Epileptic brain imaging by source localization CLARA supported by ictal-based semiology and VEEG in resource-limited settings

Video Electroencephalography (VEEG) is crucial for presurgical evaluation of Drug Refractory Epilepsy (DRE). The yield of VEEG in large volume centers, particularly those situated in Low-and Middle-Income countries (LMIC) is not well studied. We studied 1200 adults with drug resistant focal epilepsy whose seizures were recorded during VEEG in the epilepsy monitoring unit. VEEG review and analysis was done independently by trained epileptologists. Video EEG and MRI data were examined for concordance in order to generate a hypothesis for the presumed epileptogenic zone. Analysis of seizure semiology provided information on the symptomatogenic zone in most cases except for 33 (2.75%) patients. A total of 1050 (87.5%) patients showed interictal epileptiform discharges (IEDs) with most (58.3%) showing unilateral IEDs. Most patients (n = 1162, 96.83%) showed ictal EEG discharges of which 951(81.8%) had unilateral ictal onset. Abnormal MRI was seen in 978 (81.5%) patients. Concordance of electroclinical data obtained by analysis of VEEG with MRI abnormality could be established in most patients (63%). Concordance was higher for patients with ictal onset from temporal regions (83.71%) as compared to posterior cortex (55.4%) and frontal regions (43.5%.) CONCLUSION: This study highlights the high yield of VEEG in phase 1 presurgical evaluation in DRE. Systematic evaluation of data from VEEG provided lateralizing and localizing information in most cases. Concordance between VEEG and MRI findings was noted in most patients. These findings support steps to increase referral for pre-surgical evaluation in DRE.

Magnetoencephalography (MEG) could be a valuable tool in the presurgical evaluation of drug-resistant epilepsy (DRE), especially when the initial evaluation is inconclusive. In this retrospective study, we describe the profile of MEG in patients with DRE and normal magnetic resonance imaging (MRI). We included patients with focal epilepsy and normal MRI who underwent presurgical evaluation for DRE. MEG profiles of these patients, including the frequency of spikes, density of clusters, number of clusters, and concordance with video electroencephalography (VEEG), were analyzed. Of the 73 patients included, magnetic source imaging (MSI) provided localizing information in 51 (69.9%) patients. Among patients with localizing MEG findings, localizing information on VEEG too was noted in 42 (57.5% of the whole cohort). Thirty-one (42.5%) patients had concordant findings with region-specific localization, six (8.2%) patients had partial concordance, and five (6.8%) subjects showed discordant findings. There was a moderate agreement for the presumed epileptogenic zone in comparing findings derived from MEG and VEEG (kappa value of 0.451, P < 0.001). The agreement was lower when MEG localized to the frontal lobe (kappa value of 0.379, P = 0.001) than the temporal lobe (kappa value 0.442, P = 0.002). MEG can provide localizing information in most patients with a normal MRI. A moderate degree of agreement between localization by MEG and VEEG was noted. These findings highlight the usefulness of MSI in the presurgical evaluation of MRI-negative DRE.

Although the role of sleep in modulating epileptic activity is well established, many epileptologists overlook the significance of considering sleep during presurgical epilepsy evaluations in cases of drug-resistant epilepsy. Here, we conducted a comprehensive literature review from January 2000 to May 2023 using the PubMed electronic database and compiled evidence to highlight the need to revise the current clinical approach. All articles were assessed for eligibility by two independent reviewers. Our aim was to shed light on the clinical value of incorporating sleep monitoring into presurgical evaluations with stereo-electroencephalography. We present the latest developments on the important bidirectional interactions between sleep and various forms of epileptic activity observed in stereo-electroencephalography recordings. Specifically, epileptic activity is modulated by different sleep stages, peaking in non-rapid eye movement sleep, while being suppressed in rapid eye movement sleep. However, this modulation can vary across different brain regions, underlining the need to account for sleep to accurately pinpoint the epileptogenic zone during presurgical assessments. Finally, we offer practical solutions, such as automated sleep scoring algorithms using stereo-electroencephalography data alone, to seamlessly integrate sleep monitoring into routine clinical practice. It is hoped that this review will provide clinicians with a readily accessible roadmap to the latest evidence concerning the clinical utility of sleep monitoring in the context of stereo-electroencephalography and aid the development of therapeutic and diagnostic strategies to improve patient surgical outcomes.

