<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/7E52ABA1-0DF3-42BD-BE0D-8BEBAF61DF03" ns1:id="7E52ABA1-0DF3-42BD-BE0D-8BEBAF61DF03"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/1DAE2736-B7AD-407A-8B17-EC8CD5BBE60A" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/8A5B788D-7684-4F6A-B2BE-E35BEF30BCFA" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/8A5B788D-7684-4F6A-B2BE-E35BEF30BCFA" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/4AA237F3-C61B-404D-AEFA-2521769F0B9A" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2019-07-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/7D7247AB-25BE-4B59-B743-F92FE99FFACA" ns1:rel="FUND" ns1:start="2017-09-30T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">103353</ns2:identifier></ns2:identifiers><ns2:title>Improving Brain Tumor Patient Outcomes through Patient Stratification &amp;amp; Novel Biomarkers</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Glial tumours are the most common primary brain tumour, and since the majority of these are high-grade (malignant) tumours, overall patient survival is poor. A newly diagnosed glioma may be a slow-growing low-grade™ or a more heterogeneous, highly infiltrative high-grade™. Accurate diagnosis of the tumour grade, and delineation of the tumour core and infiltration into normal brain is crucial for optimum treatment. Within this project, we will deliver a fully integrated software application for analysing MRI scans to create a 3D map of the glioma core and its infiltration pattern. The software can be cloud-based to analyse patient MRI scans directly from the scanner and send tumour tissue maps to workstations in neurosurgical and radiotherapy units. Improved patient outcome is possible by use of this information at three points in patient management: i) targeting the best tumour region to obtain tissue for histological (biopsy) diagnosis; ii) enabling optimal surgical removal of the tumour core; iii) improving the planning of radiotherapy that targets the highest dose to the most malignant part of the tumour while keeping the dose to functional brain low.</ns2:abstractText></ns2:project>