Drug-resistant Epilepsy Patients Research Articles

AB076. Underutilization of epilepsy surgery in Pakistan: 10-year experience from the only comprehensive epilepsy center in the country.

Eighty percent of the global epilepsy burden is borne by developing countries, and 30% of these patients have drug-resistant epilepsy (DRE). Epilepsy surgery (ES) can significantly improve the cognition and quality of life in DRE. A comprehensive epilepsy center was established in Pakistan in 2010, the only facility for ES in a country of 231 million people. Hundreds of epilepsy patients are medically managed at the center each year. We aimed to study seizure control in all ES cases performed at the only comprehensive epilepsy center in the country during last 10 years. It was a retrospective cohort study. Medical records of all cases of ES performed at our center from 2012 to 2021 were retrieved, through the Hospital's Information Management System. Patients were also contacted via phone calls where needed, to collect information about their seizure control as per Engel Classification. Data was analyzed using SPSSv21. Thirty-three surgeries including 10 temporal lobectomies with amygdalohippocampectomy, 11 selective amygdalohippocampectomies, 9 corpus callosotomies, 1 callosotomy with lesionectomy, 1 lesionectomy and 1 temporal lobectomy were performed. The median age of patients was 23: [18-31] years. Complex partial seizures were most common (14; 42.4%), followed by generalized seizures (10; 30.3%). The median duration of AEDs before surgery was 6 (IQR: 3.25-13.75) years. Eighteen (54.5%) patients had complete freedom from disabling seizures (Engel Class IA) at a median follow-up of 3.25 (IQR: 1.12-6) years. All patients continued to receive antiepileptic drugs after surgery, and all procedures had nearly 50% optimum seizure control outcomes. The clinical outcomes of ES performed at our center are consistent with evidence. However, the small volume highlights the underutilization of this extremely important service. More studies are needed to identify the factors responsible for this disparity, so that all DRE patients have access to ES.

Alterations of apparent diffusion coefficient from ultra high b-values in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy.

Subcortical nuclei such as the thalamus and striatum have been shown to be related to seizure modulation and termination, especially in drug-resistant epilepsy. Enhance diffusion-weighted imaging (eDWI) technique and tri-component model have been used in previous studies to calculate apparent diffusion coefficient from ultra high b-values (ADCuh). This study aimed to explore the alterations of ADCuh in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy. Twenty-nine patients with MRI-negative drug-resistant epilepsy and 18 healthy controls underwent eDWI scan with 15 b-values (0-5000 s/mm2). The eDWI parameters including standard ADC (ADCst), pure water diffusion (D), and ADCuh were calculated from the 15 b-values. Regions-of-interest (ROIs) analyses were conducted in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus. ADCst, D, and ADCuh values were compared between the MRI-negative drug-resistant epilepsy patients and controls using multivariate generalized linear models. Inter-rater reliability was assessed using the intra-class correlation coefficient (ICC) and Bland-Altman (BA) analysis. False discovery rate (FDR) method was applied for multiple comparisons correction. ADCuh values in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus in MRI-negative drug-resistant epilepsy were significantly higher than those in the healthy control subjects (all p < 0.05, FDR corrected). The alterations of the ADCuh values in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy might reflect abnormal membrane water permeability in MRI-negative drug-resistant epilepsy. ADCuh might be a sensitive measurement for evaluating subcortical nuclei-related brain damage in epilepsy patients. This study aimed to explore the alterations of apparent diffusion coefficient calculated from ultra high b-values (ADCuh) in the subcortical nuclei such as the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy. The bilateral thalamus and striatum showed higher ADCuh in epilepsy patients than healthy controls. These findings may add new evidences of subcortical nuclei abnormalities related to water and ion hemostasis in epilepsy patients, which might help to elucidate the underlying epileptic neuropathophysiological mechanisms and facilitate the exploration of therapeutic targets.

