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Click here to search FindAPhD.com for PhD studentship opportunities(MRC DTP) Understanding and Mitigating Against Organ Damage from Radiotherapy using Statistical Learning from Large Cohort Data
Prof M Van Herk, Dr T House, Dr Alan McWilliam
No more applications being accepted
Competition Funded PhD Project (European/UK Students Only)
About the Project
Radiotherapy plays a major role in the treatment of lung cancer. However, the radiotherapy dose needed to eradicate the cancer cells can also damage the surrounding organs, such as the heart and lungs. Over the last 2 years, a better understanding of the association between dose delivered to these organs and excess mortality in lung cancer patients treated with radiotherapy has emerged. The precise mechanism of damage and which areas of the organs at risk are more sensitive to radiation is not currently known and the evidence does not yet allow setting dose thresholds to effectively limit these effects without affecting control of the tumour.
Central to continued improvement of our understanding of organ damage from radiation, and hence design of improved radiotherapy protocols, will be improved methods for statistical learning of risks from the large, complex datasets that are available from the world-leading clinical centre at the Christie Hospital. Such statistical learning takes the well-established biostatistical approach of survival analysis as its foundation, since survival is the primary outcome of interest. The standard approach to survival analysis of assuming that different factors arise as proportional hazards is not, however, appropriate when the factors relate to a detailed quantification of complex radiotherapy dosing. We have had success in applying regularisation techniques to dose-volume histogram data for these models in a Bayesian context by using informative structured priors.
This PhD project will develop appropriate regularisation and inference schemes for working with more detailed dosing information, apply these to the large cohort of lung cancer patients from the Christie, and consider the implications of these results for treatment strategies that reduce the possibility of organ damage.
Division of Cancer Sciences:
https://www.research.manchester.ac.uk/portal/en/facultiesandschools/division-of-molecular--clinical-cancer-sciences(0b0cf147-3dc8-4f46-a374-27dd6cca92f3).html
Manchester Cancer Research Centre:
http://www.mcrc.manchester.ac.uk/
Personal Pages:
https://www.research.manchester.ac.uk/portal/marcel.vanherk.html
https://personalpages.manchester.ac.uk/staff/thomas.house/about.html
https://www.research.manchester.ac.uk/portal/alan.mcwilliam.html
Group Twitter:
https://twitter.com/RT_physics
Entry requirements:
Applications are invited from UK/EU nationals only. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.
Central to continued improvement of our understanding of organ damage from radiation, and hence design of improved radiotherapy protocols, will be improved methods for statistical learning of risks from the large, complex datasets that are available from the world-leading clinical centre at the Christie Hospital. Such statistical learning takes the well-established biostatistical approach of survival analysis as its foundation, since survival is the primary outcome of interest. The standard approach to survival analysis of assuming that different factors arise as proportional hazards is not, however, appropriate when the factors relate to a detailed quantification of complex radiotherapy dosing. We have had success in applying regularisation techniques to dose-volume histogram data for these models in a Bayesian context by using informative structured priors.
This PhD project will develop appropriate regularisation and inference schemes for working with more detailed dosing information, apply these to the large cohort of lung cancer patients from the Christie, and consider the implications of these results for treatment strategies that reduce the possibility of organ damage.
Division of Cancer Sciences:
https://www.research.manchester.ac.uk/portal/en/facultiesandschools/division-of-molecular--clinical-cancer-sciences(0b0cf147-3dc8-4f46-a374-27dd6cca92f3).html
Manchester Cancer Research Centre:
http://www.mcrc.manchester.ac.uk/
Personal Pages:
https://www.research.manchester.ac.uk/portal/marcel.vanherk.html
https://personalpages.manchester.ac.uk/staff/thomas.house/about.html
https://www.research.manchester.ac.uk/portal/alan.mcwilliam.html
Group Twitter:
https://twitter.com/RT_physics
Entry requirements:
Applications are invited from UK/EU nationals only. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.
Funding Notes
This project is to be funded under the MRC Doctoral Training Partnership. If you are interested in this project, please make direct contact with the Principal Supervisor to arrange to discuss the project further as soon as possible. You MUST also submit an online application form - full details on how to apply can be found on the MRC DTP website http://www.manchester.ac.uk/mrcdtpstudentships
As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
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