ABSTRACT
Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.
Subject(s)
Electroencephalography , Entropy , Magnetoencephalography , Humans , Magnetoencephalography/methods , Electroencephalography/methods , Adult , Female , Male , Computer Simulation , Young Adult , Epilepsy/physiopathology , Epilepsy/diagnostic imaging , Middle Aged , Brain Mapping/methods , Brain/diagnostic imaging , Brain/physiopathology , Hippocampus/diagnostic imaging , Hippocampus/physiopathology , Models, NeurologicalABSTRACT
Functional changes in the pediatric brain following neural injuries attest to remarkable feats of plasticity. Investigations of the neurobiological mechanisms that underlie this plasticity have largely focused on activation in the penumbra of the lesion or in contralesional, homotopic regions. Here, we adopt a whole-brain approach to evaluate the plasticity of the cortex in patients with large unilateral cortical resections due to drug-resistant childhood epilepsy. We compared the functional connectivity (FC) in patients' preserved hemisphere with the corresponding hemisphere of matched controls as they viewed and listened to a movie excerpt in a functional magnetic resonance imaging (fMRI) scanner. The preserved hemisphere was segmented into 180 and 200 parcels using two different anatomical atlases. We calculated all pairwise multivariate statistical dependencies between parcels, or parcel edges, and between 22 and 7 larger-scale functional networks, or network edges, aggregated from the smaller parcel edges. Both the left and right hemisphere-preserved patient groups had widespread reductions in FC relative to matched controls, particularly for within-network edges. A case series analysis further uncovered subclusters of patients with distinctive edgewise changes relative to controls, illustrating individual postoperative connectivity profiles. The large-scale differences in networks of the preserved hemisphere potentially reflect plasticity in the service of maintained and/or retained cognitive function.
Subject(s)
Magnetic Resonance Imaging , Neuroimaging , Humans , Child , Magnetic Resonance Imaging/methods , Female , Male , Adolescent , Neuroimaging/methods , Epilepsy/surgery , Epilepsy/physiopathology , Epilepsy/diagnostic imaging , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/physiopathology , Cerebral Cortex/surgery , Neuronal Plasticity/physiology , Drug Resistant Epilepsy/surgery , Drug Resistant Epilepsy/diagnostic imaging , Drug Resistant Epilepsy/physiopathology , Brain Mapping/methods , Functional Laterality/physiologyABSTRACT
Epilepsy's myriad causes and clinical presentations ensure that accurate diagnoses and targeted treatments remain a challenge. Advanced neurotechnologies are needed to better characterize individual patients across multiple modalities and analytical techniques. At the XVIth Workshop on Neurobiology of Epilepsy: Early Onset Epilepsies: Neurobiology and Novel Therapeutic Strategies (WONOEP 2022), the session on "advanced tools" highlighted a range of approaches, from molecular phenotyping of genetic epilepsy models and resected tissue samples to imaging-guided localization of epileptogenic tissue for surgical resection of focal malformations. These tools integrate cutting edge research, clinical data acquisition, and advanced computational methods to leverage the rich information contained within increasingly large datasets. A number of common challenges and opportunities emerged, including the need for multidisciplinary collaboration, multimodal integration, potential ethical challenges, and the multistage path to clinical translation. Despite these challenges, advanced epilepsy neurotechnologies offer the potential to improve our understanding of the underlying causes of epilepsy and our capacity to provide patient-specific treatment.