The long-term outcomes in drug-resistant epilepsy patients who underwent subtotal hemispherotomy: A single-center retrospective cohort study

ObjectiveTo evaluate the long-term outcomes of subtotal hemispherotomy (SH) in treating drug-resistant epilepsy caused by unilateral hemispheric lesions and try to give the prognostic factors for these outcomes. MethodsWe retrospectively reviewed the clinical data of 19 patients who underwent SH in Sanbo Brain Hospital, Capital Medical University, Beijing, China, from May 2008 to April 2021. All clinical data and factors related to surgical and functional outcomes, including motor, neuropsychiatric, and language function, were collected and analyzed. ResultsThe surgical outcomes showed 13 (68 %) patients were seizure-free at the last follow-up (2–14 years, mean: 5.6±2.9). No changes were found in motor outcomes in 12 (63 %) patients; seven (37 %) patients had new permanent motor deficits (NPMD). Improvement in the full-scale intelligence quotient (FIQ) (p = 0.009) was observed. Univariate analysis found that patients who did not achieve seizure freedom had a significantly older age at surgery (p = 0.017) and acute post-operative seizures (APOS) (p = 0.046). Kaplan–Meier analysis also identified significant differences in seizure outcomes between the children and adult subgroups (p = 0.0017). Multivariate Cox analysis showed that older age at surgery (HR=1.055, p = 0.034) was associated with shorter time-to-seizure-recurrence. Resection of the central operculum and insula (OR= 80.433, p =0.031) and higher monthly seizure frequency (OR= 1.073, p = 0.040) were also poor prognostic factors for motor function outcomes. ConclusionSH is an effective treatment procedure in treating patients with drug-resistant epilepsy caused by hemispheric lesions with satisfied seizure outcomes, limited impairment of motor function, and preserving neuropsychiatric outcomes.

A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy.

To predict the vagus nerve stimulation (VNS) efficacy for pediatric drug-resistant epilepsy (DRE) patients, we aim to identify preimplantation biomarkers through clinical features and electroencephalogram (EEG) signals and thus establish a predictive model from a multi-modal feature set with high prediction accuracy. Sixty-five pediatric DRE patients implanted with VNS were included and followed up. We explored the topological network and entropy features of preimplantation EEG signals to identify the biomarkers for VNS efficacy. A Support Vector Machine (SVM) integrated these biomarkers to distinguish the efficacy groups. The proportion of VNS responders was 58.5% (38/65) at the last follow-up. In the analysis of parieto-occipital α band activity, higher synchronization level and nodal efficiency were found in responders. The central-frontal θ band activity showed significantly lower entropy in responders. The prediction model reached an accuracy of 81.5%, a precision of 80.1%, and an AUC (area under the receiver operating characteristic curve) of 0.838. Our results revealed that, compared to nonresponders, VNS responders had a more efficient α band brain network, especially in the parieto-occipital region, and less spectral complexity of θ brain activities in the central-frontal region. We established a predictive model integrating both preimplantation clinical and EEG features and exhibited great potential for discriminating the VNS responders. This study contributed to the understanding of the VNS mechanism and improved the performance of the current predictive model.

Individualized epidemic spreading models predict epilepsy surgery outcomes: A pseudo-prospective study.

Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but up to 50% of patients continue to have seizures one year after the resection. In order to aid presurgical planning and predict postsurgical outcome on a patient-by-patient basis, we developed a framework of individualized computational models that combines epidemic spreading with patient-specific connectivity and epileptogeneity maps: the Epidemic Spreading Seizure and Epilepsy Surgery framework (ESSES). ESSES parameters were fitted in a retrospective study (N = 15) to reproduce invasive electroencephalography (iEEG)-recorded seizures. ESSES reproduced the iEEG-recorded seizures, and significantly better so for patients with good (seizure-free, SF) than bad (nonseizure-free, NSF) outcome. We illustrate here the clinical applicability of ESSES with a pseudo-prospective study (N = 34) with a blind setting (to the resection strategy and surgical outcome) that emulated presurgical conditions. By setting the model parameters in the retrospective study, ESSES could be applied also to patients without iEEG data. ESSES could predict the chances of good outcome after any resection by finding patient-specific model-based optimal resection strategies, which we found to be smaller for SF than NSF patients, suggesting an intrinsic difference in the network organization or presurgical evaluation results of NSF patients. The actual surgical plan overlapped more with the model-based optimal resection, and had a larger effect in decreasing modeled seizure propagation, for SF patients than for NSF patients. Overall, ESSES could correctly predict 75% of NSF and 80.8% of SF cases pseudo-prospectively. Our results show that individualised computational models may inform surgical planning by suggesting alternative resections and providing information on the likelihood of a good outcome after a proposed resection. This is the first time that such a model is validated with a fully independent cohort and without the need for iEEG recordings.

