MRI-negative Epilepsy Research Articles

Multimodal and quantitative analysis of the epileptogenic zone network in the pre-surgical evaluation of drug-resistant focal epilepsy

Surgical resection for epilepsy often fails due to incomplete Epileptogenic Zone Network (EZN) localization from scalp electroencephalography (EEG), stereo-EEG (SEEG), and Magnetic Resonance Imaging (MRI). Subjective interpretation based on interictal, or ictal recordings limits conventional EZN localization. This study employs multimodal analysis using high-density-EEG (HDEEG), Magnetoencephalography (MEG), functional-MRI (fMRI), and SEEG to overcome these limitations in a patient with drug-resistant MRI-negative focal epilepsy. A 17-year-old with drug-resistant epilepsy underwent evaluation. HDEEG, MEG, fMRI, and SEEG were used, with a novel HDEEG-cap facilitating simultaneous EEG-MEG and EEG-fMRI recordings. Electrical and magnetic source imaging were performed, and fMRI data were analysed for homogenous regions. SEEG analysis involved spike detection, spike timing analysis, ictal fast activity quantification, and Granger-based connectivity analysis. Non-invasive sessions revealed consistent interictal source imaging results identifying the EZN in the right anterior cingulate cortex. EEG-fMRI highlighted broader activation in the right cingulate cortex. SEEG analysis localized spikes and fast activity in the right anterior and posterior cingulate gyri. Multi-modal analysis suggested the EZN in the right frontal lobe, primarily involving the anterior and mid-cingulate cortices. Multi-modal non-invasive analyses can optimise SEEG implantation and surgical decision-making. Invasive analyses corroborated non-invasive findings, emphasising the importance of individual-case quantitative analysis across modalities in complex epilepsy cases.

Structural and functional alterations in MRI-negative drug-resistant epilepsy and associated gene expression features

Neuroimaging techniques have been widely used in the study of epilepsy. However, structural and functional changes in the MRI-negative drug-resistant epilepsy (DRE) and the genetic mechanisms behind the structural alterations remain poorly understood. Using structural and functional MRI, we analyzed gray matter volume (GMV) and regional homogeneity (ReHo) in DRE, drug-sensitive epilepsy (DSE) and healthy controls. Gene expression data from Allen human brain atlas and GMV/ReHo were evaluated to obtain drug resistance-related and epilepsy-associated gene expression and compared with real transcriptional data in blood. We found structural and functional alterations in the cerebellum of DRE patients, which may be related to the mechanisms of drug resistance in DRE. Our study confirms that changes in brain morphology and regional activity in DRE patients may be associated with abnormal gene expression related to nervous system development. And SP1, as an important transcription factor, plays an important role in the mechanism of drug resistance.

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.

Hippocampal Glutamate Levels and Their Correlation With Subregion Volume in School-Aged Children With MRI-Negative Epilepsy: A Preliminary Study.

Abnormal levels of glutamate constitute a key pathophysiologic mechanism in epilepsy. The use of glutamate chemical exchange saturation transfer (GluCEST) imaging to measure glutamate levels in pediatric epilepsy is rarely reported in research. To investigate hippocampal glutamate level variations in pediatric epilepsy and the correlation between glutamate and hippocampal subregional volumes. Cross-sectional, prospective. A total of 38 school-aged pediatric epilepsy patients with structurally normal MRI as determined by at least two independent radiologists (60% males; 8.7 ± 2.5 years; including 20 cases of focal pediatric epilepsy [FE] and 18 cases of generalized pediatric epilepsy [GE]) and 17 healthy controls (HC) (41% males; 9.0 ± 2.5 years). 3.0 T; 3D magnetization prepared rapid gradient echo (MPRAGE) and 2D turbo spin echo GluCEST sequences. The relative concentration of glutamate was calculated through pixel-wise magnetization transfer ratio asymmetry (MTRasym) analysis of the GluCEST data. Hippocampal subfield volumes were computed from MPRAGE data using FreeSurfer. This study used t tests, one-way analysis of variance, Kruskal-Wallis tests, and Pearson correlation analysis. P < 0.05 was considered statistically significant. The MTRasym values of both the left and right hippocampi were significantly elevated in GE (left: 2.51 ± 0.23 [GE] vs. 2.31 ± 0.12 [HCs], right: 2.50 ± 0.22 [GE] vs. 2.27 ± 0.22 [HCs]). The MTRasym values of the ipsilateral hippocampus were significantly elevated in FE (2.49 ± 0.28 [ipsilateral] vs. 2.29 ± 0.16 [HCs]). The MTRasym values of the ipsilateral hippocampus were significantly increased compared to the contralateral hippocampus in FE (2.49 ± 0.28 [ipsilateral] vs. 2.35 ± 0.34 [contralateral]). No significant differences in hippocampal volume were found between different groups (left hippocampus, P = 0.87; right hippocampus, P = 0.87). GluCEST imaging have potential for the noninvasive measurement of glutamate levels in the brains of children with epilepsy. 2 TECHNICAL EFFICACY: Stage 1.

