Cortical Thickness Patterns of Cognitive Impairment Phenotypes in Drug-Resistant Temporal Lobe Epilepsy.

OBJECTIVE: In temporal lobe epilepsy (TLE), a taxonomy classifying patients into 3 cognitive phenotypes has been adopted: minimally, focally, or multidomain cognitively impaired (CI). We examined gray matter (GM) thickness patterns of cognitive phenotypes in drug-resistant TLE and assessed potential use for predicting postsurgical cognitive outcomes. METHODS: TLE patients undergoing presurgical evaluation were categorized into cognitive phenotypes. Network edge weights and distances were calculated using type III analysis of variance F-statistics from comparisons of GM regions within each TLE cognitive phenotype and age- and sex-matched healthy participants. In resected patients, logistic regression models (LRMs) based on network analysis results were used for prediction of postsurgical cognitive outcome. RESULTS: A total of 124 patients (63 females, mean age ± standard deviation [SD] = 36.0 ± 12.0 years) and 117 healthy controls (63 females, mean age ± SD = 36.1 ± 12.0 years) were analyzed. In the multidomain CI group (n = 66, 53.2%), 28 GM regions were significantly thinner compared to healthy controls. Focally impaired patients (n = 37, 29.8%) showed 13 regions, whereas minimally impaired patients (n = 21, 16.9%) had 2 significantly thinner GM regions. Regions affected in both multidomain and focally impaired patients included the anterior cingulate cortex, medial prefrontal cortex, medial temporal, and lateral temporal regions. In 69 (35 females, mean age ± SD = 33.6 ± 18.0 years) patients who underwent surgery, LRMs based on network-identified GM regions predicted postsurgical verbal memory worsening with a receiver operating curve area under the curve of 0.70 ± 0.15. INTERPRETATION: A differential pattern of GM thickness can be found across different cognitive phenotypes in TLE. Including magnetic resonance imaging with clinical measures associated with cognitive profiles has potential in predicting postsurgical cognitive outcomes in drug-resistant TLE. ANN NEUROL 2024;95:984-997.

Integration of interictal EEG source localization in presurgical epilepsy evaluation - A single-center prospective study.

OBJECTIVE: To investigate cost in working hours for initial integration of interictal EEG source localization (ESL) into clinical practice of a tertiary epilepsy center, and to examine concordance of results obtained with three different ESL pipelines. METHODS: This prospective study covered the first year of using ESL in the Epilepsy-Center Berlin-Brandenburg. Patients aged ≥14 years with drug-resistant focal epilepsy referred for noninvasive presurgical evaluation were included. Interictal ESL was based on low-density EEG and individual head models. Source maxima were obtained from two freely available software packages and one commercial provider. One physician and computer scientist documented their working hours for setting up and processing ESL. Additionally, a survey was conducted among epilepsy centers in Germany to assess the current role of ESL in presurgical evaluation. RESULTS: Of 40 patients included, 22 (55%) had enough interictal spikes for ESL. The physician's working times decreased from median 4.7 hours [interquartile range 3.9-6.4] in the first third of cases to 2.0 hours [1.9-2.4] in the remaining two thirds; P < 0.01. In addition, computer scientist and physician spent a total of 35.5 and 33.0 working hours on setting up the digital infrastructure, and on training and testing. Sublobar agreement between all three pipelines was 20%, mean measurement of agreement (kappa) 0.13. Finally, the survey revealed that 53% of epilepsy centers in Germany currently use ESL for presurgical evaluation. SIGNIFICANCE: This study provides information regarding expected effort and costs for integration of ESL into an epilepsy surgery program. Low result agreement across different ESL pipelines calls for further standardization.

Prediction of epilepsy surgery outcome using foramen ovale EEG - A machine learning approach.

