CoChat
Sign Up
Cited by 134Advanced Neuroimaging Techniques and ApplicationsDementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.

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

Open access
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, Shkedy, Ziv, Bijnens, Luc, Pemberton, Darrel J., Schmidt, Mark E., Van der Linden, Annemie, Verhoye, Marleen·2018·Alzheimer's Research & Therapy
DOI 10.1186/s13195-017-0329-8PMC PMC6389136
Open this paper in CoChat — free accountOpen PDF

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s13195-017-0329-8

Cites

61 of 61 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Experimental setup of the study. Diffusion kurtosis imaging (DKI) was performed in three cohorts of male wild-type (WT) and APP/PS1 mice at 2, 4 and 6 months of age, and these mice were sacrificed for histological analysis thereafter. In a fourth, longitudinal cohort of male WT and APP/PS1 mice, we performed DKI at 2, 4, 6 and 8 months of age and thereafter killed these mice for histological analysis
Fig. 1 Experimental setup of the study. Diffusion kurtosis imaging (DKI) was performed in three cohorts of male wild-type (WT) and APP/PS1 mice at 2, 4 and 6 months of age, and these mice were sacrificed for histological analysis thereafter. In a fourth, longitudinal cohort of male WT and APP/PS1 mice, we performed DKI at 2, 4, 6 and 8 months of age and thereafter killed these mice for histological analysisCC BY · PubMed Central
Fig. 2 Schematic overview of the data acquisition and analysis pipeline used in this study. AD Axial diffusivity, AK Axial kurtosis, DKI Diffusion kurtosis imaging, FA Fractional anisotropy, 4G8 Anti-amyloid-β (clone 4G8) antibody, GFAP Glial fibrillary acidic protein, IBA1 Ionised calcium-binding adapter molecule 1, MBP Myelin basic protein, MD Mean diffusivity, MK Mean kurtosis, MRI Magnetic resonance imaging, RD Radial diffusivity, RK Radial kurtosis, ROI Region of interest
Fig. 2 Schematic overview of the data acquisition and analysis pipeline used in this study. AD Axial diffusivity, AK Axial kurtosis, DKI Diffusion kurtosis imaging, FA Fractional anisotropy, 4G8 Anti-amyloid-β (clone 4G8) antibody, GFAP Glial fibrillary acidic protein, IBA1 Ionised calcium-binding adapter molecule 1, MBP Myelin basic protein, MD Mean diffusivity, MK Mean kurtosis, MRI Magnetic resonance imaging, RD Radial diffusivity, RK Radial kurtosis, ROI Region of interestCC BY · PubMed Central
Fig. 3 Region of interest (ROI)-based DKI analysis. The most interesting differences in diffusion tensor and diffusion kurtosis metrics of several grey and white matter ROIs. We show only data from the longitudinal cohort of wild-type WT (blue bars) and APP/PS1 mice (red bars) at 2, 4, 6 and 8 months of age. Shown are the mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD); the mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK); and the fractional anisotropy (FA). Significant differences between WT and APP/PS1 mice at any given time point are shown in black; genotype effect is indicated by green lines; age effect is indicated by orange lines; and interaction between age and genotype is indicated by blue lines. *p < 0.05, **p < 0.01 and ***p < 0.001
Fig. 3 Region of interest (ROI)-based DKI analysis. The most interesting differences in diffusion tensor and diffusion kurtosis metrics of several grey and white matter ROIs. We show only data from the longitudinal cohort of wild-type WT (blue bars) and APP/PS1 mice (red bars) at 2, 4, 6 and 8 months of age. Shown are the mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD); the mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK); and the fractional anisotropy (FA). Significant differences between WT and APP/PS1 mice at any given time point are shown in black; genotype effect is indicated by green lines; age effect is indicated by orange lines; and interaction between age and genotype is indicated by blue lines. *p < 0.05, **p < 0.01 and ***p < 0.001CC BY · PubMed Central
Fig. 4 Linear discriminant analysis and least absolute shrinkage and selection operator (LASSO) analysis of the motor cortex. a The frequency distribution histograms of the misclassification error (MCE) of the motor cortex are shown (percentage of animals which were attributed the wrong genotype). The MCE is calculated at 2, 4, 6 and 8 months of age when using only the diffusion tensor (DT) metrics (top row), the diffusion kurtosis (DK) metrics (middle row) or a combination of the DT and DK metrics (bottom row). The red lines indicate the average MCE. b LASSO analysis was done to determine which of the DTI or DKI metrics contribute the most to a correct classification of the genotype. The heat map shows all 100 iterations of the LASSO analysis for all metrics, where green indicates that the metric was used and red indicates that the metric was not used. On the right, we show the percentage of times that the metric contributed to a correct genotype classification in all of these 100 iterations (percent prevalence)
Fig. 4 Linear discriminant analysis and least absolute shrinkage and selection operator (LASSO) analysis of the motor cortex. a The frequency distribution histograms of the misclassification error (MCE) of the motor cortex are shown (percentage of animals which were attributed the wrong genotype). The MCE is calculated at 2, 4, 6 and 8 months of age when using only the diffusion tensor (DT) metrics (top row), the diffusion kurtosis (DK) metrics (middle row) or a combination of the DT and DK metrics (bottom row). The red lines indicate the average MCE. b LASSO analysis was done to determine which of the DTI or DKI metrics contribute the most to a correct classification of the genotype. The heat map shows all 100 iterations of the LASSO analysis for all metrics, where green indicates that the metric was used and red indicates that the metric was not used. On the right, we show the percentage of times that the metric contributed to a correct genotype classification in all of these 100 iterations (percent prevalence)CC BY · PubMed Central
