Imaging mouse models of neurodegeneration using multi-parametric MRI

Alzheimer’s disease (AD) is a devastating condition characterised by significant cognitive impairment and memory loss. Transgenic mouse models are increasingly being used to further our knowledge of the cause and progression of AD, and identify new targets for therapeutic intervention. These mice permit the study of specific pathological hallmarks of the disease, including intracellular deposits of hyperphosphorylated tau protein and extracellular amyloid plaques. In order to characterise these transgenic mice, robust biomarkers are required to evaluate neurodegenerative changes and facilitate preclinical evaluation of emerging therapeutics. In this work, a platform for in vivo structural imaging of the rTg4510 mouse model of tauopathy was developed and optimised. This was combined with a range of other clinically relevant magnetic resonance imaging (MRI) biomarkers including: arterial spin labelling, diffusion tensor imaging and chemical exchange saturation transfer. These techniques were applied in a single time-point study of aged rTg4510 mice, as well as a longitudinal study to serially assess neurodegeneration in the same cohort of animals. Doxycycline was administered to a subset of rTg4510 mice to suppress the tau transgene; this novel intervention strategy permitted the evaluation of the sensitivity of MRI biomarkers to the accumulation and suppression of tau. Follow-up ex vivo scans were acquired in order to assess the sensitivity of in vivo structural MRI to the current preclinical gold standard. High resolution structural MRI, when used in conjunction with advanced computational analysis, yielded high sensitivity to pathological changes occurring in the rTg4510 mouse. Atrophy was reduced in animals treated with doxycycline. All other MRI biomarkers were able to discriminate between doxycycline-treated and untreated rTg4510 mice as well as wildtype controls, and provided insight into complimentary pathological mechanisms occurring within the disease process. In addition, this imaging protocol was applied to the J20 mouse model of familial AD. This mouse exhibits widespread plaque formation, enabling the study of amyloid-specific pathological changes. Atrophy and deficits in cerebral blood flow were observed; however, the changes occurring in this model were markedly less than those observed in the rTg4510 mouse. This study was expanded to investigate the early-onset AD observed in individuals with Down’s syndrome (DS) by breeding the J20 mouse with the Tc1 mouse model of DS, permitting the relationship between genetics and neurodegeneration to be dissected. This thesis demonstrates the application of in vivo multi-parametric MRI to mouse models of neurodegeneration. All techniques were sensitive to pathological changes occurring in the models, and may serve as important biomarkers in clinical studies of AD. In addition, in vivo multi-parametric MRI permits longitudinal studies of the same animal cohort. This experimental design produces more powerful results, whilst contributing to worldwide efforts to reduce animal usage with respect to the 3Rs principles

Automated morphometric analysis and phenotyping of mouse brains from structural µMR images

In light of the utility and increasing ubiquity of mouse models of genetic and neurological disease, I describefully automated pipelines for the investigation of structural microscopic magnetic resonance images of mouse brains – for both high-throughput phenotyping, and monitoring disease. Mouse models offer unparalleled insight into genetic function and brain plasticity, in phenotyping studies; and neurodegenerative disease onset and progression, in therapeutic trials. I developed two cohesive, automatic software tools, for Voxel- and Tensor-Based Morphometry (V/TBM) and the Boundary Shift Integral (BSI), in the mouse brain. V/TBM are advantageous for their ability to highlight morphological differences between groups, without laboriously delineating regions of interest. The BSI is a powerful and sensitive imaging biomarker for the detection of atrophy. The resulting pipelines are described in detail. I show the translation and application of open-source software developed for clinical MRI analysis to mouse brain data: for tissue segmentation into high-quality, subject-specific maps, using contemporary multi-atlas techniques; and for symmetric, inverse-consistent registration. I describe atlases and parameters suitable for the preclinical paradigm, and illustrate and discuss image processing challenges encountered and overcome during development. As proof of principle and to illustrate robustness, I used both pipelines with in and ex vivo mouse brain datasets to identify differences between groups, representing the morphological influence of genes, and subtle, longitudinal changes over time, in particular relation to Down syndrome and Alzheimer’s disease. I also discuss the merits of transitioning preclinical analysis from predominately ex vivo MRI to in vivo, where morphometry is still viable and fewer mice are necessary. This thesis conveys the cross-disciplinary translation of up-to-date image analysis techniques to the preclinical paradigm; the development of novel methods and adaptations to robustly process large cohorts of data; and the sensitive detection of phenotypic differences and neurodegenerative changes in the mouse brai

