Da Ma

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.

Dexamethasone exacerbates cerebral edema and brain injury following lithium-pilocarpine induced status epilepticus

Anti-inflammatory therapies are the current most plausible drug candidates for anti-epileptogenesis and neuroprotection following prolonged seizures. Given that vasogenic edema is widely considered to be detrimental for outcome following status epilepticus, the anti-inflammatory agent dexamethasone is sometimes used in clinic for alleviating cerebral edema. In this study we perform longitudinal magnetic resonance imaging in order to assess the contribution of dexamethasone on cerebral edema and subsequent neuroprotection following status epilepticus. Lithium-pilocarpine was used to induce status epilepticus in rats. Following status epilepticus, rats were either post-treated with saline or with dexamethasone sodium phosphate (10 mg/kg or 2 mg/kg). Brain edema was assessed by means of magnetic resonance imaging (T2 relaxometry) and hippocampal volumetry was used as a marker of neuronal injury. T2 relaxometry was performed prior to, 48 h and 96 h following status epilepticus. Volume measurements were performed between 18 and 21 days after status epilepticus. Unexpectedly, cerebral edema was worse in rats that were treated with dexamethasone compared to controls. Furthermore, dexamethasone treated rats had lower hippocampal volumes compared to controls 3 weeks after the initial insult. The T2 measurements at 2 days and 4 days in the hippocampus correlated with hippocampal volumes at 3 weeks. Finally, the mortality rate in the first week following status epilepticus increased from 14% in untreated rats to 33% and 46% in rats treated with 2 mg/kg and 10 mg/kg dexamethasone respectively. These findings suggest that dexamethasone can exacerbate the acute cerebral edema and brain injury associated with status epilepticus.

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.

Longitudinal in vivo MRI in a Huntington's disease mouse model: Global atrophy in the absence of white matter microstructural damage.

Huntington’s disease (HD) is a genetically-determined neurodegenerative disease. Characterising neuropathology in mouse models of HD is commonly restricted to cross-sectional ex vivo analyses, beset by tissue fixation issues. In vivo longitudinal magnetic resonance imaging (MRI) allows for disease progression to be probed non-invasively. In the HdhQ150 mouse model of HD, in vivo MRI was employed at two time points, before and after the onset of motor signs, to assess brain macrostructure and white matter microstructure. Ex vivo MRI, immunohistochemistry, transmission electron microscopy and behavioural testing were also conducted. Global brain atrophy was found in HdhQ150 mice at both time points, with no neuropathological progression across time and a selective sparing of the cerebellum. In contrast, no white matter abnormalities were detected from the MRI images or electron microscopy images alike. The relationship between motor function and MR-based structural measurements was different for the HdhQ150 and wild-type mice, although there was no relationship between motor deficits and histopathology. Widespread neuropathology prior to symptom onset is consistent with patient studies, whereas the absence of white matter abnormalities conflicts with patient data. The myriad reasons for this inconsistency require further attention to improve the translatability from mouse models of disease.

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.

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.

A multiscale MRI approach to investigate novel drug treatment strategies in mouse models of Alzheimer's disease

described effects of age on clinical presentation (greater memory impairment in older patients, diffuse cortical deficits in younger patients) and neurodegenerative patterns (medial temporal in lateonset AD and cortical-predominant in early-onset AD). ApoE-ε4 carriers had greater right-parietal and bilateral lateral-temporal retention than non-carriers. Lower MMSE scores predicted greater uptake in inferior/middle frontal gyri and left-temporal pole, consistent with spread of tau into anterior brain regions with advancing disease. These results remained largely unchanged when age, ApoE-ε4 and MMSE were included in a combined model. Decreased performance on modified trailmaking, figure copy, and figure recall tasks was related to increased uptake in right-occipitoparietal visual association cortex, and impaired figure recall also predicted tracer retention in right>left hippocampus (Figure 3). Conclusions:We found preliminary associations between [F]AV1451 binding patterns and age, ApoE-ε4 and domain-specific cognitive performance, mirroring links between these factors and the distribution of neurofibrillary tangles at autopsy. These findings need to be confirmed in larger samples.

Imaging the efficacy of microtubule stabilizing agent epothilone d in the rtg4510 mouse model of tauopathy

Ozama Ismail, Ian F. Harrison, Holly Holmes, Niall Colgan, Jack A. Wells, James M. O’Callaghan, Nicholas M. Powell, Da Ma, Sebastien Ourselin, Simon Walker-Samuel, Tracey K. Murray, Alice Fisher, Zeshan Ahmed, Michael J. O’Neill, Ross A. Johnson, Emily C. Collins, Mark F. Lythgoe, University College London, London, United Kingdom; Centre for Medical Image Computing, University College London, London, United Kingdom; Eli Lilly and Company, Surrey, United Kingdom; Eli Lilly and Company, Indianapolis, IN, USA. Contact e-mail: o.ismail@ucl.ac.uk