Invasive epilepsy surgery evaluation

Differentiating rhythmic high-amplitude delta with superimposed (poly) spikes from extreme delta brushes: limitations of standardized nomenclature and implications for patient management

BACKGROUND

Following the standardized nomenclature proposed by the American Clinical Neurophysiology Society (ACNS), rhythmic high-amplitude delta activity with superimposed spikes (RHADS) can be reported as an extreme delta brush (EDB). The clinical implications of similar electrographic patterns being reported as RHADS versus EDB are important to highlight. We aim to review the electrographic characteristics of RHADS, evaluate whether RHADS is seen in other neurological disorders, and identify the similar and unique characteristics between RHADS and EDB to ultimately determine the most accurate way to differentiate and report these patterns. We believe that the differentiation of RHADS and EDB is important as there is a vast difference in the diagnostic approach and the medical management of associated underlying etiologies.

DATA SOURCE

We conducted an extensive search on MEDLINE and Pubmed utilizing various combinations of keywords. Searching for "gamma polymerase and EEG", or "RHADS" or "Alpers syndrome and EEG" or "EEG" AND "Alpers-Huttenlocher syndrome".

RESULTS

Three articles were found to be focused on the description of "RHADS" pattern in Alpers Syndrome. No publication to date were found when searching for the terms "EDB" AND "children", AND "infant" AND "adolescent" excluding "encephalitis" and "neonate". Although RHADS and EDB appear as similar EEG patterns, meticulous analysis can differentiate them. RHADS is not exclusive to patients with Alpers-Huttenlocher syndrome and may manifest in regions beyond the posterior head region. Reactivity to eye-opening and response to anesthesia can be two other elements that help in the differentiation of these patterns.

CONCLUSION

RHADS is not exclusive to patients with AHS and may manifest in regions beyond the posterior head region. Reactivity to eye-opening and response to anesthesia are features that help in the differentiation of these patterns.

EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes

BACKGROUND AND OBJECTIVES

Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties.

METHODS

We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time.

RESULTS

Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes.

DISCUSSION

Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.

Deep learning based decoding of single local field potential events

How is information processed in the cerebral cortex? In most cases, recorded brain activity is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. However, the brain is obviously a single-trial processor. Thus, we here demonstrate that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial basis. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both extra-cellular neural recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding.

Specific consistency score for rational selection of epilepsy resection surgery candidates

OBJECTIVE

Degree of indication for epilepsy surgery is determined by taking multiple factors into account. This study aimed to investigate the usefulness of the Specific Consistency Score (SCS), a proposed score for focal epilepsy to rate the indication for epilepsy focal resection.

METHODS

This retrospective cohort study included patients considered for resective epilepsy surgery in Kyoto University Hospital from 2011 to 2022. Plausible epileptic focus was tentatively defined. Cardinal findings were scored based on specificity and consistency with the estimated laterality and lobe. The total points represented SCS. The association between SCS and the following clinical parameters was assessed by univariate and multivariate analysis: (1) probability of undergoing resective epilepsy surgery, (2) good postoperative seizure outcome (Engel I and II or Engel I only), and (3) lobar concordance between the noninvasively estimated focus and intracranial electroencephalographic (EEG) recordings.

RESULTS

A total of 131 patients were evaluated. Univariate analysis revealed higher SCS in the (1) epilepsy surgery group (8.4 [95% confidence interval (CI) = 7.8-8.9] vs. 4.9 [95% CI = 4.3-5.5] points; p < .001), (2) good postoperative seizure outcome group (Engel I and II; 8.7 [95% CI = 8.2-9.3] vs. 6.4 [95% CI = 4.5-8.3] points; p = .008), and (3) patients whose focus defined by intracranial EEG matched the noninvasively estimated focus (8.3 [95% CI = 7.3-9.2] vs. 5.4 [95% CI = 3.5-7.3] points; p = .004). Multivariate analysis revealed areas under the curve of .843, .825, and .881 for Parameters 1, 2, and 3, respectively.

SIGNIFICANCE

SCS provides a reliable index of good indication for resective epilepsy surgery and can be easily available in many institutions not necessarily specializing in epilepsy.

Outcomes of stereoelectroencephalography following failed epilepsy surgery in children

INTRODUCTION

Stereoelectroencephalography (SEEG) is valuable for delineating the seizure onset zone (SOZ) in pharmacoresistant epilepsy when non-invasive presurgical techniques are inconclusive. Secondary epilepsy surgery after initial failure is challenging and there is limited research on SEEG following failed epilepsy surgery in children.

OBJECTIVE

The objective of this manuscript is to present the outcomes of children who underwent SEEG after failed epilepsy surgery.

METHODS

In this single-institution retrospective study, demographics, previous surgery data, SEEG characteristics, management, and follow-up were analyzed for pediatric patients who underwent SEEG after unsuccessful epilepsy surgery between August 2016 and February 2023.

RESULTS

Fifty three patients underwent SEEG investigation during this period. Of this, 13 patients were identified who had unsuccessful initial epilepsy surgery (24%). Of these 13 patients, six patients (46%) experienced unsuccessful resective epilepsy surgery that targeted the temporal lobe, six patients (46%) underwent surgery involving the frontal lobe, and one patient (8%) had laser interstitial thermal therapy (LITT) of the right insula. SEEG in two thirds of patients (4/6) with initial failed temporal resections revealed expanded SOZ to include the insula. All 13 patients (100%) had a subsequent surgery after SEEG which was either LITT (54%) or surgical resection (46%). After the subsequent surgery, a favorable outcome (Engel class I/II) was achieved by eight patients (62%), while five patients experienced an unfavorable outcome (Engel class III/IV, 38%). Of the six patients with secondary surgical resection, four patients (67%) had favorable outcomes, while of the seven patients with LITT, two patients (29%) had favorable outcomes (Engel I/II). Average follow-up after the subsequent surgery was 37 months ±23 months.

CONCLUSION

SEEG following initial failed resective epilepsy surgery may help guide next steps at identifying residual epileptogenic cortex and is associated with favorable seizure control outcomes.

Clinical utility and safety of a trapezoid-shaped electrode placement for evaluating the mesio-basal temporal lobe during epilepsy surgery

A trapezoid-shaped electrode (TSE) is used for detecting epileptogenicity in patients with temporal lobe epilepsy (TLE). However, the utility and safety associated with TSE placement have not been reported. In this study, we evaluated the safety and usefulness of TSE by analyzing the seizure detection, surgical outcomes and complications in patients with TLE who underwent intracranial electrodes (ICE) placement. Between April 2000 and August 2019, 50 patients with TLE who underwent 51 ICE placement procedures were examined. A TSE with eight contacts covering the parahippocampal gyrus and basal temporal lobe was used. Among the 37 patients who underwent TSE placement, 26 and 11 patients were diagnosed with mesial TLE (mTLE) and extra-mTLE, respectively. The 14 remaining patients without TSE placement were diagnosed with extra-mTLE. Seizure freedom was achieved in 73% (19/26) of mTLE patients detected by TSE and 50% (14/24) of extra-mTLE patients.Good seizure outcomes (Engel class I and II) were observed in 81% (21/26) patients with mTLE and 67% (16/24) patients with extra-mTLE. Radiographic complications were observed in 20% (10/50) patients who underwent ICE placement. Although 6% (3/50) patients showed transient neurological deficits, none were permanent. The electrodes responsible for the occurrence of complications included nine grid electrodes and one TSE. The complication rate after TSE placement was 3% (1/37). More than 64 electrode contacts and male sex, not TSE placement, were identified as significant risk factors for developing complications. This study demonstrated the usefulness and safety of TSE for evaluating mTLE in patients undergoing ICE placement.

Comparison of 2 Robotic Systems for Pediatric Stereoelectroencephalography Implantation

BACKGROUND

Stereoelectroencephalography (SEEG) remains critical in guiding epilepsy surgery. Robot-assisted techniques have shown promise in improving SEEG implantation outcomes but have not been directly compared. In this single-institution series, we compared ROSA and Stealth AutoGuide robots in pediatric SEEG implantation.

METHODS

We retrospectively reviewed 21 sequential pediatric SEEG implantations consisting of 6 ROSA and 15 AutoGuide procedures. We determined mean operative time, time per electrode, root mean square (RMS) registration error, and surgical complications. Three-dimensional radial distances were calculated between each electrode's measured entry and target points with respective errors from the planned trajectory line.