Corpus callosotomy: A palliative therapeutic technique may help identify resectable epileptogenic foci

Genomics in the presurgical epilepsy evaluation

Patients with epilepsy caused by mid-grade and high-grade tumors do not usually undergo formal presurgical epilepsy evaluations before tumor resection. However, a minority of these patients may benefit significantly from just such a structured presurgical evaluation especially when seizure freedom or seizure reduction is a surgical aim in addition to total tumor resection. Typical cases comprise patients with multifocal tumors, tumors with bilateral extension, tumors over eloquent cortex, and the need for differentiation of spells of an uncertain nature, for example, epileptic versus psychogenic nonepileptic seizures. If they are epileptic, the definition of the epileptic lesion versus the epileptogenic zone and eloquent cortex can be another reason for monitoring. In addition to noninvasive recordings, invasive studies that use subdural or depths electrodes can be of special importance in these patients, leading to an exact delineation of the epileptogenic zone, usually extending beyond the epileptic lesion, and allow safe differentiation of epileptic from eloquent cortex.

Magnetoencephalography: at the forefront of optimizing epilepsy surgery

F OR NEUROSURGICAL and presurgical epilepsy evaluations, localization of eloquent cortical functions is imperative in predicting the postsurgical outcome. In the case of presurgical epilepsy evaluations, localization of language and memory is an important factor in determining whether further presurgical evaluation is needed, whether intraoperative or extraoperative electrocorticography is indicated, and whether the patient is a suitable surgical candidate at all. The decades-old gold standard has been the intracarotid amobarbital procedure (IAP), or the Wada test. Functional magnetic resonance imaging (fMRI) is a newer, relatively safe neuroradiological technique for localization of cortical function. Although fMRI is a widely used research tool, it has increasingly been used in clinical settings as a technique for presurgical cortical localization. Because it is noninvasive, fMRI has multiple possible advantages compared with the IAP. Is the Wada test, therefore, replaceable? As the following concerns demonstrate, not yet.

Epilepsy is caused by abnormal electrical discharges (clinically identified by electrophysiological recording) in a specific part of the brain [originating in only one part of the brain, namely, the epileptogenic zone (EZ)]. Epilepsy is now defined as an archetypical hyperexcited neural network disorder. It can be investigated through the network analysis of interictal discharges, ictal discharges, and resting-state functional connectivity. Currently, there is an increasing interest in embedding resting-state connectivity analysis into the preoperative evaluation of epilepsy. Among the various neuroimaging technologies employed to achieve brain functional networks, magnetoencephalography (MEG) with the excellent temporal resolution is an ideal tool for estimating the resting-state connectivity between brain regions, which can reveal network abnormalities in epilepsy. What value does MEG resting-state functional connectivity offer for epileptic presurgical evaluation? Regarding this topic, this paper introduced the origin of MEG and the workflow of constructing source–space functional connectivity based on MEG signals. Resting-state functional connectivity abnormalities correlate with epileptogenic networks, which are defined by the brain regions involved in the production and propagation of epileptic activities. This paper reviewed the evidence of altered epileptic connectivity based on low- or high-frequency oscillations (HFOs) and the evidence of the advantage of using simultaneous MEG and intracranial electroencephalography (iEEG) recordings. More importantly, this review highlighted that MEG-based resting-state functional connectivity has the potential to predict postsurgical outcomes. In conclusion, resting-state MEG functional connectivity has made a substantial progress toward serving as a candidate biomarker included in epileptic presurgical evaluations.

The objective of the multimodality presurgical evaluation in patients with refractory epilepsy is to establish sufficient concordance among the various investigations. There should be maximum overlap in the epileptogenic zone, the irritative zone, the ictal onset zone, the functional deficit zone and the symptomatogenic zone. The ictal and interictal electroencephalogram measures the localization of epileptiform discharges, which should be concordant with structural abnormalities noted on MRI brain and functional abnormalities in the form of a zone of hypometabolism on fluorodeoxyglucose positron emission tomography, interictal single photon emission computerized tomography (SPECT) or hyperperfusion of the epileptogenic zone on ictal SPECT for a good surgical outcome. There should be no conflicting data from any of these studies, neuropsychological evaluation or seizure semiology.

