| dc.description.abstract | **Please note that the full text is embargoed until 02/01/2025** For patients with drug resistant epilepsy (DRE), resective surgery is the most effective treatment to achieve seizure-freedom. Its success largely depends on the resection, ablation, or disconnection of the epileptogenic zone (EZ), defined as the minimal area indispensable for the generation of seizures, with minimal or no functional deficits. To date, there is no clinical exam to delineate the EZ unambiguously. Instead, the EZ is indirectly defined through multiple noninvasive diagnostic tests used by the multidisciplinary epilepsy team, whose results are often insufficiently concordant or inconclusive. Thus, extra-operative intracranial electroencephalography (iEEG) monitoring may be needed to precisely define the EZ by localizing the seizure onset zone (SOZ, i.e., the brain area where clinical seizures generate). Yet, the SOZ does not always predict the surgical outcome, and its delineation often requires several days of recordings to capture seizures, increasing chances of complications and risks. Thus, there is an unmet need for reliable and noninvasive interictal biomarkers that can provide clinically useful information and overall improve the presurgical evaluation of children with DRE.
Over the last decades, epilepsy has been widely seen as a disorder of brain networks characterized by epileptogenic activity that spreads across large regions, involving one or both hemispheres. Within these networks, the EZ may carry higher “connection weights” compared to other regions reflecting neurophysiological abnormalities of the epileptogenic tissue. Thus, the EZ can be seen as a strongly connected node (or hub) whose removal may result in degradation of the network activity. Functional connectivity (FC) can identify these pathological hubs that facilitate the spread of epileptiform activity from iEEG and noninvasive data, such as high-density electroencephalography (HD-EEG) and magnetoencephalography (MEG), without the need of marking interictal spikes or waiting for a seizure to occur. Several iEEG studies reported high interictal FC within resection of patients with DRE having favorable post-surgical outcome. Yet, iEEG presents limitations due to its invasiveness and limited spatial sampling that often leads to erroneous results due to large brain areas left unexplored. Performing FC on noninvasive recordings, such as HD-EEG and MEG, may help to overcome these limitations. However, noninvasive measurements have significantly reduced signal-to-noise ratio relative to iEEG; as a result, FC estimated at the sensor-level may be severely affected by volume conduction or effects of field spread, resulting in inaccurate estimations of neural interactions between brain regions. Several noninvasive studies have therefore used electric and magnetic source imaging (ESI and MSI) to reconstruct neural sources from EEG and MEG, respectively, and explored source-space FC as a biomarker of the EZ. Yet, MSI and ESI are implemented in only few epilepsy centers worldwide and recording of MEG and EEG is rarely performed simultaneously.
Here, I present three research projects of my dissertation having the following aims: (i) to assess the clinical utility of combining ESI and MSI into a single solution, namely electromagnetic source imaging (EMSI) in the localization of epileptogenic and eloquent brain areas in children with DRE; (ii) to noninvasively map the epileptogenic networks in patients with DRE undergoing epilepsy surgery by analyzing interictal HD-EEG and MEG data and assessing the prognostic value of resecting the noninvasively localized networks hubs; and (iii) to both validate global and regional FC maps in children with DRE by analyzing simultaneous HD-EEG and MEG data in comparison to typically developing children (used as healthy controls) and test their clinical utility in localizing the epileptogenic focus during the presurgical evaluation of epilepsy. Results from the first project showed that EMSI results outperform those obtained by either modality alone (i.e., ESI or MSI) in the localization of epileptogenic brain areas in children with DRE. Particularly, EMSI noninvasively localized the irritative and seizure onset zones with concordant findings as ESI on iEEG gold standard, which confirmed the clinical observations. The second project showed that virtual implantation of sensors through ESI/MSI can noninvasively identify highly connected hubs in patients with DRE, even in the absence of frank epileptiform activity, and that resection of these hubs predicted the surgical outcome better than conventional source localization methods (e.g., equivalent current dipoles). Finally, the third project indicated that FC deviations from normative maps, constructed from noninvasive electrophysiological data, can identify epileptogenic regions in the brain of children with DRE facilitating their presurgical evaluation process. Overall, the dissertation proposes: (i) the fusion of complementary information captured from simultaneous MEG and HD-EEG modalities to improve the localization accuracy in children with DRE; (ii) a noninvasive method for mapping epileptogenic networks and identifying pathological hubs in the brain of patients with DRE through the “implantation” of virtual sensors based on ESI and MSI; and (iii) a validation of these methods with respect to normative connectivity maps from healthy controls. | |
