SPMIC PhD Students

My research is focus on checking the reproducibility of the susceptibility and volume of the hippocampus subfields, this help us the change in iron content which has being implicated in many neurodegenerative diseases. I am also working on the venous and arterial supply of the thalamus.

Significant gaps remain in our basic knowledge of what happens to solid oral dosage forms (tablets) in the stomach, particularly when taken with food. MRI imaging has the potential to provide new information on spatial and temporal processes occurring in the stomach. This EPSRC iCASE collaboration between GSK, gastrointestinal imaging and pharmacy specialists at the University of Nottingham will address these key issues, with the potential to lead to better in-vitro and in-silico modelling tools for oral dosage forms development, and ultimately enhance our ability to tailor drug release in the fed state.

The extracellular matrix (ECM) is an essential component of skeletal muscle. Muscle fibrosis is the excessive accumulation of ECM components, especially collagens, which negatively affects muscl regeneration after injury and is a major cause of muscle functional and qualitative decline. It is a hallmark aging and severe muscle injuries (1). The study of muscle ECM in humans necessitates the use of muscle biopsies, which are impractical in many settings, particularly in recovering trauma patients, and may limit the design of longitudinal studies. We aim to develop and validate novel sodium (23Na) and collagen MRI imaging methods that will allow identification of localised muscle damage following high load, lengthening muscle contractions and recovery regeneration of muscle during the days following damage in healthy volunteers. Furthermore, we will apply these methods to identify localised fibrotic muscle tissue and associated pathology in patients following recovery from acute trauma. Collectively these approaches will provide a completely non-invasive clinical tool to delineate muscle ECM pathophysiology, which at present requires a muscle biopsy, greatly limiting feasibility.

Joe Bradley - Google Scholar

Deuterium metabolic imaging (DMI) is a new non-invasive method for the three-dimensional mapping of metabolic activity, it involves using spectroscopic 2H magnetic resonance imaging to map the distribution of 2H-bearing metabolites generated following the infusion/injection of deuterium-labelled compounds. DMI potentially provides an alternative to FDG-PET for cancer detection, with the benefits of not requiring the use radioactive tracers while providing information about metabolism that goes beyond glucose uptake. This project aims to implement DMI on the Nottingham 7T scanner for application to brain cancer which involves developing approaches that exploit the increased signal to noise ratio available at higher fields.

Daniel Cocking - LinkedIn
Daniel Cocking Orchid
Daniel Cocking Research Gate

Electroencephalography (EEG) and Magnetoencephalography (MEG) measure the electric and magnetic components of fields originating in the brain. Haemodynamic activity related to brain function is measured using functional MRI (fMRI). Post-Stimulus Responses (PSRs) in EEG and MEG are patterns of activity that occur after a task or stimulus has ended. PSRs are thought to contain unique information to primary stimulus responses, and have been shown to relate to pathologies including Schizophrenia and Autism. My PhD aims to use EEG and MEG to uncover the functional significance of PSRs, and relate them to haemodynamics measured using fMRI.

Sebastian Coleman LinkedIn

Gamma alumina is widely used in industry for applications in catalysis, due to its high mechanical strength, high surface area, and good porosity levels. These catalytic supports have, however, complex porous structures, with porous organizations ranging from the nanometre to the millimetre scale. These properties have a significant impact on the mass transfer kinetics in the catalyst, and hence on the performance of the catalytic process. In gas diffusion-limited pellets, the optimization of the structure is vital in enabling IFPEN (industrial sponsor), and industry in general to reduce their emissions and achieve their greenhouse gas emission targets in the future. 

My research is investigating magnetic shielding for OPM MEG. I have been characterising how magnetic fields interact with high permeability magnetic shielding materials using simulations and measurements taken inside a mu-metal box. I am now developing a coil calibration technique to actively control the magnetic field inside a single layer mu-metal box using electromagnetic coils. Using continuous calibration, we aim to null the magnetic field surrounding a moving array of OPMs. My PhD is funded by the EPSRC and Magnetic Shields Limited.   

Internal combustion engines produce many unwanted by-products which are detrimental to the environment and public health. Diesel particulate filters and gasoline particulate filters are a widely used technology for the removal of these pollutants. These are mostly porous ceramic wall-flow filters which have been coated with catalytic washcoats. My research aims to improve this technology by characterising the gas-phase hydrodynamics within the opaque and not easily accessible structure of these filters. Novel hyperpolarised noble gas (HP NG) magnetic resonance imaging and velocimetry techniques are utilized to probe gas flow patterns in the supportive channels, permeation through the walls, and to investigate the influence of channel surface roughness on the flow profile. All studied in the Knudsen diffusion regime. This will be used, in conjunction with other methodologies, to assess the accessibility and potential for bypassing the catalyst caused by washcoat distribution inhomogeneities at varying free pore volumes. My research also explores an innovative approach to HP NG purification, via catalytically triggered combustion, and recompression to enable new HP NG applications to porous media and biomedical research.

