Prediction of functional outcome after surgery of centrally located brain tumours
I am interested in brain plasticity and functional reorganization in patients that recover from functional deficits after low grade glioma surgery. Functional brain imaging will be performed before and after surgery with the patient in a ‘resting-state’ ( i.e., without the need for the patient to perform a particular task during scanning) in order to visualize various functional neural networks (e.g., the motor network). The major goal of my study is to evaluate whether resting state functional connectivity (RSFC) analysis is able to quantify changes in connectivity patterns of functional neural networks, and whether these changes are correlated with the patient’s recovery from functional deficits (e.g., hemiparesis). The idea is to have a presurgical instrument that is able to visualize possible disruptions in RSFC of different neural networks due to tumour, and that may be used to predict whether or not resection of a particular brain area will result in short-term or long-term disabilities.