Can histologically normal epileptogenic zone share common electrophysiological phenotypes with focal cortical dysplasia? SEEG-based study in MRI-negative epileptic patients

AbstractMEG and EEG source analysis is frequently used for the presurgical evaluation of pharma-coresistant epilepsy patients. The source localization of the epileptogenic zone depends, among other aspects, on the selected inverse and forward approaches and their respective parameter choices. In this validation study, we compare for the inverse problem the standard dipole scanning method with two beamformer approaches and we investigate the influence of the covariance estimation method and the strength of regularization on the localization performance for EEG, MEG and combined EEG and MEG. For forward modeling, we investigate the difference between calibrated six-compartment and standard three-compartment head modeling. In a retrospective study of two patients with focal epilepsy due to focal cortical dysplasia type IIb and seizure-freedom following lesionectomy or radiofrequency-guided thermocoagulation, we used the distance of the localization of interictal epileptic spikes to the resection cavity resp. rediofrequency lesion as reference for good localization. We found that beamformer localization can be sensitive to the choice of the regularization parameter, which has to be individually optimized. Estimation of the covariance matrix with averaged spike data yielded more robust results across the modalities. MEG was the dominant modality and provided a good localization in one case, while it was EEG for the other. When combining the modalities, the good results of the dominant modality were mostly not spoiled by the weaker modality. For appropriate regularization parameter choices, the beamformer localized better than the standard dipole scan. Compared to the importance of an appropriate regularization, the sensitivity of the localization to the head modeling was smaller, due to similar skull conductivity modeling and the fixed source space without orientation constraint.

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Contralateral insular epileptogenic hub causing seizure relapse after opercular focal cortical dysplasia surgery and response to radiofrequency thermocoagulation: illustrative case

Journal of Neurosurgery: Case Lessons ◽

10.3171/case21251 ◽

2021 ◽

Vol 2 (5) ◽

Author(s):

Pushkaran Jayapaul ◽

Shameer Aslam ◽

Bindhu Mangalath Rajamma ◽

Siby Gopinath ◽

Ashok Pillai

Keyword(s):

Focal Cortical Dysplasia ◽

Positron Emission Tomography Imaging ◽

Cortical Dysplasia ◽

Illustrative Case ◽

Epileptogenic Zone ◽

Pharmacoresistant Epilepsy ◽

Novel Technique ◽

Positron Emission ◽

Seizure Relapse ◽

The Right

BACKGROUND The reevaluation and management of seizure relapse following resective surgery in magnetic resonance imaging (MRI)-negative pharmacoresistant epilepsy remains a significant challenge. OBSERVATIONS A 25-year-old right-handed male with medically refractory epilepsy presented with nonlocalizing electroencephalography (EEG) and MRI. Stereo-EEG (SEEG) implantation based on semiology and positron emission tomography imaging revealed a left frontal opercular focus with rapid bilateral insular ictal synchrony. The initial epileptogenic zone was resected and pathologically proven to be type 2A focal cortical dysplasia (FCD). Seizure relapse after 9 months was eventually reinvestigated, and repeat SEEG revealed a secondary epileptogenic focus in the contralateral insula. A novel technique of volumetric stereotactic radiofrequency ablation (vRFA) was utilized for the right insular focus, following which, the patient remains seizure-free for 20 months. He suffered a transient bilateral opercular syndrome following the second intervention that eventually resolved. LESSONS The authors present clinical evidence to suggest epileptogenic nodes distant from the primary focus as a mechanism for seizure relapse following FCD surgery and the importance of bilateral insular SEEG coverage. The authors also describe a novel technique of minimally invasive vRFA that allows ablation of a larger volume of cerebral cortex when compared to conventional bedside SEEG electrode thermocoagulation.

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On The Use of Machine Learning Algorithms to Classify Focal Cortical Dysplasia on MRI

10.5753/sbcas.2021.16063 ◽

2021 ◽

Author(s):

João Guilherme Pereira ◽

Matheus de Freitas Oliveira Baffa ◽

Fabrício Henrique Simozo ◽

Luiz Otavio Murta Junior ◽

Joaquim Cezar Felipe

Keyword(s):

Deep Neural Network ◽

Surgical Intervention ◽

Refractory Epilepsy ◽

Focal Cortical Dysplasia ◽

Cortical Dysplasia ◽

Machine Learning Algorithms ◽

Textural Features ◽

Epileptogenic Zone ◽

Neural Network Classifier ◽

Multiple Classifiers

Refractory epilepsy is a condition characterized by epileptic seizure occurrence which cannot be controlled with antiepileptic drugs. This condition is associated with an excessive neuronal discharge produced by a group of neurons in a certain epileptogenic zone. Focal Cortical Dysplasia (FCD), usually found in these zones, was detected as one of the main causes of refractory epilepsy. In these cases, surgical intervention is necessary to minimize or eliminate the seizure occurrences. However, surgical treatment is only indicated in cases where there is complete certainty of the FCD. In order to assist neurosurgeons to detect precisely these regions, this paper aims to develop a classiﬁcation method to detect FCD on MRI based on morphological and textural features from a voxel-level perspective. Multiple classiﬁers were tested throughout the extracted features, the best results achieved an accuracy of 91.76% using a Deep Neural Network classiﬁer and 96.15% with J48 Decision Tree. The set of evaluating metrics showed that the results are promising.

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