The success of epilepsy surgery critically depends on precise identification of the epileptogenic zone, which is a costly process due to extensive diagnostic testing. Localisation of epileptogenic areas for surgical resection is still an imperfect process and long term seizure freedom is seen in fewer than half of the patients operated. These factors have directed efforts towards finding alternative biomarkers of epileptogenicity. High Frequency Oscillations (HFO) and abnormal responses to Single Pulse Electrical Stimulation (SPES) in the intracranial EEG have been proposed to be indicative of the seizure onset zone (SOZ). Removal of areas positive for these biomarkers has been linked to a good post-surgical outcome. Moreover, magnetoencephalography (MEG), which is known to provide additional localising information, offers the appealing possibility of detecting epileptic activity non-invasively. This work describes the analysis of HFO and SPES in patients with refractory epilepsy undergoing presurgical evaluation. The relationship between both of these methods and the SOZ, lesion and surgical outcome was evaluated in an attempt to determine whether they could offer additional information during the presurgical assessment of epilepsy. In addition, the use of MEG for potentially detecting pathological high frequency activity non-invasively has also been explored. The detection of HFO and abnormal SPES was not as reliable as previously described and there were significant pitfalls in HFO detection in clinical EEG data. Unexpectedly, both HFO and abnormal SPES were detected in very few patients; in most, only one of the two could be detected, indicating that the information provided by these is complimentary. Detection of HFO with MEG was severely compromised by muscle artefact, which could lead to misinterpretation of high frequency activity recorded with MEG.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:654610 |
| Date | January 2015 |
| Creators | Lemesiou, A. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/1464521/ |
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