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Precision Medicine DTP - Determining clinically significant early stage lung cancers from image analysis

  • Full or part time
  • Application Deadline
    Wednesday, January 08, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Additional Supervisors: Dr Iain Philipps, Dr Duncan Mclaren & Dr Stephen Harrow


Stereotactic Ablative Body Radiotherapy (SABR) is an image guided radiotherapy technique, used to deliver a curative treatment for early stage lung cancer. It delivers a higher dose of radiotherapy in fewer treatments, with greater local control and fewer side effects compared to standard radiotherapy [1].

SABR is an effective treatment, but has local relapse rates of approximately 10% and distant relapse rates of 20%. Identifying the cohort of those at higher risk of local relapse and distant relapse on pre-treatment imaging may have three possible benefits, 1) it would identify a cohort who could benefit from additional treatment or closer follow up, 2) those at low risk of relapse who could have de-escalated follow up imaging, 3) patients who are borderline surgical candidates with a low risk tumour could avoid risks of surgery, conversely those with a high risk tumour could opt for surgery, knowing they would get the benefits of pathological examination of the tumour and nearby lymph nodes. This improved quantification of risk would significantly benefit SABR patients who are often older and less fit.


The aim of the project is to identify whether it is possible to predict tumours that will locally and distantly relapse using existing data. Approximately 200 patients have been treated with SABR in Edinburgh and a recent audit with clinical outcome data has been completed of the first 150 patients. This data would be available initially for the study and by collaborating with SABR clinicians in Glasgow and Guildford additional data would also be available.

Our group has experience of developing image analysis algorithms and software in this area [2]. We have previously demonstrated the potential of image analysis in lung cancer in a pilot study where pre-treatment radiotherapy planning CT-images of patients with lung cancer were analysed to identify those at risk of developing pneumonitis after radiotherapy [3]. Despite the fact that all patient CT-images appear similar, and that no radiation had been given at the time of CT image acquisition, the accuracy of the image analysis approach for predicting pneumonitis was 87%.

We now wish to build on these encouraging results and the process developed for image analysis, to undertake an exploratory study for a different clinical question. To determine whether it is possible to identify clinically significant early stage lung cancers using image analysis.

Training Outcomes

The student will be involved in developing a clinical decision support tool that will help process PET-CT, diagnostic CT and cone beam CT images in order to identify a high risk cohort of patients. They will then use imaging to identify those at most risk of local and distant relapse. The use of medical imaging to detect early stage lung cancers is likely to increase. The Nelson trial has shown an increased survival rate when using low dose CT compared to chest x-rays for lung cancer screening. The trial showed an increase in the proportion of patients presenting with early stage lung cancers from approximately 15% to nearly 70%. Screening for early stage lung cancers is likely to be implemented in Scotland. This work would then be applicable to these patients in Scotland.

This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.

All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.


Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.

For more information about Precision Medicine visit:

Funding Notes

Start: September 2020

Qualifications criteria: Applicants applying for a MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualification, in an appropriate science/technology area.
Residence criteria: The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £15,009 (RCUK rate 2019/20) for UK and EU nationals that meet all required eligibility criteria.

Full eligibility details are available: View Website

Enquiries regarding programme:


1. Phillips I, Sandhu S, et al. Stereotactic Ablative Body Radiotherapy Versus Radical Radiotherapy: Comparing Real-World Outcomes in Stage I Lung Cancer. Clin Oncol;2019.

2. Phillips I, Ajaz M, et al. Clinical applications of textural analysis in non-small cell lung cancer. Br J Radiol. 2018 Jan;91(1081).

3. Montgomery, D. Campbell S, et al. Predicting the occurence of radiation induced Pneumonitis by texture analysis of CT images from lung cancer patients, in Medical Image Computing and Computer Assisted Intervention (MICCAI). 2013: Nagoya, Japan.

4. Nailon WH, Lu W, et al. Predicting radiation-induced pneumonitis in NSCLC: a radiobiological and texture analysis study. Rad Oncol 2017;123(S1);S933.

How good is research at University of Edinburgh in General Engineering?
(joint submission with Heriot-Watt University)

FTE Category A staff submitted: 91.80

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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