Surgery is recognized worldwide as a rational option for drug-resistant epilepsy; however, it requires accurate localization of the epileptogenic zone (EZ). Magnetic resonance imaging (MRI) has dramatically changed presurgical evaluation in epilepsy. Nevertheless, MRI-negative cases still account for up to 25 % of all patients exposed to presurgical evaluation. Moreover, the absence of an MRI lesion renders accurate seizure focus localization more difficult and usually corresponds to a poorer outcome in epilepsy surgery, both for temporal and extratemporal epilepsies. Single perfusion photon emission computed tomography (SPECT) and 18F-FDG positron emission tomography (18F-FDG PET) have significantly changed presurgical epilepsy evaluation in nonlesional cases. Source analysis based on electrophysiological information, using either electroencephalography (EEG) or magnetoencephalography (MEG), has as much potential as SPECT and PET in the presurgical evaluation of epilepsy patients. In this chapter we aim to review the value of nuclear medicine neuroimaging and how the addition of source analysis based on electrophysiological information (EEG/MEG) improves EZ localization in drug-resistant nonlesional focal epilepsy, with a significant positive impact on surgery outcome.

Presurgical evaluation of temporal lobe epilepsy: Is an outpatient prolonged ambulatory EEG study sufficient to recommend a surgical resection?

About 23 million people worldwide suffer from medically refractory epilepsy. Surgery might be the best treatment option with a reasonable chance of seizure freedom. Surgical success depends on the exact definition of the epileptogenic zone (EZ). Magnetoencephalography (MEG) is one of the newer additions to the noninvasive presurgical work-up. This study gives an overview of the impact of MEG on the management of epilepsy patients, focusing on (1) the influence on presurgical evaluation, (2) the identification of patients with the greatest benefit, and (3) possible surgical outcome predictors. An extensive Medline literature search was conducted for studies published from 1990. MEG is in clinical use in the presurgical evaluation of epilepsies for the identification of the EZ and outcome prediction. In cases of failed surgery, it serves as a means to locate the remaining epileptogenic cortex. The usefulness of MEG has been reported for a wide range of localizations including challenging areas like the insula. In cases of multiple possible culprit lesions, MEG can mark the epileptogenic lesion, whereas in cases of nonlesional magnetic resonance imaging (MRI) findings, MEG can pinpoint a lesional or nonlesional epileptogenic cortex area. The role of MEG in the presurgical evaluation of epilepsy was shown with rates of modified approaches in 20–35% of cases. This holds true especially for cases with extratemporal epilepsy. The value of MEG source localization is highest in extratemporal epilepsy, in MRI-negative or multilesional cases, if other modalities yield contradictory or inconclusive results, or in cases of suspected multifocal epilepsy. There is clear evidence that MEG yields nonredundant information and influences the therapeutic course of patients. Various patient groups likely to benefit from MEG were identified. Considering the poor chances of seizure freedom with continued medical treatment, these patients should not be denied source localization, which could result in surgery with favorable outcomes.

