Localization Of Epileptogenic Focus Research Articles

SPECT postprocessing for epileptogenic focus localization: SISCOM versus ISAS.

Ictal SPECT can be used as an estimate for the epileptogenic zone in people with focal epilepsy. Subtraction of ictal and interictal SPECT scans reveals the area with significant ictal hyperperfusion. Some methods use a control database to also correct for physiological variance. This control database is ideally scanner specific, but it is not trivial to obtain such a database because of ethical issues. In this study, we used a publicly available control database to compare ictal-interictal SPECT analyzed by SPM (ISAS) with the most commonly used subtraction ictal SPECT co-registered to MRI (SISCOM). Ictal and interictal SPECTs of 26 patients (age range: 7-50 years, 15 adults, 11 children) with focal drug resistant epilepsy in workup for epilepsy surgery were retrospectively analyzed using both SISCOM and ISAS. The control database for ISAS was obtained from the ISAS website. Two groups of blinded reviewers determined the location of ictal hyperperfusion in all datasets. Results were compared between subtraction algorithms and with the resected area (if available) or the suspected epileptogenic zone. The number of significant clusters and the locations of maximum hyperperfusion were compared between algorithms. The location of ISAS and SISCOM hyperperfusion was the same in 14 patients (54%). ISAS localized in 6 patients where SISCOM did not. Compared to the resected area or suspected epileptogenic zone, SISCOM correctly localized in 55%, while ISAS did in 65% (not significantly different). ISAS shows significantly less clusters than SISCOM. The maximum hyperperfusion was in the reviewer's location in 65% for ISAS and 38% for SISCOM. ISAS using a publicly available control database gives comparable or better results than SISCOM. ISAS results are easier to interpret than SISCOM results. We show that ISAS is a reliable alternative for SISCOM, which could easily be implemented in epilepsy surgery clinics. We explored the effectiveness of ISAS as an alternative to the widely used SISCOM for assessing SPECT scans in epilepsy surgery candidates. Utilizing a publicly available control database, we compared the two methods in 26 patients. The results indicate that ISAS might offer increased accuracy and interpretability, making it a promising option, especially for centers without access to a specific control dataset.

18F]SynVesT-1 and [18F]FDG quantitative PET imaging in the presurgical evaluation of MRI-negative children with focal cortical dysplasia type II.

MRI-negative children with focal cortical dysplasia type II (FCD II) are one of the most challenging cases in surgical epilepsy management. We aimed to utilize quantitative positron emission tomography (QPET) analysis to complement [18F]SynVesT-1 and [18F]FDG PET imaging and facilitate the localization of epileptogenic foci in pediatric MRI-negative FCD II patients. We prospectively enrolled 17 MRI-negative children with FCD II who underwent [18F]SynVesT-1 and [18F]FDG PET before surgical resection. The QPET scans were analyzed using statistical parametric mapping (SPM) with respect to healthy controls. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of [18F]SynVesT-1 PET, [18F]FDG PET, [18F]SynVesT-1 QPET, and [18F]FDG QPET in the localization of epileptogenic foci were assessed. Additionally, we developed a multivariate prediction model based on dual trace PET/QPET assessment. The AUC values of [18F]FDG PET and [18F]SynVesT-1 PET were 0.861 (sensitivity = 94.1%, specificity = 78.2%, PPV = 38.1%, NPV = 98.9%) and 0.908 (sensitivity = 82.4%, specificity = 99.2%, PPV = 93.3%, NPV = 97.5%), respectively. [18F]FDG QPET showed lower sensitivity (76.5%) and NPV (96.6%) but higher specificity (95.0%) and PPV (68.4%) than visual assessment, while [18F]SynVesT-1 QPET exhibited higher sensitivity (94.1%) and NPV (99.1%) but lower specificity (97.5%) and PPV (84.2%). The multivariate prediction model had the highest AUC value (AUC = 0.996, sensitivity = 100.0%, specificity = 96.6%, PPV = 81.0%, NPV = 100%). The multivariate prediction model based on [18F]SynVesT-1 and [18F]FDG PET/QPET assessments holds promise in noninvasively identifying epileptogenic regions in MRI-negative children with FCD II. Furthermore, the combination of visual assessment and QPET may improve the sensitivity and specificity of diagnostic tests in localizing epileptogenic foci and achieving a preferable surgical outcome in MRI-negative FCD II.

