UCL Institute of Neurology
London, WC1N 3BG, United Kingdom
NCT Number: NCT02884947
This aim of this study is to improve the outcomes for patient with gliomas undergoing neurosurgery by maximising the extent of resection whilst minimising neurological morbidity. This will be achieved through the use of advanced MRI, fMRI and DTI, performed at two stages of the patients' clinical management.
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Notify Me18 year and older
All sexes
Observational
London, WC1N 3BG, United Kingdom
Low grade gliomas are often located near to and infiltrate into important parts of brain which are involved with language and motor function. During surgery to remove these tumours, there is a fine balance between trying to remove as much of the tumour as possible and limiting any damage to these functionally important parts of the brain which, particularly in a young patient, may result in impairment for the rest of their life.
Functional MRI (fMRI) can be used to identify these functionally important cortical areas and diffusion tensor imaging (DTI) can be used to identify the important subcortical and deep white matter tracts connecting these regions. The use of these advanced imaging techniques performed pre-operatively to plan surgery is now commonplace however their role in guiding the actual operation itself is limited because of the occurrence of 'brain shift', this being deformation in the contour of the brain parenchyma which occurs as the tumour is resected. This can result in inaccuracies if the pre-operative advanced MRI data is being used in the neuronavigational system to guide surgery.
The main aim of this study is to determine the optimal method of providing updated, spatially accurate data on the location of these functionally important areas of the brain to the neurosurgeon intra-operatively. In this study, two different techniques will be compared. The first is the acquisition of real-time fMRI and DTI acquired intra-operatively during tumour resection. The second is to use intra-operatively acquired structural and diffusion sequences to perform non-rigid co-registration of fMRI and DTI data which has been acquired before surgery. The feasibility and then the accuracy of these two techniques will be evaluated.
The second aim of this study is to better understand the effect that the tumour and surgery have on language function as this will have important implications on the planning of the surgical approach, the counselling of patients of the possible risks of surgery and in helping to decide long term treatments. This will be achieved by performing advanced MRI scans, in particular an extensive language fMRI paradigm pre-operatively and post-operatively in patients with gliomas undergoing surgery. This will be combined with clinical testing of language function. Greater understanding of the neural plasticity in this functionally important system could allow for a greater, maximal resection.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: 6 months following completion of data collection for 31 participants.
The intra-operatively acquired fMRI data will be assessed by a neuroradiologist, experienced in the interpretation of fMRI data for application to neurosurgical planning. The data will be evaluated using a 3 point scoring system.
Time frame: 12 months following completion of data collection for 31 participants.
The pre-operatively acquired DTI data, which has been co-registered using a non-rigid algorithm to intra-operatively acquired structural data, will be assessed for accuracy by comparison with intra-operatively acquired DTI using the Dice similarity coefficient (DSC).
Time frame: 12 months following completion of data collection collection for 31 participants.
The language fMRI data for participants will be compared with language fMRI data from a
control group to assess for both group and individual differences. This will be performed using multivariate regression in the analysis program: Statistical Parametric Mapping.
University College, London
Other
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