Insomnia in patients with MRI-negative epilepsy: The associated factors and 3D-pCASL cerebral blood flow perfusion changes

ObjectiveThis study aimed to identify the factors associated with insomnia in MRI-negative epilepsy and uncover the underlying pathological mechanism driving insomnia within the context of epilepsy. MethodsWe conducted a retrospective study of patients with MRI-negative epilepsy recruited consecutively from December 2021 to December 2022. All subjects completed the Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS). Additionally, some subjects underwent the three-dimensional pseudo continuous arterial spin labeling(3D-pCASL) imaging examination. Bilateral frontal lobe, temporal lobe, hippocampus, thalamus, amygdala, caudate nucleus and lenticular nucleus were selected as regions of interest(ROI) and cerebral blood flow(CBF) values were measured in these regions. Subjects were classified into insomnia (ISI ≥ 10) or non-insomnia (ISI < 10) groups, and univariate and stepwise logistic regression analyses were employed to identify the factors associated with insomnia. Furthermore, CBF values in each ROI were compared between the two groups to identify the brain regions potentially related to the underlying pathological mechanism of insomnia in epilepsy. ResultsA total of 73 patients with MRI-negative epilepsy were recruited in this study(men, 49.3 %). Among them, 14 patients(19.2 %) had insomnia. Univariate regression revealed that nocturnal seizures, number of anti-seizure medication(ASM), anxiety, use of valproic acid(VPA), depression, and excessive daytime sleepiness(EDS) may be associated with insomnia in MRI-negative epilepsy (all p＜0.05). Stepwise regression demonstrated that nocturnal seizures, anxiety, and EDS were independently associated with insomnia in MRI-negative epilepsy (OR[95 %CI]P: 14.64[2.02–106.27]0.008,49.35[3.06–796.61]0.006, 13.28[1.25–140.66]0.032, respectively). Furthermore, CBF values in the left amygdala were significantly lower in patients with MRI- negative epilepsy who had insomnia. ConclusionThe prevalence of insomnia in MRI-negative epilepsy is 19.2%. Nocturnal seizures, anxiety, and EDS were independently associated with insomnia in MRI-negative epilepsy. The noteworthy decrease in CBF values in the left amygdala might be connected to the underlying pathological mechanism of insomnia in epilepsy.

Out of Sight, Not Yet Out of Reach: Surgical Outcomes in MRI-Negative and Pathology-Negative Epilepsy Patients.

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Identification of abnormal closed-loop pathways in patients with MRI-negative pharmacoresistant epilepsy.

Epilepsy is a disorder of brain networks, that is usually combined with cognitive and emotional impairment. However, most of the current research on closed-loop pathways in epilepsy is limited to the neuronal level or has focused only on known closed-loop pathways, and studies on abnormalities in closed-loop pathways in epilepsy at the whole-brain network level are lacking. A total of 26 patients with magnetic resonance imaging-negative pharmacoresistant epilepsy (MRIneg-PRE) and 26 healthy controls (HCs) were included in this study. Causal brain networks and temporal-lag brain networks were constructed from resting-state functional MRI data, and the Johnson algorithm was used to identify stable closed-loop pathways. Abnormal closed-loop pathways in the MRIneg-PRE cohort compared with the HC group were identified, and the associations of these pathways with indicators of cognitive and emotional impairments were examined via Pearson correlation analysis. The results revealed that the abnormal stable closed-loop pathways were distributed across the frontal, parietal, and occipital lobes and included altered functional connectivity values both within and between cerebral hemispheres. Four abnormal closed-loop pathways in the occipital lobe were associated with emotional and cognitive impairments. These abnormal pathways may serve as biomarkers for the diagnosis and guidance of individualized treatments for MRIneg-PRE patients.