Electromagnetic source imaging predicts surgical outcome in children with focal cortical dysplasia

ObjectiveTo evaluate the diagnostic accuracy of electromagnetic source imaging (EMSI) in localizing spikes and predict surgical outcome in children with drug resistant epilepsy (DRE) due to focal cortical dysplasia (FCD). MethodsWe retrospectively analyzed magnetoencephalography (MEG) and high-density (HD-EEG) data from 23 children with FCD-associated DRE who underwent intracranial EEG and surgery. We localized spikes using equivalent current dipole (ECD) fitting, dipole clustering, and dynamical statistical parametric mapping (dSPM) on EMSI, electric source imaging (ESI), and magnetic source imaging (MSI). We calculated the distance from the seizure onset zone (DSOZ) and resection (DRES). We estimated receiver operating characteristic (ROC) curves with Youden’s index (J) to predict outcome. ResultsEMSI presented shorter DSOZ (15.18 ± 9.06 mm) and DRES (8.56 ± 6.24 mm) compared to ESI (DSOZ: 25.04 ± 16.20 mm, p < 0.009; DRES: 18.88 ± 17.30 mm, p < 0.03) and MSI (DSOZ: 23.37 ± 8.98 mm, p < 0.03; DRES: 15.51 ± 10.11 mm, p < 0.02) for clustering in patients with good outcome. Clustering showed shorter DSOZ and DRES compared to ECD fitting and dSPM (p < 0.05). EMSI had higher performance as outcome predictor (J = 70.63%) compared to ESI (J = 41.27%) and MSI (J = 33.33%) for clustering. ConclusionsEMSI provides superior localization and improved predictive performance than individual modalities. SignificanceEMSI can help the surgical planning and facilitate the localization of epileptogenic foci.

Interictal localization of the epileptogenic zone: Utilizing the observed resonance behavior in the spectral band of surrounding inhibition.

The gold standard for identification of the epileptogenic zone (EZ) continues to be the visual inspection of electrographic changes around seizures' onset by experienced electroencephalography (EEG) readers. Development of an epileptogenic focus localization tool that can delineate the EZ from analysis of interictal (seizure-free) periods is still an open question of great significance for improved diagnosis (e.g., presurgical evaluation) and treatment of epilepsy (e.g., surgical outcome). We developed an EZ interictal localization algorithm (EZILA) based on novel analysis of intracranial EEG (iEEG) using a univariate periodogram-type power measure, a straight-forward ranking approach, a robust dimensional reduction method and a clustering technique. Ten patients with temporal and extra temporal lobe epilepsies, and matching the inclusion criteria of having iEEG recordings at the epilepsy monitoring unit (EMU) and being Engel Class I ≥12 months post-surgery, were recruited in this study. In a nested k-fold cross validation statistical framework, EZILA assigned the highest score to iEEG channels within the EZ in all patients (10/10) during the first hour of the iEEG recordings and up to their first typical clinical seizure in the EMU (i.e., early interictal period). To further validate EZILA's performance, data from two new (Engel Class I) patients were analyzed in a double-blinded fashion; the EZILA successfully localized iEEG channels within the EZ from interictal iEEG in both patients. Out of the sampled brain regions, iEEG channels in the EZ were most frequently and maximally active in seizure-free (interictal) periods across patients in specific narrow gamma frequency band (∼60-80 Hz), which we have termed focal frequency band (FFB). These findings are consistent with the hypothesis that the EZ may interictally be regulated (controlled) by surrounding inhibitory neurons with resonance characteristics within this narrow gamma band.

