Diffusion kurtosis imaging allows the early detection and longitudinal follow‐up of amyloid‐β‐induced pathology
Open accessAbstract
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.
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Alzheimer's disease is a leading cause of dementia, but other forms such as vascular dementia, Lewy body dementia and frontotemporal dementia are also prevalent.
“Although Alzheimer’s disease (AD) is a leading cause, other forms such as vascular dementia (VD), Lewy body dementia (LBD) and frontotemporal dementia (FTD) are also prevalent9–11.”
From AI-based differential diagnosis of dementia etiologies on multimodal data (2024) · cites this paper as [10]
The Background states that Alzheimer’s disease is the most common cause of dementia, supporting the first part of the sentence. The paper does not state that vascular, Lewy body, or frontotemporal dementia are prevalent; frontotemporal dementia appears in the References, but not as a prevalence finding. (LLM, conf=0.86)
Experimental — accuracy not yet measuredAdvanced diffusion models-including DKI, NODDI, and SANDI-offer improved sensitivity to microstructural complexity and may provide more biologically informative markers than DTI.
“Advanced diffusion models—including diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and soma and neurite density imaging (SANDI) —offer improved sensitivity to microstructural complexity and may provide more biologically informative markers than DTI.”
From Diffusion MRI reveals amyloid plaque–associated cellular signatures through spatial transcriptomic integration (2026) · cites this paper as [20]
The Background says DKI is more sensitive than DTI to microstructural changes, and the Results report correlations between DKI metrics and underlying amyloid-β pathology. The paper addresses DKI, but not NODDI or SANDI, so it does not support extending that comparison to all three models. Page numbers are unavailable in our copy. (LLM, conf=0.90)
Experimental — accuracy not yet measuredThe heterogeneous FA alterations in the hippocampus may be associated primarily with plaque deposition and related inflammation.
“which may be associated primarily with the plaque deposition and related inflammation (Praet et al., 2018).”
From Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging (2022) · cites this paper as Praet et al., 2018
The Discussion (page unavailable) links hippocampal changes in APP/PS1 mice primarily to Aβ-induced inflammation, but the change was in mean diffusivity, not FA; the authors explicitly report no hippocampal FA change. The Results (page unavailable) report FA correlations with amyloid and inflammatory markers in the motor cortex, not the hippocampus. The source therefore does not establish the proposed explanation for heterogeneous hippocampal FA alterations. (LLM, conf=0.87)
Experimental — accuracy not yet measuredPrevious studies on 3×Tg-AD mice have reported significant volumetric decreases and WM microstructural abnormalities in the corpus callosum and internal capsule compared with controls.
“Previous studies on 3×Tg-AD mice have reported significant volumetric decreases (Kong et al., 2018) and WM microstructural abnormalities (Praet et al., 2018; Gatto et al., 2019; Bergamino et al., 2023) in the CC and internal capsule compared with controls.”
From Multimodal MRI combined with RNA sequencing reveals pathological signatures in the 9-month-old 3×Tg-AD mouse brain (2026) · cites this paper as Praet et al., 2018
The Results (ROI-based analysis; page unavailable) report significantly reduced fractional anisotropy in parts of the corpus callosum compared with wild-type controls, supporting a white-matter microstructural abnormality. However, the Methods identify the mice as APP/PS1, not 3×Tg-AD, and the cited passages do not report an internal-capsule finding. The volumetric-decrease claim is cited to Kong et al., not Praet et al., and is not assessed here. (LLM, conf=0.88)
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- Authors
- Praet, J., Manyakov, N. V., Muchene, L., Mai, Z., Terzopoulos, V., de Backer, S., Torremans, A., Guns, P.-J., Van De Casteele, T., Bottelbergs, A., Van Broeck, B., Sijbers, J., Smeets, D., Shkedy, Z., Bijnens, L., Pemberton, D. J., Schmidt, M. E., Van der Linden, A., & Verhoye, M.
- Affiliations
- University of Antwerp (BE)
- Janssen (Belgium) (BE)
- Hasselt University (BE)
- Icometrix (Belgium) (BE)
- HistoGeneX (Belgium) (BE)
- Corresponding author
- Verhoye, Marleen
- ORCID
- Venue
- Alzheimer's Research & Therapy
- Published
- 2018-01-09
- Volume
- 10
- Issue
- 1
- Pages
- 1-1
- ISSN
- 1758-9193 (ISSN-L)
- PMC
- PMC6389136
- OpenAlex
- W2791831747
- Cited by
- 133
- References
- 61
- Citations by year
- 2026: 7 · 2025: 19 · 2024: 22 · 2023: 18 · 2022: 22 · 2021: 22 · 2020: 15 · 2019: 5 · 2018: 3
- FWCI
- 7.77
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Alzheimer s Research & Therapy (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Document Server@UHasselt (UHasselt) (submittedVersion, cc-by)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- Funders
- FP7 IAAP (612360)
- Hercules stichting (AUHA/012)
- IWT O&O (120178)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Keywords
- diffusion kurtosis imaging, amyloid-beta, APP/PS1 mice, Alzheimer's disease, early detection of neurodegeneration, fractional anisotropy, mean kurtosis, motor cortex, septal nuclei, corpus callosum, diffusion tensor imaging, longitudinal neuroimaging, glial fibrillary acidic protein, myelin basic protein, immunohistochemistry
- MeSH terms
- Aging, Animals, Brain, Disease Models, Animal, Feasibility Studies, Follow-Up Studies, Image Interpretation, Computer-Assisted, Immunohistochemistry, Longitudinal Studies, Male, Mice, Inbred C57BL, Mice, Transgenic, Imaging, Three-Dimensional, Diffusion Magnetic Resonance Imaging, Early Diagnosis, Plaque, Amyloid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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