Resting-state functional MRI study of conventional MRI-negative intractable epilepsy in children.

The study aimed at investigating functional connectivity strength (FCS) changes in children with MRI-negative intractable epilepsy (ITE) and evaluating correlations between aberrant FCS and both disease duration and intelligence quotient (IQ). Fifteen children with ITE, 24 children with non-intractable epilepsy (nITE) and 25 matched healthy controls (HCs) were subjected to rs-fMRI. IQ was evaluated by neuropsychological assessment. Voxelwise analysis of covariance was conducted in the whole brain, and then pairwise comparisons were made across three groups using Bonferroni corrections. FCS was significantly different among three groups. Relative to HCs, ITE patients exhibited decreased FCS in right temporal pole of the superior temporal gyrus, middle temporal gyrus, bilateral precuneus, etc and increased FCS values in left triangular part of the inferior frontal gyrus, parahippocampal gyrus, supplementary motor area, caudate and right calcarine fissure and surrounding cortex and midbrain. The nITE patients presented decreased FCS in right orbital superior frontal gyrus, precuneus etc and increased FCS in bilateral fusiform gyri, parahippocampal gyri, etc. In comparison to nITE patients, the ITE patients presented decreased FCS in right medial superior frontal gyrus and left inferior temporal gyrus and increased FCS in right middle temporal gyrus, inferior temporal gyrus and calcarine fissure and surrounding cortex. Correlation analysis indicated that FCS in left caudate demonstrated correlation with verbal IQ (VIQ) and disease duration. ITE patients demonstrated changed FCS values in the temporal and prefrontal cortices relative to nITE patients, which may be related to drug resistance in epilepsy. FCS in the left caudate nucleus associated with VIQ, suggesting the caudate may become a key target for improving cognitive impairment and seizures in children with ITE.

To explore the potential mechanisms of cognitive impairment in children with MRI-negative pharmacoresistant epilepsy due to focal cortical dysplasia: A pilot study from gray matter structure view

ObjectivesTo investigate the characteristics of brain structure in children with focal cortical dysplasia (FCD)-induced pharmacoresistant epilepsy, and explore the potential mechanisms of cognitive impairment from the view of gray matter alteration. Methods25 pharmacoresistant pediatric patients with pathologically confirmed focal cortical dysplasia (FCD), and 25 gender-matched healthy controls were included in this study. 3.0T MRI data and intelligence tests using the Wechsler Intelligence Scale for Children-Forth Edition (WISC-IV) were generated for all subjects. Voxel-based morphometry (VBM)-diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) and surface-based morphometry (SBM) analyses were performed to analyze gray matter volume and cortical structure. Two-sample t-tests were used to compare the differences in gray matter volume (P＜0.05, FWE) and cortical thickness (P＜0.001, FWE) between the two groups. Also, the Spearman rank correlation analyses were employed to determine the relationship between structural alterations and neuropsychological results. ResultsThe WISC-IV scores of the FCD group were significantly lower than those of the HC group in terms of full-scale intelligence quotient (FSIQ), verbal comprehension index (VCI), perceptual reasoning index (PRI), working memory index (WMI), and processing speed index (PSI) (all P＜0.01). Compared with the HC group, in the FCD group, the gray matter volume (GMV) reduced significantly in the left cerebellum_8, cerebellum_Crus2, and bilateral thalamus (P＜0.05, FWE); the GMV increased in the bilateral medial frontal gyrus, right precuneus, and left inferior temporal gyrus (P＜0.05, FWE), and the cortical thickness increased in the bilateral frontal, parietal, and temporal areas (P＜0.001, FWE). Correlation analyses showed that the age of seizure onset had positive correlations with the WISC-IV scores significantly. Meanwhile, the cortex thicknesses of the left pars opercularis gyrus, left middle temporal gyrus, and right inferior temporal gyrus had negative correlations with the WISC-IV scores significantly. ConclusionFCD patients showed subtle structural abnormalities in multiple brain regions, with significant involvement of the primary visual cortex and language function cortex. And we also demonstrated a crucial correlation between gray matter structural alteration and cognitive impairment.

