The evolution of stereoelectroencephalography: symbiotic progress in medical imaging and procedural technologies

Stereoelectroencephalography (sEEG) was pioneered in France, at a time when cerebral anatomy was invisible to contemporaneous imaging modalities. Epilepsy surgeons relied on indirect targeting techniques to identify epileptogenic tissue. Since then, alongside the rapid rise of medical imaging technology, sEEG has experienced dramatic stepwise progress. A flurry of advancements has pushed this technique to its current-day standards, enabling neurosurgeons to access any intracranial location in a safe, highly precise, and expeditious manner. Presently, epilepsy surgeons throughout the world apply robot-assisted sEEG. Herein, the authors chronicle this incredible evolution.

Desynchronization of neuronal firing in multiparameter ultrasound stimulation

Low-intensity transcranial ultrasound stimulation, a novel neuromodulation technique, that possesses the advantages of non-invasiveness, high penetration depth, and high spatial resolution, has achieved positive neuromodulation effects in animal studies. But the regulatory mechanism remains controversial. The intramembrane cavitation effect is considered one of the mechanisms for ultrasound neuromodulation. In this study, the modified equations of ultrasonic cavitation bubble dynamics were coupled with the dual-coupled neuron Hindmarsh-Rose model, small-world neural network model, and the Jansen-Rit neural mass model, which simulate simple coupled neurons, complex neuronal networks, and discharge signals in epileptic disorders respectively. The results demonstrated that ultrasound stimulation has an appreciable modulatory effect on neuronal firing desynchronization in Hindmarsh-Rose model and small-world neural network model. The desynchronization effect is related to the stimulation frequency and intensity. Furthermore, ultrasound stimulation has an inhibitory effect on epileptic seizures, and the effect is enhanced by increasing ultrasound frequency from 0.1-1.0 MHz. This is the first combination of ultrasonic intramembrane cavitation effect theory with neurons and neural network firing desynchronization, which can provide guidance of parametric and theories support for the studies of neurological diseases such as epilepsy and Parkinson's disease.

Ex Vivo Calcium Imaging for Drosophila Model of Epilepsy

Epilepsy is a neurological disorder characterized by recurrent seizures, partially correlated with genetic origin, affecting over 70 million individuals worldwide. Despite the clinical importance of epilepsy, the functional analysis of neural activity in the central nervous system is still to be developed. Recent advancements in imaging technology, in combination with stable expression of genetically encoded calcium indicators, such as GCaMP6, have revolutionized the study of epilepsy at both brain-wide and single-cell resolution levels. Drosophila melanogaster has emerged as a tool for investigating the molecular and cellular mechanisms underlying epilepsy due to its sophisticated molecular genetics and behavioral assays. In this study, we present a novel and efficient protocol for ex vivo calcium imaging in GCaMP6-expressing adult Drosophila to monitor epileptiform activities. The whole brain is prepared from cac, a well-known epilepsy gene, knockdown flies for calcium imaging with a confocal microscope to identify the neural activity as a follow-up to the bang-sensitive seizure-like behavior assay. The cac knockdown flies showed a higher rate of seizure-like behavior and abnormal calcium activities, including more large spikes and fewer small spikes than wild-type flies. The calcium activities were correlated to seizure-like behavior. This methodology serves as an efficient methodology in screening the pathogenic genes for epilepsy and exploring the potential mechanism of epilepsy at the cellular level.

The clinical application of neuro-robot in the resection of epileptic foci: a novel method assisting epilepsy surgery

During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying and resecting MRI-negative or deep-seated epileptic foci. Here, we present a neuro-robotic navigation system that is specifically designed for resection of MRI negative epileptic foci. We recruited 52 epileptic patients, and randomly assigned them to treatment group with either neuro-robotic navigation or conventional neuronavigation system. For each patient, in the neuro-robotic navigation group, we integrated multimodality imaging including MRI and PET-CT into the robotic workstation and marked the boundary of foci from the fused image. During surgery, this boundary was delineated by the robotic laser device with high accuracy, guiding resection for the surgeon. For deeply seated foci, we exploited the neuro-robotic navigation system to localize the deepest point with biopsy needle insertion and methylene dye application to locate the boundary of the foci. Our results show that, compared with the conventional neuronavigation, the neuro-robotic navigation system performs equally well in MRI positive epilepsy patients (ENGEL I ratio: 71.4% vs 100%, p = 0.255) systems and show better performance in patients with MRI-negative focal cortical dysplasia (ENGEL I ratio: 88.2% vs 50%, p = 0.0439). At present, there are no documented neurosurgery robots with similar function and application in the field of epilepsy. Our research highlights the added value of using neuro-robotic navigation systems in resection surgery for epilepsy, particularly in cases that involve MRI-negative or deep-seated epileptic foci.

Ictal crying in epileptic seizures and psychogenic nonepileptic seizures: What are the hints to differentiate them?

OBJECTIVES

Ictal crying (IC) is a quite rare semiological manifestation of epileptic seizures (ESs) and it has been mostly reported in psychogenic nonepileptic seizures (PNESs). However, labeling IC as a pathognomonic sign of PNES can be harmful. We first aimed to investigate IC frequency in ES and PNES and highlight the differences of IC between ES and PNES. Secondly, we aimed to analyze etiology, detailed semiology, treatment options, and outcome of patients with IC in ES in more detail.

METHODS

We retrospectively screened all video-EEG monitoring unit reports from Hacettepe University Hospitals' Epilepsy Center over a 20-year period (1996-2017) for the diagnosis of IC. We included the patients with IC who had at least one documented seizure. Patients who had IC with both facial expression and vocalization compatible with crying with or without weeping and subjective feeling of sadness, were included in the study. We classified patients with IC as ES and PNES. Demographic, historical, clinical, neuroimaging, electrophysiological parameters, video-EEG data, treatment options, and prognosis of all patients were recorded. Demographic, clinical, and video-EEG data were compared between ES and PNES.

RESULTS

During the study period, 1983 patients were investigated. Six patients (all female) with ES and 37 patients (33 female) with PNES were identified. When we compared patients with PNES and ES with IC, the number of ASMs taken and duration of disease were significantly higher in patients with ES than PNES. Longer duration of seizure, longer duration of crying component, late onset of crying component in seizure, early responsiveness after seizure, not occurring during sleep, accompanied by eye closure and weeping, were found significantly higher in patients with PNES. Besides, if we analyze ES group in more detail, all had medical treatment refractory focal epilepsy and two of them whose IC was seen as an early semiological manifestation of their seizures had good outcome after nondominant anterior temporal lobectomy (ATL)+amygdalohippocampectomy (AH). However, three patients had various cortical lesions apart from temporal lobe on MRI and one patient had focal epilepsy with frontal lobe semiology with negative MRI.

CONCLUSION

Although the most common etiology for IC is PNES and it is rarely seen in ES, it can be harmful to label ictal crying as a pathognomonic sign for PNES. We proposed that there are some semiological differences in terms of IC between PNES and ES. These differences may help to distinguish IC in PNES and ES in daily practice. Moreover, it can be speculated that nondominant temporal lobe involvement may be associated with IC in ES.

Clinical Course May Be Independent from Neuroimaging in DEPDC-5-Related Epilepsy

DEPDC5 is an upstream repressor of the mechanistic target of rapamycin pathway via the GATOR-1 complex. Pathogenic variants causing loss of function typically result in familial focal epilepsy with variable foci. Neuroimaging may either be normal or show brain malformations. Lesional and nonlesional cases may be present within the same family. Here, we describe a parent-child dyad affected by a truncating DEPDC5 pathogenic variant (c.727C > T; p.Arg243*), analyze the epilepsy clinical course, and describe neuroimaging characteristics from a 3T brain magnetic resonance imaging. Despite sharing the same variant, patients diverged both in terms of epilepsy severity and neuroimaging features. Surprisingly, the mother is still suffering from drug-resistant seizures and has normal neuroimaging, while the child has been experiencing prolonged seizure freedom notwithstanding a bottom-of-sulcus focal cortical dysplasia. An increasing gradient of severity has been proposed for families with GATOR1-related epilepsies. We confirm clinical and neuroradiological expressivities are variable and also suggest the prognostication of epilepsy outcome may be particularly difficult. The epilepsy outcome could partially be independent from brain structural abnormalities.

Cost-effectiveness of HARNESS-MRI protocol in focal drug-resistant epilepsy in a limited-resources country: An Egyptian study

OBJECTIVES

The international league against epilepsy (ILAE) recommended the harmonized neuroimaging of epilepsy structural sequences (HARNESS-MRI) to improve the detection of epileptogenic lesions in patients with focal drug-resistant epilepsy (DRE). The application of this protocol is still limited in low-resource countries, mainly due to apparent high costs. We aimed to evaluate the cost-effectiveness of the HARNESS-MRI protocol in Egypt and highlighted our experience.

METHODS

Patients diagnosed with focal DRE at Cairo University epilepsy clinic underwent both conventional MRI (c-MRI) and HARNESS-MRI. Electro-clinical data were collected and analyzed. After the radiologists' initial diagnosis, a multidisciplinary team re-evaluated the MRI. Lesion detection rate and cost for detecting an extra lesion by HARNESS-MRI protocol were calculated.

RESULTS

The study included 230 patients with focal DRE (146, 62% males and 91, 38% females), with a mean age of 20.5 years. Epileptogenic lesions detected by c-MRI and HARNESS-MRI before and after the board meeting were 40, 106, and 131 lesions, respectively (P < 0.001). Sixty-nine percent of the lesions detected by HARNESS-MRI were missed on c-MRI; most commonly were mesial temporal sclerosis (MTS) and Malformations of cortical development (MCDs). Thirty-seven MTS and 32 MCDs were detected with HARNESS-MRI, compared to only 6 and 3, respectively, detected on c-MRI (P < 0.001). HARNESS-MR protocol is more cost-effective than c-MRI in detecting MRI lesions; it can save about 42$ for detecting an extra lesion in MRI.

CONCLUSION

The HARNESS-MRI protocol was cost-effective and highly recommended even in limited-resource countries for patients with focal DRE.

Utility of Gadolinium-Based Contrast in Initial Evaluation of Seizures in Children Presenting Emergently

BACKGROUND AND PURPOSE

The frequency and utility of gadolinium in evaluation of acute pediatric seizure presentation is not well known. The purpose of this study was to assess the utility of gadolinium-based contrast agents in MR imaging performed for the evaluation of acute pediatric seizure presentation.

MATERIALS AND METHODS

We identified consecutive pediatric patients with new-onset seizures from October 1, 2016, to September 30, 2021, who presented to the emergency department and/or were admitted to the inpatient unit and had an MR imaging of the brain for the evaluation of seizures. The clinical and imaging data were recorded, including the patient's age and sex, the use of IV gadolinium, and the underlying cause of epilepsy when available.

RESULTS

A total of 1884 patients were identified for inclusion. Five hundred twenty-four (28%) patients had potential epileptogenic findings on brain MR imaging, while 1153 (61%) patients had studies with normal findings and 207 (11%) patients had nonspecific signal changes. Epileptogenic findings were subclassified as the following: neurodevelopmental lesions, 142 (27%); intracranial hemorrhage (traumatic or germinal matrix), 89 (17%); ischemic/hypoxic, 62 (12%); hippocampal sclerosis, 44 (8%); neoplastic, 38 (7%); immune/infectious, 20 (4%); phakomatoses, 19 (4%); vascular anomalies, 17 (3%); metabolic, 3 (<1%); and other, 90 (17%). Eight hundred seventy-four (46%) patients received IV gadolinium. Of those, only 48 (5%) cases were retrospectively deemed to have necessitated the use of IV gadolinium: Fifteen of 48 (31%) cases were subclassified as immune/infectious, while 33 (69%) were neoplastic. Of the 1010 patients with an initial noncontrast study, 15 (1.5%) required repeat MR imaging with IV contrast to further evaluate the findings.

CONCLUSIONS

Gadolinium contrast is of limited additive benefit in the imaging of patients with an acute onset of pediatric seizures in most instances.

Evaluating the concordance of functional MRI-based language lateralization and Wada testing in epilepsy patients: A single-center analysis

BACKGROUND

For patients with drug-resistant epilepsy, surgery may be effective in controlling their disease. Surgical evaluation may involve localization of the language areas using functional magnetic resonance imaging (fMRI) or Wada testing. We evaluated the accuracy of task-based fMRI versus Wada-based language lateralization in a cohort of our epilepsy patients.

METHODS

In a single-center, retrospective analysis, we identified patients with medically intractable epilepsy who participated in presurgical language mapping (n = 35) with fMRI and Wada testing. Demographic variables and imaging metrics were obtained. We calculated the laterality index (LI) from task-evoked fMRI activation maps across language areas during auditory and reading tasks to determine lateralization. Possible scores for LI range from -1 (strongly left-hemisphere dominant) to 1 (strongly right-hemisphere dominant). Concordance between fMRI and Wada was estimated using Cohen's Kappa coefficient. Association between the LI scores from the auditory and reading tasks was tested using Spearman's rank correlation coefficient.

RESULTS

The fMRI-based laterality indices were concordant with results from Wada testing in 91.4% of patients during the reading task (κ = .55) and 96.9% of patients during the auditory task (κ = .79). The mean LIs for the reading and auditory tasks were -0.52 ± 0.43 and -0.68 ± 0.42, respectively. The LI scores for the language and reading tasks were strongly correlated, r(30) = 0.57 (p = 0.001).

CONCLUSION

Our findings suggest that fMRI is generally an accurate, low-risk alternative to Wada testing for language lateralization. However, when fMRI indicates atypical language lateralization (e.g., bilateral dominance), patients may benefit from subsequent Wada testing or intraoperative language mapping.

A Ratiometric SERS Probe for Imaging the Macrophage Phenotypes in Live Mice with Epilepsy and Brain Tumor

Macrophage performs multiple functions such as pathogen phagocytosis, antigen presentation, and tissue remodeling by polarizing toward a spectrum of phenotypes. Dynamic imaging of macrophage phenotypes is critical for evaluating disease progression and the therapeutic response of drug candidates. However, current technologies cannot identify macrophage phenotypes in vivo. Herein, a surface-enhanced Raman scattering nanoprobe, AH1, which enables the accurate determination of physiological pH with high sensitivity and tissue penetration depth through ratiometric Raman signals is developed. Due to the phenotype-dependent metabolic reprogramming, AH1 can effectively identify macrophage subpopulations by measuring the acidity levels in phagosomes. After intravenous administration, AH1 not only visualizes the spatial distribution of macrophage phenotypes in brain tumors and epileptic regions of mouse models, but also reveals the repolarization of macrophages in brain lesions after drug intervention. This work provides a new tool for dynamically monitoring the disease-associated immune microenvironment and evaluating the efficacy of immune-therapeutics in vivo.

Neonatal seizures: Etiologies, clinical characteristics, and radiological features: A cross-sectional study

Seizures are a common clinical indication of central nervous system damage or abnormality in neonates. We aimed to identify the etiologies, clinical characteristics, and radiological features of neonatal seizures. This is a cross-sectional, retrospective, descriptive study using data obtained from the neonatal intensive care unit in King Abdulaziz Medical City (KAMC), a governmental, academic tertiary hospital in Riyadh, Saudi Arabia. The population of interest were neonates diagnosed with a neonatal seizure at KAMC between April 2015 and March 2019. A total of 61 patients with neonatal seizures were included in the study. The most common etiology was hypoxic-ischemic encephalopathy (43%). A total of 32 patients were full-term (52.5%). Around one-fifth of the study sample (21.3%) had a family history of neonatal seizures. Around 43.0% of the patients had epilepsy episodes. More than half of the patients (57.0%) were on one anti-seizure medication. Patients were followed up after 1 year, they had multiple comorbidities, including developmental delay, epilepsy, and cerebral palsy. Developmental delay was identified in 62.3% of the patients. A total of 19 patients have passed away (31%). Neonatal seizures are a common manifestation of neurologic disorders in neonates and are associated with high morbidity and mortality. Therefore, early identification of seizure etiology and proper management may help to improve the outcome.

Automated recognition of epilepsy from EEG signals using a combining space-time algorithm of CNN-LSTM

Intelligent recognition methods for classifying non-stationary and non-invasive epileptic diagnoses are essential tools in neurological research. Electroencephalogram (EEG) signals exhibit better temporal characteristics in the detection of epilepsy compared to radiation medical images like computed tomography (CT) and magnetic resonance imaging (MRI), as they provide real-time insights into the disease' condition. While classical machine learning methods have been used for epilepsy EEG classification, they still often require manual parameter adjustments. Previous studies primarily focused on binary epilepsy recognition (epilepsy vs. healthy subjects) rather than as ternary status recognition (continuous epilepsy vs. intermittent epilepsy vs. healthy subjects). In this study, we propose a novel deep learning method that combines a convolution neural network (CNN) with a long short-term memory (LSTM) network for multi-class classification including both binary and ternary tasks, using a publicly available benchmark database on epilepsy EEGs. The hybrid CNN-LSTM automatically acquires knowledge without the need for extra pre-processing or manual intervention. Besides, the joint network method benefits from memory function and stronger feature extraction ability. Our proposed hybrid CNN-LSTM achieves state-of-the-art performance in ternary classification, outperforming classical machine learning and the latest deep learning models. For the three-class classification, in the method achieves an accuracy, specificity, sensitivity, and ROC of 98%, 97.4, 98.3% and 96.8%, respectively. In binary classification, the method achieves better results, with ACC of 100%, 100%, and 99.8%, respectively. Our dual stream spatiotemporal hybrid network demonstrates superior performance compared to other methods. Notably, it eliminates the need for manual operations, making it more efficient for doctors to diagnose during the clinical process and alleviating the workload of neurologists.

Diagnostic Accuracy of Epilepsy-dedicated MRI with Post-processing

PURPOSE

To evaluate the diagnostic accuracy of epilepsy-dedicated 3 Tesla MRI including post-processing by correlating MRI, histopathology, and postsurgical seizure outcomes.

METHODS

3 Tesla-MRI including a magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence for post-processing using the morphometric analysis program MAP was acquired in 116 consecutive patients with drug-resistant focal epilepsy undergoing resection surgery. The MRI, histopathology reports and postsurgical seizure outcomes were recorded from the patient's charts.

RESULTS

The MRI and histopathology were concordant in 101 and discordant in 15 patients, 3 no hippocampal sclerosis/gliosis only lesions were missed on MRI and 1 of 28 focal cortical dysplasia (FCD) type II associated with a glial scar was considered a glial scar only on MRI. In another five patients, MRI was suggestive of FCD, the histopathology was uneventful but patients were seizure-free following surgery. The MRI and histopathology were concordant in 20 of 21 glioneuronal tumors, 6 cavernomas, and 7 glial scars. Histopathology was negative in 10 patients with temporal lobe epilepsy, 4 of them had anteroinferior meningoencephaloceles. Engel class IA outcome was reached in 71% of patients.

CONCLUSION

The proposed MRI protocol is highly accurate. No hippocampal sclerosis/gliosis only lesions are typically MRI negative. Small MRI positive FCD can be histopathologically missed, most likely due to sampling errors resulting from insufficient harvesting of tissue.

Late-onset epilepsy with cognitive symptoms: Comparison of cognitive and imaging profiles with probable Alzheimer's disease

OBJECTIVE

We aimed to (i) compare the clinical, neuropsychological, and neuroimaging characteristics of unprovoked late-onset epilepsy (LOE) patients with cognitive symptoms against probable Alzheimer's disease (AD) patients; (ii) clarify how neurodegeneration and other processes could be implicated in the cognitive symptoms of unprovoked LOE patients; and (iii) characterize the longitudinal trajectory of unprovoked LOE patients with cognitive symptoms.

METHODS

Twenty-six unprovoked LOE patients with cognitive symptoms and 26 probable AD were retrospectively recruited from epilepsy and memory clinics at a single tertiary referral center. The patients underwent comprehensive clinical, neuropsychological, and 18Fluorodeoxyglucose PET-CT assessments. All LOE patients had clinical follow-up and a subset of 17 patients had repeat neuropsychological assessments.

RESULTS

At baseline, 18% of LOE patients with cognitive symptoms had dementia-range cognitive impairment and one received a diagnosis of probable AD. Compared with the probable AD group, the LOE group did not perform significantly better in global measures of cognition (total ACE-III), neuropsychological tests for fluency, working memory, language, attention, or executive function, but performed better in naming, memory, and visuospatial ability. The commonest patterns of cognitive impairment in the LOE group were frontal and left temporal, whereas all AD patients exhibited parietotemporal patterns. The AD group had more 18Fluorodeoxyglucose PET-CT hypometabolism in the parietal and occipital, but not the temporal and frontal lobes. During the 3.0 ± 3.2 years follow-up, improved seizure frequency in the LOE group covaried with improved total ACE-III score, there was no further conversion to probable AD and no group-level cognitive decline.

CONCLUSION

Unprovoked LOE patients with cognitive symptoms had varying severities of cognitive impairment, and different patterns of cognitive and imaging abnormalities compared with AD patients. They were rarely diagnosed with probable AD at presentation or follow-up. Cognitive outcome in LOE may be related to seizure control. Cerebral small vessel disease may play a role in LOE-associated cognitive impairment.

Deep learning in neuroimaging of epilepsy

In recent years, artificial intelligence, particularly deep learning (DL), has demonstrated utility in diverse areas of medicine. DL uses neural networks to automatically learn features from the raw data while this is not possible with conventional machine learning. It is helpful for the assessment of patients with epilepsy and whilst most published studies have been aimed at the automatic detection and prediction of seizures from electroencephalographic records, there is a growing number of investigations that use neuroimaging modalities (structural and functional magnetic resonance imaging, diffusion-weighted imaging and positron emission tomography) as input data. We review the application of DL to neuroimaging (sMRI, fMRI, DWI and PET) of focal epilepsy, specifically presurgical evaluation of drug-refractory epilepsy. First, a brief theoretical overview of artificial neural networks and deep learning is presented. Next, we review applications of deep learning to neuroimaging of epilepsy: diagnosis and lateralization, automated detection of lesion, presurgical evaluation and prediction of postsurgical outcome. Finally, the limitations, challenges and possible future directions in the application of these methods in the study of epilepsies are discussed. This approach could become an essential tool in clinical practice, particularly in the evaluation of images considered negative by visual inspection, in individualized treatments, and in the approach to epilepsy as a network disorder. However, greater multicenter collaboration is required to achieve the collection of sufficient data with the required quality together with the open access availability of the developed codes and tools.

Ecstatic or Mystical Experience through Epilepsy

Ecstatic epilepsy is a rare form of focal epilepsy, so named because the seizures' first symptoms consist of an ecstatic/mystical experience, including feelings of increased self-awareness, mental clarity, and "unity with everything that exists," accompanied by a sense of bliss and physical well-being. In this perspective article, we first describe the phenomenology of ecstatic seizures, address their historical context, and describe the primary brain structure involved in the genesis of these peculiar epileptic seizures, the anterior insula. In the second part of the article, we move onto the possible neurocognitive underpinnings of ecstatic seizures. We first remind the reader of the insula's role in interoceptive processing and consciously experienced feelings, contextualized by the theory of predictive coding. This leads us to hypothesize that temporary disruptions to activity in the anterior insula could interrupt the generation of interoceptive prediction errors, and cause one to experience the absence of uncertainty, and thereby, a sense of bliss. The absence of interoceptive prediction errors would in fact mimic perfect prediction of the body's physiological state. This sudden clarity of bodily perception could explain the ecstatic quality of the experience, as the interoceptive system forms the basis for unified conscious experience. Our alternative hypothesis is that the anterior insula plays an overarching role in the processing of surprise and that the dysfunction caused by the epileptic discharge could interrupt any surprise exceeding expectations, resulting in a sense of complete control and oneness with the environment.

Ictal and interictal SPECT with 99m Tc-HMPAO in presurgical epilepsy. I: Predictive value and methodological considerations

OBJECTIVE

This retrospective study investigates the predictive value of ictal subtraction single-photon emission computed tomography (SPECT) co-registered to magnetic resonance imaging (MRI) (SISCOM) for successful epilepsy surgery.

METHODS

57 patients examined with SISCOM as a part of epilepsy surgery evaluation were divided into two groups based on seizure duration after tracer injection (group 1: Seizure duration above or equal to 30 s, group 2: Seizure duration under 30 s). SISCOM was compared to the surgical site and categorized as good or poor concordance. Subsequently, Odds ratios (ORs) and positive predictive values (PPVs) were calculated for each group for good surgical outcome, freedom from disabling seizures.

RESULTS

The PPVs and ORs for good surgical outcome was 74.1% and 5.71 for group 1 and 40% and 0.22 for group 2. SISCOM had a similar positive predictive value regardless of whether the focus was in the same or neighboring lobe, but same hemisphere as the resection.

CONCLUSION

In conclusion, the implementation of a precise definition for a well-executed ictal SPECT scan with respect to seizure duration after injection enhances the positive predictive value (PPV) and odds ratio (OR) for successful surgical outcome, surpassing previous findings, whether the focus in resected lobe or the neighboring.

Focal to bilateral tonic-clonic seizures predict pharmacoresistance in focal cortical dysplasia-related epilepsy

OBJECTIVE

Focal cortical dysplasia (FCD) is the most common etiology of surgically-remediable epilepsy in children. Eighty-seven percent of patients with FCD develop epilepsy (75% is pharmacoresistant epilepsy [PRE]). Focal to bilateral tonic-clonic (FTBTC) seizures are associated with worse surgical outcomes. We hypothesized that children with FCD-related epilepsy with FTBTC seizures are more likely to develop PRE due to lesion interaction with restricted cortical neural networks.

METHODS

Patients were selected retrospectively from radiology and surgical databases from Children's National Hospital.

INCLUSION CRITERIA

3T magnetic resonance imaging (MRI)-confirmed FCD from January 2011 to January 2020; ages 0 days to 22 years at MRI; and 18 months of documented follow-up. FCD dominant network (Yeo 7-network parcellation) was determined. Association of FTBTC seizures with epilepsy severity, surgical outcome, and dominant network was tested. Binomial regression was used to evaluate predictors (FTBTC seizures, age at seizure onset, pathology, hemisphere, lobe) of pharmacoresistance and Engel outcome. Regression was used to evaluate predictors (age at seizure onset, pathology, lobe, percentage default mode network [DMN] overlap) of FTBTC seizures.

RESULTS

One hundred seventeen patients had a median age at seizure onset of 3.00 years (interquartile range [IQR] .42-5.59 years). Eighty-three patients had PRE (71%); 34 had pharmacosensitive epilepsy (PSE) (29%). Twenty patients (17%) had FTBTC seizures. Seventy-three patients underwent epilepsy surgery. Multivariate regression showed that FTBTC seizures are associated with an increased risk of PRE (odds ratio [OR] 6.41, 95% confidence interval [CI] 1.21-33.98, p = .02). FCD hemisphere/lobe was not associated with PRE. Percentage DMN overlap predicts FTBTC seizures. Seventy-two percent (n = 52) overall and 53% (n = 9) of patients with FTBTC seizures achieved Engel class I outcome.

SIGNIFICANCE

In a heterogeneous population of surgical and non-operated patients with FCD-related epilepsy, the presence of FTBTC seizures is associated with a tremendous risk of PRE. This finding is a recognizable marker to help neurologists identify those children with FCD-related epilepsy at high risk of PRE and can flag patients for earlier consideration of potentially curative surgery. The FCD-dominant network also contributes to FTBTC seizure clinical expression.

Age of epilepsy onset as modulating factor for naming deficit after epilepsy surgery: a voxel-based lesion-symptom mapping study

Age at onset of epilepsy is an important predictor of deterioration in naming ability following epilepsy surgery. In 141 patients with left hemispheric epilepsy and language dominance who received epilepsy surgery at the Epilepsy Centre Erlangen, naming of objects (Boston naming test, BNT) was assessed preoperatively and 6 months postoperatively. Surgical lesions were plotted on postoperative MRI and normalized for statistical analysis using voxel-based lesion-symptom mapping (VBLSM). The correlation between lesion and presence of postoperative naming deterioration was examined varying the considered age range of epilepsy onsets. The VBLSM analysis showed that volumes of cortex areas in the left temporal lobe, which were associated with postoperative decline of naming, increased with each year of later epilepsy onset. In patients with later onset, an increasing left posterior temporobasal area was significantly associated with a postoperative deficit when included in the resection. For late epilepsy onset, the temporomesial expansion also included the left hippocampus. The results underline that early onset of epilepsy is a good prognostic factor for unchanged postoperative naming ability following epilepsy surgery. For later age of epilepsy onset, the extent of the area at risk of postoperative naming deficit at 6 months after surgery included an increasing left temporobasal area which finally also comprised the hippocampus.

Novel Near-Infrared Fluorescence Probe for Bioimaging and Evaluating Superoxide Anion Fluctuations in Ferroptosis-Mediated Epilepsy

Ferroptosis is an iron-regulated, caspase-mediated pathway of cell death that is associated with the excessive aggregation of lipid-reactive oxygen species and is extensively involved in the evolution of many diseases, including epilepsy. The superoxide anion (O2•-), as the primary precursor of ROS, is closely related to ferroptosis-mediated epilepsy. Therefore, it is crucial to establish a highly effective and convenient method for the real-time dynamic monitoring of O2•- during the ferroptosis process in epilepsy for the diagnosis and therapy of ferroptosis-mediated epilepsy. Nevertheless, no probes for detecting O2•- in ferroptosis-mediated epilepsy have been reported. Herein, we systematically conceptualized and developed a novel near-infrared (NIR) fluorescence probe, NIR-FP, for accurately tracking the fluctuation of O2•- in ferroptosis-mediated epilepsy. The probe showed exceptional sensitivity and outstanding selectivity toward O2•-. In addition, the probe has been utilized effectively to bioimage and evaluate endogenous O2•- variations in three types of ferroptosis-mediated epilepsy models (the kainic acid-induced chronic epilepsy model, the pentylenetetrazole-induced acute epilepsy model, and the pilocarpine-induced status epilepticus model). The above applications illustrated that NIR-FP could serve as a reliable and suitable tool for guiding the accurate diagnosis and therapy of ferroptosis-mediated epilepsy.

Brain networks and epilepsy development in patients with Alzheimer disease

INTRODUCTION

This study aimed to investigate the association between brain networks and epilepsy development in patients with Alzheimer disease (AD).

METHODS

We enrolled patients newly diagnosed with AD at our hospital who underwent three-dimensional T1-weighted magnetic resonance imaging at the time of AD diagnosis and included healthy controls. We obtained the cortical, subcortical, and thalamic nuclei structural volumes using FreeSurfer and applied graph theory to obtain the global brain network and intrinsic thalamic network based on the structural volumes using BRAPH.

RESULTS

We enrolled 25 and 56 patients with AD with and without epilepsy development, respectively. We also included 45 healthy controls. The global brain network differed between the patients with AD and healthy controls. The local efficiency (2.026 vs. 3.185, p = .048) and mean clustering coefficient (0.449 vs. 1.321, p = .024) were lower, whereas the characteristic path length (0.449 vs. 1.321, p = .048) was higher in patients with AD than in healthy controls. Both global and intrinsic thalamic networks were significantly different between AD patients with and without epilepsy development. In the global brain network, local efficiency (1.340 vs. 2.401, p = .045), mean clustering coefficient (0.314 vs. 0.491, p = .045), average degree (27.442 vs. 41.173, p = .045), and assortative coefficient (-0.041 vs. -0.011, p = .045) were lower, whereas the characteristic path length (2.930 vs. 2.118, p = .045) was higher in patients with AD with epilepsy development than in those without. In the intrinsic thalamic network, the mean clustering coefficient (0.646 vs. 0.460, p = .048) was higher, whereas the characteristic path length (1.645 vs. 2.232, p = .048) was lower in patients with AD with epilepsy development than in those without.