Two-Year Follow-up Outcomes of Non-lesional Epilepsy Surgery in Iran

Background: Despite treatment with anti-epileptic drugs, 30% of epileptic patients continue to experience seizures, making surgery a viable option. Surgery has shown efficacy even in non-lesional epileptic individuals, although there is limited research on this topic. Objectives: This study aimed to investigate surgical outcomes in individuals with drug-resistant epilepsy (DRE) who undergo surgery despite having non-lesional magnetic resonance imaging (MRI) findings. Methods: This observational longitudinal study was conducted between 2017 and 2020 at a referral hospital in Tehran, Iran. Using census sampling, we screened 750 epilepsy cases and enrolled 80 patients (42 women and 38 men) with DRE and non-lesional MRI findings who underwent epilepsy surgery. We collected patients' demographics and seizure characteristics. A 2-year follow-up was conducted to assess the seizure freedom rate. We compared seizure-free and non-seizure-free patients who underwent temporal epilepsy surgery, extratemporal epilepsy surgery, corpus callosotomy, and Vagus nerve stimulation (VNS) using chi-square, Fisher exact, and binary logistic regression tests. Results: The seizure freedom rate was 62.7% for temporal surgery, 83.33% for extratemporal surgery, 26.66% for corpus callosotomy, and none for patients who underwent VNS. There was no difference between seizure-free and non-seizure-free patients in terms of their baseline characteristics, seizure semiology, lesion features, and post-operative findings (P-values &gt; 0.05), except that patients without a history of febrile convulsions tended to experience more seizure freedom after extratemporal surgery (P = 0.007). Additionally, older patients tended to experience more seizure freedom after temporal surgery (P = 0.03). Conclusions: This study underscores the potential benefits of epilepsy surgery in non-lesional DRE patients. Further research is needed to establish criteria for patient selection in this context.

Distinct plasma metabolomic signatures differentiate autoimmune encephalitis from drug-resistant epilepsy.

Differentiating forms of autoimmune encephalitis (AE) from other causes of seizures helps expedite immunotherapies in AE patients and informs studies regarding their contrasting pathophysiology. We aimed to investigate whether and how Nuclear Magnetic Resonance (NMR)-based metabolomics could differentiate AE from drug-resistant epilepsy (DRE), and stratify AE subtypes. This study recruited 238 patients: 162 with DRE and 76 AE, including 27 with contactin-associated protein-like 2 (CASPR2), 29 with leucine-rich glioma inactivated 1 (LGI1) and 20 with N-methyl-d-aspartate receptor (NMDAR) antibodies. Plasma samples across the groups were analyzed using NMR spectroscopy and compared with multivariate statistical techniques, such as orthogonal partial least squares discriminant analysis (OPLS-DA). The OPLS-DA model successfully distinguished AE from DRE patients with a high predictive accuracy of 87.0 ± 3.1% (87.9 ± 3.4% sensitivity and 86.3 ± 3.6% specificity). Further, pairwise OPLS-DA models were able to stratify the three AE subtypes. Plasma metabolomic signatures of AE included decreased high-density lipoprotein (HDL, -(CH2)n-, -CH3), phosphatidylcholine and albumin (lysyl moiety). AE subtype-specific metabolomic signatures were also observed, with increased lactate in CASPR2, increased lactate, glucose, and decreased unsaturated fatty acids (UFA, -CH2CH=) in LGI1, and increased glycoprotein A (GlycA) in NMDAR-antibody patients. This study presents the first non-antibody-based biomarker for differentiating DRE, AE and AE subtypes. These metabolomics signatures underscore the potential relevance of lipid metabolism and glucose regulation in these neurological disorders, offering a promising adjunct to facilitate the diagnosis and therapeutics.

