The role of the interictal EEG in selecting candidates for resective epilepsy surgery

Quantitative approaches to guide epilepsy surgery from intracranial EEG

Over the past 10 years, the drive to improve outcomes from epilepsy surgery has stimulated widespread interest in methods to quantitatively guide epilepsy surgery from intracranial EEG (iEEG). Many patients fail to achieve seizure freedom, in part due to the challenges in subjective iEEG interpretation. To address this clinical need, quantitative iEEG analytics have been developed using a variety of approaches, spanning studies of seizures, interictal periods, and their transitions, and encompass a range of techniques including electrographic signal analysis, dynamical systems modeling, machine learning and graph theory. Unfortunately, many methods fail to generalize to new data and are sensitive to differences in pathology and electrode placement. Here, we critically review selected literature on computational methods of identifying the epileptogenic zone from iEEG. We highlight shared methodological challenges common to many studies in this field and propose ways that they can be addressed. One fundamental common pitfall is a lack of open-source, high-quality data, which we specifically address by sharing a centralized high-quality, well-annotated, multicentre dataset consisting of >100 patients to support larger and more rigorous studies. Ultimately, we provide a road map to help these tools reach clinical trials and hope to improve the lives of future patients.

Focal Cortical Dysplasia Type Ⅲ Related Medically Refractory Epilepsy: MRI Findings and Potential Predictors of Surgery Outcome

This study aims to explore the relationship between neuropathologic and the post-surgical prognosis of focal cortical dysplasia (FCD) typed-Ⅲ-related medically refractory epilepsy. A total of 266 patients with FCD typed-Ⅲ-related medically refractory epilepsy were retrospectively studied. Presurgical clinical data, type of surgery, and postsurgical seizure outcome were analyzed. The minimum post-surgical follow-up was 1 year. A total of 266 patients of FCD type Ⅲ were included in this study and the median follow-up time was 30 months (range, 12~48 months). Age at onset ranged from 1.0 years to 58.0 years, with a median age of 12.5 years. The number of patients under 12 years old was 133 (50%) in patients with FCD type Ⅲ. A history of febrile seizures was present in 42 (15.8%) cases. In the entire postoperative period, 179 (67.3%) patients were seizure-free. Factors with p < 0.15 in univariate analysis, such as age of onset of epilepsy (p = 0.145), duration of epilepsy (p = 0.004), febrile seizures (p = 0.150), being MRI-negative (p = 0.056), seizure type (p = 0.145) and incomplete resection, were included in multivariate analysis. Multivariate analyses revealed that MRI-negative findings of FCD (OR 0.34, 95% CI 0.45-0.81, p = 0.015) and incomplete resection (OR 0.12, 95% CI 0.05-0.29, p < 0.001) are independent predictors of unfavorable seizure outcomes. MRI-negative finding of FCD lesions and incomplete resection were the most important predictive factors for poor seizure outcome in patients with FCD type Ⅲ.

Microscale dynamics of electrophysiological markers of epilepsy

OBJECTIVE

Interictal discharges (IIDs) and high frequency oscillations (HFOs) are established neurophysiologic biomarkers of epilepsy, while microseizures are less well studied. We used custom poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) microelectrodes to better understand these markers' microscale spatial dynamics.

METHODS

Electrodes with spatial resolution down to 50 µm were used to record intraoperatively in 30 subjects. IIDs' degree of spread and spatiotemporal paths were generated by peak-tracking followed by clustering. Repeating HFO patterns were delineated by clustering similar time windows. Multi-unit activity (MUA) was analyzed in relation to IID and HFO timing.

RESULTS

We detected IIDs encompassing the entire array in 93% of subjects, while localized IIDs, observed across < 50% of channels, were seen in 53%. IIDs traveled along specific paths. HFOs appeared in small, repeated spatiotemporal patterns. Finally, we identified microseizure events that spanned 50-100 µm. HFOs covaried with MUA, but not with IIDs.

CONCLUSIONS

Overall, these data suggest that irritable cortex micro-domains may form part of an underlying pathologic architecture which could contribute to the seizure network.

