Gray and white matter degeneration revealed by diffusion in an Alzheimer mouse model

Zerbi, Valerio; Kleinnijenhuis, Michiel; Fang, Xiaotian T.; Jansen, Diane; Veltien, Andor; Asten, Jack van; Timmer, Nienke; Dederen, Pieter J.; Kiliaan, Amanda J.; Heerschap, Arend

doi:10.1016/j.neurobiolaging.2012.11.017

Cited by 59 publications

(52 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We observed reduced FA values in the APP/PS1 mice mainly in the genu and the body of the corpus callosum. This is in concordance with a study by Zerbi et al, who observed this earlier-mentioned increase in DTI metrics in the hippocampus and decreased FA in the genu and body of the corpus callosum [40]. They used 12-month-old APP swe /PS1 dE9 mice, an age at which the plaque load is comparable to what we observe at around 6 months of age in our APP/PS1 mice [41].…”

Section: Discussionsupporting

confidence: 93%

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

et al. 2018

View full text Add to dashboard Cite

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.

show abstract

Section: Discussionsupporting

confidence: 93%

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

et al. 2018

View full text Add to dashboard Cite

show abstract

“…DTI studies in APP/PS1 mice, a more severe phenotype with A␤ plaque deposition and marked neuron loss, report significant increases in multiple parameters (i.e., MD, FA, AxD, RadD) in several gray matter regions, including hippocampus and cortex [25,26]. In the same strain, Zerbi et al [57] found similar results, with increased MD, AxD, and RadD in the hippocampus. Moreover, in mice with a 25% reduction in forebrain cholinergic neurons, mimicking the preferential loss of cholinergic neurons in AD, forebrain diffusivity is increased, with higher MD, FA, AxD, and RadD measures relative to controls [56].…”

Section: Discussionmentioning

confidence: 82%

In Vivo Detection of Gray Matter Neuropathology in the 3xTg Mouse Model of Alzheimer’s Disease with Diffusion Tensor Imaging

Snow

Dale

O’Brien-Moran

et al. 2017

JAD

View full text Add to dashboard Cite

Abstract.A diagnosis of Alzheimer's disease (AD), a neurodegenerative disorder accompanied by severe functional and cognitive decline, is based on clinical findings, with final confirmation of the disease at autopsy by the presence of amyloid-␤ (A␤) plaques and neurofibrillary tangles. Given that microstructural brain alterations occur years prior to clinical symptoms, efforts to detect brain changes early could significantly enhance our ability to diagnose AD sooner. Diffusion tensor imaging (DTI), a type of MRI that characterizes the magnitude, orientation, and anisotropy of the diffusion of water in tissues, has been used to infer neuropathological changes in vivo. Its utility in AD, however, is still under investigation. The current study used DTI to examine brain regions susceptible to AD-related pathology; the cerebral cortex, entorhinal cortex, and hippocampus, in 12-14-month-old 3xTg AD mice that possess both A␤ plaques and neurofibrillary tangles. Mean diffusivity did not differ between 3xTg and control mice in any region. Decreased fractional anisotropy (p < 0.01) and axial diffusivity (p < 0.05) were detected only in the hippocampus, in which both congophilic A␤ plaques and hyperphosphorylated tau accumulation, consistent with neurofibrillary tangle formation, were detected. Pathological tau accumulation was seen in the cortex. The entorhinal cortex was largely spared from AD-related neuropathology. This is the first study to demonstrate DTI abnormalities in gray matter in a mouse model of AD in which both pathological hallmarks are present, suggesting the feasibility of DTI as a non-invasive means of detecting brain pathology in vivo in early-stage AD.

show abstract

“…FA did not account for those contributions because the dendrites are only partially coherently organized and the axons are not homogeneously distributed and might be myelinated or unmyelinated in gray matter. 22,23 When overlaid to the statistical parametric mapping-integrated T1 template, the changes were seen mostly within the subcortical white matter areas with a small portion of voxels overlapped with cortex. Because it is difficult to separate the white matter and gray matter with DTI contrast, the results are elaborated with "gyrus" (which contain both subcortical white matter and cortex) as its units.…”

Section: Discussionmentioning

confidence: 99%

DTI Analysis of Presbycusis Using Voxel-Based Analysis

Ma¹,

Li²,

Gao³

et al. 2016

AJNR Am J Neuroradiol

View full text Add to dashboard Cite

BACKGROUND AND PURPOSE:Presbycusis is the most common sensory deficit in the aging population. A recent study reported using a DTI-based tractography technique to identify a lack of integrity in a portion of the auditory pathway in patients with presbycusis. The aim of our study was to investigate the white matter pathology of patients with presbycusis by using a voxel-based analysis that is highly sensitive to local intensity changes in DTI data.

show abstract

Gray and white matter degeneration revealed by diffusion in an Alzheimer mouse model

Cited by 59 publications

References 54 publications

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

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

In Vivo Detection of Gray Matter Neuropathology in the 3xTg Mouse Model of Alzheimer’s Disease with Diffusion Tensor Imaging

DTI Analysis of Presbycusis Using Voxel-Based Analysis

Contact Info

Product

Resources

About