Classification of partial seizures based on functional connectivity: A MEG study with support vector machine

Temporal lobe epilepsy (TLE) is a chronic neurological disorder that is divided into two subtypes, complex partial seizures (CPS) and simple partial seizures (SPS), based on clinical phenotypes. Revealing differences among the functional networks of different types of TLE can lead to a better understanding of the symbology of epilepsy. Whereas Although most studies had focused on differences between epileptic patients and healthy controls, the neural mechanisms behind the differences in clinical representations of CPS and SPS were unclear. In the context of the era of precision, medicine makes precise classification of CPS and SPS, which is crucial. To address the above issues, we aimed to investigate the functional network differences between CPS and SPS by constructing support vector machine (SVM) models. They mainly include magnetoencephalography (MEG) data acquisition and processing, construction of functional connectivity matrix of the brain network, and the use of SVM to identify differences in the resting state functional connectivity (RSFC). The obtained results showed that classification was effective and accuracy could be up to 82.69% (training) and 81.37% (test). The differences in functional connectivity between CPS and SPS were smaller in temporal and insula. The differences between the two groups were concentrated in the parietal, occipital, frontal, and limbic systems. Loss of consciousness and behavioral disturbances in patients with CPS might be caused by abnormal functional connectivity in extratemporal regions produced by post-epileptic discharges. This study not only contributed to the understanding of the cognitive-behavioral comorbidity of epilepsy but also improved the accuracy of epilepsy classification.

Magnetoencephalography-identified preictal spiking correlates to preictal spiking on stereotactic EEG

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Ictal MEG can assist in sEEG implantation strategy and may improve surgical outcome.

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Preictal spiking is a seizure onset pattern that has been described with intracranial EEG, but preictal spiking can also be an ictal pattern on MEG.

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MEG-predominant or MEG-unique preictal spiking may represent neuronal hypersynchronization arising from a tangential source.

Magnetoencephalography (MEG) is a noninvasive diagnostic modality that directly measures neuronal signaling by recording the magnetic field created from dendritic, intracellular, electrical currents of the neuron at the surface of the head. In clinical practice, MEG is used in the epilepsy presurgical evaluation and most commonly is an “interictal” study that can provide source localization of spike-wave discharges.

However, seizures may be recorded during MEG (“ictal MEG”) and mapping of these discharges may provide more accurate localization of the seizure onset zone. In addition, spike-negative EEG with unique MEG spike-waves may be present in up to 1/3 of MEG studies and unique MEG seizures (EEG-negative seizures) have been reported. This case report describes a patient with unique MEG seizures that exhibited MEG pre-ictal spiking in a tight cluster consistent with the independent interictal epileptiform activity. Stereotactic EEG demonstrated pre-ictal spiking concordant with the MEG pre-ictal spiking.

The 10 Common Evidence-Supported Indications for MEG in Epilepsy Surgery: An Illustrated Compendium

Unfamiliarity with the indications for and benefits of magnetoencephalography (MEG) persists, even in the epilepsy community, and hinders its acceptance to clinical practice, despite the evidence. The wide treatment gap for patients with drug-resistant epilepsy and immense underutilization of epilepsy surgery had similar effects. Thus, educating referring physicians (epileptologists, neurologists, and neurosurgeons) both about the value of epilepsy surgery and about the potential benefits of MEG can achieve synergy and greatly improve the process of selecting surgical candidates. As a practical step toward a comprehensive educational process to benefit potential MEG users, current MEG referrers, and newcomers to MEG, the authors have elected to provide an illustrated guide to 10 everyday situations where MEG can help in the evaluation of people with drug-resistant epilepsy. They are as follows: (1) lacking or imprecise hypothesis regarding a seizure onset; (2) negative MRI with a mesial temporal onset suspected; (3) multiple lesions on MRI; (4) large lesion on MRI; (5) diagnostic or therapeutic reoperation; (6) ambiguous EEG findings suggestive of "bilateral" or "generalized" pattern; (7) intrasylvian onset suspected; (8) interhemispheric onset suspected; (9) insular onset suspected; and (10) negative (i.e., spikeless) EEG. Only their practical implementation and furtherance of personal and collective education will lead to the potentially impactful synergy of the two-MEG and epilepsy surgery. Thus, while fulfilling our mission as physicians, we must not forget that ignoring the wealth of evidence about the vast underutilization of epilepsy surgery - and about the usefulness and value of MEG in selecting surgical candidates - is far from benign neglect.

Comparison of ILAE 2010 and semiological seizure classification in children with epilepsy

OBJECTIVE

The aim of this study was to compare both ILAE 2010 and semiological seizure classification (SSC) in terms of their applicability and utility and to predict epileptogenic zone in children with epilepsy.

METHODS

Both ILAE 2010 classification and SSC which is a part of five dimensional classification were applied for a total 138 children by dividing into younger (≤6y/o) and older (>6y/o) age groups over the last two years as retrospectively. After the assessment of the seizures types, epilepsy syndromes, and etiologies; the data were also compared to evaluate if having correlation between epileptogenic zone and seizure subtypes in both ILAE 2010 and SSC.

RESULTS

ILAE 2010 indicated that 66.7% of the patients had focal seizures, 15.9% had generalized seizures, and 14.4% had seizures of unknown origin. The SSC revealed that the most frequent seizure type was simple seizures (56.5%), second frequent one was complex motor seizures (46.4%) and dialeptic seizures (39.9%). To predict epileptogenic zone, SSC was found to be more specific than ILAE in terms of the more subgroups of SSC were related to the more subgroups of epileptogenic zone (p<0.05). Furthermore, there was a clear correlation between focal foci and specific seizure types in older ages, while many foci caused to same seizure types and tend to no clear focal foci with generalized onset in younger ages. On the other hand, the relationship between epileptogenic zone and etiology was more remarkable in the five dimensional classification.

SIGNIFICANCE

Preference of seizure classification system is unique for each patient and depends on requirements. Therefore, one dimension cannot be sufficient for evaluation the nature of the seizures in some patients. Furthermore, age related evolution of the seizure types should not be ignored due to ongoing maturation state of the brain. ILAE 2010 and SSC have weak and strong points compared to each other. Semiological seizure classification is more informative in terms of identifying the epileptogenic zone which may be important in specific occasions like pre-surgical work up, while ILAE is simple and easier method which can be applied for seizure description and their characteristics in daily practice.