Multi-Scale Deep Learning of Clinically Acquired Multi-Modal MRI Improves the Localization of Seizure Onset Zone in Children With Drug-Resistant Epilepsy

The present study investigates the effectiveness of a deep learning neural network for non-invasively localizing the seizure onset zone (SOZ) using multi-modal MRI data that are clinically acquired from children with drug-resistant epilepsy. A cortical parcellation was applied to localize the SOZ in cortical nodes of the epileptogenic hemisphere. At each node, the laminar surface analysis was followed to sample 1) the relative intensity of gray matter and white matter in multi-modal MRI and 2) the neighboring white matter connectivity using diffusion tractography edge strengths. A cross-validation was employed to train and test all layers of a multi-scale residual neural network (msResNet) that can classify SOZ node in an end-to-end fashion. A prediction probability of a given node belonging to the SOZ class was proposed as a non-invasive MRI marker of seizure onset likelihood. In an independent validation cohort, the proposed MRI marker provided a very large effect size of Cohen's d = 1.21 between SOZ and non-SOZ, and classified SOZ with a balanced accuracy of 0.75 in lesional and 0.67 in non-lesional MRI groups. The subsequent multi-variate logistic regression found the incorporation of the proposed MRI marker into interictal intracranial EEG (iEEG) markers further improves the differentiation between the epileptogenic focus (defined as SOZ resected during surgery) and non-epileptogenic sites (i.e., non-SOZ sites preserved during surgery) up to 15 % in non-lesional MRI group, suggesting that the proposed MRI marker could improve the localization of epileptogenic foci for successful pediatric epilepsy surgery.

Mapping Interictal activity in epilepsy using a hidden Markov model: A magnetoencephalography study.

Epilepsy is a highly heterogeneous neurological disorder with variable etiology, manifestation, and response to treatment. It is imperative that new models of epileptiform brain activity account for this variability, to identify individual needs and allow clinicians to curate personalized care. Here, we use a hidden Markov model (HMM) to create a unique statistical model of interictal brain activity for 10 pediatric patients. We use magnetoencephalography (MEG) data acquired as part of standard clinical care for patients at the Children's Hospital of Philadelphia. These data are routinely analyzed using excess kurtosis mapping (EKM); however, as cases become more complex (extreme multifocal and/or polymorphic activity), they become harder to interpret with EKM. We assessed the performance of the HMM against EKM for three patient groups, with increasingly complicated presentation. The difference in localization of epileptogenic foci for the two methods was 7± 2 mm (mean ±SD over all 10 patients); and 94% ± 13% of EKM temporal markers were matched by an HMM state visit. The HMM localizes epileptogenic areas (in agreement with EKM) and provides additional information about the relationship between those areas. A key advantage over current methods is that the HMM is a data-driven model, so the output is tuned to each individual. Finally, the model output is intuitive, allowing a user (clinician) to review the result and manually select the HMM epileptiform state, offering multiple advantages over previous methods and allowing for broader implementation of MEG epileptiform analysis in surgical decision-making for patients with intractable epilepsy.

Localization of epileptogenic foci by automatic detection of high‐frequency oscillations based on waveform feature templates

Localization of epileptogenic foci by automatic detection of high‐frequency oscillations based on waveform feature templates

Th1 and Th17 cells are critical for limiting the severity of Staphylococcus aureus craniotomy infection

