EPiQ Ependymoma
Research type
Research Study
Full title
Early imaging Predictors of Quality of Life in Children and Young People - A pilot study in Paediatric Ependymoma
IRAS ID
366589
Contact name
Shivaram Avula
Contact email
Sponsor organisation
Alder Hey Children's NHS Foundation Trust
Duration of Study in the UK
2 years, 11 months, 9 days
Research summary
Survivors of brain tumours are at risk of experiencing late effects related to neurocognition, which encompasses brain processes such as thinking, attention, language, learning, and memory. They can also experience abnormal brain functioning, including issues with movement, hearing, and vision. This can often lead to academic challenges and psychological problems, and can impact employment opportunities later in life. Early identification of patients at risk of late effects will be extremely helpful in their management. Imaging findings on early Magnetic Resonance imaging (MRI) scans, both before and after the initial surgery, could provide clues that help identify individuals at risk of developing late effects. This requires evaluating patients from a wide geographic area from multiple treatment centres, uniformly performing scans, and using a standardised method of psychological assessment. In this study, we will evaluate a group of children and young adults in the UK who have been recruited for a European trial assessing the treatment of ependymoma, a form of brain tumour. These patients have had MRI scans and psychological assessments performed in a standardised manner.
We will analyse the MRI scans of the UK patient group participating in a European Ependymoma trial performed early during their treatment. A combination of experienced neuroradiologists and image analysis scientists will conduct the analysis. Qualitative analysis involves evaluating MRI scans for features that are readily identifiable by the naked eye and can be readily translated into clinical practice. Quantitative analysis will utilise advanced computer techniques to capture subtle changes on the scans that are not readily visible to the naked eye. We will employ advanced machine learning methods to identify MRI clues from the quantitative and qualitative analysis that indicate the risk of developing neurocognitive and neurological late effects. The results from this study will be tested in larger groups of patients with different tumour types before being introduced into clinical practice.REC name
South Central - Oxford B Research Ethics Committee
REC reference
26/SC/0086
Date of REC Opinion
10 Mar 2026
REC opinion
Favourable Opinion