Application of HFO and scaling analysis of neuronal oscillations in the presurgical evaluation of focal epilepsy

PurposeTo explore the utility of high frequency oscillations (HFO) and long-range temporal correlations (LRTCs) in preoperative assessment of epilepsy. MethodsMEG ripples were detected in 59 drug-resistant epilepsy patients, comprising 5 with parietal lobe epilepsy (PLE), 21 with frontal lobe epilepsy (FLE), 14 with lateral temporal lobe epilepsy (LTLE), and 19 with mesial temporal lobe epilepsy (MTLE) to identify the epileptogenic zone (EZ). The results were compared with clinical MEG reports and resection area. Subsequently, LRTCs were quantified at the source-level by detrended fluctuation analysis (DFA) and life/waiting -time at 5 bands for 90 cerebral cortex regions. The brain regions with larger DFA exponents and standardized life-waiting biomarkers were compared with the resection results. ResultsCompared to MEG sensor-level data, ripple sources were more frequently localized within the resection area. Moreover, source-level analysis revealed a higher proportion of DFA exponents and life-waiting biomarkers with relatively higher rankings, primarily distributed within the resection area (p<0.01). Moreover, these two LRCT indices across five distinct frequency bands correlated with EZ. ConclusionHFO and source-level LRTCs are correlated with EZ. Integrating HFO and LRTCs may be an effective approach for presurgical evaluation of epilepsy.

The comparison of DBS and RNS for adult drug-resistant epilepsy: a systematic review and meta-analysis.

Neuromodulation has been proven to be a promising alternative treatment for adult patients with drug-resistant epilepsy (DRE). Deep brain stimulation (DBS) and responsive neurostimulation (RNS) were approved by many countries for the treatment of DRE. However, there is a lack of systematic studies illustrating the differences between them. This meta-analysis is performed to assess the efficacy and clinical characteristics of DBS and RNS in adult patients with DRE. PubMed, Web of Science, and Embase were retrieved to obtain related studies including adult DRE patients who accepted DBS or RNS. The clinical characteristics of these patients were compiled for the following statistical analysis. A total of 55 studies (32 of DBS and 23 of RNS) involving 1,568 adult patients with DRE were included in this meta-analysis. There was no significant difference in seizure reduction and responder rate between DBS and RNS for DRE. The seizure reduction of DBS and RNS were 56% (95% CI 50-62%, p > 0.05) and 61% (95% CI 54-68%, p > 0.05). The responder rate of DBS and RNS were 67% (95% CI 58-76%, p > 0.05) and 71% (95% CI 64-78%, p > 0.05). Different targets of DBS did not show significant effect on seizure reduction (p > 0.05). Patients with DRE who accepted DBS were younger than those of RNS (32.9 years old vs. 37.8 years old, p < 0.01). The mean follow-up time was 47.3 months for DBS and 39.5 months for RNS (p > 0.05). Both DBS and RNS are beneficial and alternative therapies for adult DRE patients who are not eligible to accept resection surgery. Further and larger studies are needed to clarify the characteristics of different targets and provide tailored treatment for patients with DRE.

Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.

Effective reduction in seizure severity and prevention of a fatty liver by a novel low ratio ketogenic diet composition in the rapid kindling rat model of epileptogenesis