Abstract A craniotomy is performed to access the brain for tumor resection, localization and resection of epileptogenic foci, and aneurysm clipping. Despite prophylaxis, infectious complications after craniotomy range from 1–3%, with approximately half caused by Staphylococcus aureus (S. aureus), which forms a biofilm on the bone flap that is recalcitrant to antibiotics. Using our novel mouse model of S. aureus craniotomy infection, Th1 and Th17 infiltrates were found to preferentially home to the brain but not the subcutaneous galea; however, their functional importance is unknown. RAG1 knockout (KO) mice displayed significant increases in bacterial burden in the brain, galea, and bone flap at days 3, 7, and 14 post-infection, which was negated following the adoptive transfer of either in vitro skewed Th1 or Th17 cells. Interestingly, in vitro skewed Th17 cells acquired Th1 characteristics upon migrating into the brain in vivo as revealed by the production of Th1-associated cytokines such as IFN-γ and TNF-α with minimal IL-17A. We established that the window of T cell protection was during acute infection, since delaying Th1 or Th17 adoptive transfer until day 7 post-infection was no longer able to attenuate S. aureus burden in RAG1 KO mice compared to T cell transfers at day −1 or 3 after infection that were effective. In vitro studies established that both Th1 and Th17 cells augmented microglial, macrophage, and neutrophil S. aureus bactericidal activity and IL-12p70 and CXCL10 production. Collectively, these findings highlight the importance of an early adaptive immune response for bacterial containment during S. aureus craniotomy infection by promoting the antimicrobial activity of infiltrating leukocytes and resident microglia.

Interictal High Gamma Oscillation Regularity as a Marker for Presurgical Epileptogenic Zone Localization.

To ensure that epilepsy surgery is effective, accurate presurgical localization of the epileptogenic zone is essential. Our previous reports demonstrated that interictal high gamma oscillation (30-70 Hz) regularity (GOR) on intracranial electroencephalograms is related to epileptogenicity. To examine whether preoperative GOR analysis with interictal high-density electroencephalography (HD-EEG) improves the accuracy of epileptogenic focus localization and enhances postoperative seizure control. We calculated GOR from 20 seconds of HD-EEG data for 21 patients with refractory focal epilepsy (4 with nonlesional temporal lobe epilepsy) scheduled for epilepsy surgery. Low-resolution brain electromagnetic tomography was used to analyze the high GOR source. To validate our findings, we made comparisons with other conventional localization methods and postoperative seizure outcomes. In all patients, the areas of interictal high GOR were identified and resected. All patients were seizure-free after the operation. The concordance between the results of interictal high GOR on HD-EEG and those of source estimation of interictal discharge was fully overlapping in 10 cases, partially overlapping in 8 cases, and discordant in 3 cases. The concordance between the results of interictal high GOR on HD-EEG and those of interictal 123 I-iomazenil single-photon emission computed tomography was fully overlapping in 8 cases, partially overlapping in 11 cases, and discordant in 2 cases. In 4 patients with nonlesional temporal lobe epilepsy, the interictal high GOR on HD-EEG was useful in confirming the epileptogenic zone. The interictal high GOR on HD-EEG is an excellent marker for presurgical epileptogenic zone localization.

Utility of 3D Double Inversion Recovery Sequence in Paediatric Epilepsy and its Comparison to 3D Fluid Attenuation Inversion Recovery Sequence and T1 Inversion Recovery Sequence : A Cross-sectional Study

Introduction: Epilepsy is a disease with predisposition to generate epileptic seizures, associated with neurobiological, cognitive, psychological, and social consequences. Nearly 30% of children undergoing medical treatment for epilepsy become refractive to the treatment. For those children, the ability to find the epileptogenic area is higher with Magnetic Resonance Imaging (MRI) of the brain. The traditional 2D spin-echo sequences used in epilepsy protocol for adults cannot be used alone in paediatric structural neuroimaging. Additional sequences are needed to identify epileptogenic areas due to differences in myelination. Here, present study compared the role of three volumetric sequences 3D-Fluid Attenuated Inversion Recovery (FLAIR) , 3D-T1 weighted Inversion Recovery (T1-IR) and 3D-Double Inversion Recovery (DIR) for paediatric epilepsy as part of structural neuroimaging. Aim: To assess the utility of 3D-DIR in paediatric epilepsy disorders and localisation of epileptogenic foci in brain, congenital malformations of brain and compare its findings with 3D-FLAIR and 3D-T1-IR. Materials and Methods: The present study was a cross-sectional study of children diagnosed with paediatric epilepsy, who were evaluated with MRI brain at Stanley Medical College, Chennai, Tamil Nadu, India, between April 2020 to April 2021 with three sequences, 3D-DIR, 3D-T1-IR and 3D-FLAIR. Lesions of atleast 3 mm in diameter were identified as foci of high signal intensity and counted in each of the three sequences separately and classified according to their location. Then, average signal intensities of the lesions were calculated manually on each of sequences using Region of Interest (ROI) analysis which had a mean size of 3 mm2 . Then the Signal-to-Noise Ratio (SNR), Contrast to-Noise Ratio (CNR), Contrast Ratio (CR), and Asymmetry Signal Ratio (ASR) were calculated. Results: Evaluation was done on 51 paediatric epilepsy patients and showed the total number of lesions detected (208 lesions) and measured contrast parameters (CR, CNR and ASR) which were found to be significantly higher in 3D-DIR, showed higher detection of the intracortical and white matter lesions than 3DFLAIR and 3D-T1-IR. SNR was higher in 3D-FLAIR. Conclusion: Present study concluded that the greatest value of the DIR sequence has a higher ability in detecting epileptogenic foci and congenital malformations of the lesions in comparison with FLAIR and T1-IR.