Automated detection of MRI-negative temporal lobe epilepsy with ROI-based morphometric features and machine learning.

Temporal lobe epilepsy (TLE) predominantly originates from the anteromedial basal region of the temporal lobe, and its prognosis is generally favorable following surgical intervention. However, TLE often appears negative in magnetic resonance imaging (MRI), making it difficult to quantitatively diagnose the condition solely based on clinical symptoms. There is a pressing need for a quantitative, automated method for detecting TLE. This study employed MRI scans and clinical data from 51 retrospective epilepsy cases, dividing them into two groups: 34 patients in TLE group and 17 patients in non-TLE group. The criteria for defining the TLE group were successful surgical removal of the epileptogenic zone in the temporal lobe and a favorable postoperative prognosis. A standard procedure was used for normalization, brain extraction, tissue segmentation, regional brain partitioning, and cortical reconstruction of T1 structural MRI images. Morphometric features such as gray matter volume, cortical thickness, and surface area were extracted from a total of 20 temporal lobe regions in both hemispheres. Support vector machine (SVM), extreme learning machine (ELM), and cmcRVFL+ classifiers were employed for model training and validated using 10-fold cross-validation. The results demonstrated that employing ELM classifiers in conjunction with specific temporal lobe gray matter volume features led to a better identification of TLE. The classification accuracy was 92.79%, with an area under the curve (AUC) value of 0.8019. The method proposed in this study can significantly assist in the preoperative identification of TLE patients. By employing this method, TLE can be included in surgical criteria, which could alleviate patient symptoms and improve prognosis, thereby bearing substantial clinical significance.

Correspondence between scalp-EEG and stereoelectroencephalography seizure-onset patterns in patients with MRI-negative drug-resistant focal epilepsy.

Our objective was to evaluate the relationship between scalp-EEG and stereoelectroencephalography (SEEG) seizure-onset patterns (SOP) in patients with MRI-negative drug-resistant focal epilepsy. We analyzed retrospectively 41 patients without visible lesion on brain MRI who underwent video-EEG followed by SEEG. We defined five types of SOPs on scalp-EEG and eight types on SEEG. We examined how various clinical variables affected scalp-EEG SOPs. The most prevalent scalp SOPs were rhythmic sinusoidal activity (56.8%), repetitive epileptiform discharges (22.7%), and paroxysmal fast activity (15.9%). The presence of paroxysmal fast activity on scalp-EEG was always seen without delay from clinical onset and correlated with the presence of low-voltage fast activity in SEEG (sensitivity = 22.6%, specificity = 100%). The main factor explaining the discrepancy between the scalp and SEEG SOPs was the delay between clinical and scalp-EEG onset. There was a correlation between the scalp and SEEG SOPs when the scalp onset was simultaneous with the clinical onset (p = 0.026). A significant delay between clinical and scalp discharge onset was observed in 25% of patients and featured always with a rhythmic sinusoidal activity on scalp, corresponding to similar morphology of the discharge on SEEG. The presence of repetitive epileptiform discharges on scalp was associated with an underlying focal cortical dysplasia (sensitivity = 30%, specificity = 90%). There was no significant association between the scalp SOP and the epileptogenic zone location (deep or superficial), or surgical outcome. In patients with MRI-negative focal epilepsy, scalp SOP could suggest the SEEG SOP and some etiology (focal cortical dysplasia) but has no correlation with surgical prognosis. Scalp SOP correlates with the SEEG SOP in cases of simultaneous EEG and clinical onset; otherwise, scalp SOP reflects the propagation of the SEEG discharge. We looked at the correspondence between the electrical activity recorded during the start of focal seizure using scalp and intracerebral electrodes in patients with no visible lesion on MRI. If there is a fast activity on scalp, it reflects similar activity inside the brain. We found a good correspondence between scalp and intracerebral electrical activity for cases without significant delay between clinical and scalp electrical onset (seen in 75% of the cases we studied). Visualizing repetitive epileptic activity on scalp could suggest a particular cause of the epilepsy: a subtype of brain malformation called focal cortical dysplasia.

Multimodal non-invasive evaluation in MRI-negative epilepsy patients.