Drug-resistant epilepsy patients may benefit from non-pharmacological therapies, such as the ketogenic diet (KD). However, its high fat content poses compliance challenges and metabolic risks. To mitigate this, we developed a novel KD composition with less fat and additional nutrients (citrate, nicotinamide riboside, and omega-3 fatty acids) for ketone-independent neuroprotection. The efficacy, metabolic and neuropathological effects of the novel KD and a classic KD were compared to a control diet in the rapid kindling model of temporal lobe epilepsy. Both KD groups entered ketosis before kindling onset, with higher ketone levels in the classic KD group. Remarkably, rats on the novel KD had slower progression of behavioral seizures as compared to rats on a control diet, while this was not the case for rats on a classic KD. Both KDs reduced electrographic after-discharge duration, preserved neurons in the dorsal hippocampus, and normalized activity in open field tests. The novel KD, despite lower fat and ketone levels, demonstrated effective reduction of behavioral seizure severity while the classic KD did not, suggesting alternative mode(s) of action are involved. Additionally, the novel KD significantly mitigated liver triglyceride and plasma fatty acid levels compared to the classic KD, indicating a reduced risk of long-term liver steatosis. Our findings highlight the potential of the novel KD to enhance therapeutic efficacy and compliance in epilepsy patients.

Comparative study of perceived invalidating environment and stress coping strategies between patients with drug resistant epilepsy and functional dissociative seizures

Background and objectivesWe investigated perceived invalidating environment during childhood and stress-coping strategies in patients with; functional dissociative seizures (FDS, n=26), drug-resistant epilepsy patients with no psychiatric comorbidity (DREnc, n=23), and drug-resistant epilepsy patients with psychiatric comorbidity (DREpc, n=34). Design/MethodsWe performed a cross-sectional study. Patients underwent Video Electroencephalography to confirm the diagnosis and completed a psychiatric assessment supported by clinical instruments. Invalidating environment and stress coping were studied through the ICES and CAE questionaries, respectively. A series of multinomial logistic regression analyses were performed with the explored variables. ResultsThe maternal negative response model predicted a higher probability of FDS condition. A chaotic family type increased the likelihood of DREpc instead of FDS. DREpc and FDS patients displayed many different behaviors to cope with stress other than trying to solve the problem, the most used strategy in the DREnc group. Parental invalidation was higher in DREpc than in FDS. ConclusionsOur results deepen the data provided by previous studies indicating that multiple variables of biosocial origin have significant effects on these groups of patients. The presence of an invalidating environment may predict FDS but also the presence of psychiatric disorders among DRE. Psychotherapeutic strategies to enhance these variables might be necessary for this population.

Treatment odyssey to epilepsy surgery in children with focal cortical dysplasia: Risk factors for delayed surgical intervention

ObjectiveTo elucidate the patient's journey to epilepsy surgery and identify the risk factors contributing to surgical delay in pediatric patients with drug-resistant epilepsy (DRE) due to focal cortical dysplasia (FCD). MethodsA retrospective review was conducted of 93 pediatric patients who underwent curative epilepsy surgery for FCD between January 2012 and March 2023 at a tertiary epilepsy center. The Odyssey plot demonstrated the treatment process before epilepsy surgery, including key milestones of epilepsy onset, first hospital visit, epilepsy diagnosis, MRI diagnosis, DRE diagnosis, and surgery. The primary outcome was surgical delay; the duration from DRE to surgery. Multivariate linear regression models were used to examine the association between surgical delay and clinical, investigative, and treatment characteristics. ResultsThe median age at seizure onset was 1.3 years (interquartile range [IQR] 0.14–3.1), and at the time of surgery, it was 6 years (range 1–11). Notably, 46% experienced surgical delays exceeding two years. The Odyssey plot visually highlighted that surgical delay comprised a significant portion of the patient journey. Although most patients underwent MRI before referral, MRI abnormalities were identified before referral only in 39% of the prolonged group, compared to 70% of the non-prolonged group. Multivariate analyses showed that delayed notification of MRI abnormalities, longer duration from epilepsy onset to DRE, older age at onset, number of antiseizure medications tried, and moderate to severe intellectual disability were significantly associated with prolonged surgical delay. ConclusionPediatric DRE patients with FCD experienced a long journey until surgery. Early and accurate identification of MRI abnormalities is important to minimize surgical delays.

Cannabidiol-enriched oil for adult patients with drug-resistant epilepsy: Prospective clinical and electrophysiological study.