RESULTS

Mean overall/per electrode operating time was 73.5/7.5 minutes for ROSA and 126.1/10.9 minutes for AutoGuide (P = 0.030 overall, P = 0.082 per electrode). Mean RMS registration error was 0.77 mm (0.55-0.93 mm) for ROSA and 0.6 mm (0.2-1.0 mm) for AutoGuide (P = 0.26). No procedures experienced complications. The mean radial (entry point error was 1.23 ± 0.11 mm for ROSA and 2.65 ± 0.12 mm for AutoGuide (P < 0.001), while the mean radial target point error was 1.86 ± 0.15 mm for ROSA and 3.25 ± 0.16 mm for AutoGuide (P < 0.001).

CONCLUSIONS

Overall operative time was greater for AutoGuide procedures, although there was no statistically significant difference in time per electrode. Both systems are highly accurate with no significant RMS error difference. While the ROSA robot yielded significantly lower entry and target point errors, both robots are safe and reliable for deep electrode insertion in pediatric epilepsy.

Trends in the Utilization of Surgical Modalities for the Treatment of Drug-Resistant Epilepsy: A Comprehensive 10-Year Analysis Using the National Inpatient Sample

BACKGROUND AND OBJECTIVES

Epilepsy is considered one of the most prevalent and severe chronic neurological disorders worldwide. Our study aims to analyze the national trends in different treatment modalities for individuals with drug-resistant epilepsy and investigate the outcomes associated with these procedural trends in the United States.

METHODS

Using the National Inpatient Sample database from 2010 to 2020, patients with drug-resistant focal epilepsy who underwent laser interstitial thermal therapy (LITT), open surgical resection, vagus nerve stimulation (VNS), or responsive neurostimulation (RNS) were identified. Trend analysis was performed using piecewise joinpoint regression. Propensity score matching was used to compare outcomes between 10 years prepandemic before 2020 and the first peak of the COVID-19 pandemic.

RESULTS

This study analyzed a total of 33 969 patients with a diagnosis of drug-resistant epilepsy, with 3343 patients receiving surgical resection (78%), VNS (8.21%), RNS (8%), and LITT (6%). Between 2010 and 2020, there was an increase in the use of invasive electroencephalography monitoring for seizure zone localization (P = .003). There was an increase in the use of LITT and RNS (P < .001), while the use of surgical resection and VNS decreased over time (P < .001). Most of these patients (89%) were treated during the pre-COVID pandemic era (2010-2019), while a minority (11%) underwent treatment during the COVID pandemic (2020). After propensity score matching, the rate of pulmonary complications, postprocedural hematoma formation, and mortality were slightly higher during the pandemic compared with the prepandemic period (P = .045, P = .033, and P = .026, respectively).

CONCLUSION

This study indicates a relative decrease in the use of surgical resections, as a treatment for drug-resistant focal epilepsy. By contrast, newer, minimally invasive surgical approaches including LITT and RNS showed gradual increases in usage.

A review of signal processing and machine learning techniques for interictal epileptiform discharge detection

Brain interictal epileptiform discharges (IEDs), as one of the hallmarks of epileptic brain, are transient events captured by electroencephalogram (EEG). IEDs are generated by seizure networks, and they occur between seizures (interictal periods). The development of a robust method for IED detection could be highly informative for clinical treatment procedures and epileptic patient management. Since 1972, different machine learning techniques, from template matching to deep learning, have been developed to automatically detect IEDs from scalp EEG (scEEG) and intracranial EEG (iEEG). While the scEEG signals suffer from low information details and high attenuation of IEDs due to the high skull electrical impedance, the iEEG signals recorded using implanted electrodes enjoy higher details and are more suitable for identifying the IEDs. In this review paper, we group IED detection techniques into six categories: (1) template matching, (2) feature representation (mimetic, time-frequency, and nonlinear features), (3) matrix decomposition, (4) tensor factorization, (5) neural networks, and (6) estimation of the iEEG from the concurrent scEEG followed by detection and classification. The methods are compared quantitatively (e.g., in terms of accuracy, sensitivity, and specificity), and their general advantages and limitations are described. Finally, current limitations and possible future research paths related to this field are mentioned.

Combined Depth and Subdural Electrodes for Lateralization of the Ictal Onset Zone in Mesial Temporal Lobe Epilepsy with Hippocampal Sclerosis

(1) Objective: This study aimed to explore the efficacy of conventional invasive techniques in confirming unilateral seizure onset localization in mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) and to investigate the association between electrode type and intracranial electroencephalography (EEG) pattern. (2) Methods: This retrospective study encompasses patients diagnosed with MTLE-HS who underwent an invasive study prior to an anterior temporal lobectomy (ATL). Intracranial EEG features were assessed for 99 seizure events from 25 selected patients who achieved seizure remission with ATL after an invasive study using bilateral combined depth and subdural electrodes. Their findings were compared to those of 21 seizure events in eight patients who exhibited suboptimal seizure outcomes. (3) Results: For the distribution of electrodes that recorded the ictal onset, hippocampal depth electrodes recorded 96% of all seizure events, while subdural electrodes recorded 52%. Among the seizures recorded in subdural electrodes, 49% were localized in medial electrodes, with only 8% occurring in lateral electrodes. The initiation of seizures exclusively detected in hippocampal depth electrodes was associated with successful seizure remission, whereas those solely recorded in the lateral strip electrodes were often linked to refractory seizures after ATL. (4) Conclusions: These findings emphasize the importance of employing a combination of depth and subdural electrodes in invasive studies for patients with MTLE-HS to enhance the accuracy of lateralization. This also cautions against sole reliance on subdural electrodes without depth electrodes, which could lead to inaccurate localization.

Interictal magnetoencephalography abnormalities to guide intracranial electrode implantation and predict surgical outcome

Intracranial EEG is the gold standard technique for epileptogenic zone localization but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography. Quantitative abnormality mapping using magnetoencephalography has recently been shown to have potential clinical value. We hypothesized that if quantifiable magnetoencephalography abnormalities were sampled by intracranial EEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent magnetoencephalography and subsequent intracranial EEG recordings as part of presurgical evaluation. Eyes-closed resting-state interictal magnetoencephalography band power abnormality maps were derived from 70 healthy controls as a normative baseline. Magnetoencephalography abnormality maps were compared to intracranial EEG electrode implantation, with the spatial overlap of intracranial EEG electrode placement and cerebral magnetoencephalography abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue and subsequent resection of the strongest abnormalities determined by magnetoencephalography and intracranial EEG corresponded to surgical success. We used the area under the receiver operating characteristic curve as a measure of effect size. Intracranial electrodes were implanted in brain tissue with the most abnormal magnetoencephalography findings-in individuals that were seizure-free postoperatively (T = 3.9, P = 0.001) but not in those who did not become seizure-free. The overlap between magnetoencephalography abnormalities and electrode placement distinguished surgical outcome groups moderately well (area under the receiver operating characteristic curve = 0.68). In isolation, the resection of the strongest abnormalities as defined by magnetoencephalography and intracranial EEG separated surgical outcome groups well, area under the receiver operating characteristic curve = 0.71 and area under the receiver operating characteristic curve = 0.74, respectively. A model incorporating all three features separated surgical outcome groups best (area under the receiver operating characteristic curve = 0.80). Intracranial EEG is a key tool to delineate the epileptogenic zone and help render individuals seizure-free postoperatively. We showed that data-driven abnormality maps derived from resting-state magnetoencephalography recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of postoperative seizure freedom, which leverages both magnetoencephalography and intracranial EEG recordings, could aid patient counselling of expected outcome.

Robot-assisted stereoencephalography vs subdural electrodes in the evaluation of temporal lobe epilepsy

OBJECTIVE

Invasive video-electroencephalography (iVEEG) is the gold standard for evaluation of refractory temporal lobe epilepsy before second stage resective surgery (SSRS). Traditionally, the presumed seizure onset zone (SOZ) has been covered with subdural electrodes (SDE), a very invasive procedure prone to complications. Temporal stereoelectroencephalography (SEEG) with conventional frame-based stereotaxy is time-consuming and impeded by the geometry of the frame. The introduction of robotic assistance promised a simplification of temporal SEEG implantation. However, the efficacy of temporal SEEG in iVEEG remains unclear. The aim of this study was therefore to describe the efficiency and efficacy of SEEG in iVEEG of temporal lobe epilepsy.

METHODS

This retrospective study enrolled 60 consecutive patients with medically intractable epilepsy who underwent iVEEG of a potential temporal SOZ by SDE (n = 40) or SEEG (n = 20). Surgical time efficiency was analyzed by the skin-to-skin time (STS) and the total procedure time (TPT) and compared between groups (SDE vs SEEG). Surgical risk was depicted by the 90-day complication rate. Temporal SOZ were treated by SSRS. Favorable outcome (Engel°1) was assessed after 1 year of follow-up.