Presurgical evaluation is still challenging for MRI-negative epilepsy patients. As non-invasive modalities are the easiest acceptable and economic methods in determining the epileptogenic zone, we analyzed the localization value of common non-invasive methods in MRI-negative epilepsy patients. In this study, we included epilepsy patients undergoing presurgical evaluation with presurgical negative MRI. MRI post-processing was performed using a Morphometric Analysis Program (MAP) on T1-weighted volumetric MRI. The relationship between MAP, magnetoencephalography (MEG), scalp electroencephalogram (EEG), and seizure outcomes was analyzed to figure out the localization value of different non-invasive methods. Eighty-six patients were included in this study. Complete resection of the MAP-positive regions or the MEG-positive regions was positively associated with seizure freedom (p = 0.028 and 0.007, respectively). When an area is co-localized by MAP and MEG, the resection of the area was significantly associated with seizure freedom (p = 0.006). However, neither the EEG lateralization nor the EEG localization showed statistical association with the surgical outcome (p = 0.683 and 0.505, respectively). In conclusion, scalp EEG had a limited role in presurgical localization and predicting seizure outcome, combining MAP and MEG results can significantly improve the localization of epileptogenic lesions and have a positive association with seizure-free outcome. PLAIN LANGUAGE SUMMARY: Due to the lack of obvious structure abnormalities on neuroimaging examinations, the identification of epilepsy lesions in MRI-negative epilepsy patients can be difficult. In this study, we intended to use non-invasive examinations to explore the potential epileptic lesions in MRI-negative epilepsy patients and to determine the results accuracy by comparing the neuroimaging results with the epilepsy surgery outcomes. A total of 86 epilepsy patients without obvious structure lesions on MRI were included, and we found that the combinations of different non-invasive examinations and neuroimaging post-processing methods are significantly associated with the seizure freedom results of epilepsy surgery.

Predictors of seizure outcomes in stereo-electroencephalography-guided radio-frequency thermocoagulation for MRI-negative epilepsy.

One-third of intractable epilepsy patients have no visually identifiable focus for neurosurgery based on imaging tests [magnetic resonance imaging (MRI)-negative cases]. Stereo-electroencephalography-guided radio-frequency thermocoagulation (SEEG-guided RF-TC) is utilized in the clinical treatment of epilepsy to lower the incidence of complications post-open surgery. This study aimed to identify prognostic factors and long-term seizure outcomes in SEEG-guided RF-TC for patients with MRI-negative epilepsy. This was a single-center retrospective cohort study. We included 30 patients who had undergone SEEG-guided RF-TC at Sanbo Brain Hospital, Capital Medical University, from April 2015 to December 2019. The probability of remaining seizure-free and the plotted survival curves were analyzed. Prognostic factors were analyzed using log-rank tests in univariate analysis and the Cox regression model in multivariate analysis. With a mean time of 31.07 ± 2.64 months (median 30.00, interquartile range: 18.00-40.00 months), 11 out of 30 patients (36.7%) were classified as International League Against Epilepsy class 1 in the last follow-up. The mean time of remaining seizure-free was 21.33 ± 4.55 months [95% confidence interval (CI) 12.41-30.25], and the median time was 3.00 ± 0.54 months (95% CI 1.94-4.06). Despite falling in the initial year, the probability of remaining seizure-free gradually stabilizes in the subsequent years. The patients were more likely to obtain seizure freedom when the epileptogenic zone was located in the insular lobe or with one focus on the limbic system (p = 0.034, hazard ratio 5.019, 95% CI 1.125-22.387). Our findings may be applied to guide individualized surgical interventions and help clinicians make better decisions.

In vivo γ-aminobutyric acid alterations as a biomarker of the therapeutic effect of MRI-negative temporal lobe epilepsy

In vivo γ-aminobutyric acid alterations as a biomarker of the therapeutic effect of MRI-negative temporal lobe epilepsy

Yield of non-invasive imaging in MRI-negative focal epilepsy.

