Hipwell, Benjamin Oliver Richard;
(2020)
Developing novel non-invasive measures of tumour physiology.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Cancer is the leading cause of death globally; ahead of heart disease, stroke and chronic obstructive pulmonary disease. There were 8.2 million attributed deaths in 2012 [1], and the number of new cases is expected to increase by 70% in the next two decades [2]. Development of novel new therapies has consequently become a multi-billion dollar industry. However, the development of new cancer therapies is limited by our ability to accurately quantify their effects. This thesis focuses on the development of novel non- invasive biomarkers for assessing changes in tumour microstructure. In chapter 3, the capabilities of an in-house diffusion MRI technique known as Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumours (VERDICT) are inves- tigated. The technique was used to detect changes in tumour microstructure caused by a) tissue fixation and b) administration of temozolomide therapy. In chapter 4, the development of a Monte Carlo tissue diffusion simulation framework is described. The simulation framework is then applied as a tool for validating diffusion MRI models, including VERDICT. Chapter 5 presents an exploration of the potential applications of machine-learning based approaches within the field of diffusion MRI. In a preliminary study, a neural network is trained on synthetic diffusion MRI data, and applied to real-world in-vivo data to try and extract microstructural tissue features without the need for explicit model fitting. The overall aim of this thesis was to assist in the development and validation of advanced diffusion MRI modelling techniques, and explore the future potential of synthetic data and machine-learning models in the extraction of new cancer biomarkers.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Developing novel non-invasive measures of tumour physiology |
| Event: | UCL (University College London) |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2020. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10106676 |
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