Nick M. Powell

Automatic structural parcellation of mouse brain MRI using multi-atlas label fusion.

Multi-atlas segmentation propagation has evolved quickly in recent years, becoming a state-of-the-art methodology for automatic parcellation of structural images. However, few studies have applied these methods to preclinical research. In this study, we present a fully automatic framework for mouse brain MRI structural parcellation using multi-atlas segmentation propagation. The framework adopts the similarity and truth estimation for propagated segmentations (STEPS) algorithm, which utilises a locally normalised cross correlation similarity metric for atlas selection and an extended simultaneous truth and performance level estimation (STAPLE) framework for multi-label fusion. The segmentation accuracy of the multi-atlas framework was evaluated using publicly available mouse brain atlas databases with pre-segmented manually labelled anatomical structures as the gold standard, and optimised parameters were obtained for the STEPS algorithm in the label fusion to achieve the best segmentation accuracy. We showed that our multi-atlas framework resulted in significantly higher segmentation accuracy compared to single-atlas based segmentation, as well as to the original STAPLE framework.

In vivo imaging of tau pathology using multi-parametric quantitative MRI

As the number of people diagnosed with Alzheimers disease (AD) reaches epidemic proportions, there is an urgent need to develop effective treatment strategies to tackle the social and economic costs of this fatal condition. Dozens of candidate therapeutics are currently being tested in clinical trials, and compounds targeting the aberrant accumulation of tau proteins into neurofibrillary tangles (NFTs) are the focus of substantial current interest. Reliable, translatable biomarkers sensitive to both tau pathology and its modulation by treatment along with animal models that faithfully reflect aspects of the human disease are urgently required. Magnetic resonance imaging (MRI) is well established as a valuable tool for monitoring the structural brain changes that accompany AD progression. However the descent into dementia is not defined by macroscopic brain matter loss alone: non-invasive imaging measurements sensitive to protein accumulation, white matter integrity and cerebral haemodynamics probe distinct aspects of AD pathophysiology and may serve as superior biomarkers for assessing drug efficacy. Here we employ a multi-parametric array of five translatable MRI techniques to characterise the in vivo pathophysiological phenotype of the rTg4510 mouse model of tauopathy (structural imaging, diffusion tensor imaging (DTI), arterial spin labelling (ASL), chemical exchange saturation transfer (CEST) and glucose CEST). Tau-induced pathological changes included grey matter atrophy, increased radial diffusivity in the white matter, decreased amide proton transfer and hyperperfusion. We demonstrate that the above markers unambiguously discriminate between the transgenic group and age-matched controls and provide a comprehensive profile of the multifaceted neuropathological processes underlying the rTg4510 model. Furthermore, we show that ASL and DTI techniques offer heightened sensitivity to processes believed to precede detectable structural changes and, as such, provides a platform for the study of disease mechanisms and therapeutic intervention.

Imaging the accumulation and suppression of tau pathology using multiparametric MRI

Mouse models of Alzheimers disease have served as valuable tools for investigating pathogenic mechanisms relating to neurodegeneration, including tau-mediated and neurofibrillary tangle pathology—a major hallmark of the disease. In this work, we have used multiparametric magnetic resonance imaging (MRI) in a longitudinal study of neurodegeneration in the rTg4510 mouse model of tauopathy, a subset of which were treated with doxycycline at different time points to suppress the tau transgene. Using this paradigm, we investigated the sensitivity of multiparametric MRI to both the accumulation and suppression of pathologic tau. Tau-related atrophy was discernible from 5.5 months within the cortex and hippocampus. We observed markedly less atrophy in the treated rTg4510 mice, which was enhanced after doxycycline intervention from 3.5 months. We also observed differences in amide proton transfer, cerebral blood flow, and diffusion tensor imaging parameters in the rTg4510 mice, which were significantly less altered after doxycycline treatment. We propose that these non-invasive MRI techniques offer insight into pathologic mechanisms underpinning Alzheimers disease that may be important when evaluating emerging therapeutics targeting one of more of these processes.

Tissue magnetic susceptibility mapping as a marker of tau pathology in Alzheimer's disease

Abstract Alzheimers disease is connected to a number of other neurodegenerative conditions, known collectively as ‘tauopathies’, by the presence of aggregated tau protein in the brain. Neuroinflammation and oxidative stress in AD are associated with tau pathology and both the breakdown of axonal sheaths in white matter tracts and excess iron accumulation grey matter brain regions. Despite the identification of myelin and iron concentration as major sources of contrast in quantitative susceptibility maps of the brain, the sensitivity of this technique to tau pathology has yet to be explored. In this study, we perform Quantitative Susceptibility Mapping (QSM) and T2* mapping in the rTg4510, a mouse model of tauopathy, both in vivo and ex vivo. Significant correlations were observed between histological measures of myelin content and both mean regional magnetic susceptibility and T2* values. These results suggest that magnetic susceptibility is sensitive to tissue myelin concentrations across different regions of the brain. Differences in magnetic susceptibility were detected in the corpus callosum, striatum, hippocampus and thalamus of the rTg4510 mice relative to wild type controls. The concentration of neurofibrillary tangles was found to be low to intermediate in these brain regions indicating that QSM may be a useful biomarker for early stage detection of tau pathology in neurodegenerative diseases. HighlightsThe rTg4510 is a mouse model of tauopathy.We applied QSM and T2* Mapping MRI techniques to the rTg4510 in vivo and ex vivo.QSM demonstrated sensitivity to regions of low and intermediate tau burden.QSM may hold potential as a non‐invasive early biomarker of tau pathology.

Early microgliosis precedes neuronal loss and behavioural impairment in mice with a frontotemporal dementia-causing CHMP2B mutation

Abstract Frontotemporal dementia (FTD)‐causing mutations in the CHMP2B gene lead to the generation of mutant C‐terminally truncated CHMP2B. We report that transgenic mice expressing endogenous levels of mutant CHMP2B developed late‐onset brain volume loss associated with frank neuronal loss and FTD‐like changes in social behaviour. These data are the first to show neurodegeneration in mice expressing mutant CHMP2B and indicate that our mouse model is able to recapitulate neurodegenerative changes observed in FTD. Neuroinflammation has been increasingly implicated in neurodegeneration, including FTD. Therefore, we investigated neuroinflammation in our CHMP2B mutant mice. We observed very early microglial proliferation that develops into a clear pro‐inflammatory phenotype at late stages. Importantly, we also observed a similar inflammatory profile in CHMP2B patient frontal cortex. Aberrant microglial function has also been implicated in FTD caused by GRN, MAPT and C9orf72 mutations. The presence of early microglial changes in our CHMP2B mutant mice indicates neuroinflammation may be a contributing factor to the neurodegeneration observed in FTD.Frontotemporal dementia (FTD)-causing mutations in the CHMP2B gene lead to the generation of mutant C-terminally truncated CHMP2B. We report that transgenic mice expressing endogenous levels of mutant CHMP2B developed late-onset The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors. The authors wish it to be known that, in their opinion, Peter L. Oliver, Diego Gomez-Nicola and Adrian M. Isaacs should be regarded as Joint Senior

Fully-automated μMRI morphometric phenotyping of the Tc1 mouse model of Down Syndrome

We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to the Tc1 mouse model of Down syndrome, to identify new morphological phenotypes in the brain of this first transchromosomic animal carrying human chromosome 21. We incorporate an accessible approach for simultaneously scanning multiple ex vivo brains, requiring only a 3D-printed brain holder, and novel image processing steps for their separation and orientation. We employ clinically established multi-atlas techniques–superior to single-atlas methods–together with publicly-available atlas databases for automatic skull-stripping and tissue segmentation, providing high-quality, subject-specific tissue maps. We follow these steps with group-wise registration, structural parcellation and both Voxel- and Tensor-Based Morphometry–advantageous for their ability to highlight morphological differences without the laborious delineation of regions of interest. We show the application of freely available open-source software developed for clinical MRI analysis to mouse brain data: NiftySeg for segmentation and NiftyReg for registration, and discuss atlases and parameters suitable for the preclinical paradigm. We used this pipeline to compare 29 Tc1 brains with 26 wild-type littermate controls, imaged ex vivo at 9.4T. We show an unexpected increase in Tc1 total intracranial volume and, controlling for this, local volume and grey matter density reductions in the Tc1 brain compared to the wild-types, most prominently in the cerebellum, in agreement with human DS and previous histological findings.

Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy

With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our “in-skull” preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes.