SIGNIFICANCE

These results, supporting the possibility that epileptogenic cortex comprises a mosaic of irritable domains, suggests that microscale approaches might be an important perspective in devising novel seizure control therapies.

A needs assessment of pediatric epilepsy surgery in Haiti

OBJECTIVE

Epilepsy disproportionately affects low- and/or middle-income countries (LMICs). Surgical treatments for epilepsy are potentially curative and cost-effective and may improve quality of life and reduce social stigmas. In the current study, the authors estimate the potential need for a surgical epilepsy program in Haiti by applying contemporary epilepsy surgery referral guidelines to a population of children assessed at the Clinique d'Épilepsie de Port-au-Prince (CLIDEP).

METHODS

The authors reviewed 812 pediatric patient records from the CLIDEP, the only pediatric epilepsy referral center in Haiti. Clinical covariates and seizure outcomes were extracted from digitized charts. Electroencephalography (EEG) and neuroimaging reports were further analyzed to determine the prevalence of focal epilepsy or surgically amenable syndromes and to assess the lesional causes of epilepsy in Haiti. Lastly, the toolsforepilepsy instrument was applied to determine the proportion of patients who met the criteria for epilepsy surgery referral.

RESULTS

Two-thirds of the patients at CLIDEP (543/812) were determined to have epilepsy based on clinical and diagnostic evaluations. Most of them (82%, 444/543) had been evaluated with interictal EEG, 88% of whom (391/444) had abnormal findings. The most common finding was a unilateral focal abnormality (32%, 125/391). Neuroimaging, a prerequisite for applying the epilepsy surgery referral criteria, had been performed in only 58 patients in the entire CLIDEP cohort, 39 of whom were eventually diagnosed with epilepsy. Two-thirds (26/39) of those patients had abnormal findings on neuroimaging. Most patients (55%, 18/33) assessed with the toolsforepilepsy application met the criteria for epilepsy surgery referral.

CONCLUSIONS

The authors' findings suggest that many children with epilepsy in Haiti could benefit from being evaluated at a center with the capacity to perform basic brain imaging and neurosurgical treatments.

Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset

The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics are poorly understood. In this study, we analysed the spatial distribution of interictal spikes over time in 20 adult and paediatric patients (12 females, mean age = 34.5 years, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery. Interictal spikes were detected in the 24 h surrounding each seizure and spikes were clustered based on spatial location. The temporal dynamics of spike spatial distribution were calculated for each patient and the effects of sleep and seizures on these dynamics were evaluated. Finally, spike location was assessed in relation to seizure onset location. We found that spike spatial distribution fluctuated significantly over time in 14/20 patients (with a significant aggregate effect across patients, Fisher's method: P < 0.001). A median of 12 sequential hours were required to capture 80% of the variability in spike spatial distribution. Sleep and postictal state affected the spike spatial distribution in 8/20 and 4/20 patients, respectively, with a significant aggregate effect (Fisher's method: P < 0.001 for each). There was no evidence of pre-ictal change in the spike spatial distribution for any patient or in aggregate (Fisher's method: P = 0.99). The electrode with the highest spike frequency and the electrode with the largest area of downstream spike propagation both localized the seizure onset zone better than predicted by chance (Wilcoxon signed-rank test: P = 0.005 and P = 0.002, respectively). In conclusion, spikes localize seizure onset. However, temporal fluctuations in spike spatial distribution, particularly in relation to sleep and post-ictal state, can confound localization. An adequate duration of intracranial recording-ideally at least 12 sequential hours-capturing both sleep and wakefulness should be obtained to sufficiently sample the interictal network.

