Improving treatment of glioblastoma, 1.0
Research type
Research Study
Full title
Improving treatment of glioblastoma: distinguishing progression from pseudoprogression
IRAS ID
235541
Contact name
T C Booth
Contact email
Sponsor organisation
King's College London
Clinicaltrials.gov Identifier
n/a, n/a
Duration of Study in the UK
4 years, 4 months, 20 days
Research summary
Glioblastoma is the most aggressive kind of brain cancer and leads on average to 20 years of life lost, more than any other cancer. Images of the brain are taken before the operation, and every few months after treatment, to see if the cancer regrows. It can be hard for doctors to tell if what they see in these images represent growing cancer or a side-effect of treatment. The similarity of the appearance of the treatment side-effects to cancer is confusing and is known as "pseudoprogression" (as opposed to true cancer progression).
If doctors mistake the appearance of treatment side-effects for growing cancer, they may think that the treatment is failing and change the patient’s treatment too early or put them into a clinical trial. This means that patients may not be given the full treatment and the results from some clinical trials cannot be trusted.
The aim of this study is to provide doctors with a computer program that will use images of the brain that are routinely obtained throughout treatment, in order to help them more accurately identify when the cancer regrows.
The first phase of the project will be spent training a machine learning program using old patient data from King's College Hospital's Neuroradiology Department, as well as old patient data from publicly-accessible imaging archives. The training phase of the study should be completed within the first 18 months of the project.
The machine learning program will then be tested using patient data that it has not seen before and will be compared to the current standard criteria. We ask patients who are referred to King's College Hospital for treatment to allow access to their relevant medical data. There will be no additional demand on the patient’s time nor any participant burden.REC name
London - Brighton & Sussex Research Ethics Committee
REC reference
18/LO/1873
Date of REC Opinion
30 Oct 2018
REC opinion
Favourable Opinion