The absence of MRI-lesion reduces considerably the probability of having an excellent outcome (International League Against Epilepsies [ILAE] class I-II) after epilepsy surgery. Surgical success in magnetic-resonance imaging (MRI)-negative cases relies therefore mainly on non-invasive techniques such as positron-emission tomography (PET), subtraction ictal/inter-ictal single-photon-emission-computed-tomography co-registered to MRI (SISCOM), electric source imaging (ESI) and morphometric MRI analysis (MAP). We were interested in identifying the optimal imaging technique or combination to achieve post-operative class I-II in patients with MRI-negative focal epilepsy. We identified 168 epileptic patients without MRI lesion. Thirty-three (19.6%) were diagnosed with unifocal epilepsy, underwent surgical resection and follow-up ⩾ 2 years. Sensitivity, specificity, predictive values, and diagnostic odds ratio (OR) were calculated for each technique individually and in combination (after co-registration). 23/33 (70%) were free of disabling seizures (75.0% with temporal and 61.5% extratemporal lobe epilepsy). None of the individual modalities presented an OR > 1.5, except ESI if only patients with interictal epileptiform discharges (IEDs) were considered (OR 3.2). On a dual combination, SISCOM with ESI presented the highest outcome (OR = 6). MAP contributed to detecting indistinguishable focal cortical dysplasia in particular in extratemporal epilepsies with a sensitivity of 75%. Concordance of PET, ESI on interictal epileptic discharges, and SISCOM was associated with the highest chance for post-operative seizure control (OR = 11). If MRI is negative, the chances to benefit from epilepsy surgery are almost as high as in lesional epilepsy, provided that multiple established non-invasive imaging tools are rigorously applied and co-registered together.

Cognitive Impairment in MRI-Negative Epilepsy: Relationship between Neurophysiological and Neuropsychological Measures.

Epileptic patients frequently encounter cognitive impairment. Functions that are mostly affected involve memory, attention, and executive function; however, this is mainly dependent on the location of the epileptic activity. The aim of the present study is to assess cognitive functions in MRI-negative epilepsy patients by means of neurophysiological and neuropsychological measures, as well as study the concept of transient cognitive impairment in patients with epileptiform discharges during EEG acquisition. The patients were enrolled from an outpatient Epilepsy/Clinical Neurophysiology clinic over a time period of 6 months. The study sample comprised 20 MRI-negative epilepsy patients (mean age ± standard deviation (SD), 30.3 ± 12.56 years; age range, 16-60 years; average disease duration, 13.95 years) and 10 age-matched controls (mean age ± SD, 24.22 ± 15.39 years), who were also education-matched (p > 0.05). Patients with epileptogenic lesions were excluded from the study. Informed consent was obtained from all subjects involved in the study. Auditory ERPs and the cognitive screening tool EpiTrack were administered to all subjects. Latencies of P300 and slow waves were prolonged in patients compared to controls (p < 0.05). The ASM load and patients' performance in the EpiTrack maze subtest were the most significant predictors of P300 latency. A decline in the memory, attention, and speed of information processing was observed in patients with cryptogenic epilepsy compared to age-matched controls, as reflected by P300 latency and EpiTrack scores.

Skull-base temporal encephalocele: Hidden cause of temporal lobe epilepsy.

In the present study patients with previously diagnosed MRI-negative temporal lobe epilepsy (TLE) on long-term video electroencephalography (VEEG) monitoring were re-evaluated with high resolution 3T MRI brain to look out for a skull base temporal lobe encephalocoele (TE). A total of 234 VEEGs were analyzed. TLE had been diagnosed in 104 patients based on semiology, ictal, interictal EEG data, and brain positron emission tomography (PET) studies. Of these, 99 patients had temporal lobe abnormality (78 had mesial temporal sclerosis, 8 had tumor, 3 had focal cortical dysplasia, and 10 had mixed pathology). Out of the five 1.5T MRI-negative TLE patients, two patients were diagnosed with TE on subsequent 3T MRI brain scans and one patient underwent electrocorticography-guided tailored resection for complete removal of epileptogenic tissue; with Engels class I seizure freedom at one year follow-up. We propose that TE should be carefully searched for, as a cause of refractory TLE, using high-resolution MRI sequences.

Focal epilepsy without overt epileptogenic lesions: no evidence of microstructural brain tissue damage in multi-parametric quantitative MRI.