KCC2 antagonism and gabaergic synchronization in the entorhinal cortex in the absence of ionotropic glutamatergic receptor signalling

γ-Aminobutyric acid (GABA), which is released by interneurons, plays an active role in generating interictal epileptiform spikes during blockade of ionotropic glutamatergic signalling, but it remains unclear whether and how the K+-Cl- cotransporter 2 (KCC2) influences these paroxysmal events. Therefore, we employed tetrode recordings in the in vitro rat entorhinal cortex (EC) to analyze the effects of the KCC2 antagonist VU0463271 on 4-aminopyridine (4AP)-induced interictal spikes that were pharmacologically isolated by applying ionotropic glutamatergic receptor antagonists. After the addition of VU0463271, these interictal spikes continued to occur at similar rates as in control (i.e., during application of 4AP with ionotropic glutamatergic receptor antagonists) but were smaller and shorter. Despite the absence of ionotropic glutamatergic receptor signalling, both interneurons and principal cells increased their firing during interictal spikes. Moreover, we found that KCC2 antagonism increased interneuron firing but decreased principal cell firing during the interictal spike rising phase; in contrast, during the falling phase, interneuron firing decreased in the presence of VU0463271 while no change was observed in principal cell firing. Overall, our results show that KCC2 antagonism enhances interneuron excitability at the onset of interictal spikes generated by the EC neuronal networks during blockade of ionotropic glutamatergic transmission but disrupts later neuronal recruitment.

[Pre-surgical Diagnosties in Patients with Intractable epilepsy]

PURPOSE

To conduct a systematic assessment of scientific publications devoted to pre-surgical examination of patients with intactable epilepsy.

MATERIAL AND METHODS

We found, using PubMed and available Internet search tools, and analyzed 1.414 articles on pre-surgical diagnostics in patients with intractable epilepsy.

RESULTS

Epilepsy is a chronic disorder caused by brain injury, which manifests as repeated epileptic seizures and is accompanied by a variety of personality changes. Mortality risks in the population of patients with uncontrolled intractable epilepsy significantly exceed those in the general population. Early onset of comprehensive treatment prevents pathological personality changes and reduces the risks of mortality. However, complete seizure control is not achieved in 30% of patients, and they develop pharmacoresistance later, which is the reason for considering these patients as candidates for surgical treatment. In the literature, many approaches to pre-surgical examination are described as each clinic has its own concept of pre-surgical diagnostics and its own approaches to surgical management. Based on the conducted analysis, we tried to summarize the received information and describe current ideas about pre-surgical examination of patients with intactable epilepsy.

CONCLUSION

On the basis of analyzed literature, we performed a systematic assessment and the evaluated effectiveness of various approaches in the pre-surgical diagnostics of patients with intactable epilepsy.

Real-Time Localization of Epileptogenic Foci EEG Signals: An FPGA-Based Implementation

The epileptogenic focus is a brain area that may be surgically removed to control of epileptic seizures. Locating it is an essential and crucial step prior to the surgical treatment. However, given the difficulty of determining the localization of this brain region responsible of the initial seizure discharge, many works have proposed machine learning methods for the automatic classification of focal and non-focal electroencephalographic (EEG) signals. These works use automatic classification as an analysis tool for helping neurosurgeons to identify focal areas off-line, out of surgery, during the processing of the huge amount of information collected during several days of patient monitoring. In turn, this paper proposes an automatic classification procedure capable of assisting neurosurgeons online, during the resective epilepsy surgery, to refine the localization of the epileptogenic area to be resected, if they have doubts. This goal requires a real-time implementation with as low a computational cost as possible. For that reason, this work proposes both a feature set and a classifier model that minimizes the computational load while preserving the classification accuracy at 95.5%, a level similar to previous works. In addition, the classification procedure has been implemented on a FPGA device to determine its resource needs and throughput. Thus, it can be concluded that such a device can embed the whole classification process, from accepting raw signals to the delivery of the classification results in a cost-effective Xilinx Spartan-6 FPGA device. This real-time implementation begins providing results after a 5 s latency, and later, can deliver floating-point classification results at 3.5 Hz rate, using overlapped time-windows.