RESULTS

Robot-assisted SEEG significantly reduced the duration of surgery (STS and TPT) compared to SDE implantations. There was no significant difference in complication rates. Notably, all surgical revisions in this study were attributed to SDE. Unilateral temporal SOZ was detected in 34/60 cases. Of the 34 patients, 30 underwent second stage SSRS. Both SDE and SEEG had a good predictive value for the outcome of temporal SSRS with no significant group difference.

SIGNIFICANCE

Robot-assisted SEEG improves the accessibility of the temporal lobe for iVEEG by increasing surgical time efficiency and by simplifying trajectory selection without losing its predictive value for SSRS.

Detection of pathological high-frequency oscillations in refractory epilepsy patients undergoing simultaneous stereo-electroencephalography and magnetoencephalography

BACKGROUND

Stereo-electroencephalography (SEEG) and magnetoencephalography (MEG) have generally been used independently as part of the pre-surgical evaluation of drug-resistant epilepsy (DRE) patients. However, the possibility of simultaneously employing these recording techniques to determine whether MEG has the potential of offering the same information as SEEG less invasively, or whether it could offer a greater spatial indication of the epileptogenic zone (EZ) to aid surgical planning, has not been previously evaluated.

METHODS

Data from 24 paediatric and adult DRE patients, undergoing simultaneous SEEG and MEG as part of their pre-surgical evaluation, was analysed employing manual and automated high-frequency oscillations (HFOs) detection, and spectral and source localisation analyses.

RESULTS

Twelve patients (50%) were included in the analysis (4 males; mean age=25.08 years) and showed interictal SEEG and MEG HFOs. HFOs detection was concordant between the two recording modalities, but SEEG displayed higher ability of differentiating between deep and superficial epileptogenic sources. Automated HFO detector in MEG recordings was validated against the manual MEG detection method. Spectral analysis revealed that SEEG and MEG detect distinct epileptic events. The EZ was well correlated with the simultaneously recorded data in 50% patients, while 25% patients displayed poor correlation or discordance.

CONCLUSION

MEG recordings can detect HFOs, and simultaneous use of SEEG and MEG HFO identification facilitates EZ localisation during the presurgical planning stage for DRE patients. Further studies are necessary to validate these findings and support the translation of automated HFO detectors into routine clinical practice.

Sensing local field potentials with a directional and scalable depth electrode array

Objective. A variety of electrophysiology tools are available to the neurosurgeon for diagnosis, functional therapy, and neural prosthetics. However, no tool can currently address these three critical needs: (a) access to all cortical regions in a minimally invasive manner; (b) recordings with microscale, mesoscale, and macroscale resolutions simultaneously; and (c) access to spatially distant multiple brain regions that constitute distributed cognitive networks.Approach.We modeled, designed, and demonstrated a novel device for recording local field potentials (LFPs) with the form factor of a stereo-electroencephalographic electrode and combined with radially distributed microelectrodes.Main results. Electro-quasistatic models demonstrate that the lead body amplifies and shields LFP sources based on direction, enablingdirectional sensitivity andscalability, referred to as thedirectional andscalable (DISC) array.In vivo,DISC demonstrated significantly improved signal-to-noise ratio, directional sensitivity, and decoding accuracy from rat barrel cortex recordings during whisker stimulation. Critical for future translation, DISC demonstrated a higher signal to noise ratio (SNR) than virtual ring electrodes and a noise floor approaching that of large ring electrodes in an unshielded environment after common average referencing. DISC also revealed independent, stereoscopic current source density measures whose direction was verified after histology.Significance. Directional sensitivity of LFPs may significantly improve brain-computer interfaces and many diagnostic procedures, including epilepsy foci detection and deep brain targeting.

Clinical Impacts of Stereotactic Electroencephalography on Epilepsy Surgery and Associated Issues in the Current Situation in Japan

Stereotactic electroencephalography (SEEG) is receiving increasing attention as a safe and effective technique in the invasive evaluation for epileptogenic zone (EZ) detection. The main clinical question is whether the use of SEEG truly improves outcomes. Herein, we compared outcomes in our patients after three types of intracranial EEG (iEEG): SEEG, the subdural electrode (SDE), and a combined method using depth and strip electrodes. We present here our preliminary results from two demonstrative cases. Several international reports from large epilepsy centers found the following clinical advantages of SEEG: 1) three-dimensional analysis of structures, including bilateral and multilobar structures; 2) low rate of complications; 3) less pneumoencephalopathy and less patient burden during postoperative course, which allows the initiation of video-EEG monitoring immediately after implantation and does not require resection to be performed in the same hospitalization; and 4) a higher rate of good seizure control after resection. In other words, SEEG more accurately identified the EZ than the SDE method. We obtained similar results in our preliminary experiences under limited conditions. In Japan, as of August 2022, dedicated electrodes and SEEG accessories have not been approved and the use of the robot arm is not widespread. The Japanese medical community is hopeful that these issues will soon be resolved and that the experience with SEEG in Japan will align with that of large epilepsy centers internationally.

Implantation of Intracranial Electrodes Predicts Worse Outcome in Mesial Temporal Lobe Epilepsy

OBJECTIVE

Anteromesial resection is an effective method for treating seizures arising from the medial temporal lobe, as these cases are often the most straightforward and have the best outcomes. Nevertheless, some patients who go on to have a mesial resection are recommended to have an implantation of electrodes before surgery. Whether the need for such an implant alters the rate of seizure freedom is not well-studied in this particular subgroup of epilepsy patients.

METHODS

We performed a retrospective review of consecutive anteromesial surgeries for medial temporal lobe epilepsy performed between 2005 and 2020. Of a total of 39 patients, 19 required electrode implantation (electrode group) and 20 did not (no-electrode group). The primary outcomes assessed were reduction in seizure frequency and Engel score. Complication rates were also compared.

RESULTS

Postresection seizure frequency reduction was nonsignificantly higher in the no-electrode group (97.0 ± 10.3%) than in the electrode group (88.5 ± 23.7%, P = 0.15). The rate of Engel I outcome was nonsignificantly higher in the no-electrode group (84.2%) than in the electrode group (65.0%, P = 0.17). Major complication rates were nonsignificantly higher in the no-electrode group (15.8 ± 1.9%) than in the electrode group (5.0 ± 1.1%, P = 0.26). Power analysis revealed that 74 patients would need to be included in each group to reach statistical significance.

CONCLUSIONS

Although not statistically significant, our study showed a trend for improved seizure control if a decision was made not to implant electrodes prior to potentially curative anteromesial resection. Engel I outcome in this group reached approximately 85%. A larger multi-instiutional study may be required to reach statistical significance.

Localizing targets for neuromodulation in drug-resistant epilepsy using intracranial EEG and computational model

Neuromodulation has emerged as a promising technique for the treatment of epilepsy. The target for neuromodulation is critical for the effectiveness of seizure control. About 30% of patients with drug-resistant epilepsy (DRE) fail to achieve seizure freedom after surgical intervention. It is difficult to find effective brain targets for neuromodulation in these patients because brain regions are damaged during surgery. In this study, we propose a novel approach for localizing neuromodulatory targets, which uses intracranial EEG and multi-unit computational models to simulate the dynamic behavior of epileptic networks through external stimulation. First, we validate our method on a multivariate autoregressive model and compare nine different methods of constructing brain networks. Our results show that the directed transfer function with surrogate analysis achieves the best performance. Intracranial EEGs of 11 DRE patients are further analyzed. These patients all underwent surgery. In three seizure-free patients, the localized targets are concordant with the resected regions. For the eight patients without seizure-free outcome, the localized targets in three of them are outside the resected regions. Finally, we provide candidate targets for neuromodulation in these patients without seizure-free outcome based on virtual resected epileptic network. We demonstrate the ability of our approach to locate optimal targets for neuromodulation. We hope that our approach can provide a new tool for localizing patient-specific targets for neuromodulation therapy in DRE.

Sensorimotor outcomes after resection for perirolandic drug-resistant epilepsy: a systematic review and individual patient data meta-analysis

OBJECTIVE

The prevalence of long-term postoperative sensorimotor deficits in children undergoing perirolandic resective epilepsy surgery is unclear. The risk of developing these deficits must be weighed against the potential reduction in seizure frequency after surgery. In this study, the authors investigated the prevalence of sensorimotor deficits after resective surgery at ≥ 1 year postoperatively.