My PhD project is about using sodium magnetic resonance spectroscopy (MRS) and imaging (MRI) to study sodium in human tissues, skin samples in particular, in a high magnetic field of 9.4 T in patients with type 2 Diabetes Mellitus (T2DM) compared to controls. Using these methods, we are trying to explore mechanisms of sodium accumulation in the skin and why its content is increased in patients with T2DM.My project also includes the development of low-field portable sodium NMR sensors to make studies of sodium in human skin easier, more affordable, non-invasive, and as informative as in high field as possible.

I am interested in the possibility of studying the brain’s microstructure non-invasively using diffusion MRI (dMRI), but validation studies are needed as dMRI lacks specificity.  A common approach involves comparing measures of microstructure derived from dMRI and microscopy. Unfortunately, microscopy is usually 2D and limited to thin sections of small tissue samples. Recently, novel tissue clearing techniques and 3D light sheet microscopy allow for detailed study of the whole, intact, rodent brain. I am capitalising on these developments for whole-brain microstructure imaging in rodents by building a 3D multi-modal and cross-resolution imaging framework using dMRI and 3D light-sheet microscopy.

Computational Neuroimaging Laboratory

I work on the development and optimisation of the hyperpolarisation of noble gases. Hyperpolarised (HP) noble gases are effective contrast agents for pulmonary MRI to investigate lung function and microstructure. Instead of detecting signal from organic tissue (typical of conventional MRI), one can image the gas within void space of the lung cavities and dissolved in the pulmonary tissue itself. These techniques give great insight into lung function, including ventilation and gas diffusion through the parenchyma, but also provide information about the alveolar microstructure. Following earlier work with helium-3, HP xenon-129 is approved for clinical MRI use in the UK. Additionally, krypton-83 is under active development in model systems and previous work demonstrated surface sensitive contrast via interactions of its nuclear quadrupole moment. My work centres on development of these methods, from improvements in production to application in a clinical setting. I’m part of a ‘first of its kind’ UK wide study, using HP xenon MRI to investigate long term damage to the lungs due to Covid-19.

The main focus of my research project is to: (a) investigate the neural antecedents of tics in Tourette syndrome, and (b) evaluate the use of median nerve electrical stimulation as a potential therapy. I will use a variety of neuroimaging techniques including OPM-MEG and fMRI to investigate the brain network activity associated with the occurrence of tics and the urge-to-tic. I will also investigate the entrainment and neuromodulatory effects of rhythmic median nerve stimulation on the sensorimotor cortex using MEG and magnetic resonance spectroscopy.

Mairi Houlgreave LinkedIn

My research involves developing minimally supervised machine learning approaches to segmenting MRI images, and optimising the image acquisition process such that segmentation is performed more efficiently. Traditionally, machine learning algorithms are fed hundreds of raw and labelledimages such that the system learns to map pixels of input images to labels. This is not ideal in medical scenarios, where labelled images must be produced by experts, making the training processprohibitively expensive. My research involves developing segmentation systems that use minimal labelling, and also optimising the image acquisition process itself using information gained by the segmentation system.

I work developing new frameworks for Bayesian inference of microstructural models in diffusion MRI, used for brain connectivity mapping. Compared to previous conventional approaches that can be computationally expensive and time-consuming, we have been investigating more efficient approximate Bayesian approaches, as well as network-based simulation-based approaches. The latter allows model inversion even in challenging cases when a forward prediction is possible, but an analytically tractable likelihood is not available. These new approaches allow uncertainty quantification in modeling and the project utilizes them to assess new denoising approaches that the field has proposed for EPI MRI datasets.

I work on the development of high resolution 7T functional and structural MRI methods for detailed layer specific acquisition and analysis. I have developed a bespoke pipeline to analyse simultaneous EEG-fMRI data acquired at 7T with the aim to examine a fundamental neuroscience question regarding the origin of the EEG-alpha rhythm.  In addition, I am working on the application of a denoising method (NORDIC) to improve the data quality of GE-EPI, ASL and VASO acquisitions in order to measure layer specific signals.

Oxford-Nottingham Biomedical Imaging CDT

I work in medical imaging. I'm trying to make MRI scans faster and get higher quality images. By applying machine learning and compressed sensing techniques I have been able to drastically reduce the scan time for several demanding imaging protocols including for a COPD lung imaging study, where I was able to reduce the scan time from >1 minute to 5.2 seconds whilst keeping acceptable image quality.

www.joshuamcateer.com
Joshua McAteer LinkedIn 

I am a 3rd year BBSRC DTP PhD student working with Dr Nic Blockley on 'Interpreting the Dynamics of the Cerebrovascular Response in Health and Disease' using pseudocontinuous Arterial Spin Labelling Magnetic Resonance Imaging (pCASL-MRI). This involves using hypercapnic challenges (breathing in high carbon dioxide (CO2) mixed with air) to signal the blood vessels in the brain to increase the blood flow. We aim to accurately measure this change in blood flow to provide new insights into vascular diseases of the brain and provide clinicians with information for diagnosis. 