In patients with epilepsies of structural origin, brain atrophy and pathological alterations of the tissue microstructure extending beyond the putative epileptogenic lesion have been reported. However, in patients without any evidence of epileptogenic lesions on diagnostic magnetic resonance imaging (MRI), impairment of the brain microstructure has been scarcely elucidated. Using multiparametric quantitative (q) magnetic resonance imaging MRI, we aimed to investigate diffuse impairment of the microstructural tissue integrity in MRI-negative focal epilepsy patients. 27 MRI-negative patients with focal epilepsy (mean age 33.1 ± 14.2 years) and 27 matched healthy control subjects underwent multiparametric qMRI including T1, T2, and PD mapping at 3 T. After tissue segmentation based on synthetic anatomies, mean qMRI parameter values were extracted from the cerebral cortex, the white matter (WM) and the deep gray matter (GM) and compared between patients and control subjects. Apart from calculating mean values for the qMRI parameters across the respective compartments, voxel-wise analyses were performed for each tissue class. There were no significant differences for mean values of quantitative T1, T2, and PD obtained from the cortex, the WM and the deep GM between the groups. Furthermore, the voxel-wise analyses did not reveal any clusters indicating significant differences between patients and control subjects for the qMRI parameters in the respective compartments. Based on the employed methodology, no indication for an impairment of the cerebral microstructural tissue integrity in MRI-negative patients with focal epilepsy was found in this study. Further research will be necessary to identify relevant factors and mechanisms contributing to microstructural brain tissue damage in various subgroups of patients with epilepsy.

Magnetoencephalography-based approaches to epilepsy classification.

Epilepsy is a chronic central nervous system disorder characterized by recurrent seizures. Not only does epilepsy severely affect the daily life of the patient, but the risk of premature death in patients with epilepsy is three times higher than that of the normal population. Magnetoencephalography (MEG) is a non-invasive, high temporal and spatial resolution electrophysiological data that provides a valid basis for epilepsy diagnosis, and used in clinical practice to locate epileptic foci in patients with epilepsy. It has been shown that MEG helps to identify MRI-negative epilepsy, contributes to clinical decision-making in recurrent seizures after previous epilepsy surgery, that interictal MEG can provide additional localization information than scalp EEG, and complete excision of the stimulation area defined by the MEG has prognostic significance for postoperative seizure control. However, due to the complexity of the MEG signal, it is often difficult to identify subtle but critical changes in MEG through visual inspection, opening up an important area of research for biomedical engineers to investigate and implement intelligent algorithms for epilepsy recognition. At the same time, the use of manual markers requires significant time and labor costs, necessitating the development and use of computer-aided diagnosis (CAD) systems that use classifiers to automatically identify abnormal activity. In this review, we discuss in detail the results of applying various different feature extraction methods on MEG signals with different classifiers for epilepsy detection, subtype determination, and laterality classification. Finally, we also briefly look at the prospects of using MEG for epilepsy-assisted localization (spike detection, high-frequency oscillation detection) due to the unique advantages of MEG for functional area localization in epilepsy, and discuss the limitation of current research status and suggestions for future research. Overall, it is hoped that our review will facilitate the reader to quickly gain a general understanding of the problem of MEG-based epilepsy classification and provide ideas and directions for subsequent research.

Distinguishing Patients with MRI-Negative Temporal Lobe Epilepsy from Normal Controls Based on Individual Morphological Brain Network.

Temporal Lobe Epilepsy (TLE) is the most common subtype of focal epilepsy and the most refractory to drug treatment. Roughly 30% of patients do not have easily identifiable structural abnormalities. In other words, MRI-negative TLE has normal MRI scans on visual inspection. Thus, MRI-negative TLE is a diagnostic and therapeutic challenge. In this study, we investigate the cortical morphological brain network to identify MRI-negative TLE. The 210 cortical ROIs based on the Brainnetome atlas were used to define the network nodes. The least absolute shrinkage and selection operator (LASSO) algorithm and Pearson correlation methods were used to calculate the inter-regional morphometric features vector correlation respectively. As a result, two types of networks were constructed. The topological characteristics of networks were calculated by graph theory. Then after, a two-stage feature selection strategy, including a two-sample t-test and support vector machine-based recursive feature elimination (SVM-RFE), was performed in feature selection. Finally, classification with support vector machine (SVM) and leave-one-out cross-validation (LOOCV) was employed for the training and evaluation of the classifiers. The performance of two constructed brain networks was compared in MRI-negative TLE classification. The results indicated that the LASSO algorithm achieved better performance than the Pearson pairwise correlation method. The LASSO algorithm provides a robust method of individual morphological network construction for distinguishing patients with MRI-negative TLE from normal controls.