METHODS

A systematic review and individual patient data meta-analysis was conducted using PubMed, Embase, and Scopus databases. Subgroups of patients were identified and categorized according to their outcomes as follows: group A patients were denoted as seizure free with no postoperative sensorimotor deficits; group B patients experienced seizure recurrence with no deficit; group C patients were seizure free with deficits; and group D patients were not seizure free and with deficits. Rates of sensory deficits were examined in patients undergoing postcentral gyrus resection, and rates of motor deficits were aggregated in patients undergoing precentral gyrus resection.

RESULTS

Of 797 articles resulting from the database searches, 6 articles including 164 pediatric patients at a mean age of 7.7 ± 5.2 years with resection for drug-resistant perirolandic epilepsy were included in the study. Seizure freedom was observed in 118 (72.9%) patients at a mean follow-up of 3.4 ± 1.8 years. In total, 109 (66.5%) patients did not develop sensorimotor deficits at last follow-up, while 55 (33.5%) had permanent deficits. Ten (14.3%) of 70 patients with postcentral gyrus resection had permanent sensory deficits. Of the postcentral gyrus resection patients, 41 (58.6%) patients were included in group A, 19 (27.1%) in group B, 7 (10.0%) in group C, and 3 (4.3%) in group D. Forty (37.7%) of 106 patients with precentral resections had permanent motor deficits. Of the precentral gyrus resection patients, 50 (47.2%) patients were in group A, 16 (15.1%) in group B, 24 (22.6%) in group C, and 16 (15.1%) in group D. Patients without focal cortical dysplasia were more likely to have permanent motor deficits relative to those with focal cortical dysplasia in the precentral surgery cohort (p = 0.02).

CONCLUSIONS

In total, 58.6% of patients were seizure free without deficit, 27.1% were not seizure free and without deficit, 10.0% were seizure free but with deficit, and 4.3% were not seizure free and with deficit. Future studies with functional and quality-of-life data, particularly for patients who experience seizure recurrence with no deficits (as in group B in the present study) and those who are seizure free with deficits (as in group C) after treatment, are necessary to guide surgical decision-making.

Stimulation induced aura during subdural recording: A useful predictor of postoperative outcome in refractory epilepsy

INTRODUCTION

Electrical cortical stimulation (ECS) is a routine procedure commonly conducted in intracranial EEG (iEEG) monitoring in refractory epilepsy and associated with postoperative outcome in stereoelectroencephalography (SEEG) exploration. To better understand this effective method, this study aimed to examine the role of ECS in subdural recording.

METHODS

The ECS results of 144 consecutive patients who were monitored via subdural electrodes and received epilepsy surgery were retrospectively collected. The occurrence of stimulation induced aura (SIA) and seizure (SIS) and their distributions as well as their associations with postoperative outcomes were analyzed.

RESULTS

Among all 144 patients, 47.2% (68/144) achieved Engel class I recovery with a mean follow-up of 6.6±2.2 years (2.0-9.8 years). The percentages of patients who showed SIA and SIS were 16.0% (23/144) and 43.8% (63/144), respectively. Our data indicated that 30.4% (42/138) of SIS occurred in frontal lobe, which was significantly higher than the 7.7% (10/130) occurred in temporal lobe and the 8.5% (11/129) in parieto-occipital region (p<0.001). Meanwhile, no such distribution difference was discovered in SIA (p=0.229). Univariate and multifactorial analyses showed that SIA was the only independent predictor for postoperative outcome and patients with SIA were 4.8 times more likely to achieve seizure-free (95% CI 1.557-14.789, p = 0.006).

CONCLUSIONS

Our study demonstrated that SIS sites are more likely to be located in the frontal lobe and SIA independently predicts optimal postoperative outcome in subdural recording.

Brain Surgery for Medically Intractable Epilepsy

This review covers the broad topic of brain surgery in the treatment of pediatric intractable epilepsy. The authors review the latest advancements in the presurgical workup as well as the mandatory tests needed to explore the epilepsy workup in these children. They describe the different types of epilepsy from a surgical standpoint (temporal, extratemporal, multifocal, and hemispheric epilepsies) and various surgical procedures that can be proposed depending on the clinical scenario: lesionectomies, lobectomies, hemispherectomies, neuromodulation, and palliative surgeries. They also describe the key differences of the pediatric patient as compared with the adult patient in such pathologic conditions.

Utility of adding electrodes in patients undergoing invasive seizure localization: A case series

Introduction

Surgery can be an effective treatment for epilepsy if the seizure onset is adequately localized. Invasive monitoring is used if noninvasive methods are inconclusive. Initial invasive monitoring may fail if the pre-surgical hypothesis regarding location of epileptic foci is wrong. At this point, a decision must be made whether to remove all electrodes without a clearly defined location of onset or to implant additional electrodes with the aim of achieving localization by expanding coverage.

Methods

Electrodes were placed according to a hypothesis derived from noninvasive monitoring techniques in adult patients with long term epilepsy. Seizure onset was not clearly localized at the end of the invasive monitoring period in ten patients, and additional electrodes were placed based on a new hypothesis that incorporated data from the invasive monitoring period.

Results

Successful localization was achieved in nine patients. There were no complications with adding additional electrodes. At final follow up, four patients were seizure free while four others had at least a 50% reduction in seizures after undergoing surgical intervention.

Conclusion

Seizure foci were localized safely in 90% of adult patients with long term epilepsy after implanting additional electrodes and expanding coverage. Patients undergoing invasive monitoring without clear localization should have additional electrodes placed to expand monitoring coverage as it is safe and effective.

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Noninvasive Detection of Hippocampal Epileptiform Activity on Scalp Electroencephalogram

Importance

The hippocampus is a highly epileptogenic brain region, yet over 90% of hippocampal epileptiform activity (HEA) cannot be identified on scalp electroencephalogram (EEG) by human experts. Currently, detection of HEA requires intracranial electrodes, which limits our understanding of the role of HEA in brain diseases.

Objective

To develop and validate a machine learning algorithm that accurately detects HEA from a standard scalp EEG, without the need for intracranial electrodes.

Design, Setting, and Participants

In this diagnostic study, conducted from 2008 to 2021, EEG data were used from patients with temporal lobe epilepsy (TLE) and healthy controls (HCs) to train and validate a deep neural network, HEAnet, to detect HEA on scalp EEG. Participants were evaluated at tertiary-level epilepsy centers at 2 academic hospitals: Massachusetts General Hospital (MGH) or Brigham and Women's Hospital (BWH). Included in the study were patients aged 12 to 78 years with a clinical diagnosis of TLE and HCs without epilepsy. Patients with TLE and HCs with a history of intracranial surgery were excluded from the study.

Exposures

Simultaneous intracranial EEG and/or scalp EEG.

Main Outcomes and Measures

Performance was assessed using cross-validated areas under the receiver operating characteristic curve (AUC ROC) and precision-recall curve (AUC PR) and additional clinically relevant metrics.

Results

HEAnet was trained and validated using data sets that were derived from a convenience sample of 141 eligible participants (97 with TLE and 44 HCs without epilepsy) whose retrospective EEG data were readily available. Data set 1 included the simultaneous scalp EEG and intracranial electrode recordings of 51 patients with TLE (mean [SD] age, 40.7 [15.9] years; 30 men [59%]) at MGH. An automatically generated training data set with 972 095 positive HEA examples was created, in addition to a held-out expert-annotated testing data set with 22 762 positive HEA examples. HEAnet's performance was validated on 2 independent scalp EEG data sets: (1) data set 2 (at MGH; 24 patients with TLE and 20 HCs; mean [SD] age, 42.3 [16.2] years; 17 men [39%]) and (2) data set 3 (at BWH; 22 patients with TLE and 24 HCs; mean [SD] age, 43.0 [14.4] years; 20 men [43%]). For single-event detection of HEA on data set 1, HEAnet achieved a mean (SD) AUC ROC of 0.89 (0.01) and a mean (SD) AUC PR of 0.39 (0.03). On external validation with data sets 2 and 3, HEAnet accurately distinguished TLE from HC (AUC ROC of 0.88 and 0.95, respectively) and predicted epilepsy lateralization with 100% and 92% accuracy, respectively. HEAnet tracked dynamic changes in HEA in response to seizure medication adjustments and performed comparably with human experts in diagnosing TLE from 1-hour scalp EEG recordings, diagnosing TLE in several individuals that experts missed. Without reducing specificity, addition of HEAnet to human expert EEG review increased sensitivity for diagnosing TLE in humans from 50% to 58% to 63% to 67%.

Conclusions and Relevance

Results of this diagnostic study suggest that HEAnet provides a novel, noninvasive, quantitative, and clinically relevant biomarker of hippocampal hyperexcitability in humans.

Surgical Treatments for Epilepsy

PURPOSE OF REVIEW

More than 20 new antiseizure medications have been approved by the US Food and Drug Administration (FDA) in the past 3 decades; however, outcomes in newly diagnosed epilepsy have not improved, and epilepsy remains drug resistant in up to 40% of patients. Evidence supports improved seizure outcomes and quality of life in those who have undergone epilepsy surgery, but epilepsy surgery remains underutilized. This article outlines indications for epilepsy surgery, describes the presurgical workup, and summarizes current available surgical approaches.

RECENT FINDINGS

Class I evidence has demonstrated the superiority of resective surgery compared to medical therapy for seizure control and quality of life in patients with drug-resistant epilepsy. The use of minimally invasive options, such as laser interstitial thermal therapy and stereotactic radiosurgery, are alternatives to resective surgery in well-selected patients. Neuromodulation techniques, such as responsive neurostimulation, deep brain stimulation, and vagus nerve stimulation, offer a suitable alternative, especially in those where resective surgery is contraindicated or where patients prefer nonresective surgery. Although neuromodulation approaches reduce seizure frequency, they are less likely to be associated with seizure freedom than resective surgery.

SUMMARY

Appropriate patients with drug-resistant epilepsy benefit from epilepsy surgery. If two well-chosen and tolerated medication trials do not achieve seizure control, referral to a comprehensive epilepsy center for a thorough presurgical workup and discussion of surgical options is appropriate. Mounting Class I evidence supports a significantly higher chance of stopping disabling seizures with surgery than with further medication trials.

Beyond rates: time-varying dynamics of high frequency oscillations as a biomarker of the seizure onset zone

Objective. High frequency oscillations (HFOs) recorded by intracranial electrodes have generated excitement for their potential to help localize epileptic tissue for surgical resection. However, the number of HFOs per minute (i.e. the HFO 'rate') is not stable over the duration of intracranial recordings; for example, the rate of HFOs increases during periods of slow-wave sleep. Moreover, HFOs that are predictive of epileptic tissue may occur in oscillatory patterns due to phase coupling with lower frequencies. Therefore, we sought to further characterize between-seizure (i.e. 'interictal') HFO dynamics both within and outside the seizure onset zone (SOZ).Approach. Using long-term intracranial EEG (mean duration 10.3 h) from 16 patients, we automatically detected HFOs using a new algorithm. We then fit a hierarchical negative binomial model to the HFO counts. To account for differences in HFO dynamics and rates between sleep and wakefulness, we also fit a mixture model to the same data that included the ability to switch between two discrete brain states that were automatically determined during the fitting process. The ability to predict the SOZ by model parameters describing HFO dynamics (i.e. clumping coefficients and coefficients of variation) was assessed using receiver operating characteristic curves.Main results. Parameters that described HFO dynamics were predictive of SOZ. In fact, these parameters were found to be more consistently predictive than HFO rate. Using concurrent scalp EEG in two patients, we show that the model-found brain states corresponded to (1) non-REM sleep and (2) awake and rapid eye movement sleep. However the brain state most likely corresponding to slow-wave sleep in the second model improved SOZ prediction compared to the first model for only some patients.Significance. This work suggests that delineation of SOZ with interictal data can be improved by the inclusion of time-varying HFO dynamics.

Higher-order tensor decomposition based scalp-to-intracranial EEG projection for detection of interictal epileptiform discharges

Objective.Interictal epileptiform discharges (IEDs) occur between two seizures onsets. IEDs are mainly captured by intracranial recordings and are often invisible over the scalp. This study proposes a model based on tensor factorization to map the time-frequency (TF) features of scalp EEG (sEEG) to the TF features of intracranial EEG (iEEG) in order to detect IEDs from over the scalp with high sensitivity.Approach.Continuous wavelet transform is employed to extract the TF features. Time, frequency, and channel modes of IED segments from iEEG recordings are concatenated into a four-way tensor. Tucker and CANDECOMP/PARAFAC decomposition techniques are employed to decompose the tensor into temporal, spectral, spatial, and segmental factors. Finally, TF features of both IED and non-IED segments from scalp recordings are projected onto the temporal components for classification.Main results.The model performance is obtained in two different approaches: within- and between-subject classification approaches. Our proposed method is compared with four other methods, namely a tensor-based spatial component analysis method, TF-based method, linear regression mapping model, and asymmetric-symmetric autoencoder mapping model followed by convolutional neural networks. Our proposed method outperforms all these methods in both within- and between-subject classification approaches by respectively achieving 84.2% and 72.6% accuracy values.Significance.The findings show that mapping sEEG to iEEG improves the performance of the scalp-based IED detection model. Furthermore, the tensor-based mapping model outperforms the autoencoder- and regression-based mapping models.

Probabilistic comparison of gray and white matter coverage between depth and surface intracranial electrodes in epilepsy

In this study, we quantified the coverage of gray and white matter during intracranial electroencephalography in a cohort of epilepsy patients with surface and depth electrodes. We included 65 patients with strip electrodes (n = 12), strip and grid electrodes (n = 24), strip, grid, and depth electrodes (n = 7), or depth electrodes only (n = 22). Patient-specific imaging was used to generate probabilistic gray and white matter maps and atlas segmentations. Gray and white matter coverage was quantified using spherical volumes centered on electrode centroids, with radii ranging from 1 to 15 mm, along with detailed finite element models of local electric fields. Gray matter coverage was highly dependent on the chosen radius of influence (RoI). Using a 2.5 mm RoI, depth electrodes covered more gray matter than surface electrodes; however, surface electrodes covered more gray matter at RoI larger than 4 mm. White matter coverage and amygdala and hippocampal coverage was greatest for depth electrodes at all RoIs. This study provides the first probabilistic analysis to quantify coverage for different intracranial recording configurations. Depth electrodes offer increased coverage of gray matter over other recording strategies if the desired signals are local, while subdural grids and strips sample more gray matter if the desired signals are diffuse.

Olfactory function in patients with temporal lobe epilepsy; correlation of functional magnetic resonance imaging for olfaction with the laterality of the epileptic focus

The olfactory function shares the same cerebral structures as those involved in the origin and propagation of focal temporal lobe seizures. Likewise, functional magnetic resonance imaging (fMRI) allows the study of olfactory function. This suggests that by quantitatively studying the olfactory function with an olfactory paradigm through fMRI it is possible to identify the functional alteration produced by the epileptic focus. The objective of the present study was to assess the olfactory function in the side of the epileptic focus in patients with mesial temporal lobe epilepsy, using fMRI for smell, and propose a non-invasive diagnostic method for patients candidates to mesial temporal lobe epilepsy surgery.

METHODS

Patients (n = 18) with clinical diagnosis of mesial temporal lobe epilepsy, refractory to pharmacological treatment: 7 patients (38.9%) with non-invasive studies consistent enough to submit them to anterior temporal lobectomy, and 11 (61.1%) patients where focal onset seizures were identified by stereoelectroencephalography (SEEG) on the left temporal lobe in 5 (27.8%) and in both temporal lobes in 2 (11.1%). Patients were evaluated using EEG, MRI, neuropsychological data, and fMRI with olfactory paradigm. Results of the fMRI were compared with the laterality of the epileptic focus determined by intracranial electroencephalogram recordings through stereotactically placed electrodes, and with post-surgical outcome at one year of follow-up.

RESULTS

fMRI showed a lower olfactory activation in 81.8% concordant with unilateral onset seizures. There were significant differences of olfactory fMRI activation between epileptic and non-epileptic foci.

CONCLUSION

Functional magnetic resonance imaging with an olfactory paradigm may be a non-invasive diagnostic tool to determine the laterality of seizure onset in the mesial temporal lobe.

A Standardized Electrode Nomenclature for Stereoelectroencephalography Applications

PURPOSE

Stereoelectroencephalography (SEEG) is widely performed on individuals with medically refractory epilepsy for whom invasive seizure localization is desired. Despite increasing adoption in many centers across the world, no standardized electrode naming convention exists, generating confusion among both clinical and research teams.

METHODS

We have developed a novel nomenclature, named the Standardized Electrode Nomenclature for SEEG Applications system. Concise, unique, informative, and unambiguous labels provide information about entry point, deep targets, and relationships between electrodes. Inter-rater agreement was evaluated by comparing original electrode names from 10 randomly sampled cases (including 136 electrodes) with those prospectively assigned by four additional blinded raters.

RESULTS

The Standardized Electrode Nomenclature for SEEG Application system was prospectively implemented in 40 consecutive patients undergoing SEEG monitoring at our institution, creating unique electrode names in all cases, and facilitating implantation design, SEEG recording and mapping interpretation, and treatment planning among neurosurgeons, neurologists, and neurophysiologists. The inter-rater percent agreement for electrode names among two neurosurgeons, two epilepsy neurologists, and one neurosurgical fellow was 97.5%.

