XClose

UCL EPSRC Centre for Doctoral Training in Intelligent Integrated Imaging in Healthcare

Home
Menu

NOW CLOSED: Quantifying image distortion in MRI for Radiotherapy treatment planning

NOW CLOSED :4-year PhD studentship funded by The National Physics Laboratory (NPL) and the i4health CDT - Deadline 11th May 2023

Quantifying image distortion in MRI for Radiotherapy treatment planning

18 April 2023

UCL supervisors: Simon Walker-Samuel (CABI), Chris Clark (ICH)

NPL supervisors: Matt Cashmore, Matt Hall (Medical Physics/MRI)

MRI is a key medical imaging modality. It provides high quality 3D images with unique soft tissue contrast which are useful across a huge range of clinical applications including imaging tumours and for surgical planning. One key application is in radiotherapy, where MRI is increasingly used to plan the delivery of radiation to the site of a tumour while minimising the dose to neighbouring, healthy tissue. Compared to more traditional approaches using CT, MRI provides improved tissue contrast and quantitative imaging biomarker definition (making the tumour easier to delineate) for targeting and treatment monitoring,  and also removes the need to expose the patient to Ionising radiation during imaging.

One very important consideration, however, is spatial distortion in the MR images. The presence of a patient in the scanner distorts the applied magnetic field and means that images contain small errors in the size, shape, and position of tissue features. This means that the errors and uncertainties in radiation delivery cannot be fully quantified, meaning that very conservative estimates must be used instead of the careful approaches applied elsewhere in the treatment planning pipeline.

This PhD aims to develop a detailed understanding of MR image distortion to fully quantify its effects and incorporate them into the treatment planning pipeline. The project is partly based on carefully building and imaging test objects (also known as phantoms) which distort the field in a controlled way, building from simple, easily understood objects to more complex objects which are more representative of the geometry and biomarker characteristics of organs such as the brain, and partly on modelling the physics behind image distortion. The aim is to quantitatively characterise the distortion field and to incorporate this into Radiotherapy audits. There is scope to include physics-based modelling, statistics, and other advanced approaches such as AI to inform treatment planning and monitoring with the most complete and accurate description of image distortion possible.

The supervision team comprises experts in MRI, modelling, and measurement science. It is in partnership with a leading MRI phantom manufacturer who bring knowledge of advanced materials and manufacturing capabilities. We also work closely with teams who provide radiotherapy audits nationally across the UK. The successful applicant would gain experience across practical imaging, advanced modelling, image analysis, and measurement science and would have the opportunity to emphasise their own strengths and interests in completing the work.

The project will cover:

  • Development of susceptibility-matched materials, including evaluation of manufacturability and associated uncertainties in manufacturing
  • Design and characterisation of 3D printed distortion phantoms of a range of complexities Including mimics of key physical properties
  • MRI scanning of test objects and volunteers
  • Simulation of phantoms and applied field and pulse sequences
  • Assessing the performance of image distortion correction algorithms, quantifying errors in reconstruction
  • Quantification of image-based uncertainties due to field distortion effects and processing  

This is a fully funded, four-year studentship based jointly at UCL and NPL. Funding will be at least the UCL minimum. Stipend details can be found here.

The funding covers home student fees and a stipend, but not international student fees.UCL’s fee eligibility criteria can a be found by following this link.

The project also includes working with an industrial collaborator, CaliberMRI, quantitative MRI commercialization partner with NIST and a phantom manufacturer/quality assurance platform developer based in Boulder CO. The project includes scope to spend time with CaliberMRI learning more about their methods and technologies. For any questions, or to have an informal chat please contact Simon Walker-Samuel (simon.walkersamuel@ucl.ac.uk) at UCL or Matt Cashmore (matt.cashmore@npl.co.uk) at NPL.

Application Deadline: 11th May 2023

How to apply:

  • Please send an expression of interest and current CV to: simon.walkersamuel@ucl.ac.uk and cdtadmin@ucl.ac.uk .Please quote Project Code:  23006 in the email subject line.
  • Make a formal application to via the UCL application portal  . Please select the programme code Medical Imaging TMRMEISING01 and enter Project Code 23006 under ‘Name of Award 1’

Application Process:

  • After the deadline, all applicants that specified Project 23006 and with a Portico application will be considered for interview.
  • Candidates will normally be invited for interview within two-weeks of the deadline
  • The interview panel will normally consist of the supervision team on the project and the CDT Director.
  • The interview will normally consist of a short presentation (5-10mins) by the candidate followed by questions from a panel.
  • The successful candidate will be informed by email and given a week to confirm whether they wish to accept the PhD place and funding.
  • Note that applications without specifying the project they are applying for and/or making a formal Portico application will be automatically rejected.
  • Once accepted, a formal UCL offer of admission will be sent to the applicant as well as an offer of studentship funding.