Cannabidiol-enriched oil (CBDO) is being used increasingly to improve seizure control in adult patients with drug-resistant epilepsy (DRE), despite the lack of large-scale studies supporting its efficacy in this patient population. We aimed to assess the effects of add-on CBDO on seizure frequency as well as on gait, cognitive, affective, and sleep-quality metrics, and to explore the electrophysiological changes in responder and non-responder DRE patients treated with add-on CBDO. We prospectively recruited adult DRE patients who were treated with add-on CBDO. Patients were evaluated prior to treatment and following 4 weeks of a maintenance daily dose of ≈260 mg CBD and ≈12 mg Δ9-tetrahydrocannabinol (THC). The outcome measures included seizure response to CBDO (defined as ≥50% decrease in seizures compared to pre-CBDO baseline), gait testing, Montreal Cognitive Assessment (MoCA), Hospital Anxiety and Depression Scale (HADS), and sleep-quality questionnaire assessments. Patients underwent electroencephalography (EEG) recording during rest as well as event-related potentials (ERPs) during visual Go/NoGo task while sitting and while walking. Nineteen patients were recruited, of which 16 finished pre- and post-CBDO assessments. Seven patients (43.75%) were responders demonstrating an average reduction of 82.4% in seizures, and nine patients (56.25%) were non-responders with an average seizure increase of 30.1%. No differences in demographics and clinical parameters were found between responders and non-responders at baseline. However, responders demonstrated better performance in the dual-task walking post-treatment (p = .015), and correlation between increase in MoCA and seizure reduction (r = .810, p = .027). Post-CBDO P300 amplitude was lower during No/Go-sitting in non-responders (p = .028) and during No/Go-walking in responders (p = .068). CBDO treatment can reduce seizures in a subset of patients with DRE, but could aggravate seizure control in a minority of patients; yet we found no specific baseline clinical or electrophysiological characteristics that are associated with response to CBDO. However, changes in ERPs in response to treatment could be a promising direction to better identify patients who could benefit from CBDO treatment.

Tolerability of tariquidar – A third generation P-gp inhibitor as add-on medication to antiseizure medications in drug-resistant epilepsy

PurposeP-glycoprotein (P-gp) has been hypothesized to be involved in drug-resistance of epilepsy by actively extruding antiseizure medications (ASMs) from the brain. The P-gp inhibitor tariquidar (TQD) has been shown to effectively inhibit P-gp at the human blood-brain barrier, improving brain entry of several ASMs. A potential strategy to overcome drug-resistance is the co-administration of P-gp inhibitors such as TQD to ASMs. Here we present data on the tolerability of single-dose TQD as a potential add-on medication to ASMs. MethodsWe performed a multi-centre cohort study including drug-resistant epilepsy patients and healthy controls from the United Kingdom and Austria. TQD was administered intravenously at five different doses (2 mg/kg or 3 mg/kg of TQD were given to drug-resistant epilepsy patients and healthy controls, higher doses of TQD at 4 mg/kg, 6 mg/kg and 8 mg/kg as well as a prolonged infusion aiming at a dose of 6 mg/kg were only given to healthy controls). Adverse events were recorded and graded using the Common Terminology Criteria (CTCAE) scale. Additionally, TQD plasma concentration levels were measured and compared between drug-resistant patients and healthy controls. ResultsIn total, 108 participants received TQD once at variable doses and it was overall well tolerated. At doses of 2 or 3 mg/kg TQD, only two of the 19 drug-resistant epilepsy patients and a third of the healthy controls (n = 14/42) reported adverse events probably related to TQD. The majority of those adverse events (96 %) were reported as mild. One drug-resistant epilepsy patient reported adverse events 24-hours after TQD administration possibly related to TQD-induced increased ASMs levels in the brain. ConclusionsTQD is an effective and well tolerated P-gp inhibitor as a single dose and could potentially be used intermittently in conjunction with ASMs to improve efficacy. This promising strategy to overcome drug-resistance in epilepsy should be investigated further in clinical randomised controlled trials.

Neuronal synchrony and critical bistability: Mechanistic biomarkers for localizing the epileptogenic network.

