, Marleen
Issue Date: 2018
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-beta (A beta) 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 A beta-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-A beta (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 A beta-induced pathology.
Notes: Verhoye, M (reprint author), Univ Antwerp, Bioimaging Lab, Campus Drie Eiken CDE Uc1-14,Univ Pl 1, B-2610 Antwerp, Belgium,
Keywords: Magnetic resonance imaging; Diffusion tensor imaging; Diffusion kurtosis imaging; Alzheimer's disease; APP/PS1
Document URI:
e-ISSN: 1758-9193
DOI: 10.1186/s13195-017-0329-8
ISI #: 000425762700001
Rights: © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.
Category: A1
Type: Journal Contribution
Validations: ecoom 2019
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
praet 1.pdfPublished version6.67 MBAdobe PDFView/Open
Show full item record


checked on Sep 2, 2020


checked on May 21, 2022

Page view(s)

checked on May 27, 2022


checked on May 27, 2022

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.