Fig. 5 Representative histological images of the motor cortex of the wild-type (WT) and APP/PS1 mice (left and right columns, respectively) at 2, 4, 6 and 8 months of age (top to bottom rows). The different panels show the anti-amyloid-β (clone 4G8) antibody staining for amyloid-β plaques (a), the myelin basic protein staining for myelin basic protein (b), the glial fibrillary acidic protein staining for astrogliosis (c) and the ionised calcium-binding adapter molecule 1staining for microgliosis (d)
Fig. 5 Representative histological images of the motor cortex of the wild-type (WT) and APP/PS1 mice (left and right columns, respectively) at 2, 4, 6 and 8 months of age (top to bottom rows). The different panels show the anti-amyloid-β (clone 4G8) antibody staining for amyloid-β plaques (a), the myelin basic protein staining for myelin basic protein (b), the glial fibrillary acidic protein staining for astrogliosis (c) and the ionised calcium-binding adapter molecule 1staining for microgliosis (d)CC BY · PubMed Central
Fig. 6 Region of interest-based histological correlation analysis. a Graphs showing the Pearson correlations between mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK) and fractional anisotropy (FA) and percent optical density (%O.D.) of anti-amyloid-β (clone 4G8) antibody (4G8), glial fibrillary acidic protein (GFAP), ionised calcium-binding adapter molecule 1 (IBA1) and myelin basic protein (MBP). The graph includes data from the wild-type (WT) mice (triangles) and APP/PS1 mice (circles) at 2 months of age (grey), 4 months of age (green), 6 months of age (blue) and 8 months of age (red). b Pearson correlation values (r) and p values of these correlations between the different diffusion tensor and diffusion kurtosis metrics and the histological parameters
Fig. 6 Region of interest-based histological correlation analysis. a Graphs showing the Pearson correlations between mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK) and fractional anisotropy (FA) and percent optical density (%O.D.) of anti-amyloid-β (clone 4G8) antibody (4G8), glial fibrillary acidic protein (GFAP), ionised calcium-binding adapter molecule 1 (IBA1) and myelin basic protein (MBP). The graph includes data from the wild-type (WT) mice (triangles) and APP/PS1 mice (circles) at 2 months of age (grey), 4 months of age (green), 6 months of age (blue) and 8 months of age (red). b Pearson correlation values (r) and p values of these correlations between the different diffusion tensor and diffusion kurtosis metrics and the histological parametersCC BY · PubMed Central
Fig. 7 Voxel-based statistical parametric mapping. a Statistical parametric maps at two different levels in the brains of mice at 8 months of age. On these images, for each of the seven metrics (mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD], mean kurtosis [MK], axial kurtosis [AK], radial kurtosis [RK] and fractional anisotropy [FA]), the voxels with a decreased value in APP/PS1 mice compared with wild-type (WT) mice are shown in blue, and the voxels with an increased value in APP/PS1 mice compared with WT mice are shown in red. Only voxels with a false discovery rate-corrected p > 0.05 are shown. b Close-up of the FA statistical parametric map showing reduced FA in APP/PS1 mice in the septal nuclei at 8 months of age (blue voxels). c Voxel-based correlation values between the percent optical density (%O.D.) anti-amyloid-β (clone 4G8) antibody (4G8), myelin basic protein (MBP), glial fibrillary acidic protein (GFAP) and ionised calcium-binding adapter molecule 1 (IBA1) and the diffusion tensor metrics (DT), the diffusion kurtosis metrics (DK), and the DT and DK metrics (DT/DK)
Fig. 7 Voxel-based statistical parametric mapping. a Statistical parametric maps at two different levels in the brains of mice at 8 months of age. On these images, for each of the seven metrics (mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD], mean kurtosis [MK], axial kurtosis [AK], radial kurtosis [RK] and fractional anisotropy [FA]), the voxels with a decreased value in APP/PS1 mice compared with wild-type (WT) mice are shown in blue, and the voxels with an increased value in APP/PS1 mice compared with WT mice are shown in red. Only voxels with a false discovery rate-corrected p > 0.05 are shown. b Close-up of the FA statistical parametric map showing reduced FA in APP/PS1 mice in the septal nuclei at 8 months of age (blue voxels). c Voxel-based correlation values between the percent optical density (%O.D.) anti-amyloid-β (clone 4G8) antibody (4G8), myelin basic protein (MBP), glial fibrillary acidic protein (GFAP) and ionised calcium-binding adapter molecule 1 (IBA1) and the diffusion tensor metrics (DT), the diffusion kurtosis metrics (DK), and the DT and DK metrics (DT/DK)CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 61 references

Research works printed but not linked: 1

  1. Avants B, Tustison N, Song G. Advanced Normalization Tools: V1.0. Insight J. 2009;July–December:1–35.

Cited by

Sorted by citations

See all 134

Related

Metadata

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
Publisher
Springer Science and Business Media LLC
Published
2018-01-09
Volume
10
Issue
1
Pages
1-1
ISSN
1758-9193 (ISSN-L)
DOI
10.1186/s13195-017-0329-8
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
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
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › 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 ›

Are you an author, or do you see a problem with this page? Request a review