Seizure-free Patients Research Articles

Virtual implantation using conventional scalp EEG delineates seizure onset and predicts surgical outcome in children with epilepsy

ObjectiveDelineation of the seizure onset zone (SOZ) is required in children with drug resistant epilepsy (DRE) undergoing neurosurgery. Intracranial EEG (icEEG) serves as gold standard but has limitations. Here, we examine the utility of virtual implantation with electrical source imaging (ESI) on ictal scalp EEG for mapping the SOZ and predict surgical outcome. MethodsWe retrospectively analyzed EEG data from 35 children with DRE who underwent surgery and dichotomized into seizure-free (SF) and non-seizure-free (NSF). We estimated virtual sensors (VSs) at brain locations that matched icEEG implantation and compared ictal patterns at VSs vs icEEG. We calculated the agreement between VSs SOZ and clinically defined SOZ and built receiver operating characteristic (ROC) curves to test whether it predicted outcome. ResultsTwenty-one patients were SF after surgery. Moderate agreement between virtual and icEEG patterns was observed (kappa = 0.45, p < 0.001). Virtual SOZ agreement with clinically defined SOZ was higher in SF vs NSF patients (66.6% vs 41.6%, p = 0.01). Anatomical concordance of virtual SOZ with clinically defined SOZ predicted outcome (AUC = 0.73; 95% CI: 0.57–0.89; sensitivity = 66.7%; specificity = 78.6%; accuracy = 71.4%). ConclusionsVirtual implantation on ictal scalp EEG can approximate the SOZ and predict outcome. SignificanceSOZ mapping with VSs may contribute to tailoring icEEG implantation and predict outcome.

Altered Temporal Variations of Functional Connectivity Associated With Surgical Outcomes in Drug-Resistant Temporal Lobe Epilepsy.

BackgroundCurrently, more than one-third of patients with drug-resistant temporal lobe epilepsy (TLE) continue to develop seizures after resection surgery. Dynamic functional network connectivity (DFNC) analyses, capturing temporal properties of functional connectivity during MRI acquisition, may help us identify unfavorable surgical outcomes. The purpose of this work was to explore the association of DFNC variations of preoperative resting-state MRI and surgical outcomes in patients with drug-resistant TLE.MethodsWe evaluated 61 patients with TLE matched for age and gender with 51 healthy controls (HC). Patients with TLE were classified as seizure-free (n = 39) and not seizure-free (n = 16) based on the Engel surgical outcome scale. Six patients were unable to confirm the postoperative status and were not included in the subgroup analysis. The DFNC was calculated using group spatial independent component analysis and the sliding window approach.ResultsDynamic functional network connectivity analyses suggested two distinct connectivity “States.” The dynamic connectivity state of patients with TLE was different from HC. TLE subgroup analyses showed not seizure-free (NSF) patients spent significantly more time in State II compared to seizure-free (SF) patients and HC. Further, the number of transitions from State II to State I was significantly lower in NSF patients. SF patients had compensatory enhancement of DFNC strengths between default and dorsal attention network, as well as within the default network. While reduced DFNC strengths of within-network and inter-network were both observed in NSF patients, patients with abnormally temporal properties and more extension DFNC strength alterations were less likely to receive seizure freedom.ConclusionsOur study indicates that DFNC could offer a better understanding of dynamic neural impairment mechanisms of drug-resistant TLE functional network, epileptic brain network reorganization, and provide an additional preoperative evaluation support for surgical treatment of drug-resistant TLE.

Questionnaire-based assessment of sleep disorders in an adult population of Tuberous Sclerosis Complex

Background and objectiveTuberous Sclerosis Complex (TSC) is a rare systemic disease with a high prevalence of sleep disorders (SD), although they are still largely under-recognized. The objective of this study was to assess the prevalence of SD in adult patients with TSC, and to evaluate the relationship between sleep, epilepsy, and TSC associated neuropsychiatric disorders (TAND). Materials and methodsWe administered Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI) and Epworth Sleepiness Scale (ESS) to 114 adult patients referring to different Italian centers. We also collected information on epilepsy and TAND. ResultsPSQI, ISI, and ESS revealed a positive score, respectively, in 52 (46.0%), 30 (26.5%), and 16 (14.1%) patients.PSQI was positive in 26.7% of seizure free patients versus 61.9% with active epilepsy (p = 0.003), and the association remained significative applying a multivariate logistic model considering age, antiseizure medications, TAND and nocturnal epileptic seizures (p = 0.02). ISI was positive in 3.3% of seizure free patients versus 41.3% with active epilepsy (p = 0.0004). Applying a multivariate logistic model with the independent variables listed above, the association remained significant (p = 0.007).On the other hand, multivariate logistic model considering active epilepsy as an independent variable, revealed that TAND didn't appear a significant risk factor for positive PSQI (p = 0.43) nor ISI (p = 0.09). ConclusionsOur results confirmed that SD are highly prevalent in adults with TSC, with active epilepsy acting as a significant risk factor. A careful assessment of sleep, above all in epileptic patients, is of crucial importance.

Predictors of hyperkinetic seizures

ObjectiveTo identify predisposing factors for hyperkinetic seizure occurrence in a representative cohort of surgically treated patients with drug-resistant focal epilepsy. MethodsWe retrospectively recruited all seizure-free patients after epilepsy surgery with a postoperative follow-up ≥12 months. Patients were classified as presenting with hyperkinetic seizures if at least 2 episodes occurred during their disease history, based on clear-cut anamnestic description and/or video-EEG/stereo-EEG recordings. We performed univariable and multivariable logistic regression models to study the association between the occurrence of hyperkinetic seizures and some predictors. ResultsFrom a pool of 1758 consecutive patients who underwent surgery from 1996 to 2017, we identified 974 seizure-free cases. Considering at least 1-year follow-up, 937 cases were included (511 males, 91 patients with hyperkinetic seizures). Variables significantly associated with an increased risk of hyperkinetic seizure occurrence were (1) presence of epilepsy with sleep-related seizures (SRE) (P < 0.001); (2) histological diagnosis of type II focal cortical dysplasia (FCD) (P < 0.001); (3) resection including the frontal lobe (P = 0.002) (4) duration of epilepsy at surgery (P < 0.001) and (5) high seizure frequency at surgery (weekly: P = 0.02 – daily: P = 0.05). A resection including the occipital lobe reduced the risk of hyperkinetic seizures (P = 0.05). About 63% of patients had hyperkinetic seizure onset before 12 years and it was rarely reported before 5 years of age. SignificanceOur findings underlie the role of SRE, type II FCD and frontal epileptogenic zone as predictors of hyperkinetic seizure occurrence and highlight an age-dependent effect in favoring hyperkinetic manifestations.

Validation of direct cortical stimulation in presurgical evaluation of epilepsy

ObjectiveDirect cortical stimulation (DCS) is standard for intracranial presurgical evaluation in drug-resistant epilepsy (DRE). Few studies have reported levels of concordance between spontaneous seizure generators and triggered seizures during DCS. The present work reports validity measures of DCS for detecting the seizure onset zone (SOZ) during stereoelectroencephalography (SEEG). MethodsWe evaluated all patients who underwent SEEG evaluation at our epilepsy center between 2013 and 2019. Data were analyzed using contingency tables. Validity measures of the diagnostic test were computed for all patients evaluated with DCS and for seizure free patients. ResultsFifty-eight consecutive patients were evaluated through DCS. One hundred seventy-three clinical seizures were elicited with DCS. Electroclinical identical to spontaneous seizures were considered true positive (TP) seizures. They showed a high specificity (96.9%) for detecting the SOZ in patients that remained seizure free one year after treatment. Sensitivity was low (23.0%), and a high percentage of false-negative stimulations was documented in the SOZ. The accuracy was 87.9%. ConclusionsDCS is a technique with high specificity but a low sensitivity for the localization of the SOZ. The DCS validity measures need to be known when considered for surgical decisions. The interpretation of DCS-triggered seizures and the differentiation of true-positive vs false-positive seizures should be carefully evaluated. SignificanceDCS seizure triggering is highly specific for SOZ localization.

OC05: Measuring the effects of first antiepileptic medication in Temporal Lobe Epilepsy: Predictive value of quantitative-EEG analysis

To determine the quantitative EEG responses in a population of drug-naïve patients with Temporal Lobe Epilepsy (TLE) after Levetiracetam (LEV) initiation as first antiepileptic drug (AED). We hypothesized that the outcome of AED treatment can be predicted from EEG data in patients with TLE. Methods: Twenty-three patients with TLE and twenty-five healthy controls were examined. Clinical outcome was dichotomized into seizure-free (SF) and non-seizure-free (NSF) after two years of LEV. EEG parameters were compared between healthy controls and patients with TLE at baseline (EEGpre) and after three months of AED therapy (EEGpre-post) and between SF and NSF patients. Receiver Operating Characteristic curves models were built to test whether EEG parameters predicted outcome. Results: AED therapy induces an increase in EEG power for Alpha (p = 0.06) and a decrease in Theta (p < 0.05). Connectivity values were lower in SF compared to NSF patients (p < 0.001). Quantitative EEG predicted outcome after LEV treatment with an estimated accuracy varying from 65.2% to 91.3% (area under the curve [AUC] = 0.56–0.93) for EEGpre and from 69.9% to 86.9% (AUC = 0.69–0.94) for EEGpre-post. Conclusions: AED therapy induces EEG modifications in TLE patients, and such modifications are predictive of clinical outcome. Significance: Quantitative EEG may help understanding the effect of AEDs in the central nervous system and offer new prognostic biomarkers for patients with epilepsy.

SEEG in 3D: Interictal Source Localization From Intracerebral Recordings

BackgroundStereo-electroencephalography (SEEG) uses a three-dimensional configuration of depth electrodes to localize epileptiform activity, but traditional analysis of SEEG is spatially restricted to the point locations of the electrode contacts. Interpolation of brain activity between contacts might allow for three-dimensional representation of epileptiform activity and avoid pitfalls of SEEG interpretation.ObjectiveThe goal of this study was to validate SEEG-based interictal source localization and assess the ability of this technique to monitor far-field activity in non-implanted brain regions.MethodsInterictal epileptiform discharges were identified on SEEG in 26 patients who underwent resection, ablation, or disconnection of the suspected epileptogenic zone. Dipoles without (free) and with (scan) gray matter restriction, and current density (sLORETA and SWARM methods), were calculated using a finite element head model. Source localization results were compared to the conventional irritative zone (IZ) and the surgical treatment volumes (TV) of seizure-free vs. non-seizure-free patients.ResultsThe median distance from dipole solutions to the nearest contact in the conventional IZ was 7 mm (interquartile range 4–15 mm for free dipoles and 4–14 mm for scan dipoles). The IZ modeled with SWARM predicted contacts within the conventional IZ with 83% (75–100%) sensitivity and 94% (88–100%) specificity. The proportion of current within the TV was greater in seizure-free patients (P = 0.04) and predicted surgical outcome with 45% sensitivity and 93% specificity. Dipole solutions and sLORETA results did not correlate with seizure outcome. Addition of scalp EEG led to more superficial modeled sources (P = 0.03) and negated the ability to predict seizure outcome (P = 0.23). Removal of near-field data from contacts within the TV resulted in smearing of the current distribution (P = 0.007) and precluded prediction of seizure freedom (P = 0.20).ConclusionsSource localization accurately represented interictal discharges from SEEG. The proportion of current within the TV distinguished between seizure-free and non-seizure-free patients when near-field recordings were obtained from the surgical target. The high prevalence of deep sources in this cohort likely obscured any benefit of concurrent scalp EEG. SEEG-based interictal source localization is useful in illustrating and corroborating the epileptogenic zone. Additional techniques are needed to localize far-field epileptiform activity from non-implanted brain regions.

Sustained seizure freedom with adjunctive perampanel in patients with convulsive seizures: Post hoc analysis of open-label extension studies 307 and 332

ObjectiveSince increased mortality rates have been associated with convulsive seizures, it is important to achieve seizure control in these patients. Here, we report post hoc analyses to assess long-term seizure-freedom rates with adjunctive perampanel in patients (aged ≥ 12 years) with refractory focal to bilateral tonic-clonic seizures (FBTCS) or generalized tonic-clonic seizures (GTCS) who participated in open-label extension (OLEx) studies. MethodsPatients with focal-onset seizures, with/without FBTCS, who completed double-blind, Phase III Studies 304, 305, or 306 could enter OLEx Study 307 (16-week blinded Conversion; 256-week Maintenance). Patients with GTCS who completed the double-blind phase of Study 332 could enter the OLEx Phase (6-week blinded Conversion; 136-week Maintenance). Maximum perampanel dose: 12 mg/day. Seizure-freedom rates for up to 24 months were assessed in perampanel-treated patients who achieved seizure freedom during the double-blind studies to determine if their seizure-free status was maintained during the OLEx. In addition, to ensure any patients who only achieved seizure freedom during the OLEx were captured, seizure-freedom rates were also assessed in all patients who achieved and maintained a seizure-free status for a period of at least six consecutive months at any time during the double-blind and/or OLEx studies; some of these patients may have received placebo during the double-blind study but only their time on perampanel is included in the seizure-free analysis. Univariate and multivariate analyses were used to identify predictive factors for achieving seizure freedom for at least 6 months. Treatment-emergent adverse events (TEAEs) were assessed. ResultsOverall, 53.8% (n = 42/78) of patients who received perampanel and were FBTCS free during the double-blind studies remained seizure free for up to 24 months during Study 307, and 31.6% (n = 6/19) of patients who were GTCS free during the double-blind phase of Study 332 remained seizure free for up to 24 months during the OLEx Phase. Over 40% (FBTCS, 41.5% [n = 197/475]; GTCS, 52.9% [n = 73/138]) of patients were seizure free for a period of at least six consecutive months. Multivariate analysis showed that the best predictors of achieving seizure freedom from FBTCS for at least 6 months were lower baseline seizure frequency (p = 0.0014) and absence of enzyme-inducing anti-seizure medications at baseline (p = 0.0056); multivariate analysis was not conducted for GTCS since only one variable was identified as a significant predictor of seizure freedom in the univariate analysis (lower baseline seizure frequency).Perampanel was generally well tolerated with no new safety signals identified. The most common TEAE was dizziness. For both seizure types, 10% or fewer seizure-free patients discontinued perampanel due to TEAEs. ConclusionsThese results suggest that adjunctive perampanel may be a suitable long-term treatment option for patients (aged ≥ 12 years) with convulsive seizures to achieve and maintain seizure freedom.

EuroQOL-5D-3L does not adequately map quality-of-life deterioration in severely affected patients with epilepsy

IntroductionThe steadily increasing impact of health-related quality of life (HRQOL) on reasonable diagnostic and therapeutic decisions makes the correct mapping of HRQOL indispensable in modern epileptology. The aim of this study was to address the reliability of the often-used generic HRQOL screening questionnaire EuroQOL 5-dimension, 3-level (EQ-5D-3L) by comparing its normalized index value (calculated via the time trade-off method) and visual analog scale (VAS) to the gold standard of the extensive Quality of Life in Epilepsy Inventory (QOLIE-31). QOLIE-10 scores were compared with the extensive QOLIE-31 and EQ-5D-3L TTO. MethodsWe conducted a retrospective analysis of a monocentric study of 184 patients with epilepsy. Bivariate Spearman correlation analysis and Fisher’s r-to-z transformation were used to compare the strengths of correlations of EQ-5D-3L, QOLIE-10 and QOLIE-31 with different epilepsy-specific domains (disease severity, drug interactions, emotional well-being, stigmatization, seizure-related anxiety, cognitive impairment). ResultsThe different metrics of EQ-5D-3L, QOLIE-10 and QOLIE-31 showed moderate to very strong intra- and inter-metric correlations for overall HRQOL. Quality of Life in Epilepsy Inventory-31 VAS and EQ-5D-3L VAS did not show any significantly different strengths of correlations with respect to the domains studied. In contrast, the correlation strength of the normalized EQ-5D-3L index value differed significantly from the QOLIE-31 T-score for several domains, for example, for drug-related adverse events, neuropsychological deficits, symptoms of depression and seizure worry. In seizure-free patients, EQ-5D-3L VAS and EQ-5D-3L index values correlated significantly less with the domain of “cognitive impairment” than the QOLIE-31 T-score. In patients without relevant neuropsychological deficits, the strengths of correlations with the assessed domains did not differ significantly between EQ-5D-3L metrics and the QOLIE-31 T-score. The HRQOL mapping probability of QOLIE-10 was inferior to QOLIE-31 and comparable to EQ-5D-3L regarding the analyzed domains. ConclusionIn contrast to the EQ-5D-3L VAS, EQ-5D-3L index values do not adequately map health-related quality of life in severely affected patients with epilepsy and therefore should not be used as screening tools. The QOLIE-31 T-score remains the gold standard for HRQOL assessment in patients with epilepsy.

For Seizure-Free Patients Taking Antiseizure Medication, When to Consider Medication Withdrawal?

For Seizure-Free Patients Taking Antiseizure Medication, When to Consider Medication Withdrawal?

Abnormal functional connectivity profiles predict drug responsiveness in patients with temporal lobe epilepsy.

This work was undertaken to study the functional connectivity differences between non-seizure-free and seizure-free patients with temporal lobe epilepsy (TLE) and to identify imaging predictors for drug responsiveness in TLE. In this prospective study, 52 patients with TLE who presented undetermined antiseizure medication responsiveness and 55 demographically matched healthy controls were sequentially recruited from Xiangya Hospital. Functional magneticresonanceimaging data were acquired during a Chinese version of the verbal fluency task. The patients were followed up until the outcome could be classified. The subject groups were compared in terms of activation profile, task-residual functional connectivity (trFC), and generalized psychophysiological interaction (gPPI) analyses. Moreover, we extracted imaging characteristics for logistic regression and receiver operating characteristic evaluation. With a mean follow-up of 1.1years, we identified 27 non-seizure-free patients and 19seizure-free patients in the final analyses. The Chinese character verbal fluency task successfully activated the language network and cognitive control network (CCN) and deactivated the default mode network (DMN). In the non-seizure-freedom group, the trFC between the hippocampus and bilateral brain networks was attenuated (p<.05, familywise error corrected). For the gPPI analysis, group differences were mainly located in the precuneus, middle frontal gyrus, and inferior parietal lobule (p<.001, uncorrected; k ≥ 10). The regression model presented high accuracy when predicting non-seizure-free patients (area under the curve = .879, 95% confidence interval = .761-.998). In patients with TLE who would not achieve seizure freedom with current antiseizure medications, the functional connectivity between the hippocampus and central nodes of the DMN, CCN, and language network was disrupted, leading to language decline. Independent of hippocampal sclerosis, abnormalities, especially the effective connectivity from the hippocampus to the DMN, were predictive biomarkers of drug responsiveness in patients with TLE.

Antiseizure Medication Withdrawal in Seizure-Free Patients: Practice Advisory Update Summary: Report of the AAN Guideline Subcommittee.

To update a 1996 American Academy of Neurology practice parameter. The authors systematically reviewed literature published from January 1991 to March 2020. The long-term (24-60 months) risk of seizure recurrence is possibly higher among adults who have been seizure-free for 2 years and taper antiseizure medications (ASMs) vs those who do not taper ASMs (15% vs 7% per the 1 Class I article addressing this issue). In pediatric patients, there is probably no significant difference in seizure recurrence between those who begin tapering ASMs after 2 years vs 4 years of seizure freedom, and there is insufficient evidence of significant difference in risk of seizure recurrence between those who taper ASMs after 18 months of seizure freedom and those tapering after 24 months. There is insufficient evidence that the rate of seizure recurrence with ASM withdrawal following epilepsy surgery after 1 year of seizure freedom vs after 4 years is not significantly different than maintaining patients on ASMs. An epileptiform EEG in pediatric patients increases the risk of seizure recurrence. ASM withdrawal possibly does not increase the risk of status epilepticus in adults. In seizure-free adults, ASM weaning possibly does not change quality of life. Withdrawal of ASMs at 25% every 10 days to 2 weeks is probably not significantly different from withdrawal at 25% every 2 months in children who are seizure-free in more than 4 years of follow-up. Fourteen recommendations were developed.

Disparate properties of afterdischarges elicited by electric cortical stimulation in MRI lesional epilepsy patients with different surgical outcomes

PurposeThe purpose of this study was to demonstrate the prognostic value of afterdischarges(ADs) on surgical outcome by comparing the disparate properties in epilepsy patients with different surgical outcomes Methods27 lesional epilepsy patients were retrospectively analyzed. The brain region covered by subdural electrodes in each patient was dichotomized into the area of the brain lobe(s) where the MRI lesion is located (region ML) and other brain areas (region nML). The occurrence of ADs and ADs evolving into clinical seizure, ADs threshold and ADs duration in region ML and nML were compared between seizure-free (SF) and non-seizure-free (nSF) patients. ResultsA total of 2535 contacts were analyzed, and the total occurrence of ADs was 18.6% (471/2535). The overall occurrence of ADs in region ML (24.8%) was significantly higher than that in region nML (10.3%) (P < 0.001). In region ML, compared with SF patients, nSF patients had a lower occurrence of ADs (19.2% vs. 31.2%, P < 0.001), a higher occurrence of ADs evolves into clinical seizure (8.7% vs. 2.4%, P = 0.006), a higher ADs threshold (12.8 ± 4.1 mA vs. 11.0 ± 3.7 mA, P < 0.001) and a shorter ADs duration (15.3 ± 14.2 s vs. 20.6 ± 17.0 s, P < 0.001). However, in region nML, there was no significant difference in properties of ADs between SF and nSF patients. ConclusionHigher occurrence of ADs in region ML might predict a good outcome, whereas higher occurrence of ADs evolving into clinical seizure, higher ADs threshold and shorter ADs duration might predict an unfavorable surgical outcome. ADs might help predict surgical outcomes in epilepsy patients.

Mapping connectivity fingerprints for presurgical evaluation of temporal lobe epilepsy

BackgroundSurgery may render temporal lobe epilepsy (TLE) patients seizure-free. However, TLE is a heterogenous entity and surgical prognosis varies between patients. Network-based biomarkers have been shown to be altered in TLE patients and hold promise for classifying TLE subtypes and improving pre-surgical prognosis. The aim of the present study is to investigate a network-based biomarker, the weighted degree of connectivity (wDC), on an individual level, and its relation to TLE subtypes and surgical prognosis.MethodsThirty unilateral TLE patients undergoing the same surgical procedure (anterior temporal resection) and 18 healthy controls were included. All patients were followed-up in the same center for a mean time of 6.85 years and classified as seizure-free (SF) and non seizure-free (non-SF). Using pre-surgical resting state functional MRI, whole brain wDC values for patients and controls were calculated. Then, we divided both temporal lobes in three Regions-of-interest (ROIs) -mesial, pole and lateral- as these areas are known to behave differently in seizure onset and propagation, delimiting different TLE profiles. The wDC values for the defined ROIs of each individual patient were compared with the healthy group.ResultsAfter surgery, 14 TLE patients remained SF. As a group, patients had higher wDC than controls in both the temporal pole (p < 0.05) as well as in the mesial regions (p < 0.002) of the to-be-resected temporal lobe. When comparing between SF and non-SF patients, a step-wise binary logistic regression model including all the ROIs, showed that having an increased wDC of the temporal pole (p < 0.05) and the mesial area (p < 0.05) of the to-be-resected temporal lobe was associated with seizure freedom long-term after surgery.ConclusionsThis study provides a network-based presurgical biomarker that could pave the way towards personalized prediction. In patients with TLE undergoing anterior temporal resections, having an increased wDC at rest could be a signature of the epileptogenic area, and could help identifying those patients who would benefit most from surgery.

