Leeds Institute of Cancer and Pathology PhD Studentship 2015 intake
Please contact the Lead Supervisor with informal enquiries
Title of Project
AMIRA: Automated MRI based RAdiotherapy planning for brain and pelvic tumours
Lead Supervisor
Current post(s)
Section
Associate Professor in
Clinical Oncology Associate Professor Ann
University of Leeds and
Henry
LICAP
Clinical Lead for
a.henry@leeds.ac.uk
Radiotherapy - Leeds
Teaching Hospitals
Co-Supervisor(s)
Current post(s)
Section
Department of Medical
Dr Richard Speight
Clinical Scientist
Physics and Engineering Leeds Teaching Hospitals
Professor in Clinical
Professor Susan Short
LICAP
Oncology
Professor David SebagProfessor in Clinical
LICAP
Montefiore
Oncology
Subject Area
MRI within radiotherapy treatment planning
Project Summary (up to 300 words)
Almost half of cancer patients undergo radiotherapy as part of their treatment.
Currently radiotherapy treatment planning involves using a CT scan to individually
design treatment to maximise radiation to the tumour and minimise radiation to
healthy tissue. Some tumours are difficult to visualise on CT and MRI allows more
accurate tumour visualisation, particularly for brain and pelvic tumours. The
proposed project aims to replace CT with MRI for radiotherapy planning for the
first time in the UK.
There are a number of technical barriers that must be overcome to accurately use
‘MRI only’ radiotherapy planning; this project aims to address these issues for
brain/prostate/ano-rectal cancers. In addition to increasing accuracy of
radiotherapy we hypothesise MRI can have further benefits in terms of efficiency,
including automation of tumour definition and treatment plan optimisation.
This project will work within current research collaborations with partner NHS sites
(Northern Cancer Centre, Newcastle), commercial partners (Mirada Medical and
Elekta) and world leaders in the use of MRI in radiotherapy (University Hospital of
Umeå Sweden, Royal Brisbane and Women's Hospital Australia and Calvary
Mater Hospital Australia). There may be opportunity to perform some work in the
groups mentioned above as part of the project.
The overall aim of this PhD would be a proof of principle that: 1) MRI can be used
as a basis of radiotherapy treatment plan design; 2) structures can be
automatically defined on MRI; and 3) MRI-only radiotherapy plan production can
be successfully automated. If successful it would be the first time any of these 3
objectives have been achieved in the clinic to benefit patients and we hope the
results of this PhD will be the basis of the pilot data required to run a large multicentre evaluation to prove patient benefits of MRI in radiotherapy.
Techniques associated with project
The techniques/work to be done are broken down below into the 3 main project
areas below:
1: Proving that tumour and healthy tissue can be automatically defined on
MRI
- Optimisation of MRI acquisition for brain, prostate and ano-rectal cancer
patients.
- Generate a collection of MRI images of patients previously treated for each of
the three cancer sites, with tumours and healthy tissues defined by clinicians, to
be used to automatically define structures on subsequent cases. Up to 50 cases
per cancer site may be needed.
- Commercial software is available to automate structure definition for CT,
deformable image registration algorithms will need optimising for the software to
be appropriate for MRI. This will be done with supervision from Dr Mark Gooding
from a commercial partner (Mirada Medical).
- For a cohort of subsequent cases (20 for each site), test if the software can
automatically define tumours and healthy tissue better than or as well as
clinicians.
2: Proving that radiotherapy treatment plans can be produced on MRI rather
than the traditional CT
- Develop the process where an MRI scan is converted into a pseudo-CT, the
format required for radiotherapy treatment planning computer systems. There are
a number of techniques for creating pseudo-CT that are used by collaborators in
the literature [1-2]. These techniques involve novel MRI sequences that can
directly image bone or image registration techniques. The techniques need
assessing and optimising for clinical use in multiple NHS institutions.
- Convert MRI for the 20 patients for each treatment site in section 1 into pseudoCT format and demonstrate that planning the radiotherapy treatment on the
pseudo-CT is an improvement to planning on the CT alone.
3: Proving Demonstrate automation of planning and feasibility in multiple
centres
- Develop a process for automation of MRI-only radiotherapy plan production. This
will involve developing software to optimise plans automatically or working with a
commercial partner (Elekta) who has research software (iCycle [3]) that automates
plan production for CT based plans.
- Demonstrate that we can automate the treatment planning process in the MRI
only workflow for the 20 patients from each treatment site. Show that plans are
better or as good as manually produced plans for patients.
- Demonstrate that we can use the same process in different hospitals/software
systems (preliminary discussions with Hull and Newcastle are already underway).
References (up to 3)
1. Nyholm T, Jonsson J, Counterpoint: Opportunities and Challenges of a
Magnetic Resonance Imaging – Only Radiotherapy Work Flow, Semin
Radiat Oncol 24:175-180 (2014).
2. Dowling JA, Lambert J, Parker J, et al. An Atlas-Based Electron Density
Mapping Method for Magnetic Resonance Imaging (MRI) - Alone Treatment
Planning and Adaptive MRI-Based Prostate RadiationTherapy, Int J
Radiation Oncol Biol Phys, 83(1):e5-e11 (2012).
3. Breedveld S, Storchi P, Voet P, et al. iCycle: Integrated, multicriterial beam
angle, and profile optimization for generation of coplanar and noncoplanar
IMRT plans, Med Phys, 39:951-963 (2012).