Focal epilepsies and focal disorders

Electroencephalographic (EEG) investigations are crucial in the diagnosis and management of patients with focal epilepsies. EEG may reveal different interictal epileptiform discharges (IEDs: abnormal spikes, sharp waves). The EEG visibility of a spike depends on the surface area of cortex involved (>10cm²) and the brain localization of cortical generators. Regions generating IEDs (defining the "irritative zone") are not necessarily equivalent to the seizure onset zone. Focal seizures are dynamic processes originating from one or several brain regions (that generate fast oscillations and are called the epileptogenic zone) before spreading to other structures (that generate lower frequency oscillations and are called the propagation zone). Several factors limit the expression of seizures on scalp EEG, such as the area involved, degree of synchronization, and depth of the cortical generators. Different scalp EEG seizure onset patterns may be observed: fast discharge, background flattening, rhythmic spikes, sinusoidal discharge, or sharp activity. However, to a large extent EEG changes are linked to seizure propagation. Finally, in the context of presurgical evaluation, the combination of interictal and ictal EEG features is crucial to provide an optimal hypothesis concerning the epileptogenic zone.

Preoperative evaluation using magnetoencephalography: Experience in 382 epilepsy patients

OBJECTIVE

Identifying epilepsy patients for whom clinical MEG is likely to be beneficial avoids or optimizes burdensome ancillary investigations. We determined whether it could be predicted upfront if MEG would be able to generate a hypothesis about the location of the epileptogenic zone (EZ), and in which patients MEG fails to do so.

METHODS

MEG recordings of 382 epilepsy patients with inconclusive findings regarding EZ localization prior to MEG were acquired for preoperative evaluation. MEG reports were categorized for several demographic, clinical and MEG variables. First, demographic and clinical variables were associated with MEG localization ability for upfront prediction. Second, all variables were compared between patients with and without MEG location in order to characterize patients without MEG location.

RESULTS

Our patient group had often complex etiology and did not contain the (by other means) straightforward and well-localized cases, such as those with concordant tumor and EEG location. For our highly-selected patient group, MEG localization ability cannot be predicted upfront, although the odds of a recording with MEG location were significantly higher in the absence of a tumor and in the presence of widespread MRI abnormalities. Compared to the patients with MEG location, patients without MEG location more often had a tumor, widespread EEG abnormalities, non-lateralizing MEG abnormalities, non-concordant MEG/EEG abnormalities and less often widespread MRI abnormalities or epileptiform MEG activity. In a subgroup of 48 patients with known surgery outcome, more patients with concordant MEG and resection area were seizure-free than patients with discordant results.

CONCLUSIONS

MEG potentially adds information about the location of the EZ even in patients with a complex etiology, and the clinical advice is to not withhold MEG in epilepsy surgery candidates. Providing a hypothesis about the location of the EZ using MEG is difficult in patients with inconclusive EEG and MRI findings, and in the absence of specific epileptiform activity. More refined methods are needed for patients where MEG currently does not contribute to the hypothesis about the location of the EZ.

Towards precision medicine in epilepsy surgery

Up to a third of all patients with epilepsy are refractory to medical therapy even in the context of the introduction of new antiepileptic drugs (AEDs) with considerable advantages in safety and tolerability over the last two decades. It has been widely accepted that epilepsy surgery is a highly effective therapeutic option in a selected subset of patients with refractory focal seizure. There is no doubt that accurate localization of the epileptogenic zone (EZ) is crucial to the success of resection surgery for intractable epilepsy. The pre-surgical evaluation requires a multimodality approach wherein each modality provides unique and complimentary information. Accurate localization of EZ still remains challenging, especially in patients with normal features on MRI. Whereas substantial progress has been made in the methods of pre-surgical assessment in recent years, which widened the applicability of surgical treatment for children and adults with refractory seizure. Advances in neuroimaging including voxel-based morphometric MRI analysis, multimodality techniques and computer-aided subtraction ictal SPECT co-registered to MRI have improved our ability to identify subtle structural and metabolic lesions causing focal seizure. Considerable observations from animal model with epilepsy and pre-surgical patients have consistently found a strong correlation between high frequency oscillations (HFOs) and epileptogenic brain tissue that suggest HFOs could be a potential biomarker of EZ. Since SEEG emphasizes the importance to study the spatiotemporal dynamics of seizure discharges, accounting for the dynamic, multidirectional spatiotemporal organization of the ictal discharges, it has greatly deep our understanding of the anatomo-electro-clinical profile of seizure. In this review, we focus on some state-of-the-art pre-surgical investigations that contribute to the precision medicine. Furthermore, advances also provide opportunity to achieve the minimal side effects and maximal benefit individually, which meets the need for the current concept of precision medicine in epilepsy surgery.