High-resolution pediatric age\u2013specific 18F-FDG PET template: a pilot study in epileptogenic focus localization

BackgroundPET imaging has been widely used in diagnosis of neurological disorders; however, its application to pediatric population is limited due to lacking pediatric age–specific PET template. This study aims to develop a pediatric age–specific PET template (PAPT) and conduct a pilot study of epileptogenic focus localization in pediatric epilepsy.MethodsWe recruited 130 pediatric patients with epilepsy and 102 age-matched controls who underwent 18F-FDG PET examination. High-resolution PAPT was developed by an iterative nonlinear registration-averaging optimization approach for two age ranges: 6–10 years (n = 17) and 11–18 years (n = 50), respectively. Spatial normalization to the PAPT was evaluated by registration similarities of 35 validation controls, followed by estimation of potential registration biases. In a pilot study, epileptogenic focus was localized by PAPT-based voxel-wise statistical analysis, compared with multi-disciplinary team (MDT) diagnosis, and validated by follow-up of patients who underwent epilepsy surgery. Furthermore, epileptogenic focus localization results were compared among three templates (PAPT, conventional adult template, and a previously reported pediatric linear template).ResultsSpatial normalization to the PAPT significantly improved registration similarities (P < 0.001), and nearly eliminated regions of potential biases (< 2% of whole brain volume). The PAPT-based epileptogenic focus localization achieved a substantial agreement with MDT diagnosis (Kappa = 0.757), significantly outperforming localization based on the adult template (Kappa = 0.496) and linear template (Kappa = 0.569) (P < 0.05). The PAPT-based localization achieved the highest detection rate (89.2%) and accuracy (80.0%). In postsurgical seizure-free patients (n = 40), the PAPT-based localization also achieved a substantial agreement with resection areas (Kappa = 0.743), and the highest detection rate (95%) and accuracy (80.0%).ConclusionThe PAPT can significantly improve spatial normalization and epileptogenic focus localization in pediatric epilepsy. Future pediatric neuroimaging studies can also benefit from the unbiased spatial normalization by PAPT.Trial registration.NCT04725162: https://clinicaltrials.gov/ct2/show/NCT04725162

International consensus on the use of [18F]-FDG PET/CT in pediatric patients affected by epilepsy.

Positron emission tomography (PET) with 18F-fluorodeoxyglucose ([18F]-FDG) hasbeen increasingly applied in precise localization of epileptogenic focus in epilepsypatients, including pediatric patients. The aim of this international consensus is toprovide the guideline and specific considerations for [18F]-FDG PET in pediatricpatients affected by epilepsy. An international, multidisciplinary task group is formed, and the guideline for brain [18F]-FDG PET/CT in pediatric epilepsy patients has been discussed and approved, whichinclude but not limited to the clinical indications, patient preparation,radiopharmaceuticals and administered activities, image acquisition, image processing,image interpretation, documentation and reporting, etc. CONCLUSION: This is the first international consensus and practice guideline for brain [18F]-FDGPET/CT in pediatric epilepsy patients. It will be an international standard for thispurpose in clinical practice.

