The project will be based at the School of Engineering (ENGIN) and Velindre Hospital.
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 at ENGIN, and will become skilled in the following areas: (1) Establishing optimal MRI sequences for radiomic feature extraction, (2) Image segmentation and rendering, (3) Radiomic feature extraction and qualification, (4) Developing databases, (5) Informatics and statistical analyses.
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:
• Physics/Medical Physics
• Medical/Clinical Engineering
• Computer Science with application to image processing
Applicants whose first language is not English will be required to demonstrate proficiency in the English language (minimum IELTS 6.5 or equivalent).
Informal enquiries are welcome and should be addressed to Dr.Emiliano Spezi ([email protected]
). Further details about ENGIN and Velindre can be found at the following links: http://research.engineering.cf.ac.uk
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.
Applicants should submit an application for postgraduate study via the Cardiff University webpages (http://www.cardiff.ac.uk/study/postgraduate/research/programmes/programme/engineering ) including;
• 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
• Current academic transcripts
Applicants should select Doctor of Philosophy (Engineering), with a start date of January, April or July 2018.
In the research proposal section of your application, please specify the project title and supervisor of this project and copy the project description in the text box provided. In the funding section, please select "I will be applying for a scholarship / grant" and specify that you are applying for advertised funding, reference ES-PSE2018-1