Luminal Index MRI Identification of Treatment critical Prostate Cancer (LIMIT PCa)
Co-Lead: Prof Shonit Punwani, University College London (UCL)
Co-Lead: Dr Fiona Walter, University of Cambridge
University College London (UCL): Prof. Daniel Alexander, Ms Chris Brew-Graves, Prof. Mark Emberton, Prof. Sue Mallett, Prof. Caroline Moore, Prof. Nora Pashayan, Dr Christian von Wagner
University of Cambridge: Dr Tristan Barrett, Mr Christof Kastner, Prof. Steve Morris, Prof. Evis Sala
University of Manchester: Prof. Robert Bristow, Prof. Noel Clarke, Prof. James O’Connor
iCAD: Dr Jonathan Go
Oregon Health and Science University (OHSU): Assistant Prof. Ryan Kopp
Project Summary
We know that MRI is good for detection of prostate cancer but at present this can only be provided in a hospital setting. Whilst this is being used there are still many men (about 16%) that are being diagnosed with late stage disease and almost 12,000 men dying per year from prostate cancer in the UK. Clearly, these men are not being scanned early enough in the timecourse of their disease for treatment to make a difference. If we can detect their cancer earlier we think we might be able to reduce deaths from prostate cancer.
We have developed a new MRI technique that can allow prostate cancer to be detected using a 5-minute scan. As this scan is simple, cheap and has good performance, it can be delivered within the community setting even using a MRI scanner located in a travelling van. We think that providing scans in the community setting could allow men, who would otherwise not be scanned, the opportunity to have their cancer detected earlier.
Within this project we are bringing together leading doctors and scientists from hospital and GP settings to work out the best pathway to deliver a community-based MRI scan. This is a first step which will tell us whether a large national trial of our detection strategy using our new MRI technique is feasible. We expect it will be feasible, and the results of this study will allow us to plan the national trial.
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