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PhD Studentship in Epilepsy imaging and surgical planning


Project Description

The Centre for Medical Image Computing (CMIC), in collaboration with the Department of Clinical and Experimental Epilepsy at the UCL Institute of Neurology, is inviting applications for a studentship in epilepsy imaging and surgical planning.

About 30-40% of people with epilepsy continue to have seizures despite anti-epileptic drug therapy. In those individuals where a single brain region is responsible for the seizure and drug therapy does not help, surgery can be a successful and cost-effective treatment and improve quality of life. The most commonly performed surgery in epilepsy, anterior temporal lobe resection, has a significant risk of language deficits if the surgery is in side of the brain responsible for language and speech. We expect that the language difficulties arise from damage to the fibre bundles connecting the language areas. These fibres, or neural highways, lie deeper in the brain and might be unknowingly damaged during the surgery. We aim to ameliorate the possible decrease in language capabilities as a result of epilepsy surgery. This will improve the patient’s quality of life after surgery. We also hope it will help people that were afraid of language decline to choose surgery as an alternative treatment.

Research aims

The first aim is to determine whether damage to any of the language-related fibre bundles within the brain in surgery is associated with a decline in language function. This will be done using MRI scans and language test data we have collected over the last ten years. Analysing the MRI data from before their surgeries, you will be using diffusion MRI and fibre tractography to create a map of the fibre connections. Combining this with an MRI scan after people’s surgery, it is possible to determine if the surgery damaged any of these connections. From the cognitive tests routinely done on these patients both before and after surgery, we know who has had their language skills decline. Combining this all will inform us which fibre connections are essential in language use, to tell us which we need to actively spare when planning and doing the surgeries.

The second aim of the project is to use this in the planning of upcoming surgeries. We plan to find these essential connections before a patient’s surgery to inform the surgeons where they are. During the operation, we can show the location of these connections to the surgeons on a screen. This will help them plan and perform the operation to avoid these fibre bundles.

You will have the opportunity to engage in professional development and training beyond the laboratory: by attending conferences; publishing in academic journals; assisting with teaching; and attending courses through the UCL Doctoral Skills Development Programme.

About the Departments

The Centre for Medical Image Computing (CMIC) is a research centre bridging the Department of Computer Science and Department of Medical Physics & Biomedical Engineering, with the studentship hosted by Computer Science. Both departments are one of the largest of its kind in the UK. Internationally leading research in the department includes medical imaging, physiological monitoring, radiotherapy and biomedical engineering. The department has close links to several major teaching hospitals. This provides a highly stimulating multidisciplinary environment for learning and for scientific research. Both Departments hold a Athena Swan Bronze Awards which recognise and celebrate good practice and commitment to advancing diversity in science, technology, engineering, mathematics and medicine (STEMM) in higher education and research. The awards reflect our commitment to the advancement and promotion of diversity and equality.

Studentship Description

A three-year PhD studentship is available in the UCL Centre for Medical Image Computing in collaboration with the Department of Clinical and Experimental Epilepsy at UCL’s Institute of Neurology. The funding, from Epilepsy Research UK, covers an annual tax-free stipend (24,854) and tuition fees for UK or EU applicants only.

Person Specification

Successful applicants will have achieved or be predicted a first class or upper second class UK Bachelors degree or Masters degree, preferably in biomedical engineering, neuroscience, medicine, life sciences or equivalent degrees. Good working knowledge of Matlab and/or Python and experience with medical image analysis is desirable.

Equivalent non-UK qualifications and knowledge and expertise gained in the workplace may also be considered, where appropriate. Please explain how you meet this requirement in your application.

Eligibility

One studentship is available which will cover the cost of tuition fees for UK/EU students and a stipend of at least £24,854 per annum tax free for 3 years. EU students who have not been resident in the UK may apply. Outstanding students not meeting these conditions (including students from outside the EU) may apply if they have funding to support international fees.

For more information about this opportunity please contact the supervisors:
Primary supervisor: Dr Sjoerd B. Vos
Secondary supervisors: Prof John S. Duncan, Prof Daniel Alexander, Dr Peter Taylor (Newcastle University).
If you have any scientific queries, please contact Dr Sjoerd Vos ()

Applications (including a covering letter, CV and names of two referees) should be sent to Dr Sjoerd Vos () who will also be happy to handle any informal enquiries.

Funding Notes

One studentship is available which will cover the cost of tuition fees for UK/EU students and a stipend of at least £24,854 per annum tax free for 3 years. EU students who have not been resident in the UK may apply. Outstanding students not meeting these conditions (including students from outside the EU) may apply if they have funding to support international fees.

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