Advances in Brain Imaging Techniques for Patients With Intractable Epilepsy.

Intractable epilepsy, also known as drug resistance or refractory epilepsy, is a major problem affecting nearly one-third of epilepsy patients. Surgical intervention could be an option to treat these patients. Correct identification and localization of epileptogenic foci is a crucial preoperative step. Some of these patients, however, have no abnormality on routine magnetic resonance imaging (MRI) of the brain. Advanced imaging techniques, therefore, can be helpful to identify the area of concern. Moreover, a clear delineation of certain anatomical brain structures and their relation to the surgical lesion or the surgical approach is essential to avoid postoperative complications, and advanced imaging techniques can be very helpful. In this review, we discuss and highlight the use of advanced imaging techniques, particularly positron emission tomography (PET)–MRI, single-photon emission computed tomography, functional MRI, and diffusion tensor imaging–tractography for the preoperative assessment of epileptic patients.

Epileptic olfactory auras: a clinical spectrum

To investigate the relative frequency of olfactory aura in a large number of patients with focal epilepsy, and examine the full clinical spectrum of epileptic olfactory auras (OAs) and their relationship to hemispheric lateralization and localization of epileptogenic focus. This retrospective study was based on the medical records of 1384 patients with focal epilepsy. Of these, 71 (5.1%) patients were present with OAs, comprising 25 (35.2%) men and 46 (64.8%) women with a mean age of 35.43 ± 12.89years. These 71 patients were classified according to the clinical features of the OAs, and the electroencephalography and magnetic resonance imaging findings were examined. The relative frequency of OAs was 5.1% in the focal epileptic patients. The clinical spectrum of OAs in our cases was outlined as follows, complex OAs and elementary OAs. Elementary OAs were divided into three subgroups: elementary neutral OAs, elementary unpleasant OAs, and elementary pleasant OAs. In our cases, there was no difference between the right and left hemispheres in terms of lateralization of the epileptogenic focus. In all the 71 patients, the epileptogenic zone was most commonly localized in the temporal lobe (n = 58; 81.7%). The relative frequency of OAs in focal epilepsies is likely to be found higher than expected. Elementary OAs occur much more frequently than complex OAs. Among the elementary OAs, elementary unpleasant OAs and elementary neutral OAs are the most common types, whereas elementary pleasant OAs are extremely rare.

A comparative study of recent neuroimaging techniques to show temporal region is the most common site in focal epilepsy irrespective of age

Epilepsy is a chronic disease characterized by recurrent seizures that may affect 2% of the population classification of seizures based solely on EEG and clinical findings can result in the misclassification of some patients, particularly those individuals with partial seizures that rapidly generalize. The information provided by imaging techniques can contribute to the proper classification of certain epileptic disorders in non-invasive localisation of epileptogenic foci. Neuroimaging has an important role in the investigation, localisation and treatment of patients with epilepsy. It is presently recognized that epilepsy is often associated with gross or subtle structural or metabolic lesions of the brain. Neuroimaging is mandatory in the work-up of epilepsy for localisation of the seizure focus for possible surgical cure. In this study it was concluded that that temporal lobe is most common site as epileptic lesion by different neuroimaging techniques. Keywords: EEG, Electroencephalography, PET, Positron emission tomography, CT, Computed tomography, MRI, Magnetic resonance imaging, MRS, MR spectroscopy.