CONCLUSIONS

This standardized naming convention, Standardized Electrode Nomenclature for SEEG Application, provides a simple, concise, reproducible, and informative method for specifying the target(s) and relative position of each SEEG electrode in each patient, allowing for successful sharing of information in both the clinical and research settings. General adoption of this nomenclature could pave the way for improved communication and collaboration between institutions.

Risk of seizure clusters and status epilepticus following rapid and ultra-rapid medication discontinuation during intracranial EEG monitoring

OBJECTIVE

Anti-seizure medications (ASMs) are discontinued in the course of intracranial EEG (iEEG) monitoring for presurgical evaluation. The ASM withdrawal facilitates an emergence of seizures but may also precipitate seizure clusters (SC) and status epilepticus (SE). The aim of this study was to compare the rates of SC and SE during the ultra-rapid withdrawal (URW) and rapid withdrawal (RW) of ASMs during iEEG.

METHODS

We performed a retrospective observational study of all consecutive patients with drug resistant epilepsy who completed iEEG at our comprehensive epilepsy center from 2012-2018. SC was defined as three or more seizures in 24 h with a return to baseline between the events. SE was defined as ≥ 5 min of clinical seizure or ≥ 10 min of ictal electrographic activity or series of seizures with no return to the neurological baseline between the events.

RESULTS

Of 107 patients who completed iEEG with intracranial grid or strip electrodes, 46 (43%) were male. Median age at the time of iEEG was 35.4 years (interquartile range [IQR], 26.4 - 44.9). Ninety patients (84.1%) had all AEDs held on admission, while 16 patients (15%) underwent a rapid taper. The median time to first seizure was 15.1 (8.2 - 22.6) h. Sixty-two patients (57.9%) developed SC, while 10 (9.4%) developed SE. Twenty-six patients (36.1%) with these complications required intravenous lorazepam or other rescue ASMs, while the remaining patients had spontaneous resolution of seizures; intubations were not required. While there were differences in the proportions in patients who experienced SC, SE, or neither in the URW and RW groups, these differences were not significant at the 0.05 alpha level.

SIGNIFICANCE

Ultra-rapid and rapid ASM withdrawal are accompanied by SC and SE the majority of which terminate spontaneously. These data support the use of either approach of the medication taper for seizure provocation in iEEG.

Robot-assisted stereoelectroencephalography electrode placement in twenty-three pediatric patients: a high-resolution analysis of individual lead placement time and accuracy at a single institution

PURPOSE

We describe a detailed evaluation of predictors associated with individual lead placement efficiency and accuracy for 261 stereoelectroencephalography (sEEG) electrodes placed for epilepsy monitoring in twenty-three children at our institution.

METHODS

Intra- and post-operative data was used to generate a linear mixed model to investigate predictors associated with three outcomes (lead placement time, lead entry error, lead target error) while accounting for correlated observations from the same patients. Lead placement time was measured using electronic time-stamp records stored by the ROSA software for each individual electrode; entry and target site accuracy was measured using postoperative stereotactic CT images fused with preoperative electrode trajectory planning images on the ROSA computer software. Predictors were selected from a list of variables that included patient demographics, laterality of leads, anatomic location of lead, skull thickness, bolt cap device used, and lead sequence number.

RESULTS

Twenty-three patients (11 female, 48%) of mean age 11.7 (± 6.1) years underwent placement of intracranial sEEG electrodes (median 11 electrodes) at our institution over a period of 1 year. There were no associated infections, hemorrhages, or other adverse events, and successful seizure capture was obtained in all monitored patients. The mean placement time for individual electrodes across all patients was 6.56 (± 3.5) min; mean target accuracy was 4.5 (± 3.5) mm. Lesional electrodes were associated with 25.7% (95% CI: 6.7-40.9%, p = 0.02) smaller target point errors. Larger skull thickness was associated with larger error: for every 1-mm increase in skull thickness, there was a 4.3% (95% CI: 1.2-7.5%, p = 0.007) increase in target error. Bilateral lead placement was associated with 26.0% (95% CI: 9.9-44.5%, p = 0.002) longer lead placement time. The relationship between placement time and lead sequence number was nonlinear: it decreased consistently for the first 4 electrodes, and became less pronounced thereafter.

CONCLUSIONS

Variation in sEEG electrode placement efficiency and accuracy can be explained by phenomena both within and outside of operator control. It is important to keep in mind the factors that can lead to better or worse lead placement efficiency and/or accuracy in order to maximize patient safety while maintaining the standard of care.

Epilepsy surgery in Africa: state of the art and challenges

OBJECTIVE

Epilepsy is an important public health problem representing 0.6% of the global burden of disease that particularly impacts people living in the lowest income countries where epilepsy incidence may be 10 fold more than in the developed world. The battery of treatments designed to counteract the clinical manifestations of this disease are various and range from a wide spectrum of antiseizure medicationand specific diets, to surgical techniques for resection of the epileptogenic focus. The aim of our study was to describe the State of the art of Epilepsy Surgery (ES) in Africa and examine ways to deal with the high surgical treatment gap.

METHODOLOGY

In an observational study, we prospectively disseminated questionnaires via email or directly administered to main epileptologists and neurologists involved in epilepsy care, in key African countries. We also conducted a literature search using PubMed, Google scholar on ES in all the African countries.

RESULTS

We received responses from the majority of African countries, which allowed us to identify 3 levels of care for ES in African countries, a first level that uses ES with invasive presurgical evaluation, a second level that uses ES but without invasive presurgical evaluation, and a third level that does not use ES, and we summarized these results on a map.

DISCUSSION

This paper studied the availability of ES as a treatment modality in several African countries. We aimed to establish optimal pathways for initiating ES with noninvasive Electroencephalography and readily available investigations. This could be achieved through collaboration with epilepsy programs in developed countries directly or by using telemedicine.

Detrended fluctuation analysis in the presurgical evaluation of parietal lobe epilepsy patients

OBJECTIVE

To examine the usability of long-range temporal correlations (LRTCs) in non-invasive localization of the epileptogenic zone (EZ) in refractory parietal lobe epilepsy (RPLE) patients.

METHODS

We analyzed 10 RPLE patients who had presurgical MEG and underwent epilepsy surgery. We quantified LRTCs with detrended fluctuation analysis (DFA) at four frequency bands for 200 cortical regions estimated using individual source models. We correlated individually the DFA maps to the distance from the resection area and from cortical locations of interictal epileptiform discharges (IEDs). Additionally, three clinical experts inspected the DFA maps to visually assess the most likely EZ locations.

RESULTS

The DFA maps correlated with the distance to resection area in patients with type II focal cortical dysplasia (FCD) (p<0.05), but not in other etiologies. Similarly, the DFA maps correlated with the IED locations only in the FCD II patients. Visual analysis of the DFA maps showed high interobserver agreement and accuracy in FCD patients in assigning the affected hemisphere and lobe.

CONCLUSIONS

Aberrant LRTCs correlate with the resection areas and IED locations.

SIGNIFICANCE

This methodological pilot study demonstrates the feasibility of approximating cortical LRTCs from MEG that may aid in the EZ localization and provide new non-invasive insight into the presurgical evaluation of epilepsy.

Gray Matter Sampling Differences Between Subdural Electrodes and Stereoelectroencephalography Electrodes

Objective: Stereoelectroencephalography (SEEG) has seen a recent increase in popularity in North America; however, concerns regarding the spatial sampling capabilities of SEEG remain. We aimed to quantify and compare the spatial sampling of subdural electrode (SDE) and SEEG implants.

Methods: Patients with drug-resistant epilepsy who underwent invasive monitoring were included in this retrospective case-control study. Ten SEEG cases were compared with ten matched SDE cases based on clinical presentation and pre-implantation hypothesis. To quantify gray matter sampling, MR and CT images were coregistered and a 2.5mm radius sphere was superimposed over the center of each electrode contact. The estimated recording volume of gray matter was defined as the cortical voxels within these spherical models. Paired t-tests were performed to compare volumes and locations of SDE and SEEG recording. A Ripley's K-function analysis was performed to quantify differences in spatial distributions.

Results: The average recording volume of gray matter by each individual contact was similar between the two modalities. SEEG implants sampled an average of 20% more total gray matter, consisted of an average of 17% more electrode contacts, and had 77% more of their contacts covering gray matter within sulci. Insular coverage was only achieved with SEEG. SEEG implants generally consist of discrete areas of dense local coverage scattered across the brain; while SDE implants cover relatively contiguous areas with lower density recording.