Postsurgical seizure freedom in drug-resistant epilepsy (DRE) patients varies from 30% to 80%, implying that in many cases the current approaches fail to fully map the epileptogenic zone (EZ). We aimed to advance a novel approach to better characterize epileptogenicity and investigate whether the EZ encompasses a broader epileptogenic network (EpiNet) beyond the seizure zone (SZ) that exhibits seizure activity. We first used computational modeling to test putative complex systems-driven and systems neuroscience-driven mechanistic biomarkers for epileptogenicity. We then used these biomarkers to extract features from resting-state stereoelectroencephalograms recorded from DRE patients and trained supervised classifiers to localize the SZ against gold standard clinical localization. To further explore the prevalence of pathological features in an extended brain network outside of the clinically identified SZ, we also used unsupervised classification. Supervised SZ classification trained on individual features achieved accuracies of .6-.7 area under the receiver operating characteristic curve (AUC). Combining all criticality and synchrony features further improved the AUC to .85. Unsupervised classification discovered an EpiNet-like cluster of brain regions, in which 51% of brain regions were outside of the SZ. Brain regions in the EpiNet-like cluster engaged in interareal hypersynchrony and locally exhibited high-amplitude bistability and excessive inhibition, which was strikingly similar to the high seizure risk regime revealed by our computational modeling. The finding that combining biomarkers improves SZ localization accuracy indicates that the novel mechanistic biomarkers for epileptogenicity employed here yield synergistic information. On the other hand, the discovery of SZ-like brain dynamics outside of the clinically defined SZ provides empirical evidence of an extended pathophysiological EpiNet.

DeepFLAIR: A neural network approach to mitigate signal and contrast loss in temporal lobes at 7 Tesla FLAIR images

Background and purposeHigher magnetic field strength introduces stronger magnetic field inhomogeneities in the brain, especially within temporal lobes, leading to image artifacts. Particularly, T2-weighted fluid-attenuated inversion recovery (FLAIR) images can be affected by these artifacts. Here, we aimed to improve the FLAIR image quality in temporal lobe regions through image processing of multiple contrast images via machine learning using a neural network. MethodsThirteen drug-resistant MR-negative epilepsy patients (age 29.2 ± 9.4y, 5 females) were scanned on a 7 T MRI scanner. Magnetization-prepared (MP2RAGE) and saturation-prepared with 2 rapid gradient echoes, multi-echo gradient echo with four echo times, and the FLAIR sequence were acquired. A voxel-wise neural network was trained on extratemporal-lobe voxels from the acquired structural scans to generate a new FLAIR-like image (i.e., deepFLAIR) with reduced temporal lobe inhomogeneities. The deepFLAIR was evaluated in temporal lobes through signal-to-noise (SNR), contrast-to-noise (CNR) ratio, the sharpness of the gray-white matter boundary and joint-histogram analysis. Saliency mapping demonstrated the importance of each input image per voxel. ResultsSNR and CNR in both gray and white matter were significantly increased (p < 0.05) in the deepFLAIR's temporal ROIs, compared to the FLAIR. The gray-white matter boundary sharpness was either preserved or improved in 10/13 right-sided temporal regions and was found significantly increased in the ROIs. Multiple image contrasts were influential for the deepFLAIR reconstruction with the MP2RAGE second inversion image being the most important. ConclusionsThe deepFLAIR network showed promise to restore the FLAIR signal and reduce contrast attenuation in temporal lobe areas. This may yield a valuable tool, especially when artifact-free FLAIR images are not available.

Enhancement of Subjective Quality of Life Following Surgical Intervention in Patients With Drug-Resistant Epilepsy: A Depressive Symptom-Independent Outcome.

