Medical Imaging

EPSRC Centre for Doctoral Training

Research

Projects

  • 101 - Towards real-time optimization of parameter settings for SonazoidTM enhanced ultrasound imaging

    This is an industrial PhD project aimed at developing novel imaging techniques for contrast-enhanced liver imaging using the ultrasound contrast agent (UCA) SonazoidTM. UCAs are micrometer size bubbles (with the size range of 3-10 µm diameters) that consist of an inert gas core encapsulated by a stabilizing shell (protein, lipid or polymer). More...

  • 105 - A machine learning approach to solving the SAR problem for ultrahigh field MRI

    Ultrahigh field (UHF) MRI has the potential to provide very high resolution anatomical images with new types of contrast compared with more conventional lower field MRI. However the required high-frequency RF fields are highly spatially variable inside the human body, and in order to image outside the brain multiple transmitters (so called parallel transmit, pTx) are required1. An issue with this approach is that quantification of potential RF heating effects is not straightforward. Currently UHF-MRI facilities use conservative safety limits that ensure safety but stop UHF-MRI from reaching its true potential. UHF-MRI also often requires specialist operators, limiting workflow and clinical applicability. More...

  • 118 - Passive Imaging of Acoustic Sources: Novel imaging algorithms for monitoring therapeutic ultrasound

    Acoustic sources are objects that emit sound, such as a car, a dolphin, and underground rivers. Sound emitted from these sources can be captured to identify them or characterise their behaviours. Acoustic detection is unique, because it can describe objects through opaque material. One limitation with acoustic detection methods was that they are unable to locate – with good precision – where the sound is coming from. More...

  • 119 - Optimising acquisition and analysis methods enabling clinical use of Arterial Spin Labelling perfusion MRI in neurological patients

    Though non-invasive measurements of cerebral perfusion with Arterial Spin Labelling have been around for many years, their clinical impact is still limited. Most product ASL sequence implementations provide limited coverage, signal-to-noise, inadequate standardisation for quantification and reproducibility and there is relatively little consensus on post-acquisition processing. This project aims to develop a combination of acquisition and a streamlined processing methods to robustly measure cerebral perfusion in the clinic and present the results to the clinicians alongside healthy control templates, to facilitate and support neuroradiological reporting. More...

  • 201 - Development and Implementation of MRI compatible dual Cerenkov and fluorescence endoscopy

    We propose to combine the advantages of widely-available MRI-based whole-body imaging with the promising emerging optical technique of fluorescence microendoscopy and Cerenkov luminescence. We plan to design and implement three detection modules to expand the clinical utility of microendoscopy, comprising wide-field video-rate fluorescence imaging, fluorescence spectrometry and Cerenkov luminescence point detection. These modules will allow sub-micron fluorophore detection, selectivity and quantification, together with the Cerenkov luminescence, an emerging technology which allows the direct optical visualisation radioisotope decay signals. More...

  • 202 - Imaging cancer stem cells using carbon-11 radiolabelled dithiocarbamate complexes

    Cancer stem cells (CSCs) are a subpopulation of cancer cells with characteristics resembling stem cells, including differentiation and unceasing proliferation. Owing to these stem-cell-like properties, CSCs divide in a slow and controlled manner, and thus evade conventional apoptosis-inducing chemotherapies that typically target fast growing cells. There is much evidence to now show that CSCs are responsible for tumorigenicity, metastasis and therapeutic resistance. Upon surviving initial treatment, CSCs are able to reform tumour masses and generate motile-proficient cancer cells capable of colonizing secondary tumour sites. Therefore, cancer therapies must have the ability to eliminate entire tumour populations, including CSCs, to provide long-lasting durable responses. More...

  • 203 - Ultra-bright magnetic organic semiconductor nanoparticles for multimodal imaging

    Conjugated polymer nanoparticles are an attractive alternative to quantum dots in imaging due to the lack of heavy metal or inorganic decomposition products. Such particles, often referred to as SPNs (semiconducting polymer nanoparticles) or P-dots (polymer dots) are generally much brighter than inorganic quantum dots, easier to prepare and have, to-date, shown no toxicity issues that prevent their routine use or ultimate clinical applications. The MG group has developed much of the chemistry behind SPN synthesis, which is now being commercialised through KCL. More...

  • 212 - New Lipophilic Cations for Imaging Apoptosis and the Mitochondria

    Apoptosis is the most common form of programmed cell death and is a key mechanism in many pathological diseases. These include cancer, diabetes, neurodegenerative disorders and aging. Being able to fully understand this mechanism could lead to huge advances in detection, drug development and treatment. Currently there are very few non-invasive techniques capable of quantifying and assessing the process of apoptosis in humans. The discovery that mitochondria play an important role in the early stages of apoptosis has directed focus to targeting the mitochondria as a means of identifying disease. Changes in mitochondrial membrane potential (m) can be directly related to mitochondrial dysfunction, representing a biophysical process that could be targeted with imaging. More...

  • 307 - Development of a decision support tool for neuroimaging using explainable ML

    The purpose of this project is to develop an ML-based decision support tool for brain Magnetic Resonance Images (MRI) with application to neurological disorders. A particular focus will be on the development of a decision support tool that will not only be able to diagnose patients based on clinical imaging and non-imaging information, but will also be able explain how it has reached its decision. For this, we will use a large database of multi-modal brain MRI from patients with different forms of dementia. More...

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