Significance: Average recording volumes per electrode contact are similar for SEEG and SDE, but SEEG may allow for greater overall volumes of recording as more electrodes can be routinely implanted. The primary difference lies in the location and distribution of gray matter than can be sampled. The selection between SEEG and SDE implantation depends on sampling needs of the invasive implant.

What do intracerebral electrodes measure?

OBJECTIVE

Gain insight and improve our interpretation of measurements from intracerebral electrodes. Determine if interpretation of intracerebral EEG is dependent on electrode characteristics.

METHODS

We use intracerebral EEG measurements differing only in the recording electrodes (Dixi or homemade electrodes), and numerical simulations to determine the spatial sensitivity of intracerebral electrodes and its dependence on several parameters.

RESULTS

There is a difference in the high frequency (>20 Hz) power depending on the electrode type, which cannot be explained by the different contact sizes or distance between contacts. Simulations show that the width of the gap between electrode and brain and the extent of the generators have an effect on sensitivity, while other parameters are less important.

CONCLUSIONS

The sensitivity of intracerebral electrodes is not affected in an important way by the dimensions of the contacts, but depends on the extent of generators. The unusual insertion technique of homemade electrodes resulting in a large gap between functional brain and electrodes, explains the observed signal difference.

SIGNIFICANCE

Numerical simulation is a useful tool in the choice or design of intracerebral electrodes, and increases our understanding of their measurements. The interpretation of intracerebral EEG is not affected by differences between typical commercially available electrodes.

Incorporating Uncertainty in Data Labeling into Automatic Detection of Interictal Epileptiform Discharges from Concurrent Scalp-EEG via Multi-way Analysis

Interictal epileptiform discharges (IEDs) are elicited from an epileptic brain, whereas they can also be due to other neurological abnormalities. The diversity in their morphologies, their strengths, and their sources within the brain cause a great deal of uncertainty in their labeling by clinicians. The aim of this study is therefore to exploit and incorporate this uncertainty (the probability of the waveform being an IED) in the IED detection system which combines spatial component analysis (SCA) with the IED probabilities referred to as SCA-IEDP-based method. For comparison, we also propose and study SCA-based method in which probability of the waveform being an IED is ignored. The proposed models are employed to detect IEDs in two different classification approaches: (1) subject-dependent and (2) subject-independent classification approaches. The proposed methods are compared with two other state-of-the-art methods namely, time-frequency features and tensor factorization methods. The proposed SCA-IEDP model has achieved superior performance in comparison with the traditional SCA and other competing methods. It achieved 79.9% and 63.4% accuracy values in subject-dependent and subject-independent classification approaches, respectively. This shows that considering the IED probabilities in designing an IED detection system can boost its performance.

Clinical safety of intracranial EEG electrodes in MRI at 1.5 T and 3 T: a single-center experience and literature review

PURPOSE

Intracranial electroencephalography (EEG) can be a critical part of presurgical evaluation for drug resistant epilepsy. With the increasing use of intracranial EEG, the safety of these electrodes in the magnetic resonance imaging (MRI) environment remains a concern, particularly at higher field strengths. However, no studies have reported the MRI safety experience of intracranial electrodes at 3 T. We report an MRI safety review of patients with intracranial electrodes at 1.5 and 3 T.

METHODS

One hundred and sixty-five consecutive admissions for intracranial EEG monitoring were reviewed. A total of 184 MRI scans were performed on 135 patients over 140 admissions. These included 118 structural MRI studies at 1.5 T and 66 functional MRI studies at 3 T. The magnetic resonance (MR) protocols avoided the use of high specific energy absorption rate sequences that could result in electrode heating. The intracranial implantations included 114 depth, 15 subdural, and 11 combined subdural and depth electrodes. Medical records were reviewed for patient-reported complications and radiologic complications related to these studies. Pre-implantation, post-implantation, and post-explantation imaging studies were reviewed for potential complications.

RESULTS

No adverse events or complications were seen during or after MRI scanning at 1.5 or 3 T apart from those attributed to electrode implantation. There was also no clinical or imaging evidence of worsening of pre-existing implantation-related complications after MR imaging.

CONCLUSION

No clinical or radiographic complications are seen when performing MRI scans at 1.5 or 3 T on patients with implanted intracranial EEG electrodes while avoiding high specific energy absorption rate sequences.

Minimally Invasive, Endoscopic-Assisted Device for Subdural Electrode Implantation in Epilepsy

BACKGROUND

Subdural grids and strip electrodes provide wide coverage of the cerebral cortex, precise delineation of the extent of the seizure onset zone, and improved spatial sampling to perform functional mapping for eloquent cortex.

OBJECTIVE

To describe a novel device that allows for a minimally invasive approach to implantation of subdural grid and strip electrodes.

METHODS

A skull mounted device was created to allow for implantation of subdural electrodes through a keyhole craniotomy with direct visualization using the aid of a flexible neurovideoscope. The initial studies in preparation for grid development performed on cadaveric skulls were analyzed to determine the size of craniotomy required for deployment, maximal distance of strip electrode deployment from center of craniotomy, and visual inspection of the cortex was performed for any underlying damage.

RESULTS

The device allowed for the placement of subdural electrodes through a 40-mm craniotomy. Subdural electrodes were deployed in multiple directions to a distance of a 70-mm radius from the center of the craniotomy. There was no visual damage to the underlying cortex after the procedures were completed.

CONCLUSION

Large craniotomies are typically desired to provide direct visualization of the implantation of subdural electrodes, but can increase the risk of subdural hemorrhages and infections. This study describes a novel minimally invasive endoscopically assisted device for the implantation of subdural strip electrodes under direct visualization. With this device, we are able to limit the size of the craniotomy, avoid incision through the temporalis muscle, and implant subdural electrodes with visualization of the cortex.

Cloud based ensemble machine learning approach for smart detection of epileptic seizures using higher order spectral analysis

The present paper proposes a smart framework for detection of epileptic seizures using the concepts of IoT technologies, cloud computing and machine learning. This framework processes the acquired scalp EEG signals by Fast Walsh Hadamard transform. Then, the transformed frequency-domain signals are examined using higher-order spectral analysis to extract amplitude and entropy-based statistical features. The extracted features have been selected by means of correlation-based feature selection algorithm to achieve more real-time classification with reduced complexity and delay. Finally, the samples containing selected features have been fed to ensemble machine learning techniques for classification into several classes of EEG states, viz. normal, interictal and ictal. The employed techniques include Dagging, Bagging, Stacking, MultiBoost AB and AdaBoost M1 algorithms in integration with C4.5 decision tree algorithm as the base classifier. The results of the ensemble techniques are also compared with standalone C4.5 decision tree and SVM algorithms. The performance analysis through simulation results reveals that the ensemble of AdaBoost M1 and C4.5 decision tree algorithms with higher-order spectral features is an adequate technique for automated detection of epileptic seizures in real-time. This technique achieves 100% classification accuracy, sensitivity and specificity values with optimally small classification time.

Trends in the use of automated algorithms for the detection of high-frequency oscillations associated with human epilepsy

High-frequency oscillations (HFOs) in intracranial electroencephalography (EEG) are a promising biomarker of the epileptogenic zone and tool for surgical planning. Many studies have shown that a high rate of HFOs (number per minute) is correlated with the seizure-onset zone, and complete removal of HFO-generating brain regions has been associated with seizure-free outcome after surgery. In order to use HFOs as a biomarker, these transient events must first be detected in electrophysiological data. Because visual detection of HFOs is time-consuming and subject to low interrater reliability, many automated algorithms have been developed, and they are being used increasingly for such studies. However, there is little guidance on how to select an algorithm, implement it in a clinical setting, and validate the performance. Therefore, we aim to review automated HFO detection algorithms, focusing on conceptual similarities and differences between them. We summarize the standard steps for data pre-processing, as well as post-processing strategies for rejection of false-positive detections. We also detail four methods for algorithm testing and validation, and we describe the specific goal achieved by each one. We briefly review direct comparisons of automated algorithms applied to the same data set, emphasizing the importance of optimizing detection parameters. Then, to assess trends in the use of automated algorithms and their potential for use in clinical studies, we review evidence for the relationship between automatically detected HFOs and surgical outcome. We conclude with practical recommendations and propose standards for the selection, implementation, and validation of automated HFO-detection algorithms.

Forecasting Seizure Freedom After Epilepsy Surgery Assessing Concordance Between Noninvasive and StereoEEG Findings

BACKGROUND

Accurate localization of the probable Epileptogenic Zone (EZ) from presurgical studies is crucial for achieving good prognosis in epilepsy surgery.