Development of Anatomical and Functional Magnetic Resonance Imaging Measures of Alzheimer Disease

Alzheimer disease is considered to be a progressive neurodegenerative condition, clinically characterized by cognitive dysfunction and memory impairments. Incorporating imaging biomarkers in the early diagnosis and monitoring of disease progression is increasingly important in the evaluation of novel treatments. The purpose of the work in this thesis was to develop and evaluate novel structural and functional biomarkers of disease to improve Alzheimer disease diagnosis and treatment monitoring. Our overarching hypothesis is that magnetic resonance imaging methods that sensitively measure brain structure and functional impairment have the potential to identify people with Alzheimer’s disease prior to the onset of cognitive decline. Since the hippocampus is considered to be one of the first brain structures affected by Alzheimer disease, in our first study a reliable and fully automated approach was developed to quantify medial temporal lobe atrophy using magnetic resonance imaging. This measurement of medial temporal lobe atrophy showed differences (pnovel biomarker of brain activity was developed based on a first-order textural feature of the resting state functional magnetic resonance imagining signal. The mean brain activity metric was shown to be significantly lower (pp18F labeled fluorodeoxyglucose positron emission tomography. In the final study, we examine whether combined measures of gait and cognition could predict medial temporal lobe atrophy over 18 months in a small cohort of people (N=22) with mild cognitive impairment. The results showed that measures of gait impairment can help to predict medial temporal lobe atrophy in people with mild cognitive impairment. The work in this thesis contributes to the growing evidence the specific magnetic resonance imaging measures of brain structure and function can be used to identify and monitor the progression of Alzheimer’s disease. Continued refinement of these methods, and larger longitudinal studies will be needed to establish whether the specific metrics of brain dysfunction developed in this thesis can be of clinical benefit and aid in drug development

Posterior cortical atrophy: a neuropsychological and neuroimaging study

This thesis investigates the neuroimaging and neuropsychological characteristics of Posterior Cortical Atrophy (PCA) which is most often caused by Alzheimer’s disease (AD) pathology. Posterior cortical atrophy describes a predominantly posterior pattern of atrophy and cognitive deficits. PCA has been poorly characterized and is likely to have been under-recognized. Using magnetic resonance imaging (MRI), patterns of cortical thickness were assessed in patients with pathologically-confirmed AD and different clinical presentations during life (including amnestic, visual and behavioural phenotypes). In addition to atrophy in the medial temporal lobe, tissue loss in posterior regions is indicative of AD pathology. Since medial temporal lobe atrophy is not specific to AD, posterior atrophy may aid distinction between AD and other dementias. Using easily-applied visual rating scales for medial temporal and posterior atrophy in patients with pathologically-confirmed AD and frontotemporal lobar degeneration (FTLD), it was shown that posterior atrophy ratings improve classification accuracy of AD from FTLD and controls. Cross-sectional and longitudinal image analysis techniques were used to characterize atrophy patterns in PCA compared with controls and typical amnestic AD. Whilst the cross-sectional analysis revealed differential patterns of tissue loss in these two groups, with PCA showing greatest atrophy in posterior parietal regions, and typical AD predominantly in medial temporal lobe regions, longitudinal results showed that at five years disease duration, both PCA and typical AD had global grey matter loss and cortical thinning compared with controls. The nature of visual deficits in PCA was assessed by administering detailed neuropsychological tests. The behavioural data showed that visual deficits were not uniformly affected in PCA, with considerable heterogeneity of visual impairments shown. Cortical thickness measures were used to assess atrophy patterns in PCA patients with predominant space versus object perception impairments, revealing overlap in cortical thinning patterns between these two PCA subgroups. In summary this thesis investigates the common and differential atrophy patterns of atypical AD presentations as well as the degree of heterogeneity of deficits which exist within the PCA presentation

MRI-based measures in Alzheimer's disease and related disorders.