The Histone Deacetylase Inhibitor Nicotinamide Exacerbates Neurodegeneration in the Lactacystin Rat Model of Parkinson's Disease

Histone hypoacetylation is associated with dopaminergic neurodegeneration in Parkinsons disease (PD), because of an imbalance in the activities of the enzymes responsible for histone (de)acetylation. Correction of this imbalance, with histone deacetylase (HDAC) inhibiting agents, could be neuroprotective. We therefore hypothesize that nicotinamide, being a selective inhibitor of HDAC class III as well as having modulatory effects on mitochondrial energy metabolism, would be neuroprotective in the lactacystin rat model of PD, which recapitulates the formation of neurotoxic accumulation of altered proteins within the substantia nigra to cause progressive dopaminergic cell death. Rats received nicotinamide for 28 days, starting 7 days after unilateral injection of the irreversible proteasome inhibitor, lactacystin, into the substantia nigra. Longitudinal motor behavioural testing and structural magnetic resonance imaging were used to track changes in this model of PD, and assessment of nigrostriatal integrity, histone acetylation and brain gene expression changes post‐mortem used to quantify nicotinamide‐induced neuroprotection. Counterintuitively, nicotinamide dose‐dependently exacerbated neurodegeneration of dopaminergic neurons, behavioural deficits and structural brain changes in the lactacystin‐lesioned rat. Nicotinamide treatment induced histone hyperacetylation and over‐expression of numerous neurotrophic and anti‐apoptotic factors in the brain, yet failed to result in neuroprotection, rather exacerbated dopaminergic pathology. These findings highlight the importance of inhibitor specificity within HDAC isoforms for therapeutic efficacy in PD, demonstrating the contrasting effects of HDAC class III inhibition upon cell survival in this animal model of the disease.

In Vivo Imaging of Tau Pathology Using Magnetic Resonance Imaging Textural Analysis

Background: Non-invasive characterization of the pathological features of Alzheimers disease (AD) could enhance patient management and the development of therapeutic strategies. Magnetic resonance imaging texture analysis (MRTA) has been used previously to extract texture descriptors from structural clinical scans in AD to determine cerebral tissue heterogeneity. In this study, we examined the potential of MRTA to specifically identify tau pathology in an AD mouse model and compared the MRTA metrics to histological measures of tau burden. Methods: MRTA was applied to T2 weighted high-resolution MR images of nine 8.5-month-old rTg4510 tau pathology (TG) mice and 16 litter matched wild-type (WT) mice. MRTA comprised of the filtration-histogram technique, where the filtration step extracted and enhanced features of different sizes (fine, medium, and coarse texture scales), followed by quantification of texture using histogram analysis (mean gray level intensity, mean intensity, entropy, uniformity, skewness, standard-deviation, and kurtosis). MRTA was applied to manually segmented regions of interest (ROI) drawn within the cortex, hippocampus, and thalamus regions and the level of tau burden was assessed in equivalent regions using histology. Results: Texture parameters were markedly different between WT and TG in the cortex (E, p < 0.01, K, p < 0.01), the hippocampus (K, p < 0.05) and in the thalamus (K, p < 0.01). In addition, we observed significant correlations between histological measurements of tau burden and kurtosis in the cortex, hippocampus and thalamus. Conclusions: MRTA successfully differentiated WT and TG in brain regions with varying degrees of tau pathology (cortex, hippocampus, and thalamus) based on T2 weighted MR images. Furthermore, the kurtosis measurement correlated with histological measures of tau burden. This initial study indicates that MRTA may have a role in the early diagnosis of AD and the assessment of tau pathology using routinely acquired structural MR images.

Grey Matter Sublayer Thickness Estimation in the Mouse Cerebellum

The cerebellar grey matter morphology is an important feature to study neurodegenerative diseases such as Alzheimer’s disease or Down’s syndrome. Its volume or thickness is commonly used as a surrogate imaging biomarker for such diseases. Most studies about grey matter thickness estimation focused on the cortex, and little attention has been drawn on the morphology of the cerebellum. Using ex vivo high-resolution MRI, it is now possible to visualise the different cell layers in the mouse cerebellum. In this work, we introduce a framework to extract the Purkinje layer within the grey matter, enabling the estimation of the thickness of the cerebellar grey matter, the granular layer and molecular layer from gadolinium-enhanced ex vivo mouse brain MRI. Application to mouse model of Down’s syndrome found reduced cortical and layer thicknesses in the transchromosomic group.