Background:For patients with drug-resistant focal epilepsy (DRE), surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures. Accurate localization of the EZ is crucial and is typically achieved through comprehensive presurgical approaches such as seizure semiology interpretation, electroencephalography (EEG), magnetic resonance imaging (MRI), and intracranial EEG (iEEG). However, interpreting seizure semiology poses challenges because it relies heavily on expert knowledge and is often based on inconsistent and incoherent descriptions, leading to variability and potential limitations in presurgical evaluation. To overcome these challenges, advanced technologies like large language models (LLMs)—with ChatGPT being a notable example—offer valuable tools for analyzing complex textual information, making them well-suited to interpret detailed seizure semiology descriptions and assist in accurately localizing the EZ.Objective:This study evaluates the clinical value of ChatGPT in interpreting seizure semiology to localize EZs in presurgical assessments for patients with focal epilepsy and compares its performance with epileptologists.Methods:Two data cohorts were compiled: a publicly sourced cohort consisting of 852 semiology-EZ pairs from 193 peer-reviewed journal publications and a private cohort of 184 semiology-EZ pairs collected from Far Eastern Memorial Hospital (FEMH) in Taiwan. ChatGPT was evaluated to predict the most likely EZ locations using two prompt methods: zero-shot prompting (ZSP) and few-shot prompting (FSP). To compare ChatGPT’s performance, eight epileptologists were recruited to participate in an online survey to interpret 100 randomly selected semiology records. The responses from ChatGPT and the epileptologists were compared using three metrics: regional sensitivity (RSens), weighted sensitivity (WSens), and net positive inference rate (NPIR).Results:In the publicly sourced cohort, ChatGPT demonstrated high RSens reliability, achieving 80–90% for the frontal and temporal lobes, 20–40% for the parietal lobe, occipital lobe, and insular cortex, and only 3% for the cingulate cortex. The WSens, which accounts for biased data distribution, consistently exceeded 67%, while the mean NPIR remained around 0. These evaluation results based on the private FEMH cohort are consistent with those from the publicly sourced cohort. A group t-test with 1000 bootstrap samples revealed that ChatGPT-4 significantly outperformed epileptologists in RSens for commonly represented EZs, such as the frontal and temporal lobes (p < 0.001). Additionally, ChatGPT-4 demonstrated superior overall performance in WSens (p < 0.001). However, no significant differences were observed between ChatGPT and the epileptologists in NPIR, highlighting comparable performance in this metric.Conclusions:ChatGPT demonstrated clinical value as a tool to assist the decision-making in the epilepsy preoperative workup. With ongoing advancements in LLMs, it is anticipated that the reliability and accuracy of LLMs will continue to improve in the future.

For patients with drug-resistant focal epilepsy, surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures. Accurate localization of the EZ is crucial and is typically achieved through comprehensive presurgical approaches such as seizure semiology interpretation, electroencephalography (EEG), magnetic resonance imaging (MRI), and intracranial EEG (iEEG). However, interpreting seizure semiology is challenging because it heavily relies on expert knowledge. The semiologies are often inconsistent and incoherent, leading to variability and potential limitations in presurgical evaluation. To overcome these challenges, advanced technologies like large language models (LLMs)-with ChatGPT being a notable example-offer valuable tools for analyzing complex textual information, making them well-suited to interpret detailed seizure semiology descriptions and accurately localize the EZ. This study evaluates the clinical value of ChatGPT for interpreting seizure semiology to localize EZs in presurgical assessments for patients with focal epilepsy and compares its performance with that of epileptologists. We compiled 2 data cohorts: a publicly sourced cohort of 852 semiology-EZ pairs from 193 peer-reviewed journal publications and a private cohort of 184 semiology-EZ pairs collected from Far Eastern Memorial Hospital (FEMH) in Taiwan. ChatGPT was evaluated to predict the most likely EZ locations using 2 prompt methods: zero-shot prompting (ZSP) and few-shot prompting (FSP). To compare the performance of ChatGPT, 8 epileptologists were recruited to participate in an online survey to interpret 100 randomly selected semiology records. The responses from ChatGPT and epileptologists were compared using 3 metrics: regional sensitivity (RSens), weighted sensitivity (WSens), and net positive inference rate (NPIR). In the publicly sourced cohort, ChatGPT demonstrated high RSens reliability, achieving 80% to 90% for the frontal and temporal lobes; 20% to 40% for the parietal lobe, occipital lobe, and insular cortex; and only 3% for the cingulate cortex. The WSens, which accounts for biased data distribution, consistently exceeded 67%, while the mean NPIR remained around 0. These evaluation results based on the private FEMH cohort are consistent with those from the publicly sourced cohort. A group t test with 1000 bootstrap samples revealed that ChatGPT-4 significantly outperformed epileptologists in RSens for the most frequently implicated EZs, such as the frontal and temporal lobes (P<.001). Additionally, ChatGPT-4 demonstrated superior overall performance in WSens (P<.001). However, no significant differences were observed between ChatGPT and the epileptologists in NPIR, highlighting comparable performance in this metric. ChatGPT demonstrated clinical value as a tool to assist decision-making during epilepsy preoperative workups. With ongoing advancements in LLMs, their reliability and accuracy are anticipated to improve.