The value of rapid eye movement sleep in the localization of epileptogenic foci for patients with focal epilepsy

PurposeOur aim was to investigate the value of rapid eye movement (REM) during prolonged scalp video-electroencephalography (VEEG) in the localization of epileptogenic foci for patients with focal epilepsy. MethodWe retrospectively studied a total of 59 patients with focal epilepsy and 31 of 59 received surgery. We assessed localization of interictal epileptiform discharges (IEDs) during REM, non–rapid eye movement sleep (NREM) and wakefulness to compare with the localization of ictal EEG, clinical semiology, magnetic resonance imaging (MRI) and positron emission tomography (PET) and stereo-electroencephalogram (SEEG). We graded postoperative follow-up outcome according to Engel criteria to further verify the accuracy of localization of epileptogenic foci in REM-IEDs. NREM-IEDs and Wakefulness-IEDs. Stepwise multiple logistic regression was carried out to assess for independent association of good prognosis with REM accurate localization, temporal lobe epilepsy and MRI accurate localization. ResultsClinical semiology was concordant to REM‐IEDs in 40 patients (72.7 %), NREM‐IEDs in 27 (49.1 %), and Wakefulness‐IEDs in 25 (45.5 %). MRI lesion was concordant with REM‐IEDs in 35 patients (81.4 %), Wakefulness‐IEDs in 26 (60.5 %), and NREM‐IEDs in 25 (58.1 %). PET localization was concordant with REM‐IEDs in 20 patients (76.9 %), Wakefulness‐IEDs and NREM‐IEDs in 11 (42.3 %). SEEG localization was concordant with REM-IEDs in 15 patients (65.2 %), Wakefulness‐IEDs in 10 (43.5 %), and NREM‐IEDs in 8 (34.8 %). Thirty-one patients received surgery, and 30 (96.8 %) of them achieved good seizure control (Engel I-III). The surgical site was concordant with REM‐IEDs in 23 (74.2 %), Wakefulness‐IEDs and NREM‐IEDs in 14 (45.2 %). In addition, the accuracy of REM-IEDs localization in temporal epilepsy (90 %) was higher than that extra-temporal epilepsy (45.5 %). REM accurate localization of epileptogenic foci was an independent factor contributing to good prognosis (P = 0.025, OR = 12.368). ConclusionsCompared with NREM-IEDs and Wakefulness-IEDs, REM-IEDs had most value for localization of epileptogenic foci in patients with focal epilepsy. REM-IEDs- accurate localization of epileptogenic foci was an independent factor contributing to good prognosis for postsurgical patients with focal epilepsy.

Does Tc-99m ECD ictal brain SPECT have incremental value in localization of epileptogenic zone and predicting postoperative seizure freedom in cases with discordant video electroencephalogram and MRI findings?

Localization of epileptogenic focus in drug-refractory epilepsy using Tc-99m ethylene cystine dimer (ECD) brain single photon emission computed tomography (SPECT) is less studied in patients with discordant findings on video electroencephalogram (VEEG) and MRI. The study was done to evaluate brain SPECT for epileptogenic focus localization and postoperative seizure freedom. Epilepsy patients with discordant VEEG and MRI findings underwent brain SPECT at ictal and interictal phases. Various groups unilateral/bilateral mesial temporal sclerosis (MTS), solitary and multifocal lesional, nonlesional epilepsy were studied for localization of epileptogenic focus and postoperative seizure freedom (>2 years) using Engels classification. Reasons for nonoperability was evaluated in nonoperated group. SPECT could localize epileptogenic focus in 49/67 (73.13%) and guided surgery in 19/33 (57.57%) patients in operated group. SPECT was useful in 12 (46.12%) of unilateral (2)/bilateral (10) MTS. Postoperative seizure freedom of Engels Class I and II in 22 (66.67%), III in six (18.2%) and IV in one patient based on SPECT findings (P = 0.0086). Overall sensitivity and specificity were 79.3% and 85.7%, respectively. SPECT could localize epileptogenic focus in 23/34 (67.64%) patients in nonoperated group; 10 (29.41%) patients refused for surgery and no epileptogenic focus was localized in the rest of 14 (41.2%). Ictal SPECT showed incremental value and was found necessary for epileptogenic focus localization and subsequent surgery in unilateral/bilateral MTS in this study. Seizure freedom in patients undergoing epilepsy surgery based on ictal SPECT assistance was comparable to the surgical group not requiring ictal SPECT.

