O'Callaghan, JM; (2015) Development of magnetic resonance imaging techniques for mouse models of Alzheimer's Disease. Doctoral thesis , UCL (University College London).

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Abstract

Due to increasing life expectancy in western societies, a rise in the prevalence of Alzheimer’s Disease (AD) is expected to have adverse social and economic consequences. The success of emerging treatments for AD relies heavily on the ability to test their efficacy. Sensitive biomarkers are required that provide information specific to the therapeutic targets. Through manipulation of the genome, transgenic mice have been bred to exhibit particular pathological features of AD in isolation. Magnetic Resonance Imaging (MRI) of these mouse models can be used to observe phenotypic abnormalities in-vivo in a controlled environment. As summarised in the introductory chapter, the aim of this work was to develop MRI techniques for inclusion in multi-parametric protocols to characterise AD models in-vivo. Structural MRI has become an increasingly popular tool in the measurement of atrophy of brain tissue over time and requires both accuracy and stability of the imaging system. In chapter 3, a protocol for the calibration of system gradients for high resolution, pre-clinical MRI is described. A structural phantom has been designed and 3D printed for use in a 9.4T small bore MRI and micro CT system. Post processing software is used to monitor gradient stability and provide corrections for scaling errors and non-linearity. Diffusion Tensor Imaging (DTI) and Quantitative Susceptibility Mapping (QSM) are MRI techniques that have shown sensitivity to changes in white matter regions of the brain. QSM may also provide a non invasive method for measurement of increased iron concentration in grey matter tissue observed in AD. Chapters 4 and 5 evaluate the utility of these measurements as imaging biomarkers in a mouse model that exhibits tau pathology associated with AD. Discrepancies between transgenic and wild-type groups were identified for both MRI techniques indicating the potential benefit of their inclusion in a multi-parametric in-vivo protocol.

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