INTRODUCTION: Patients with drug-resistant focal epilepsy may benefit from ablative or resective surgery. In presurgical work-up, intracranial EEG markers have been shown to be useful in identification of the seizure onset zone and prediction of post-surgical seizure freedom. However, in most cases, implantation of depth or subdural electrodes is performed, exposing patients to increased risks of complications. METHODS: We analysed EEG data recorded from a minimally invasive approach utilizing foramen ovale (FO) and epidural peg electrodes using a supervised machine learning approach to predict post-surgical seizure freedom. Power-spectral EEG features were incorporated in a logistic regression model predicting one-year post-surgical seizure freedom. The prediction model was validated using repeated 5-fold cross-validation and compared to outcome prediction based on clinical and scalp EEG variables. RESULTS: Forty-seven patients (26 patients with post-surgical 1-year seizure freedom) were included in the study, with 31 having FO and 27 patients having peg onset seizures. The area under the receiver-operating curve for post-surgical seizure freedom (Engel 1A) prediction in patients with FO onset seizures was 0.74 ± 0.23 using electrophysiology features, compared to 0.66 ± 0.22 for predictions based on clinical and scalp EEG variables (p < 0.001). The most important features for prediction were spectral power in the gamma and high gamma ranges. EEG data from peg electrodes was not informative in predicting post-surgical outcomes. CONCLUSION: In this hypothesis-generating study, a data-driven approach based on EEG features derived from FO electrodes recordings outperformed the predictive ability based solely on clinical and scalp EEG variables. Pending validation in future studies, this method may provide valuable post-surgical prognostic information while minimizing risks of more invasive diagnostic approaches.

Diagnostic and prognostic value of EEG patterns recorded on foramen ovale and epidural peg electrodes.

OBJECTIVE: To describe and assess the significance of EEG characteristics recorded during presurgical video-EEG monitoring (VEM) utilizing foramen ovale (FO) and epidural peg electrodes. METHODS: Seizure onset (SOP) and termination pattern morphology and regions, ipsilateral and contralateral latencies, seizure duration, and interictal spike counts were examined in 106 patients (412 seizures). An EEG feature-based logistic regression model predicting one-year post-surgical seizure freedom was assessed using a 5-fold nested cross-validation approach. RESULTS: Four SOPs and five termination patterns were identified. Seventy-one percent of patients had a single unique SOP, the most common being sharp activity ≤ 13 Hz (28.9% of seizures). Seizures recorded by FO electrodes were associated with SOPs ≤ 13 Hz (OR 1.9, p = .008). Focal-to-bilateral tonic-clonic seizures were associated with SOPs > 13 Hz (p = .04) and bilateral spike and wave termination (p < .001). In patients with temporal lobe epilepsy, logistic regression based prediction of post-surgical outcome had a mean area under the curve of 0.69, with the most important features being SOP, right sided interictal epileptic activity, and contralateral latency. CONCLUSIONS: FO and peg recordings yield characteristic EEG patterns. SIGNIFICANCE: EEG features of FO and peg recordings may have diagnostic and prognostic utility in presurgical VEM.

Electrodiagnostic artifacts due to neurostimulation devices for drug resistant epilepsy.

Background: Neurostimulation devices including vagus nerve stimulation (VNS), deep brain stimulation (DBS), and responsive neurostimulation (RNS) are approved therapeutic options for drug resistant epilepsy (DRE). As these devices are increasingly used in clinical practice, it is of importance to recognize their artifacts in electrodiagnostic studies. Methods: This is a retrospective study of all adult DRE patients treated with neuromodulation devices for epilepsy at our center between 2012 and 2021. Available EEGs were reviewed for neurostimulator-related artifacts. Results: Fifty-two patients were included. 37% of patients had neurostimulation related electrophysiological artifacts (20% of VNS, 75% of DBS, all patients with dual VNS-DBS treatment, and in the single patient with RNS). Artifacts were intermittent, appearing most commonly simultaenously in the EEG and ECG. VNS artifacts were monomorphic appearing mostly in the lower temporal EEG electrodes, whereas DBS artifacts were with variable morphology, amplitude, and scalp distribution. At times, the artifacts resembled electrographic seizures in the EEG and mimicked extrasystole or asystole in the ECG. Conclusions: With the increasing use of neurostimulation treatments for DRE, and the need for frequent electrodiagnostic studies in this patient population, it is important clinicians recognize these electrophysiological findings as artifacts, to avoid misdiagnosis and facilitate accurate interpretation.

Anterior thalamic deep brain stimulation in epilepsy patients refractory to vagus nerve stimulation: A single center observational study.