This thesis investigates the use of manual measures of brain structure delineation on MR scans in order to assess atrophy in dementia. It further investigates the automation of atrophy measures. A new protocol for outlining the cingulate is described and was applied to groups of Alzheimer's disease (AD) and control subjects. The application of existing hippocampal and amygdala protocols to a group of pathologically-confirmed AD, frontotemporal lobar degeneration (FTLD) and controls is detailed. This analysis shows cross-sectional measurements were useful subject-group discriminators and that patterns of atrophy within and between structures may distinguish diseases. Manual delineation of regions (cingulate and hippocampus) was extended to longitudinal studies to establish atrophy rates in groups of AD, FTLD and controls. The cingulate was shown to be at least as affected as the hippocampus by disease. Hippocampal atrophy rates from inter-scan intervals of six months were compared with measurements in the same subjects of one-year intervals. Results from studies combining cross-sectional and longitudinal hippocampal data are described. These assess the asymmetry of the structure and investigate the pre-symptomatic decrease in volume in familial AD subjects. Semi-automated techniques were performed which utilise registration of serial hippocampi to assess change longitudinally. Results show the semi-automated techniques to be reliable and consistent with manual measures. These techniques were then applied to scans from a multi-centre clinical trial and again consistency with manual measures was assessed. The generation of fully-automated template-based hippocampal segmentations is described. The approximate regions generated from the template were used to quantify the boundary shift integral and the resultant atrophy rates were compared with manual rates revealing automated measures to be consistent with manual measures. These results are put within the context of other similar studies by performing a meta analysis of hippocampal atrophy rates. Implications for diagnosis and monitoring disease progression are discussed

Brain structure and function in Huntington's disease gene carriers far from predicted disease onset

Whilst there are currently no available disease modifying therapies for Huntington’s Disease (HD), recent progress in huntingtin-lowering strategies hold great promise. Initiating therapies early in the disease course will be important and a complete characterisation of the premanifest period will help inform when to initiate disease modifying therapies and the biomarkers that may be useful in such trials. Previous research has characterised the premanifest period up to approximately 15 years from predicted onset, but even at this early stage the disease process is already underway as evidenced by striatal and white matter atrophy, reductions in structural connectivity within brain networks, rising biofluid biomarkers of neuronal dysfunction, elevations in psychiatric symptoms and emerging subtle cognitive impairments. In order to understand how early neurodegeneration can be detected and which measures are most sensitive to the early disease processes, we need to look even earlier in the disease course. This thesis documents the recruitment and analysis of the HD Young Adult Study: a premanifest cohort further from predicted clinical onset than previously studied with an average of 24 years prior to predicted onset. Differences between gene carriers and controls were examined across a range of imaging, cognitive, neuropsychiatric and biofluid measures. The structural and functional brain connectivity in this cohort is then investigated in further detail. By providing a detailed characterisation of brain structure and function in the early premanifest period along with the most sensitive biomarkers at this stage, this work will inform future treatment strategies that may seek to delay the onset of functional impairments in HD

Evaluation of recurrent glioma and Alzheimer’s disease using novel multimodal brain image processing and analysis

Novel analysis techniques were applied to two different sets of multi-modality brain images. Localised metabolic rate within the hippocampus was assessed for its ability to differentiate between groups of healthy, mildly cognitively impaired, and Alzheimer’s disease brains, and an investigation of its potential clinical diagnostic utility was conducted. Relative uptake and retention of two PET tracers (11Carbon Methionine and 18Fluoro Thymidine) in a post-treatment glioma patient cohort was utilized to perform survival prediction analysis

Clinical, biochemical and neuroimaging studies in familial Alzheimer's disease.

This thesis investigates several aspects of familial Alzheimer disease (FAD). The specific results of the work undertaken for this thesis were: (1) The proportion of FAD accounted for by mutations in known genes was 68% in 31 FAD families Those without mutations were ten years older and associated with APOE e4 (2) The phenotype of PSEN1 FAD was found to share an early age at onset and features broadly suggestive of AD. However the phenotype was broad and included spastic paraparesis in association with "cotton wool" plaques in PSEN1 E280G (3) Plasma amyloid P peptide was found to be a potentially useful biomarker of FAD with levels being elevated in mutations carriers compared with non-carriers, and levels in at risk subjects falling halfway between the groups (4) Cerebral atrophy in early onset AD was 2-8% (95% CI 2-3-3-3) per year which rose by 0-32% per year (0-15-0-50) (5) Pre-symptomatic medial temporal lobe atrophy in FAD at risk family members who become symptomatic was demonstrated with MRI medial temporal lobe volumes 16.6% lower in patients than controls and a higher rate of atrophy in patients than controls (6) Cerebral atrophy in FAD was shown to begin in the posterior cingulate, temporoparietal and medial temporal cortices in presymptomatic FAD patients, a finding in accordance with previous cross-sectional neuropathological studies (7) By contrast the onset and progression of cerebral atrophy in non-AD familial dementia was shown to markedly different in an presymptomatic FTLD patient with focal left frontal lobe onset reflecting the different clinical presentation (8) Cerebral atrophy in FAD was found not to progress significantly faster than sporadic AD despite a twenty year age difference between the groups