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

A.7 In vivo hippocampal mGluR5 abnormalities predict MTLE post-surgical outcome

Background: PET imaging of [11C]ABP688 shows reduced hippocampal mGluR5 availability in mesial temporal lobe epilepsy (MTLE) patients, however the relation with post-surgical outcomes is unclear. Here, we tested whether [11C]ABP688 binding in hippocampal subfields vulnerable to glutamate excitotoxicity is related to post-surgical outcome. Methods: [11C]ABP688-PET was obtained from 31 unilateral MTLE patients and 30 controls. Hippocampal subfields were automatically segmented into 1) CA1-3, 2) CA4/dentate gyrus (DG), and 3) Subiculum and manually corrected. Partial volume corrected [11C]ABP688 non-displaceable binding potential (BPND) was calculated in the subfields and compared between seizure-free and non-seizure-free patients. Results: [11C]ABP688 BPND was significantly reduced in ipsilateral CA1-3 &amp; CA4/DG (p&lt;0.001) compared to controls. No difference was seen in Subiculum. Ipsilateral CA1-3 [11C]ABP688 BPND was lower in seizure-free (p=0.012; Engel Ia, n=13) vs non-seizure-free (Engel Ic-III, n=10) patients, and this effect was independent of subfield volume. In a subset of patients with [18F]FDG-PET, CA1-3 [11C]ABP688 BPND was significantly lower in seizure-free patients (p=0.03), while no difference was found for [18F]FDG uptake. Conclusions: Reduced CA1-3 mGluR5 availability was associated with post-surgical seizure-freedom independent of atrophy and hypometabolism. Thus, [11C]ABP688-PET may offer a potential biomarker for surgical outcomes and may be particularly relevant for pre-surgical workup in MRI- and [18F]FDG-negative MTLE patients.

Neurocraft: software for microscale brain network dynamics

The brain operates at millisecond timescales but despite of that, the study of its functional networks is approached with time invariant methods. Equally, for a variety of brain conditions treatment is delivered with fixed temporal protocols unable to monitor and follow the rapid progression and therefore the cycles of a disease. To facilitate the understanding of brain network dynamics we developed Neurocraft, a user friendly software suite. Neurocraft features a highly novel signal processing engine fit for tracking evolving network states with superior time and frequency resolution. A variety of analytics like dynamic connectivity maps, force-directed representations and propagation models, allow for the highly selective investigation of transient pathophysiological dynamics. In addition, machine-learning tools enable the unsupervised investigation and selection of key network features at individual and group-levels. For proof of concept, we compared six seizure-free and non seizure-free focal epilepsy patients after resective surgery using Neurocraft. The network features were calculated using 50 intracranial electrodes on average during at least 120 epileptiform discharges lasting less than one second, per patient. Powerful network differences were detected in the pre-operative data of the two patient groups (effect size = 1.27), suggesting the predictive value of dynamic network features. More than one million patients are treated with cardiac and neuro modulation devices that are unable to track the hourly or daily changes in a subject’s disease. Decoding the dynamics of transition from normal to abnormal states may be crucial in the understanding, tracking and treatment of neurological conditions. Neurocraft provides a user-friendly platform for the research of microscale brain dynamics and a stepping stone for the personalised device-based adaptive neuromodulation in real-time.

Machine learning for predicting levetiracetam treatment response in temporal lobe epilepsy

ObjectiveTo determine the predictive power for seizure-freedom of 19-channels EEG, measured both before and after three months the initiation of the use of Levetiracetam (LEV), in a cohort of people after a new diagnosis of temporal-lobe epilepsy (TLE) using a machine-learning approach. MethodsTwenty-three individuals with TLE were examined. We dichotomized clinical outcome into seizure-free (SF) and non-seizure-free (NSF) after two years of LEV. EEG effective power in different frequency bands was compared using baseline EEG (T0) and the EEG after three months of LEV therapy (T1) between SF and NSF patients. Partial Least Square (PLS) analysis was used to test and validate the prediction of the model for clinical outcome. ResultsA total of 152 features were extracted from the EEG recordings. When considering only the features calculated at T1, a predictive power for seizure-freedom (AUC = 0.750) was obtained. When employing both T0 and T1 features, an AUC = 0.800 was obtained. ConclusionsThis study provides a proof-of-concept pipeline for predicting the clinical response to anti-seizure medications in people with epilepsy. SignificanceFuture studies may benefit from the pipeline proposed in this study in order to develop a model that can match each patient to the most effective anti-seizure medication.

Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI.

Background: Potentially curative epilepsy surgery can be offered if a single, discrete epileptogenic zone (EZ) can be identified. For individuals in whom there is no clear concordance between clinical localization, scalp EEG, and imaging data, intracranial EEG (icEEG) may be needed to confirm a predefined hypothesis regarding irritative zone (IZ), seizure onset zone (SOZ), and EZ prior to surgery. However, icEEG has limited spatial sampling and may fail to reveal the full extent of epileptogenic network if predefined hypothesis is not correct. Simultaneous icEEG-fMRI has been safely acquired in humans and allows exploration of neuronal activity at the whole-brain level related to interictal epileptiform discharges (IED) captured intracranially.Methods: We report icEEG-fMRI in eight patients with refractory focal epilepsy who had resective surgery and good postsurgical outcome. Surgical resection volume in seizure-free patients post-surgically reflects confirmed identification of the EZ. IEDs on icEEG were classified according to their topographic distribution and localization (Focal, Regional, Widespread, and Non-contiguous). We also divided IEDs by their location within the surgical resection volume [primary IZ (IZ1) IED] or outside [secondary IZ (IZ2) IED]. The distribution of fMRI blood oxygen level-dependent (BOLD) changes associated with individual IED classes were assessed over the whole brain using a general linear model. The concordance of resulting BOLD map was evaluated by comparing localization of BOLD clusters with surgical resection volume. Additionally, we compared the concordance of BOLD maps and presence of BOLD clusters in remote brain areas: precuneus, cuneus, cingulate, medial frontal, and thalamus for different IED classes.Results: A total of 38 different topographic IED classes were identified across the 8 patients: Focal (22) and non-focal (16, Regional = 9, Widespread = 2, Non-contiguous = 5). Twenty-nine IEDs originated from IZ1 and 9 from IZ2. All IED classes were associated with BOLD changes. BOLD maps were concordant with the surgical resection volume for 27/38 (71%) IED classes, showing statistical global maximum BOLD cluster or another cluster in the surgical resection volume. The concordance of BOLD maps with surgical resection volume was greater (p < 0.05) for non-focal (87.5%, 14/16) as compared to Focal (59%, 13/22) IED classes. Additionally, BOLD clusters in remote cortical and deep brain areas were present in 84% (32/38) of BOLD maps, more commonly (15/16; 93%) for non-focal IED-related BOLD maps.Conclusions: Simultaneous icEEG-fMRI can reveal BOLD changes at the whole-brain level for a wide range of IEDs on icEEG. BOLD clusters within surgical resection volume and remote brain areas were more commonly seen for non-focal IED classes, suggesting that a wider hemodynamic network is at play.

Multiscale Entropy Analysis of Heart Rate Variability in Neonatal Patients with and without Seizures.

The complex physiological dynamics of neonatal seizures make their detection challenging. A timely diagnosis and treatment, especially in intensive care units, are essential for a better prognosis and the mitigation of possible adverse effects on the newborn’s neurodevelopment. In the literature, several electroencephalographic (EEG) studies have been proposed for a parametric characterization of seizures or their detection by artificial intelligence techniques. At the same time, other sources than EEG, such as electrocardiography, have been investigated to evaluate the possible impact of neonatal seizures on the cardio-regulatory system. Heart rate variability (HRV) analysis is attracting great interest as a valuable tool in newborns applications, especially where EEG technologies are not easily available. This study investigated whether multiscale HRV entropy indexes could detect abnormal heart rate dynamics in newborns with seizures, especially during ictal events. Furthermore, entropy measures were analyzed to discriminate between newborns with seizures and seizure-free ones. A cohort of 52 patients (33 with seizures) from the Helsinki University Hospital public dataset has been evaluated. Multiscale sample and fuzzy entropy showed significant differences between the two groups (p-value < 0.05, Bonferroni multiple-comparison post hoc correction). Moreover, interictal activity showed significant differences between seizure and seizure-free patients (Mann-Whitney Test: p-value < 0.05). Therefore, our findings suggest that HRV multiscale entropy analysis could be a valuable pre-screening tool for the timely detection of seizure events in newborns.