Longitudinal structural and cognitive functional imaging and outcome prediction in focal epilepsy treated with gene therapy and surgical resection.

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Background:In people whose epilepsy does not respond to epilepsy medications (drug refractory epilepsy), epilepsy surgery to remove the part of the brain where seizures arise (the epileptic zone), may be an option. One of the most serious complications of epilepsy surgery is memory and language decline if critical brain areas are removed during surgery. This affects quality of life after surgery even in people whose seizures stop after surgery. To date, there is no standardised way of predicting whose memory may decline after surgery. It is very important that we are able to have an informed discussion with people and their families before epilepsy surgery. Discussions include the chance of stopping seizures with surgery and the risks incurred, including memory and language decline. Potassium gene therapy (EKC) where an engineered potassium gene is inserted neurosurgically into the epileptogenic zone via a probe /rod was shown to be effective in reducing seizure activity in mice. Professor Walker (project partner) and colleagues secured a MRC Developmental Pathway Funding Scheme for a Phase I/IIa pilot clinical trial for the first in-human trial of potassium gene therapy in the treatment of medication refractory epilepsy. 10 patients from our surgical cohort at the National Hospital for Neurology and Neurosurgery (NHNN) will be recruited. The risk of EKC to brain structure and function including cognitive functions and mood is not known.Main aims:In this project1) we aim to describe the memory network in people with drug refractory epilepsy compared to healthy controls using novel connectivity methods applied to memory functional magnetic resonance imaging (fMRI) and related diffusion imaging (dMRI)2) We will then study the effect of both epilepsy surgery and EKC on brain structure and function four and twelve months after these procedures. 3 Using these two different scans in combination, we aim to create a model of predicting memory outcome in people undergoing epilepsy surgery by creating a machine learning (artificial intelligence) model of prediction.Method:We will study 30 healthy controls, 10 EKC and 60 patients who will have surgical resection. Patients will be clinically assessed in hospital and as a multidisciplinary group we will decide if the best suited treatment for them is surgical resection or EKC. All participants will have a full memory and neuropsychiatric assessment. They will then have memory functional magnetic resonance imaging (fMRI) to show precisely where in their brain their memory functions lie. By using diffusion MRI (dMRI) we will study brain tracts that are important for memory functions. Novel graph theory techniques will be used to study the memory network. Four and 12 months after surgery and EKC, patients will have the same assessments of memory, mood and repeat memory fMRI and dMRI. Controls will have a similar assessment at three equivalent timepoints to patients. We will then investigate both memory fMRI and dMRI together to see if these methods in combination in a machine learning model will be useful in predicting memory decline after surgery.Importance:1. Exploring the changes in memory, mood and corresponding MRI networks will be critical in describing the safety and efficacy of both novel gene therapy and conventional surgical resection for future wider application. 2. Using the information above, in the future, we will be able to individualise epilepsy surgery. There is a computer programme called EpiNav that will take into account which brain areas are most important for memory in each person. Using EpiNav, the safest trajectory/ pathway for inserting the rod into the brain for EKC by avoiding these critical brain areas can be planned. It will also suggest how much of the brain can be safely removed during surgery to reduce the risk of memory decline.