Cognitive Correlates of Hippocampal Atrophy and Ventricular Enlargement in Adults with or without Mild Cognitive Impairment

We analyzed structural magnetic resonance imaging data from 58 cognitively normal and 101 mild cognitive impairment subjects. We used a general linear regression model to study the association between cognitive performance with hippocampal atrophy and ventricular enlargement using the radial distance method. Bilateral hippocampal atrophy was associated with baseline and longitudinal memory performance. Left hippocampal atrophy predicted longitudinal decline in visuospatial function. The multidomain ventricular analysis did not reveal any significant predictors

Multimodal population brain imaging in the UK Biobank prospective epidemiological study

Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank

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

Developing novel non-invasive MRI techniques to assess cerebrospinal fluid-interstitial fluid (CSF-ISF) exchange

The pathological cascade of events in Alzheimer’s disease (AD) is initiated decades prior to the onset of symptoms. Despite intensive research, the relative time-course/interaction of these events is yet to be determined. Recent evidence suggests that impairments to brain clearance (facilitated by the compartmental exchange of cerebrospinal-fluid (CSF) with interstitial-fluid (ISF)), contributes to the build-up of amyloid and tau (AD hallmarks). Therefore, abnormalities in CSF-ISF exchange dynamics, may represent an early driver of downstream events. Clinical evaluation of this hypothesis is hampered due to the lack of non-invasive CSF-ISF exchange assessment techniques. In this thesis, the primary aim was to develop a physiologically relevant, non-invasive CSF-ISF exchange assessment technique that would circumvent the limitations associated with current procedures (primarily their invasiveness). Towards this goal, animal studies were conducted to investigate the feasibility of a contrast enhanced-magnetic resonance imaging (CE-MRI) approach as a potential non-invasive CSF-ISF exchange imaging technique. Another aim of this thesis was to investigate whether the proposed MRI platform could detect abnormalities in CSF-ISF exchange, a condition hypothesised to occur in the early stages of AD. As such, pharmacological intervention studies were conducted to alter CSF-ISF exchange dynamics. CE-MRI, in conjunction with high-level image post-processing, demonstrated high sensitivity to physiological CSF-ISF exchange. This novel, non-invasive platform, captured dynamic, whole-brain infiltration of contrast agent from the blood to the CSF and into the parenchyma, via a pathway named ‘VEntricular-Cerebral TranspORt (VECTOR)’. Additionally, the platform detected significant abnormalities in CSF-ISF exchange following pharmacological intervention, demonstrating the potential of VECTOR in the study of the parenchymal accumulation of aberrant proteins. Development of this platform is a breakthrough step towards the clinical assessment of CSF-ISF exchange abnormalities to study its role in disease onset/progression, an approach that may inform understanding of the causal sequence of pathological events that occurs in AD development

The anthropometric, environmental and genetic determinants of right ventricular structure and function

BACKGROUND Measures of right ventricular (RV) structure and function have significant prognostic value. The right ventricle is currently assessed by global measures, or point surrogates, which are insensitive to regional and directional changes. We aim to create a high-resolution three-dimensional RV model to improve understanding of its structural and functional determinants. These may be particularly of interest in pulmonary hypertension (PH), a condition in which RV function and outcome are strongly linked. PURPOSE To investigate the feasibility and additional benefit of applying three-dimensional phenotyping and contemporary statistical and genetic approaches to large patient populations. METHODS Healthy subjects and incident PH patients were prospectively recruited. Using a semi-automated atlas-based segmentation algorithm, 3D models characterising RV wall position and displacement were developed, validated and compared with anthropometric, physiological and genetic influences. Statistical techniques were adapted from other high-dimensional approaches to deal with the problems of multiple testing, contiguity, sparsity and computational burden. RESULTS 1527 healthy subjects successfully completed high-resolution 3D CMR and automated segmentation. Of these, 927 subjects underwent next-generation sequencing of the sarcomeric gene titin and 947 subjects completed genotyping of common variants for genome-wide association study. 405 incident PH patients were recruited, of whom 256 completed phenotyping. 3D modelling demonstrated significant reductions in sample size compared to two-dimensional approaches. 3D analysis demonstrated that RV basal-freewall function reflects global functional changes most accurately and that a similar region in PH patients provides stronger survival prediction than all anthropometric, haemodynamic and functional markers. Vascular stiffness, titin truncating variants and common variants may also contribute to changes in RV structure and function. CONCLUSIONS High-resolution phenotyping coupled with computational analysis methods can improve insights into the determinants of RV structure and function in both healthy subjects and PH patients. Large, population-based approaches offer physiological insights relevant to clinical care in selected patient groups.Open Acces

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

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

High-throughput transgenic mouse phenotyping using microscopic-MRI

With the completion of the human genome sequence in 2003, efforts have shifted towards elucidating gene function. Such phenotypic investigations are aided by advances in techniques for genetic modification of mice, with whom we share ~99% of genes. Mice are key models for both examination of basic gene function and translational study of human conditions. Furthering these efforts, ambitious programmes are underway to produce knockout mice for the ~25,000 mouse genes. In the coming years, methods to rapidly phenotype mouse morphology will be in great demand. This thesis demonstrates the development of non-invasive microscopic magnetic resonance imaging (\muMRI) methods for high-resolution ex-vivo phenotyping of mouse embryo and mouse brain morphology. It then goes on to show the application of computational atlasing techniques to these datasets, enabling automated analysis of phenotype. First, the issue of image quality in high-throughput embryo MRI was addressed. After investigating preparation and imaging parameters, substantial gains in signal- and contrast-to-noise were achieved. This protocol was applied to a study of Chd7+/- mice (a model of CHARGE syndrome), identifying cardiac defects. Combining this protocol with automated segmentation-propagation techniques, phenotypic differences were shown between three groups of mice in a volumetric analysis involving a number of organ systems. Focussing on the mouse brain, the optimal preparation and imaging parameters to maximise image quality and structural contrast were investigated, producing a high-resolution in-skull imaging protocol. Enhanced delineation of hippocampal and cerebellar structures was observed, correlating well to detailed histological comparisons. Subsequently this protocol was applied to a phenotypic investigation of the Tc1 model of Down syndrome. Using both visual inspection and automated, tensor based morphometry, novel phenotypic findings were identified in brain and inner ear structures. It is hoped that a combination of \muMRI with computational analysis techniques, as presented in this work, may help ease the burden of current phenotyping efforts