To evaluate the impact of depressive symptoms on the subjective perception of quality of life in patients with drug-resistant epilepsy (DRE) after surgical treatment for seizures. Methods: A case-control study with DRE patients who received surgical treatment (n=19) and matched non-operated patients (n=23). We assessed the quality of life using the Subjective Handicap of Epilepsy (SHE) scale, alongside measuring depressive symptoms using the Beck Depression Inventory (BDI). The mean age of the participants was 45 years, with females constituting 52.4% of the patients. A majority (73.8%) had been diagnosed with temporal lobe epilepsy. Those who had undergone surgical intervention showed significantly enhanced performance across all quality-of-life domains on the SHE scale independently of depressive symptoms. The domains of "Work and Activity,""Physical Health,"and "Self-Perception" displayed the greatest improvements, with the surgical group's averages outperforming the control group by factors of 1.87, 2.53, and 2.81, respectively. Influential differences impacting the quality-of-life scores included seizure frequency, the quantity of antiepileptic drugs utilized, and the incidence of convulsive seizures. The findings suggest that surgical control of seizures in drug-resistant focal epilepsy is associated with improvement in quality of life across various domains, independently of the depressive symptoms of the patients.

Optimized microburst VNS elicits fMRI responses beyond thalamic-specific response from standard VNS.

In parallel to standard vagus nerve stimulation (VNS), microburst stimulation delivery has been developed. We evaluated the fMRI-related signal changes associated with standard and optimized microburst stimulation in a proof-of-concept study (NCT03446664). Twenty-nine drug-resistant epilepsy patients were prospectively implanted with VNS. Three 3T fMRI scans were collected 2 weeks postimplantation. The maximum tolerated VNS intensity was determined prior to each scan starting at 0.125 mA with 0.125 mA increments. FMRI scans were block-design with alternating 30 sec stimulation [ON] and 30 sec no stimulation [OFF]: Scan 1 utilized standard VNS and Scan 3 optimized microburst parameters to determine target settings. Semi-automated on-site fMRI data processing utilized ON-OFF block modeling to determine VNS-related fMRI activation per stimulation setting. Anatomical thalamic mask was used to derive highest mean thalamic t-value for determination of microburst stimulation parameters. Paired t-tests corrected at P < 0.05 examined differences in fMRI responses to each stimulation type. Standard and microburst stimulation intensities at Scans 1 and 3 were similar (P = 0.16). Thalamic fMRI responses were obtained in 28 participants (19 with focal; 9 with generalized seizures). Group activation maps showed standard VNS elicited thalamic activation while optimized microburst VNS showed widespread activation patterns including thalamus. Comparison of stimulation types revealed significantly greater cerebellar, midbrain, and parietal fMRI signal changes in microburst compared to standard VNS. These differences were not associated with seizure responses. While standard and optimized microburst VNS elicited thalamic activation, microburst also engaged other brain regions. Relationship between these fMRI activation patterns and clinical response warrants further investigation. The study was registered with clinicaltrials.gov (NCT03446664).

Serum biomarkers in patients with drug-resistant epilepsy: a proteomics-based analysis.

To investigate the serum biomarkers in patients with drug-resistant epilepsy (DRE). A total of 9 DRE patients and 9 controls were enrolled. Serum from DRE patients was prospectively collected and analyzed for potential serum biomarkers using TMT18-labeled proteomics. After fine quality control, bioinformatics analysis was conducted to find differentially expressed proteins. Pathway enrichment analysis identified some biological features shared by differential proteins. Protein-protein interaction (PPI) network analysis was further performed to discover the core proteins. A total of 117 serum differential proteins were found in our study, of which 44 were revised upwards and 73 downwards. The up-regulated proteins mainly include UGGT2, PDIA4, SEMG1, KIAA1191, CCT7 etc. and the down-regulated proteins mainly include ROR1, NIF3L1, ITIH4, CFP, COL11A2 etc. Pathway enrichment analysis identified that the upregulated proteins were mainly enriched in processes such as immune response, extracellular exosome, serine-type endopeptidase activity and complement and coagulation cascades, and the down-regulated proteins were enriched in signal transduction, extracellular exosome, zinc/calcium ion binding and metabolic pathways. PPI network analysis revealed that the core proteins nodes include PRDX6, CAT, PRDX2, SOD1, PARK7, GSR, TXN, ANXA1, HINT1, and S100A8 etc. The discovery of these differential proteins enriched our understanding of serum biomarkers in patients with DRE and potentially provides guidance for future targeted therapy.