Anterior thalamic deep brain stimulation (DBS) is a palliative treatment that may be considered in patients with drug resistant epilepsy (DRE) that fail treatment with vagus nerve stimulation (VNS). Combining VNS and DBS treatment is a therapeutic approach rarely reported. This single center observational study aims to describe response to DBS treatment in 11 epilepsy patients resistant to medications and VNS. Patients either had inactivated VNS (DBS only) or were treated with simultaneous DBS and VNS (DBS-VNS). Focal impaired awareness (FIA) and most disabling seizure rates were examined pre-DBS implantation, 3 months following implantation, and last follow up. Overall, a decrease in FIA (47.0 ± 30.7 %, p = 0.02) and most disabling seizure rate (54.8 ± 34.2 %, p = 0.03) was seen at last follow-up (average follow-up 28.5 ± 13.5 months). Eight of 11 patients were DBS responders (most disabling seizure rate reduction above 50%). No difference in seizure control was found between seven DBS only and four DBS-VNS patients. Our results argue that patients who have failed antiseizure medication and VNS therapies, could benefit from better seizure control if treated with adjunctive DBS. Larger prospective studies are needed to assess the efficacy and safety of combined neurostimulation treatments in DRE.

Presurgical video-EEG monitoring with foramen ovale and epidural peg electrodes: a 25-year perspective.

BACKGROUND: Epilepsy surgery cases are becoming more complex and increasingly require invasive video-EEG monitoring (VEM) with intracranial subdural or intracerebral electrodes, exposing patients to substantial risks. We assessed the utility and safety of using foramen ovale (FO) and epidural peg electrodes (FOP) as a next step diagnostic approach following scalp VEM. METHODS: We analyzed clinical, electrophysiological, and imaging characteristics of 180 consecutive patients that underwent FOP VEM between 1996 and 2021. Multivariate logistic regression was used to assess predictors of clinical and electrophysiological outcomes. RESULTS: FOP VEM allowed for immediate resection recommendation in 36 patients (20.0%) and excluded this option in 85 (47.2%). Fifty-nine (32.8%) patients required additional invasive EEG investigations; however, only eight with bilateral recordings. FOP VEM identified the ictal onset in 137 patients, compared to 96 during prior scalp VEM, p = .004. Predictors for determination of ictal onset were temporal lobe epilepsy (OR 2.9, p = .03) and lesional imaging (OR 3.1, p = .01). Predictors for surgery recommendation were temporal lobe epilepsy (OR 6.8, p < .001), FO seizure onset (OR 6.1, p = .002), and unilateral interictal epileptic activity (OR 3.8, p = .02). One-year postsurgical seizure freedom (53.3% of patients) was predicted by FO ictal onset (OR 5.8, p = .01). Two patients experienced intracerebral bleeding without persisting neurologic sequelae. CONCLUSION: FOP VEM adds clinically significant electrophysiological information leading to treatment decisions in two-thirds of cases with a good benefit-risk profile. Predictors identified for electrophysiological and clinical outcome can assist in optimally selecting patients for this safe diagnostic approach.

De novo status epilepticus possibly related to battery depletion of anterior thalamic brain stimulator.

Anterior thalamic deep brain stimulation is an effective therapeutic option for patients with drug-refractory focal epilepsy who are poor surgical candidates. Although the precise mechanism of action of thalamic neurostimulation is unknown, studies demonstrating increased efficacy over time have raised the possibility that therapeutic benefits are mediated by stimulation-related long-term neuroplastic changes. Adverse effects related to hardware malfunction have been previously described, and most commonly include local infection, sensory disturbances, and migration of leads. However, the withdrawal effect of sudden deep brain stimulation malfunction on seizure control is unclear. We present the case of a 21-year-old patient with intractable focal epilepsy who developed status epilepticus concurrently with unexpected deep brain stimulator battery failure, 21 months post implantation. This case demonstrates an unfamiliar possible adverse effect of anterior thalamic stimulation withdrawal and emphasizes the importance of stimulator hardware assessment in patients presenting with seizure worsening.

Host cell virus entry mechanisms enhance anti-JCV-antibody switch in natalizumab-treated multiple sclerosis patients.