High resolution functional localization of epileptogenic focus with glutamate and electrical signals detection by ultramicroelectrode arrays

Epileptogenic focus is the predominant brain area to form seizures, while it is very difficult to be located precisely with existing technology. Dual-mode neural signals involving neurotransmitter release and electrical signals for high resolution functional localization of epileptogenic focus accurately remains an unsolved tough problem. In this work, an implantable ultramicroelectrode array (UMEA) with high resolution was fabricated for epileptogenic focus functional localization based on multiple neural activities involving glutamate concentration, neural spike pattern and local field potential (LFP) power. A higher signal to noise ratio (D = 1 μm, S/N = 7.93) is obtained comparing with our previous microelectrodes (D = 25 μm, S/N = 3.39). Abnormality occurred in the epileptic brains even without seizure by comparing with normal ones. The subcellular recording of neural activities from cortex to thalamus demonstrated that a higher value of Glu concentration, spike firing rate, spike amplitude and LFP power is obtained at hippocampus CA3 and dentate gyrus (DG) than other regions, which is considered as the origination of epileptogenic focus. This dual-mode neural activities used for functional localization at high spatiotemporal resolution, especially with the release of neurotransmitter, provide us with a platform for high-precision surgical planning and treatment.

Research on information sensing of PET monoamine receptor imaging in measuring childhood epilepsy health

Abstract To explore the information sensing of 1 of 18F-FDG PET / CT brain metabolic imaging in measuring preoperative localization of childhood epilepsy focus and surgical decision-making. The clinical data of 69 childhood patients who underwent 18F-FDG PET / CT brain metabolism imaging measurement in our hospital from June 2013 to September 2019 were retrospectively analysed to evaluate 18F-FDG PET / CT brain metabolism. The application value of imaging in the localization of epilepsy-induced epilepsy, and compared with MRI, explore the application value of 18F-FDG PET / CT brain metabolic imaging in epilepsy focus location and surgical treatment options before epilepsy surgery. Of the 69 patients, 53 patients had positive 18F-FDG PET / CT brain metabolic imaging, 16 patients showed negative, and the epilepsy foci were accurately located in 48 patients, and some of them were partially detected. For epilepsy foci, 18F-FDG PET / CT brain metabolic imaging has a consistent localization rate of 73.9% (51/69). 43 cases were positive by magnetic resonance examination, accurate positioning of the epileptogenic focus in 38 children, and partial positioning of 3 children. The consistent rate of localization of the epileptogenic focus was 59.4% (41/69). 18F-FDG PET / CT brain the coincidence rate of metabolic and MRI examinations was 76.8% (53/69). After Kappa consistency test, Kappa = 0.466. 18F-FDG PET / CT brain metabolism imaging has higher consistency in the location of epilepsy focus and electrophysiological examination before refractory epilepsy, which is better than MRI examination. The combined use of the two examinations can improve preoperative epilepsy. The positioning of the foci helps clinicians to choose suitable children for surgery and exclude children who are not suitable for surgery.

Comparison of EMD, DWT and WPD for the localization of epileptogenic foci using Random Forest classifier

Localization of epileptogenic foci is an essential phase in surgical treatment planning using the earliest time detection of the seizure onset in the recordings of electroencephalogram (EEG). These recordings are defined as the areas of the brain which can be surgically removed to reach control of seizure. The characteristics of the brain area affected by partial epilepsy can be analyzed using focal and non-focal EEG signals. In this work, a method for the classification of focal and non-focal EEG signals is presented to compare different feature extraction methods combined with multi-scale principal component analysis (MSPCA) denoising and Random Forest (RF) as a machine learning technique. After de-noising, different feature extraction methods (EMD, DWT and WPD) are applied. The performance of RF classifier is measured according to accuracy, the area under the Receiver Operating Characteristics (ROC) curve (AUC) and F-measure. EEG based focal region localization with Wavelet Packet Decomposition (WPD) feature extraction and RF classifier reach 99.92% accuracy. Hence, WPD combined with RF machine learning classifier can be used to differentiate the focal and non-focal EEG signals.