Perspectives of epilepsy surgery in resource-poor countries: a study in Georgia

BACKGROUND

To identify patients with concordant seizure semiology, interictal epileptiform discharges on standard EEG and brain MRI changes to define the patients with pharmacoresistant epilepsy (PRE) who would be suitable for epilepsy surgery according to non-invasive protocol.

METHODS

The medical records of the patients with epilepsy seen in Epilepsy Center of Institute of Neurology and Neuropsychology (ECINN) (Tbilisi, Georgia) were reviewed retrospectively. The diagnostic work-up included neurological examination, standard EEG, and MRI. The degree of concordance of the seizure semiology, EEG, and neuroimaging was used to determine the potential candidates for surgery. The probability of seizure freedom rate was estimated based on known predictive values of anatomical, electrophysiological, and semiological characteristics.

RESULTS

A total of 83 (25 %) patients met the criteria of PRE. Fourteen (17 %) patients had complete concordance of seizure semiology, MRI, and EEG. Out of these patients, 11 had mesial temporal sclerosis on MRI and three had focal cortical dysplasia (FCD). Estimated seizure-free surgical success rate in this group was 75-95 % without the need for further investigations. Out of 25 (30 %) non-lesional MRI cases, the concordance of seizure semiology and EEG was in nine patients with probable success rate up to 60 %. Thirteen patients (16 %) had discordant EEG and MRI data and were not suitable for surgery without further testing.

CONCLUSIONS

A significant portion of PRE patients with concordant anatomical, electrophysiological, and semiological characteristics can be treated surgically in resource-limited countries. Nevertheless, most patients will still require further investigation for proper localization of epileptogenic focus.

Classification of EEG abnormalities in partial epilepsy with simultaneous EEG-fMRI recordings

Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the "irritative zone" (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram-functional Magnetic Resonance Imagining (EEG-fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG-fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert classification (7 and 5, respectively). In contrast, in only one case presented the new algorithm resulted in fewer classes and activation areas. We propose that the use of automated spike sorting algorithms to classify IED provides an efficient tool for mapping IED-related fMRI changes and increases the EEG-fMRI clinical value for the pre-surgical assessment of patients with severe epilepsy.

Is interictal EEG activity a biomarker for mood disorders in temporal lobe epilepsy?

OBJECTIVE

Psychiatric comorbidities are frequent in temporal lobe epilepsy (TLE), and symptoms of these comorbidities may be related to epilepsy activity. Here we evaluated interictal EEG activity in TLE patients with or without psychiatric comorbidities.

METHODS

A cohort study of 78 patients with TLE, with evaluation of wake/sleep interictal scalp EEG. All subjects were submitted to a psychiatric structured clinical interview (SCID) for the diagnosis of lifetime psychiatric comorbidities. Three major diagnostic categories were studied: mood disorders, anxiety disorders, and psychosis. We then evaluated differences in interictal EEG activity between patients with and without these psychiatric comorbidities.

RESULTS

Infrequent EEG interictal spikes, defined as less than one event per minute, were significantly associated with mood disorders in TLE (p=0.02).

CONCLUSIONS

Low intensity seizure disorder has been associated with a decrease in interictal EEG discharges and with an increase in psychiatric symptoms in TLE, a phenomenon known as forced normalization. In our study, we observed a low interictal spike frequency on EEG in TLE patients with mood disorders.

SIGNIFICANCE

A low spike index might be a neurophysiological marker for depression in temporal lobe epilepsy.