Objective
To analyze longitudinal seizure outcomes following epilepsy surgery, including reoperations, in patients with intractable focal epilepsy.
Methods
Clinicoradiological characteristics of ...patients who underwent epilepsy surgery from 1995 to 2016 with follow‐up of ≥1 year were reviewed. In patients undergoing reoperations, the latest resection was considered the index surgery. The primary outcome was complete seizure freedom (Engel I) at last follow‐up. Potentially significant outcome variables were first identified using univariate analyses and then fit in multivariate Cox proportional hazards models.
Results
Of 898 patients fulfilling study criteria, 110 had reoperations; 92 had one resection prior to the index surgery and 18 patients had two or more prior resective surgeries. Two years after the index surgery, 69% of patients with no prior surgeries had an Engel score of I, as opposed to only 42% of those with one prior surgery, and 33% of those with two or more prior resections (P < .001). Among surgical outcome predictors, the number of prior epilepsy surgeries, female sex, lesional initial magnetic resonance imaging, no prior history of generalization, and pathology correlated with better seizure outcomes on univariate analysis. However, only sex (P = .011), history of generalization (P = .016), and number of prior surgeries (P = .002) remained statistically significant in the multivariate model.
Significance
Although long‐term seizure control is possible in patients with failed prior epilepsy surgery, the chances of success diminish with every subsequent resection. Outcome is additionally determined by inherent biological markers (sex and secondary generalization tendency), rather than traditional outcome predictors, supporting a hypothesis of “surgical refractoriness.”
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Summary
Objective
We aimed to determine the rates and predictors of resection and seizure freedom after bilateral stereo‐electroencephalography (SEEG) implantation.
Methods
We reviewed 184 patients ...who underwent bilateral SEEG implantation (2009‐2015). Noninvasive and invasive evaluation findings were collected. Outcomes of interest included subsequent resection and seizure freedom. Statistical analyses employed multivariable logistic regression and proportional hazard modeling. Preoperative and postoperative seizure frequency, severity, and quality of life scales were also compared.
Results
Following bilateral SEEG implantation, 106 of 184 patients (58%) underwent resection. Single seizure type (P = 0.007), a family history of epilepsy (P = 0.003), 10 or more seizures per month (P = 0.004), lower number of electrodes (P = 0.02), or sentinel electrode placement (P = 0.04) was predictive of undergoing a resection, as were lack of nonlocalized (P < 0.0001) or bilateral (P < 0.0001) ictal‐onset zones on SEEG. Twenty‐six of 81 patients (32% with follow‐up greater than 1 year) remained seizure‐free. Predictors of seizure freedom were single seizure type (P = 0.01), short epilepsy duration (P = 0.008), use of 2 or fewer antiepileptic drugs (AEDs) at the time of surgery (P = 0.0006), primary localization hypothesis involving the frontal lobe (P = 0.002), sentinel electrode placement only (P = 0.02), and lack of overlap between ictal‐onset zone and eloquent cortex (P = 0.04), along with epilepsy substrate histopathology (P = 0.007). Complete resection of a suspected focal cortical dysplasia showed a trend to increased likelihood of seizure freedom (P = 0.09). The 44 of 55 patients (80%) who underwent resection and experienced seizure recurrence had >50% seizure reduction, as opposed to 26 of 45 patients (58%) who continued medical therapy alone (P = 0.003). Seventy‐two percent of patients had a clinically meaningful quality of life improvement (>10% decrease in the Quality of Life in Epilepsy QOLIE‐10 score) at 1 year.
Significance
A strong preimplantation hypothesis of a suspected unifocal epilepsy increases the odds of resection and seizure freedom. We discuss a tailored approach, taking into account localization hypothesis and suspected epilepsy etiology in guiding implantation and subsequent surgical strategy.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Objective
Inflammation plays an essential role in epilepsy. Studies indicate that cytokines and neurotrophic factors can act in neuroexcitability and epileptogenesis. We aimed to investigate the ...association between plasma inflammatory and neurotrophic markers, seizure frequency, and chronic epilepsy subtypes.
