Multimodality Imaging of Tumour Pathophysiology and Response to Pharmacological Intervention

This thesis describes the need for imaging the tumour pathophysiological microenvironment in order to understand response to treatment. Specifically looking at tumour vascularisation in in vivo murine xenograft models of disease, response to treatment with vascular disruption is assessed via photoacoustic tomography (PAT) and magnetic resonance imaging (MRI). Photoacoustic imaging is a novel imaging modality based on the detection of ultrasound waves created by the absorption of nano-second pulsed laser energy within tissue chromophores. It has the spectral specificity of optical techniques whilst also achieving the high resolution of ultrasound. Haemoglobin is the main chromophore found in biological tissue and this modality is therefore ideally suited to imaging tumour vascularisation. Using a Fabry-Perot interferometer this thesis demonstrates for the first time the feasibility of using PAT for re-clinical research and the characterisation of typical tumour vascular features in a non-invasive non-ionising manner. Response to different concentrations of a vascular disrupting drug is then demonstrated, with novel insights in to how tumours recover from vascular damage observed. MRI of response to vascular disruption is also presented. As MRI is widely used in the clinic it can serve as a translational tool of novel imaging biomarkers, and serves to further understand the differences in response of pathologically vascularised of tumours. This thesis looks at markers associated with disruption of haemodynamics, using apparent diffusion (ADC) to elucidate onset of necrosis, increase in haemoglobin concentration (R2*) as indication of impaired flow, and arterial spin labelling (ASL) as a marker of tumour blood perfusion. This is shown in both subcutaneous and clinically relevant liver metastasis models. Taken as whole, the results from this thesis indicate that whilst understanding the response of the tumour vasculature to pharmacological intervention is complex, novel imaging techniques can provide invaluable translational information on the pathophysiology of tumours

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus