Optimal timing of interictal FDG-PET for epilepsy surgery: A systematic review on time since last seizure

Interictal 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) is used in the workup for epilepsy surgery when MRI and EEG video monitoring are not conclusive. Timing of FDG-PET is crucial to avoid the metabolically dynamic (post)ictal state that complicates interpretation, but the exact time window is unclear. We performed a systematic review to provide an evidence-based recommendation for the minimal time interval between last seizure and FDG-PET acquisition. We searched PubMed and Embase for articles on the effect of time since last seizure on FDG-PET outcome. Quality assessment was conducted with the Critical Appraisal Skills Programme Cohort Study Checklist. We identified five studies. Three studies were classified as of low to moderate quality, mainly due to undocumented data or insufficient statistical measurements. Two high-quality studies included only adults with Temporal Lobe Epilepsy (TLE). The metabolic interictal phase is 24 or 48 hours after the last seizure, depending on seizure type. The recommendation is based on the best available evidence from two small study populations for TLE. If clinically possible, interictal FDG-PET in adults should be performed at least 24 hours after focal aware seizures and 48 hours after focal impaired awareness and focal to bilateral tonic–clonic seizures

High-resolution electric source imaging for presurgical evaluation of tuberous sclerosis complex patients

Objective: We retrospectively assessed the localizing value of patient-history-based semiology (PHS), video-based semiology (VS), long-term monitoring video electroencephalography (LTM-VEEG) and interictal high resolution electric source imaging (HR-ESI) in the presurgical workup of patients with tuberous sclerosis complex (TSC). Methods: Data from 24 consecutive TSC surgical candidates who underwent both HR-ESI and LTM-VEEG was retrospectively collected. PHS and VS were analyzed to hypothesize the symptomatogenic zone localization. LTM-VEEG and HR-ESI localization results were extracted from the diagnostic reports. Localizing value was compared between modalities, taken the resected/disconnected area of surgical patients in consideration. HR-ESI's impact on the epileptogenic zone hypothesis and surgical workup was evaluated. Results: Semiology, interictal EEG, ictal EEG and HR-ESI were localizing in 25%, 54%, 63% and 79% of patients. Inter-modality concordance ranged between 33–89%. In good surgical outcome patients, PHS, VS, interictal EEG, ictal EEG and HR-ESI showed concordance with resected area in 1/9 (11%), 0/9 (0%), 4/9 (44%), 3/9 (33%) and 6/9 patients (67%). HR-ESI positively impacts clinical management in 50% of patients. Conclusions: In presurgical evaluation of TSC patients, semiology often has limited localizing value. Presurgical work-up benefits from HR-ESI. Significance: Our findings may advice future presurgical epilepsy workup of TSC patients with the ultimate aim to improve outcome

High-frequency oscillations recorded with surface EEG in neonates with seizures

Objective: Neonatal seizures are often the first symptom of perinatal brain injury. High-frequency oscillations (HFOs) are promising new biomarkers for epileptogenic tissue and can be found in intracranial and surface EEG. To date, we cannot reliably predict which neonates with seizures will develop childhood epilepsy. We questioned whether epileptic HFOs can be generated by the neonatal brain and potentially predict epilepsy. Methods: We selected 24 surface EEGs sampled at 2048 Hz with 175 seizures from 16 neonates and visually reviewed them for HFOs. Interictal epochs were also reviewed. Results: We found HFOs in thirteen seizures (7%) from four neonates (25%). 5025 ictal ripples (rate 10 to 1311/min; mean frequency 135 Hz; mean duration 66 ms) and 1427 fast ripples (rate 8 to 356/min; mean frequency 298 Hz; mean duration 25 ms) were marked. Two neonates (13%) showed interictal HFOs (285 ripples and 25 fast ripples). Almost all HFOs co-occurred with sharp transients. We could not find a relationship between neonatal HFOs and outcome yet. Conclusions: Neonatal HFOs co-occur with ictal and interictal sharp transients. Significance: The neonatal brain can generate epileptic ripples and fast ripples, particularly during seizures, though their occurrence is not common and potential clinical value not evident yet

DeltaScan for the Assessment of Acute Encephalopathy and Delirium in ICU and non-ICU Patients, a Prospective Cross-Sectional Multicenter Validation Study

Objectives: To measure the diagnostic accuracy of DeltaScan: a portable real-time brain state monitor for identifying delirium, a manifestation of acute encephalopathy (AE) detectable by polymorphic delta activity (PDA) in single-channel electroencephalograms (EEGs). Design: Prospective cross-sectional study. Setting: Six Intensive Care Units (ICU's) and 17 non-ICU departments, including a psychiatric department across 10 Dutch hospitals. Participants: 494 patients, median age 75 (IQR:64-87), 53% male, 46% in ICUs, 29% delirious. Measurements: DeltaScan recorded 4-minute EEGs, using an algorithm to select the first 96 seconds of artifact-free data for PDA detection. This algorithm was trained and calibrated on two independent datasets. Methods: Initial validation of the algorithm for AE involved comparing its output with an expert EEG panel's visual inspection. The primary objective was to assess DeltaScan's accuracy in identifying delirium against a delirium expert panel's consensus. Results: DeltaScan had a 99% success rate, rejecting 6 of the 494 EEG's due to artifacts. Performance showed and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.86 (95% CI: 0.83-0.90) for AE (sensitivity: 0.75, 95%CI=0.68-0.81, specificity: 0.87 95%CI=0.83-0.91. The AUC was 0.71 for delirium (95%CI=0.66-0.75, sensitivity: 0.61 95%CI=0.52-0.69, specificity: 72, 95%CI=0.67-0.77). Our validation aim was an NPV for delirium above 0.80 which proved to be 0.82 (95%CI: 0.77-0.86). Among 84 non-delirious psychiatric patients, DeltaScan differentiated delirium from other disorders with a 94% (95%CI: 87-98%) specificity. Conclusions: DeltaScan can diagnose AE at bedside and shows a clear relationship with clinical delirium. Further research is required to explore its role in predicting delirium-related outcomes.</p

Bewust van kleine epileptische aanvallen : Niet alle patienten verliezen het bewustzijn bij een aanval

Epilepsie is een veelvoorkomende aandoening. Het aantal jaren dat mensen ermee moeten leven is doorgaans groter dan bij andere neurologische aandoeningen, omdat veel vormen van epilepsie op jonge leeftijd beginnen en iemand er oud mee kan worden. In opgetelde ziektejaren staat epilepsie dan ook op de tweede plaats van alle neurologische aandoeningen. Het aantal nieuwe gevallen van epilepsie bedraagt wereldwijd 50 per 100.000 mensen per jaar. Als we rekenen met de Europese prevalentie van 6 per 1000 zijn er naar schatting 100.000 mensen met epilepsie in Nederland. Het aantal ouderen bij wie de diagnose wordt gesteld, neemt toe, omdat epilepsie een complicatie kan zijn van vrijwel alle hersenaandoeningen. Iedere arts krijgt dus te maken met mensen met epilepsie

Multimodal seizure detection : A review

A review is given on the combined use of multiple modalities in non electroencephalography (EEG)-based detection of motor seizures in children and adults. A literature search of papers was done on multimodal seizure detection with extraction of data on type of modalities, study design and algorithm, sensitivity, false detection rate, and seizure types. Evidence of superiority was sought for using multiple instead of single modalities. Seven papers were found from 2010 to 2017, mostly using contact sensors such as accelerometers (n = 5), electromyography (n = 2), heart rate (n = 2), electrodermal activity (n = 1), and oximetry (n = 1). Remote sensors included video, radar, movement, and sound. All studies but one were in-hospital, with video-EEG as a gold standard. Algorithms were based on physiology and supervised machine learning, but did not always include a separate test dataset. Sensitivity ranged from 4% to 100% and false detection rate from 0.25 to 20 per 8 hours. Tonic-clonic seizure detection performed best. False detections tended to be restricted to a minority (16%-30%) of patients. Use of multiple sensors increased sensitivity; false detections decreased in one study, but increased in another. These preliminary studies suggest that detection of tonic-clonic seizures might be feasible, but larger field studies are required under more rigorous design that precludes bias. Generic algorithms probably suffice for the majority of patients

Towards human BCI applications based on cognitive brain systems: An investigation of neural signals recorded from the dorsolateral prefrontal cortex

One of the critical issues in brain-computer interface (BCI) research is how to translate a person's intention into brain signals for controlling computer programs. The motor system is currently the primary focus, where signals are obtained during imagined motor responses. However, cognitive brain systems are also attractive candidates, in that they may be more amenable to conscious control, yielding better regulation of magnitude and duration of localized brain activity. We report on a proof of principle study for the potential use of a higher cognitive system for BCI, namely the working memory (WM) system. We show that mental calculation reliably activates the WM network as measured with functional magnetic resonance imaging (fMRI). Moreover, activity in the dorsolateral prefrontal cortex (DLPFC) indicates that this region is active for the duration of mental processing. This supports the notion that DLPFC can be activated, and remains active, at will. Further confirmation is obtained from a patient with an implanted electrode grid for diagnostic purposes, in that gamma power within DLPFC increases during mental calculation and remains elevated for the duration thereof. These results indicate that cortical regions involved in higher cognitive functions may serve as a readily self-controllable input for BCI applications. It also shows that fMRI is an effective tool for identifying function-specific foci in individual subjects for subsequent placement of cortical electrodes. The fact that electrocorticographic (ECoG) signal confirmed the functional localization of fMRI provides a strong argument for incorporating fMRI in BCI research

Evoked directional network characteristics of epileptogenic tissue derived from single pulse electrical stimulation

We investigated effective networks constructed from single pulse electrical stimulation (SPES) in epilepsy patients who underwent intracranial electrocorticography. Using graph analysis, we compared network characteristics of tissue within and outside the epileptogenic area. In 21 patients with subdural electrode grids (1cm interelectrode distance), we constructed a binary, directional network derived from SPES early responses (<100ms). We calculated in-degree, out-degree, betweenness centrality, the percentage of bidirectional, receiving and activating connections, and the percentage of connections toward the (non-)epileptogenic tissue for each node in the network. We analyzed whether these network measures were significantly different in seizure onset zone (SOZ)-electrodes compared to non-SOZ electrodes, in resected area (RA)-electrodes compared to non-RA electrodes, and in seizure free compared to not seizure-free patients. Electrodes in the SOZ/RA showed significantly higher values for in-degree and out-degree, both at group level, and at patient level, and more so in seizure-free patients. These differences were not observed for betweenness centrality. There were also more bidirectional and fewer receiving connections in the SOZ/RA in seizure-free patients. It appears that the SOZ/RA is densely connected with itself, with only little input arriving from non-SOZ/non-RA electrodes. These results suggest that meso-scale effective network measures are different in epileptogenic compared to normal brain tissue. Local connections within the SOZ/RA are increased and the SOZ/RA is relatively isolated from the surrounding cortex. This offers the prospect of enhanced prediction of epilepsy-prone brain areas using SPES

Pathological responses to single‐pulse electrical stimuli in epilepsy: The role of feedforward inhibition

Delineation of epileptogenic cortex in focal epilepsy patients may profit from single-pulse electrical stimulation during intracranial EEG recordings. Single-pulse electrical stimulation evokes early and delayed responses. Early responses represent connectivity. Delayed responses are a biomarker for epileptogenic cortex, but up till now, the precise mechanism generating delayed responses remains elusive. We used a data-driven modelling approach to study early and delayed responses. We hypothesized that delayed responses represent indirect responses triggered by early response activity and investigated this for 11 patients. Using two coupled neural masses, we modelled early and delayed responses by combining simulations and bifurcation analysis. An important feature of the model is the inclusion of feedforward inhibitory connections. The waveform of early responses can be explained by feedforward inhibition. Delayed responses can be viewed as second-order responses in the early response network which appear when input to a neural mass falls below a threshold forcing it temporarily to a spiking state. The combination of the threshold with noisy background input explains the typical stochastic appearance of delayed responses. The intrinsic excitability of a neural mass and the strength of its input influence the probability at which delayed responses to occur. Our work gives a theoretical basis for the use of delayed responses as a biomarker for the epileptogenic zone, confirming earlier clinical observations. The combination of early responses revealing effective connectivity, and delayed responses showing intrinsic excitability, makes single-pulse electrical stimulation an interesting tool to obtain data for computational models of epilepsy surgery

Decoding four hand gestures with a single bipolar pair of electrocorticography electrodes

Objective. Electrocorticography (ECoG) based brain-computer interfaces (BCIs) can be used to restore communication in individuals with locked-in syndrome. In motor-based BCIs, the number of degrees-of-freedom, and thus the speed of the BCI, directly depends on the number of classes that can be discriminated from the neural activity in the sensorimotor cortex. When considering minimally invasive BCI implants, the size of the subdural ECoG implant must be minimized without compromising the number of degrees-of-freedom. Approach. Here we investigated if four hand gestures could be decoded using a single ECoG strip of four consecutive electrodes spaced 1 cm apart and compared the performance between a unipolar and a bipolar montage. For that we collected data of seven individuals with intractable epilepsy implanted with ECoG grids, covering the hand region of the sensorimotor cortex. Based on the implanted grids, we generated virtual ECoG strips and compared the decoding accuracy between (a) a single unipolar electrode (Unipolar Electrode), (b) a combination of four unipolar electrodes (Unipolar Strip), (c) a single bipolar pair (Bipolar Pair) and (d) a combination of six bipolar pairs (Bipolar Strip). Main results. We show that four hand gestures can be equally well decoded using 'Unipolar Strips' (mean 67.4 ± 11.7%), 'Bipolar Strips' (mean 66.6 ± 12.1%) and 'Bipolar Pairs' (mean 67.6 ± 9.4%), while 'Unipolar Electrodes' (61.6 ± 5.9%) performed significantly worse compared to 'Unipolar Strips' and 'Bipolar Pairs'. Significance. We conclude that a single bipolar pair is a potential candidate for minimally invasive motor-based BCIs and encourage the use of ECoG as a robust and reliable BCI platform for multi-class movement decoding