Methods
We studied 446 patients with epilepsy and 166 healthy controls. We classified patients according to etiology and seizure frequency. We measured plasma levels of interleukin‐1 (IL‐1), IL‐2, IL‐4, IL‐6, IL‐10, IL‐17, interferon‐γ (IFNγ), tumor necrosis factor α (TNFα), soluble TNF receptor 1 (sTNFr1), sTNFr2, brain‐derived neurotrophic factor (BDNF), neurotrophic factor 3 (NT3), NT4/5, ciliary neurotrophic factor (CNTF), nerve growth factor (NGF), and glial cell line‐derived neurotrophic factor (GDNF) by enzyme‐linked immunosorbent assay or cytometric bead array.
Results
The plasma levels of BDNF, NT3, NGF, and sTNFr2 were higher, whereas IL‐2, IL‐4, IL‐6, IL‐10, IL‐17, IFNγ, TNFα, CNTF, and sTNFr1 were lower in patients than controls. IL1, GDNF, and NT4/5 were similar between groups. These markers did not correlate with age, sex, and epilepsy duration. The molecule sTNFr2 was the best marker to discriminate patients from controls (area under the curve = .857), also differing between patients with frequent and infrequent seizures.
Significance
This large cohort confirmed that patients with epilepsy have abnormal levels of plasma inflammatory and neurotrophic markers independent of the underlying etiology. Plasma level of sTNFr2 was related to seizure frequency and discriminated people with or without epilepsy with good accuracy, making it a potential biomarker for epilepsy and seizure burden.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in ...advancing our understanding of brain processes in the epilepsies. Smaller‐scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well‐established by the ENIGMA Consortium, ENIGMA‐Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event‐based modeling analysis. We explore age of onset‐ and duration‐related features, as well as phenomena‐specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA‐Epilepsy.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Objective
Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large ...multicenter cross‐sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE‐HS) correlate with clinical features.
Methods
We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1‐weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA‐Epilepsy consortium, comprising 804 people with MTLE‐HS and 1625 healthy controls from 25 centers. Features with a moderate case–control effect size (Cohen d ≥ .5) were used to train an event‐based model (EBM), which estimates a sequence of disease‐specific biomarker changes from cross‐sectional data and assigns a biomarker‐based fine‐grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance.
Results
In MTLE‐HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10−16), age at onset (ρ = −.18, p = 9.82 × 10−7), and ASM resistance (area under the curve = .59, p = .043, Mann–Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE‐HS with mild or nondetectable abnormality on T1W MRI.
Significance
From cross‐sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE‐HS subjects in other cohorts and help establish connections between imaging‐based progression staging and clinical features.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Aims
The causes of distinct patterns of reduced cortical thickness in the common human epilepsies, detectable on neuroimaging and with important clinical consequences, are unknown. We investigated ...the underlying mechanisms of cortical thinning using a systems‐level analysis.
Methods
Imaging‐based cortical structural maps from a large‐scale epilepsy neuroimaging study were overlaid with highly spatially resolved human brain gene expression data from the Allen Human Brain Atlas. Cell‐type deconvolution, differential expression analysis and cell‐type enrichment analyses were used to identify differences in cell‐type distribution. These differences were followed up in post‐mortem brain tissue from humans with epilepsy using Iba1 immunolabelling. Furthermore, to investigate a causal effect in cortical thinning, cell‐type‐specific depletion was used in a murine model of acquired epilepsy.
Results
We identified elevated fractions of microglia and endothelial cells in regions of reduced cortical thickness. Differentially expressed genes showed enrichment for microglial markers and, in particular, activated microglial states. Analysis of post‐mortem brain tissue from humans with epilepsy confirmed excess activated microglia. In the murine model, transient depletion of activated microglia during the early phase of the disease development prevented cortical thinning and neuronal cell loss in the temporal cortex. Although the development of chronic seizures was unaffected, the epileptic mice with early depletion of activated microglia did not develop deficits in a non‐spatial memory test seen in epileptic mice not depleted of microglia.
Conclusions
These convergent data strongly implicate activated microglia in cortical thinning, representing a new dimension for concern and disease modification in the epilepsies, potentially distinct from seizure control.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
The aim was to compare the outcomes of subdural electrode (SDE) implantations versus stereotactic electroencephalography (SEEG), the 2 predominant methods of intracranial electroencephalography ...(iEEG) performed in difficult-to-localize drug-resistant focal epilepsy.
The Surgical Therapies Commission of the International League Against Epilepsy created an international registry of iEEG patients implanted between 2005 and 2019 with ≥1 year of follow-up. We used propensity score matching to control exposure selection bias and generate comparable cohorts. Study endpoints were: (1) likelihood of resection after iEEG; (2) seizure freedom at last follow-up; and (3) complications (composite of postoperative infection, symptomatic intracranial hemorrhage, or permanent neurological deficit).