OBJECTIVE

To evaluate the degree of concordance at a sublobar localization derived from noninvasive studies (video electroencephalography, EEG; magnetic resonance imaging, MRI; 18-fluorodeoxyglucose positron emission tomography FDG-PET, FDG-PET) and EZ estimated by stereoEEG, in forecasting seizure recurrence in a long-term cohort of patients with focal drug-resistant epilepsy.

METHODS

We selected patients with a full presurgical evaluation and with postsurgical outcome at least 1 yr after surgery. Multivariate Cox regression analysis for seizure freedom (Engel Ia) was performed.

RESULTS

A total of 74 patients were included, 62.2% were in Engel class Ia with a mean follow-up of 2.8 + 2.4 yr after surgery. In the multivariate analysis for Engel Ia vs &gt;Ib, complete resection of the EZ found in stereoEEG (hazard ratio, HR: 0.24, 95%CI: 0.09-0.63, P = .004) and full concordance between FDG-PET and stereoEEG (HR: 0.11, 95%CI: 0.02-0.65, P = .015) portended a more favorable outcome. Most of our results were maintained when analyzing subgroups of patients.

CONCLUSION

The degree of concordance between noninvasive studies and stereoEEG may help to forecast the likelihood of cure before performing resective surgery, particularly using a sublobar classification and comparing the affected areas in the FDG-PET with EZ identified with stereoEEG.

The nature, frequency and value of stimulation induced seizures during extraoperative cortical stimulation for functional mapping

PURPOSE

The aim of this retrospective service evaluation was to determine the nature, frequency and clinical value of seizure occurrence during extraoperative direct cortical stimulation for functional mapping in patients undergoing invasive recordings (icEEG) for epilepsy surgery workup.

METHODS

We reviewed 145 sequential cases of patients with refractory focal epilepsy who underwent intracranial electrode implantation and extraoperative direct cortical stimulation (CS) for functional mapping. CS intended for mapping can elicit as a by-product electrical or electroclinical events, such as afterdischarges, subclinical EEG seizures, and stimulation-induced seizures (SIS). SIS may have habitual or non-habitual semiology (as defined by comparison to the patient's spontaneous events).

RESULTS

In our cohort, electrical (subclinical EEG seizures) or electroclinical events, (SIS) were recorded in 34.5% (50/145) patients during CS. SIS occurred in 23.4% (34/145) of all patients, of which over half were habitual SIS (SIS_hab). In most cases the location of contacts eliciting habitual SIS originated from the same location as the spontaneous ictal onset zone in icEEG. Of those with SIS _hab undergoing surgery (n = 13), seizure freedom was achieved in 61.5%, and of those with SIS_NH undergoing surgery (n = 10), 40% became seizure free (ns).

CONCLUSIONS

Electroclinical SIS occur in about a quarter of CS for functional mapping; SIS are habitual in the majority of cases, and where elicited, SIS in icEEG could be an additional diagnostic tool to localize the seizure onset zone. However, a significant minority of stimulations lead to non-habitual SIS.

Intracranial EEG in the 21st Century

Intracranial electroencephalography (iEEG) has been the mainstay of identifying the seizure onset zone (SOZ), a key diagnostic procedure in addition to neuroimaging when considering epilepsy surgery. In many patients, iEEG has been the basis for resective epilepsy surgery, to date still the most successful treatment for drug-resistant epilepsy. Intracranial EEG determines the location and resectability of the SOZ. Advances in recording and implantation of iEEG provide multiple options in the 21st century. This not only includes the choice between subdural electrodes (SDE) and stereoelectroencephalography (SEEG) but also includes the implantation and recordings from microelectrodes. Before iEEG implantation, especially in magnetic resonance imaging -negative epilepsy, a clear hypothesis for seizure generation and propagation should be based on noninvasive methods. Intracranial EEG implantation should be planned by a multidisciplinary team considering epileptic networks. Recordings from SDE and SEEG have both their advantages and disadvantages. Stereo-EEG seems to have a lower rate of complications that are clinically significant, but has limitations in spatial sampling of the cortical surface. Stereo-EEG can sample deeper areas of the brain including deep sulci and hard to reach areas such as the insula. To determine the epileptogenic zone, interictal and ictal information should be taken into consideration. Interictal spiking, low frequency slowing, as well as high frequency oscillations may inform about the epileptogenic zone. Ictally, high frequency onsets in the beta/gamma range are usually associated with the SOZ, but specialized recordings with combined macro and microelectrodes may in the future educate us about onset in higher frequency bands. Stimulation of intracranial electrodes triggering habitual seizures can assist in identifying the SOZ. Advanced computational methods such as determining the epileptogenicity index and similar measures may enhance standard clinical interpretation. Improved techniques to record and interpret iEEG may in the future lead to a greater proportion of patients being seizure free after epilepsy surgery.

Stimulation Mapping Using Stereoelectroencephalography: Current and Future Directions

Electrical stimulation mapping (ESM) using stereoelectroencephalography (SEEG) is an essential component in the workup of surgical epilepsy. Since the initial application of ESM in the mid-1960s, it remains unparalleled in defining eloquent brain areas and delimiting seizure foci for the purposes of surgical planning. Here, we briefly review the current state of SEEG stimulation, with a focus on the techniques used for identifying the epileptogenic zone and eloquent cortex. We also summarize clinical data on the efficacy of SEEG stimulation in surgical outcomes and functional mapping. Finally, we briefly highlight future applications of SEEG ESM, including novel functional mapping approaches, identifying rare seizure semiologies, neurophysiologic investigations for understanding cognitive function, and its role in SEEG-guided radiofrequency thermal coagulation.

Cerebral Palsy: Current Opinions on Definition, Epidemiology, Risk Factors, Classification and Treatment Options

Cerebral palsy (CP) is one of the most frequent causes of motor disability in children. According to the up-to-date definition, CP is a group of permanent disorders of the development of movement and posture, causing activity limitations that are attributed to non-progressive disturbances that occurred in the developing foetal or infant brain. The CP definition has evolved over time; the problem is aetiologically and clinically very heterogeneous. According to European data, the average frequency of CP is 2.08 per 1000 live births, but in the group of children born with a body weight below 1500 g, the frequency is 70 times higher when compared with the group of children with a body weight over 2500 g at birth. The risk factors for CP can be divided into pre-conception, prenatal, perinatal and postnatal ones. CP commonly co-exists with epilepsy, in particular drug-resistant epilepsy, but also with mental retardation, visual and hearing impairment, as well as feeding and behavioral disorders. The degree of motor problem varies from mild to very severe making the child totally dependent on caregivers. Cerebral palsy is divided into forms depending on the type of motor disorders which dominate the clinical presentation; the traditional classifications by Ingram and Hagberg have now been replaced by the Surveillance of Cerebral Palsy in Europe classification which divides CP into spastic, dyskinetic and ataxic forms. Although cerebral palsy is a clinical diagnosis, modern diagnostic imaging provides information that allows the division of the results of magnetic resonance imaging in children with cerebral palsy into five groups according to the magnetic resonance imaging classification system. Just as the clinical presentation and the factors predisposing for CP are very diverse, treatment is also a very complex problem. Modern treatment of spasticity includes both botulinum toxin therapies and surgical techniques, eg, rhizotomy. The authors present current views on definitions, risk factors, diagnostics and treatment of CP as well as comorbid problems, eg, drug-resistant epilepsy.

Electroencephalography in Epilepsy Evaluation

PURPOSE OF REVIEW

Epilepsy is a heterogeneous disorder that is often associated with abnormal electroencephalogram (EEG) findings. This article provides an overview of common EEG findings in epileptic disorders. The physiologic basis of EEG and intracranial EEG studies is also discussed.

RECENT FINDINGS

EEG is widely used in clinical practice. Because of the paroxysmal nature of seizure disorders, interictal epileptiform discharges, such as spikes and sharp waves, are often used to support the diagnosis of epilepsy when a habitual seizure is not captured by EEG. Interictal and ictal EEG findings also underlie the classification of seizures and epilepsy. Continuous critical care EEG monitoring has become an invaluable study in the diagnosis and treatment of subclinical seizures and nonconvulsive status epilepticus. Intracranial EEG with subdural or intraparenchymal electrodes is warranted when localization of the seizure focus and mapping of eloquent brain areas are required to plan epilepsy surgery.

SUMMARY

The EEG is a key tool in the diagnosis of epilepsy. Interictal and ictal EEG findings are crucial for the confirmation and classification of seizure disorders. Intracranial EEG monitoring is also indispensable for planning surgery for some patients.