Estimating the individual risk for the development of progressive multifocal leukoencephalopathy (PML) in anti-John Cunningham virus (JCV) antibody-negative patients with multiple sclerosis (MS) treated with natalizumab is a major challenge. A serological conversion occurring under treatment from anti-JCV antibody-negative to positive status may significantly increase this risk. We investigated changes in peripheral blood cells' gene expression induced by natalizumab treatment in anti-JCV antibody-negative MS patients and tested blood transcriptional profile that characterizes patients predisposed to antibody switch under natalizumab treatment. After 3 years of natalizumab treatment, 24.6 % of anti-JCV antibody-negative MS patients switched to become anti-JCV antibody-positive (JCV switchers). Natalizumab induced 946 and 1186 significantly differentiating genes in JCV switchers and non-switchers, respectively. In JCV switchers, the signature was enriched by over-expression of genes associated with the first stages of viral entry to host cells including macropinocytosis (p = 1.82E-06), virus entry via endocytosis (p = 1.60E-06), clathrin-mediated endocytosis (p = 1.13E-04), and caveolar-mediated endocytosis (p = 4.50E-04) pathways. Further analysis to identify pre-existing transcriptional differences that characterize future JCV switchers prior to treatment initiation also demonstrated a transcriptional signature enriched by similar viral entry mechanisms. These findings, verified in an additional independent cohort of natalizumab-treated patients, could lead to future identification of patients that remain anti-JCV antibody-negative thus allowing safe continuation of treatment, as well as the development of future targeted therapeutic interventions to reduce the risk of PML.

Transcriptional response to interferon beta-1a treatment in patients with secondary progressive multiple sclerosis.

BACKGROUND: Interferon (IFN) beta-1a is an approved treatment for relapsing remitting multiple sclerosis (RRMS) and has been examined for use in secondary progressive multiple sclerosis (SPMS). However, no information regarding blood transcriptional changes induced by IFN treatment in SPMS patients is available. Our aim was to identify a subgroup of SPMS patients presenting a gene expression signature similar to that of RRMS patients who are clinical responders to IFN treatment. METHODS: SPMS patients (n = 50, 20 IFN treated and 30 untreated) were classified using unsupervised hierarchical clustering according to IFN inducible gene expression profile identified in RRMS clinical responders to treatment. IFN inducible gene expression profile was determined by finding differentially expressed genes (DEGs) between IFN treated (n = 10) and untreated (n = 25) RRMS patients. Validation was performed on an additional independent group of 27 SPMS IFN treated patients by qRT-PCR. RESULTS: One hundred and four DEGs, enriched by IFN signaling pathway (p = 7.4E-08), were identified in IFN treated RRMS patients. Classification of SPMS patients based on these DEGs yielded two patient groups: (1) IFN transcriptional responders (n = 12, 60% of SPMS treated patients) showing gene-expression profile similar to IFN treated RRMS patients; (2) IFN transcriptional non-responders (n = 8) showing expression profile similar to untreated patients. IFN transcriptional responders were characterized by a more active disease, as defined by higher EDSS progression and annual relapse rate. CONCLUSION: Within the IFN treated SPMS population, 60% of patients have a transcriptional response to IFN which is similar to that of RRMS patients who are IFN responders to treatment.

Optimizing multiple sclerosis diagnosis: gene expression and genomic association.

OBJECTIVE: The diagnosis of multiple sclerosis (MS) at disease onset is sometimes masqueraded by other diagnostic options resembling MS clinically or radiologically (NonMS). In the present study we utilized findings of large-scale Genome-Wide Association Studies (GWAS) to develop a blood gene expression-based classification tool to assist in diagnosis during the first demyelinating event. METHODS: We have merged knowledge of 110 MS susceptibility genes gained from MS GWAS studies together with our experimental results of differential blood gene expression profiling between 80 MS and 31 NonMS patients. Multiple classification algorithms were applied to this cohort to construct a diagnostic classifier that correctly distinguished between MS and NonMS patients. Accuracy of the classifier was tested on an additional independent group of 146 patients including 121 MS and 25 NonMS patients. RESULTS: We have constructed a 42 gene-transcript expression-based MS diagnostic classifier. The overall accuracy of the classifier, as tested on an independent patient population consisting of diagnostically challenging cases including NonMS patients with positive MRI findings, achieved a correct classification rate of 76.0 ± 3.5%. INTERPRETATION: The presented diagnostic classification tool complements the existing diagnostic McDonald criteria by assisting in the accurate exclusion of other neurological diseases at presentation of the first demyelinating event suggestive of MS.