PhD in Engineering: Developing Radiomics as an Imaging Biomarker in High Grade Glioma
|Application deadline||31 March 2018|
|Start date||January/April/July 2018|
|Level of study||Postgraduate research|
|Award type||PhD studentship|
|Number of studentships||1|
The commonest primary brain tumour in adults is grade IV glioma, Glioblastoma multiforme (GBM).
These are aggressive tumours and current treatment options are limited with a poor overall prognosis. Assessing response to radiotherapy and chemotherapy treatment remains challenging using standard imaging techniques with uncertainty often present in differentiating true tumour progression from treatment-induced changes. Diagnostic, prognostic and predictive information from standard brain imaging remains limited and a surgical biopsy is required to allow molecular genetic testing to provide these important biomarkers. However, biopsy or surgical resection is often limited or unfeasible due to tumour location and the associated risk of morbidity from damage to surrounding normal brain tissue.
Radiomics refers to the extraction and analysis of quantitative imaging features with high throughput from medical images and offers an exciting and original approach to these challenges in high-grade gliomas. In this study, we will apply radiomics to Magnetic Resonance Imaging (MRI) scans of patients with high-grade gliomas using latest techniques and correlate imaging signatures with known prognostic or predictive biomarkers to measure correlations. Our hypothesis is that radiomic models will provide diagnostic, prognostic or predictive biomarkers for these tumours. This research is clinically focused with the aim of validating radiomic models with the potential for being applied to address some of the key clinical questions outlined.
This study will be highly relevant providing clinically significant biomarkers on primary high-grade gliomas. We have established a multidisciplinary team of researchers, physicists and oncologists to collaborate on this project. The successful candidate will develop the radiomic pipeline, building on existing research in the School of Engineering, and will become skilled in the following areas:
- Establishing optimal MRI sequences for radiomic feature extraction.
- Image segmentation and rendering.
- Radiomic feature extraction and qualification.
- Developing databases.
- Informatics and statistical analyses.
Reader - Teaching and Research
Director of Radiotherapy Trials and Clinical Reader in Oncology
This project with also be supervised by Dr James Powell from Velindre Cancer Centre.
|Tuition fee support||Full UK/EU tuition fees|
|Maintenance stipend||Doctoral stipend matching UK Research Council National Minimum|
|Residency||UK Research Council eligibility conditions apply|
This project is best suited for students with strong interests in Medical Physics and Clinical Engineering, Medical Image Processing, Data Analysis and Software Development. Applicants for a studentship must hold, at least, a 2.1 degree or Master’s degree in in a relevant subject such as:
Applicants whose first language is not English will be required to demonstrate proficiency in the English language (minimum IELTS 6.5 or equivalent).
This studentship is open to Home, EU and Overseas candidates consisting of full UK/EU tuition fees, as well as a Doctoral Stipend (£14,553 p.a. for 2017/18, updated each year) for eligible candidates. Please note that overseas candidates will be required to pay the difference between the home and overseas fee.
Consideration is automatic on applying for a Doctor of Philosophy in Engineering with a start date of January 2018.
In the "Research proposal and Funding" section of your application, please specify the project title and supervisors of this project and copy the project description in the text box provided.
Please select “No, I am not self-funding my research” when asked whether you are self-funding your research.
Please add “PhD in Engineering: Developing Radiomics as an Imaging Biomarker in High Grade Glioma" when asked "Please provide the name of the funding you are applying for".
You application should include:
- an upload of your CV
- a personal statement/covering letter
- two references (applicants are recommended to have a third academic referee, if the two academic referees are within the same department/school)
- current academic transcripts.
We reserve the right to close applications early should sufficient applications be received.