Localized epilepsy and neural networks.

Rationale:
Epilepsy is common in patients with circumscribed brain abnormalities, such as primary brain tumours and focal cortical dysplasias. In a substantial number of these patients, anti-epileptic drug treatment is ineffective. Patients with lesional epilepsy in whom no brain tumour is present will be referred to epilepsy surgery programs. The aim of these programs is to (1) identify and, subsequently, (2) remove the ictal zone. This leads to long-term seizure freedom in only 30-60% of patients.
Although in patients with brain tumours the primary aim of surgery is the removal of the tumour, it is increasingly acknowledged that resective surgery may also result in a decrease of seizure frequency. For both patient groups, improvement of outcome of epilepsy surgery will therefore be extremely relevant.

Electrocorticography (ECoG) and magnetoencephalography (MEG) are imaging techniques that are used for detection of seizure activity and epileptic source localization as well as assessment of functional connectivity and neural network features throughout the brain. Recent research advances concerning functional connectivity and network properties of the brain have indicated that these techniques may be used for epileptic source localization and to investigate factors that determine the frequency of epileptic seizures. Application of these methods in candidates for epilepsy surgery may lead to more effective treatment and improvement of surgical outcome.

Objective:
The primary objective of this study is to characterize functional brain networks in patients considered for (i) epilepsy surgery and (ii) tumour surgery with epilepsy surgery techniques. Characterization will be done preoperatively (MEG), during surgery (ECoG) and post surgery (MEG). At each stage, networks will be characterized using graph theoretical measures that are expected to be related to seizure proneness.

The secondary objectives of this study are:
(1) To relate network properties at different stages to (i) seizure frequency, (ii) seizure burden, and (iii) cognition; (2) To develop a model to predict the effect of surgery on network changes and reduction of seizure burden.

Study design:
This is a longitudinal observational study.

Study population:
40 Adult (≥18 years), pharmacoresistant epilepsy patients who undergo epilepsy surgery, and adult brain tumour patients with epilepsy who undergo tumour surgery with epilepsy surgery techniques.

Main study parameters/endpoints:
The main study parameters are ECoG and MEG measures assessing functional connectivity and neuronal brain networks (clustering coefficient and path length), as well as the clinical measures of seizure frequency, epilepsy burden and cognition.

Better guided resection of brain areas that are, regarding network characteristics, important for seizure onset and propagation may result in improved clinical outcome. However, before such guidance is possible, more insight into the effects of resective surgery on functional network characteristics, and on clinical outcome, is required. In order to do this, we propose the development of a computational model that predicts the impact of resective surgery on neural networks. Furthermore, we plan to study the correlation between network characteristics, based on MEG and ECoG recordings, and surgical outcome, in terms of epilepsy frequency, epilepsy burden and cognition.

1. Pre-resection;

2. 3 months post-resection;

3. 9 months post-resection.

N/A