Ten study sites from 7 countries and 3 continents contributed 2,012 patients, including 1,468 (73%) eligible for analysis (526 SDE and 942 SEEG), of whom 988 (67%) underwent subsequent resection. Propensity score matching improved covariate balance between exposure groups for all analyses. Propensity-matched patients who underwent SDE had higher odds of subsequent resective surgery (odds ratio OR = 1.4, 95% confidence interval CI 1.05, 1.84) and higher odds of complications (OR = 2.24, 95% CI 1.34, 3.74; unadjusted: 9.6% after SDE vs 3.3% after SEEG). Odds of seizure freedom in propensity-matched resected patients were 1.66 times higher (95% CI 1.21, 2.26) for SEEG compared with SDE (unadjusted: 55% seizure free after SEEG-guided resections vs 41% after SDE).
In comparison to SEEG, SDE evaluations are more likely to lead to brain surgery in patients with drug-resistant epilepsy but have more surgical complications and lower probability of seizure freedom. This comparative-effectiveness study provides the highest feasible evidence level to guide decisions on iEEG. ANN NEUROL 2021;90:927-939.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Objective
Patients undergoing frontal lobectomy demonstrate lower seizure‐freedom rates than patients undergoing temporal lobectomy and several other resective interventions. We attempted to utilize ...automated preoperative quantitative analysis of focal and global cortical volume loss to develop predictive volumetric indicators of seizure outcome after frontal lobectomy.
Methods
Ninety patients who underwent frontal lobectomy were stratified based on seizure freedom at a mean follow‐up time of 3.5 (standard deviation SD 2.5) years. Automated quantitative analysis of cortical volume loss organized by distinct brain region and laterality was performed on preoperative T1‐weighted magnetic resonance imaging (MRI) studies. Univariate statistical analysis was used to select potential predictors of seizure freedom. Backward variable selection and multivariate logistical regression were used to develop models to predict seizure freedom.
Results
Forty‐eight of 90 (53.3%) patients were seizure‐free at the last follow‐up. Several frontal and extrafrontal brain regions demonstrated statistically significant differences in both volumetric cortical volume loss and volumetric asymmetry between the left and right sides in the seizure‐free and non–seizure‐free cohorts. A final multivariate logistic model utilizing only preoperative quantitative MRI data to predict seizure outcome was developed with a c‐statistic of 0.846. Using both preoperative quantitative MRI data and previously validated clinical predictors of seizure outcomes, we developed a model with a c‐statistic of 0.897.
Significance
This study demonstrates that preoperative cortical volume loss in both frontal and extrafrontal regions can be predictive of seizure outcome after frontal lobectomy, and models can be developed with excellent predictive capabilities using preoperative MRI data. Automated quantitative MRI analysis can be quickly and reliably performed in patients with frontal lobe epilepsy, and further studies may be developed for integration into preoperative risk stratification.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Objective
To assess and validate the performance of a new tool developed for segmenting and characterizing lacunas in postoperative MR images of epilepsy patients.
Methods
A MATLAB‐based pipeline was ...implemented using SPM12 to produce the 3D mask of the surgical lacuna and estimate its volume. To validate its performance, we compared the manual and automatic lacuna segmentations obtained from 51 MRI scans of epilepsy patients who underwent temporal lobe resections.
Results
The code is consolidated as a tool named ResectVol, which can be run via a graphical user interface or command line. The automatic and manual segmentation comparison resulted in a median Dice similarity coefficient of 0.77 (interquartile range: 0.71‐0.81).
Significance
Epilepsy surgery is the treatment of choice for pharmacoresistant focal epilepsies, and despite the extensive literature on the subject, we still cannot predict surgical outcomes accurately. As the volume and location of the resected tissue are fundamentally relevant to this prediction, researchers commonly perform a manual segmentation of the lacuna, which presents human bias and does not provide detailed information about the structures removed. In this study, we introduce ResectVol, a user‐friendly, fully automatic tool to accomplish these tasks. This capability enables more advanced analytical techniques applied to surgical outcomes prediction, such as machine‐learning algorithms, by facilitating coregistration of the resected area and preoperative findings with other imaging modalities such as PET, SPECT, and functional MRI ResectVol is freely available at https://www.lniunicamp.com/resectvol.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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