CONCLUSION

We found that the global brain network differs between patients with AD and healthy controls. In addition, we demonstrated significant associations between brain networks (both global brain and intrinsic thalamic networks) and epilepsy development in patients with AD.

Longitudinal evolution of electroencephalogram (EEG): Findings over five years of follow-up in children with Zika-related microcephaly from the Microcephaly Epidemic Research Group Pediatric Cohort (2015-2020)

OBJECTIVE

To assess the longitudinal evolution of EEG findings in children with Zika related-microcephaly (ZRM) and to evaluate the associations of these patterns with the children's clinical and neuroimaging characteristics.

METHODS

As part of the follow-up of the Microcephaly Epidemic Research Group Pediatric Cohort (MERG-PC) in Recife, Brazil, we performed serial EEG recordings in a subgroup of children with ZRM to evaluate changes in background rhythms and epileptiform activity (EA). Latent class analysis was used to identify patterns in the evolution of EA over time; clinical and neuroimaging findings were compared across the identified groups.

RESULTS

Out of the 72 children with ZRM who were evaluated during 190 EEGs/videoEEGs, all participants presented with abnormal background activity, 37.5% presented with an alpha-theta rhythmic activity, and 25% presented with sleep spindles, which were less commonly observed in children with epilepsy. EA changed over time in 79.2% of children, and three distinct trajectories were identified: (i) multifocal EA over time, (ii) no discharges/focal EA evolving to focal/multifocal EA, and (iii) focal/multifocal EA evolving to epileptic encephalopathy patterns (e.g., hypsarrhythmia or continuous EA in sleep). The multifocal EA over time trajectory was associated with periventricular and thalamus/basal ganglia calcifications, brainstem and corpus callosum atrophy and had less focal epilepsy, whereas the children in the trajectory which evolved to epileptic encephalopathy patterns had more frequently focal epilepsy.

SIGNIFICANCE

These findings suggest that, in most children with ZRM, trajectories of changes in EA can be identified and associated with neuroimaging and clinical features.

Temporal stability of intracranial electroencephalographic abnormality maps for localizing epileptogenic tissue

OBJECTIVE

Identifying abnormalities on interictal intracranial electroencephalogram (iEEG), by comparing patient data to a normative map, has shown promise for the localization of epileptogenic tissue and prediction of outcome. The approach typically uses short interictal segments of approximately 1 min. However, the temporal stability of findings has not been established.

METHODS

Here, we generated a normative map of iEEG in nonpathological brain tissue from 249 patients. We computed regional band power abnormalities in a separate cohort of 39 patients for the duration of their monitoring period (.92-8.62 days of iEEG data, mean = 4.58 days per patient, >4800 hours recording). To assess the localizing value of band power abnormality, we computedD RS -a measure of how different the surgically resected and spared tissue was in terms of band power abnormalities-over time.

RESULTS

In each patient, theD RS value was relatively consistent over time. The medianD RS of the entire recording period separated seizure-free (International League Against Epilepsy [ILAE] = 1) and not-seizure-free (ILAE> 1) patients well (area under the curve [AUC] = .69). This effect was similar interictally (AUC = .69) and peri-ictally (AUC = .71).

SIGNIFICANCE

Our results suggest that band power abnormality D_RS, as a predictor of outcomes from epilepsy surgery, is a relatively robust metric over time. These findings add further support for abnormality mapping of neurophysiology data during presurgical evaluation.

An open presurgery MRI dataset of people with epilepsy and focal cortical dysplasia type II

Automated detection of lesions using artificial intelligence creates new standards in medical imaging. For people with epilepsy, automated detection of focal cortical dysplasias (FCDs) is widely used because subtle FCDs often escape conventional neuroradiological diagnosis. Accurate recognition of FCDs, however, is of outstanding importance for affected people, as surgical resection of the dysplastic cortex is associated with a high chance of postsurgical seizure freedom. Here, we make publicly available a dataset of 85 people affected by epilepsy due to FCD type II and 85 healthy control persons. We publish 3D-T1 and 3D-FLAIR, manually labeled regions of interest, and carefully selected clinical features. The open presurgery MRI dataset may be used to validate existing automated algorithms of FCD detection as well as to create new approaches. Most importantly, it will enable comparability of already existing approaches and support a more widespread use of automated lesion detection tools.