- Room N/1.51, Queen's Buildings - South Building, 5 The Parade, Newport Road, Cardiff, CF24 3AA
I am a research associate within the School of Engineering, where I am a member of the Cancer Research and Data Analytics group. My current work focusses on the automatic delineation of tumours using Positron Emission Tomography (PET). I am involved with the PEARL clinical trial which will adapt the radiotherapy treatment plan mid-way through patient treatment, based on the tumour segmentation of an interim PET scan, with the airm of reducing patient toxicity.
I have a strong background and interest in medical image processing, where I have experience with imaging related to radiotherapy treatments including CT, MRI and PET.
PhD Automated MRI-only radiotherapy planning for brain tumours, University of Leeds, 2019
MSc Physics and Computing in Medicine and Biology, University of Manchester, 2011
MPhys Physics, University of Manchester, 2010
Research associate, School of Engineering, Cardiff University, 2018 - present
Clinical Scientist (radiotherapy physics), Lancashire Teaching Hospitals NHS Trust, 2014 - 2015
Trainee Clinical Scientist (Part II, specialising in radiotherapy physics), The Christie NHS Foundation Trust, 2012 - 2014
Trainee Clinical Scientist (Part I), The Christie NHS Foundation Trust, 2010 - 2012
Honours and awards
- Travel Grant, Institute of Physics and Engineering in Medicine (2016)
- Conference award, Leeds for Life Foundation (2016)
Registered with the Health and Care Professions Council
Member of the Institute of Physics and Engineering in Medicine
- UK Radiation Oncology (UKRO) Conference, Nottingham (2013)
PEARL Clinical Trial
Oropharyngeal cancers caused by the Human Papillomavirus are known to have a better outcome than other head and neck cancers. As a result, many patients are cured of their disease, however they have to live with the side effects of their treatment for decades afterwards.
The positron emission tomography (PET)-based adaptive radiotherapy clinical trial (PEARL) will investigate the feasibility of adapting the volume receiving the highest dose midway through treatment, to reduce the toxicity to normal tissues, whilst maintaining the same progression free survival rate.
The use of an automatic segmentation algorithm in this trial will allow the delineation of the biological tumour volume to be standardised, meaning that inter-observer variation will not affect the segmentation.
The biological gross tumour volume (bGTV) will be segmented using an automatic decision tree-based learning algorithm for advanced image segmentation (ATLAAS). ATLAAS predicts which PET-based segmentation method will perform the best, out of seven different segmentation algorithms, based on characteristics of the tumour volume.
50 patients will be recruited to the trial. ATLAAS segmentation of the bGTV will be performed for each patient on a PET scan acquired prior to treatment. This will be used, along with other clinical information, to create the gross tumour volume (GTV). Margins will be added to this to encompass the microscopic tumour, producing the clinical tumour volumes (CTV1 (GTV+5mm) and CTV2 (GTV+10mm)).
At 2 weeks, an interim PET (iPET) scan will be acquired. If a response is seen, an ATLAAS segmentation using this scan, along with clinical information, will create bGTV_iP. A margin will be added to this to produce the bCTV1. This will receive a total dose of 66 Gy (equal to the dose received by CTV1 under a standard protocol). The non-avid region within the CTV1 volume will receive a dose of 60 Gy and CTV2 a dose of 54 Gy (CTV2 would receive 60 Gy under a standard protocol).
Progression free survival at 2 years and the metabolic response rate at 3 months will be measured to ensure that these are comparable to those of the standard treatment. To assess toxicity, the percentage reduction in dose to organs at risk will be recorded. Additionally, swallowing measurements, a quality of life questionnaire and acute and late toxicity assessments will be completed for each patient.
Clinical trials: PEARL 2018 - present
Collaborations: Velindre Cancer Centre, Cardiff 2018 - present
No results were found