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Developing Magnetic Resonance Targeting Methods

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Magnetic resonance targeting (MRT) is a novel method which repurposes the imaging gradient coils, inherent in most clinical magnetic resonance imaging (MRI) systems, to essentially steer super paramagnetic iron oxide (SPIO) labelled particles to a target regions deep within a sample. MRT finds application in cellular therapy, the success of which depends on the ability to deliver the cells to the site of injury. We have already demonstrated that in a preclinical model MRT can be used to direct macrophages, carrying an oncolytic virus, from the bloodstream into primary and metastatic tumour sites in mice. This resulted in a significant increase in tumour macrophage infiltration and reduction in tumour burden and metastasis (Muthana et.al. 2015). However, the MRT technique was not fully optimised and once the induced forces are fully understood as a function of both the hardware and physiological constraints, the targeting efficiency can be further controlled. This is important because MR imaging is heavily used in medical diagnosis; and therefore combining conventional imaging with this novel functionality (once fully parameterised) opens up the possibility for real-time image-guided targeting using an MRI system for improved efficacy and reduced treatment costs.

This Ph.D project therefore involves the development, implementation and parameterisation of MRT on a 7 Tesla preclinical scanner within the department of Chemistry. Physically the steering force induced by the gradient coils on magnetically labelled cells is dependent on whether the SPIOs have become magnetically saturated. When unsaturated, the force is dependent on the magnetic susceptibility of the SPIOs, the magnetic field and also the magnetic field gradient. However, once the SPIOs reach saturation, the force is no longer dependent on the magnetic susceptibility of the particle but the saturation magnetization and as such only the magnetic field gradient will affect the force applied to the cells. In-vivo the force will also depend on blood flow rates and vascular drag forces. You will investigate, using different SPIOs, the effect on targeting efficiency of pulse gradient duration (1-10 ms), gradient strength (0-660mT/m), fluid flow rates (capillary like upwards), vessel radius and total targeting duration. The project will primarily involve phantom work (bifurcating vascular models). Once developed, testing will move in-vivo. You will design/engineer a series bespoke radio frequency (RF) resonators/coils and test the practicality of performing conventional imaging interlaced with targeting to enable interactive manipulation and assessment of the distribution of particles and therefore, in the future, potential therapies. Using the data collected you will model this multi-parametric space to assess the feasibility of using MRT on clinical scanners in patients (where the hardware and physiological constraints are different to previously published work). The final stage of this project will be a feasibility study through the implantation and testing of this innovative MR method on a clinical scanner (3T Siemens) at the University of York.

All research students follow our innovative Doctoral Training in Chemistry (iDTC): cohort-based training to support the development of scientific, transferable and employability skills. All research students take the core training package which provides both a grounding in the skills required for their research, and transferable skills to enhance employability opportunities following graduation. Core training is progressive and takes place at appropriate points throughout a student’s higher degree programme, with the majority of training taking place in Year 1. In conjunction with the Core training, students, in consultation with their supervisor(s), select training related to the area of their research.

You will gain advanced training in magnetic resonance imaging, coil development, pulse programming and signal processing. The project is underpinned by the large multidisciplinary research project implementing MRT technology in oncology and this will help ensure we produce a skilled researcher with a broad range of experience. You will learn to design and implement experiments on a pre-clinical 7T and clinical 3T MRI system, gaining necessary Home Office training and ethical training. Our research students receive wide-ranging support as they learn to interpret their own data and communicate their results through group presentations, conferences and scientific manuscripts.

The Department of Chemistry holds an Athena SWAN Gold Award and is committed to supporting equality and diversity for all staff and students. The Department strives to provide a working environment which allows all staff and students to contribute fully, to flourish, and to excel. Chemistry at York was the first academic department in the UK to receive the Athena SWAN Gold award, first attained in 2007 and then renewed in October 2010 and in April 2015.

Funding Notes

This project is open to students who can fund their own studies or who have been awarded a scholarship separate from this project. The Chemistry Department at York is pleased to offer Wild Fund Scholarships to those from countries outside the UK. Wild Fund Scholarships offer up to full tuition fees for those from countries from outside the European Union. EU students may also be offered £6,000 per year towards living costs. For further information see: View Website

References

M Muthana*, A J Kennerley*, R Hughes, E Fagnano, J Richardson, M Paul, C Murdoch, F Wright, C Payne, M Lythgoe, N Farrow, J Dobson, J Conner, J M Wild, C Lewis (2015) Directing Cell Therapy to Anatomic Target Sites in-vivo with Magnetic Resonance Targeting. Nature Coms 6.

Related Subjects

How good is research at University of York in Chemistry?

FTE Category A staff submitted: 47.06

Research output data provided by the Research Excellence Framework (REF)

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