Colette Milbourn Google Scholar

My research focuses on the characterization of abdominal fat in Crohn's disease (CD).CD is an inflammatory bowel disease that affects 150k people in the UK alone. Abnormal overgrowth of inner abdominal fat is a characteristic radiological finding in CD. To date, radiologists just describe it but cannot provide more objective data regarding fat volume and other various characteristics such as abdominal fat blood flow. I use advanced MRI techniques and develop image processing algorithms to quantify abdominal fat properties in CD, such as abdominal fat volumes, fatty acid composition and abdominal vessels branching.

Iyad Naim Research Gate

My PhD is focussed on understanding how physical activity affects the ageing process, and to isolate changes due to ageing from those due to an inactive lifestyle. To do this, non-active older and younger male volunteers, and older endurance cyclists, are undergoing MR scans at rest, during exercise using an Ergospect CardioStepper, and during a recovery. 

My research is based on Harmonisation which has the aim of reducing the variability induced by MRI scanners whilst preserving biological variability. The overall goal is to address the lack of consistency, accuracy and reproducibility in quantitative imaging caused by nuisance factors such as scanning hardware, protocol and hardware and software. 

Asante Ntata GitHub

My PhD is in pulmonary MRI, specifically looking at non-contrast proton-based methods. My project focuses on the development of proton MRI lung imaging, which could allow for both structural and functional assessment of many different conditions, including cystic fibrosis, COPD and long COVID. In particular, the ability to generate regionally-localized functional information without extensive pulse sequence modification or additional hardware makes these proton-based methods promising candidates for clinical translation.

The development of compact and light-weight optically-pumped magnetometers (OPMs) has enabled the creation of a wearable magnetoencephalography (MEG) system, in which sensors are held close to the scalp in a helmet that moves with the wearer. However, movement of an OPM through a background magnetic field generates artefacts in MEG data that can mask brain activity. My work aims to map the background magnetic field precisely, and to cancel out this magnetic field using electromagnetic coils. This will reduce motion artefacts in OPM-MEG data and allow a greater range of participant motion to be performed whilst high-quality data are obtained.

Molly Rea Google Scholar

My PhD project investigates the role of neurophysiological inhibition and cortical somatomotor representations in individuals with Tourette’s syndrome (TS). Furthermore, this project will investigate how this neurophysiological inhibition and mapping may be related to the altered sensory processing experienced in TS. This project involves the use of transcranial magnetic stimulation (TMS) and multimodal imaging techniques, such as fMRI and GABA-edited MRS.

Caitlin Smith PhD profile
Caitlin Smith Research Gate 
Caitlin Smith LinkedIn 

Type 2 Diabetes Mellitus (T2D) affects 1 in 10 over 40s in the UK with 90% of suffers being overweight. It has been found that weight loss alongside changes to diet and lifestyle can lead to the reversal of T2D. With many obese patients going on the waiting list for bariatric surgery but only 1% of these receiving it, an alternate treatment is needed. Using MRI of the liver, pancreas, muscle and heart and MRS techniques including 1H cardiac and 31P liver measures, I will investigate the mechanisms in which bariatric surgery induces the reversal of T2D.  This will help understand whether changes occur through weight loss or hormonal changes following surgery.

Oral coated formulations have the potential to improve treatment outcomes of a range of diseases in distal intestinal tract whilst limiting systemic drug absorption and adverse effects. Their development is challenging, partly because of limited knowledge of the physiological and pathological distal gastrointestinal factors, including colonic chyme fluid distribution and motor function. Recently, non-invasive techniques such as magnetic resonance imaging (MRI) have started to provide novel important insights. In this PhD, a coated capsule is formulated that can withstand the upper gastrointestinal tract conditions. The capsule is filled with olive oil as MRI-visible marker fluid to test the ability of MRI to track such a coated capsule in the gastrointestinal tract and to assess whether it is possible to image its loss of integrity. 

Cystic fibrosis (CF) is a common life limiting autosomal recessive condition that affects over 10,000 people in the UK. Most people with CF will experience gastrointestinal (GI) symptoms such as pain, bloating and flatulence and up to two thirds will miss school or work due to their symptoms.  
Building on previous work, we are working to help reduce the burden of these symptoms by using MRI to understand the causes of GI symptoms and complications in people with CF. We also hope to create an optimised MRI protocol for use in future research into candidate therapeutics or clinical monitoring.