Subject(s)
Epilepsy , Humans , Epilepsy/diagnosis , Epilepsy/diagnostic imaging , Epilepsy/physiopathology , Epilepsy/genetics , Neuroimaging/methodsABSTRACT
BACKGROUND: Endovascular treatment (EVT) is the standard of care of ischaemic stroke due to occlusion of large vessels. Although EVT can significantly improve short- and long-term outcomes, functional dependence can persist despite the achievement of a successful recanalization. The evidence about the predictors of post-stroke epilepsy (PSE) in patients with stroke treated by EVT is limited. We aimed to evaluate the relationship between futile recanalization and the risk of PSE. METHODS: We retrospectively identified consecutive adults with first-ever ischaemic stroke of anterior circulation who were treated with EVT. Futile recanalization was defined as poor 3-month functional status (modified Rankin scale score ≥ 3) despite complete or near-complete recanalization. Study outcome was the occurrence of PSE during the follow-up. RESULTS: The study included 327 patients with anterior circulation ischaemic stroke treated with EVT. Futile recanalization occurred in 116 (35.5%) patients and 26 (8.0%) developed PSE during a median follow-up of 35 [interquartile range, 22.7-55.2] months. Futile recanalization was more common among patients who developed PSE compared to those who did not (76.9% versus 31.9%; p < 0.001). Futile recanalization [hazard ratio (HR) = 5.63, 95% confidence interval (CI): 1.88-16.84; p = 0.002], large artery atherosclerosis (HR = 3.48, 95% CI: 1.44-8.40; p = 0.006), cortical involvement (HR = 15.51, 95% CI: 2.06-116.98; p = 0.008), and acute symptomatic status epilepticus (HR = 14.40, 95% CI: 2.80-73.98; p = 0.001) increased the risk of PSE. CONCLUSIONS: Futile recanalization after EVT is associated with increased risk of PSE in patients with ischaemic stroke due to occlusion of large vessel of the anterior circulation.
Subject(s)
Endovascular Procedures , Epilepsy , Ischemic Stroke , Humans , Male , Female , Aged , Retrospective Studies , Middle Aged , Ischemic Stroke/complications , Ischemic Stroke/diagnostic imaging , Epilepsy/etiology , Epilepsy/diagnostic imaging , Endovascular Procedures/methods , Medical Futility , Follow-Up Studies , Stroke/complications , Stroke/diagnostic imaging , Aged, 80 and over , Risk FactorsABSTRACT
Accurate resection cavity segmentation on MRI is important for neuroimaging research involving epilepsy surgical outcomes. Manual segmentation, the gold standard, is highly labour intensive. Automated pipelines are an efficient potential solution; however, most have been developed for use following temporal epilepsy surgery. Our aim was to compare the accuracy of four automated segmentation pipelines following surgical resection in a mixed cohort of subjects following temporal or extra temporal epilepsy surgery. We identified 4 open-source automated segmentation pipelines. Epic-CHOP and ResectVol utilise SPM-12 within MATLAB, while Resseg and Deep Resection utilise 3D U-net convolutional neural networks. We manually segmented the resection cavity of 50 consecutive subjects who underwent epilepsy surgery (30 temporal, 20 extratemporal). We calculated Dice similarity coefficient (DSC) for each algorithm compared to the manual segmentation. No algorithm identified all resection cavities. ResectVol (n = 44, 88 %) and Epic-CHOP (n = 42, 84 %) were able to detect more resection cavities than Resseg (n = 22, 44 %, P < 0.001) and Deep Resection (n = 23, 46 %, P < 0.001). The SPM-based pipelines (Epic-CHOP and ResectVol) performed better than the deep learning-based pipelines in the overall and extratemporal surgery cohorts. In the temporal cohort, the SPM-based pipelines had higher detection rates, however there was no difference in the accuracy between methods. These pipelines could be applied to machine learning studies of outcome prediction to improve efficiency in pre-processing data, however human quality control is still required.
Subject(s)
Magnetic Resonance Imaging , Humans , Magnetic Resonance Imaging/methods , Adult , Female , Male , Epilepsy/surgery , Epilepsy/diagnostic imaging , Young Adult , Image Processing, Computer-Assisted/methods , Middle Aged , Adolescent , Algorithms , Neurosurgical Procedures/methods , Neuroimaging/methodsABSTRACT
AIMS: We intend to elucidate the alterations of cerebral networks in patients with insular glioma-related epilepsy (GRE) based on resting-state functional magnetic resonance images. METHODS: We collected 62 insular glioma patients, who were subsequently categorized into glioma-related epilepsy (GRE) and glioma with no epilepsy (GnE) groups, and recruited 16 healthy individuals matched to the patient's age and gender to form the healthy control (HC) group. Graph theoretical analysis was applied to reveal differences in sensorimotor, default mode, visual, and executive networks among different subgroups. RESULTS: No significant alterations in functional connectivity were found in either hemisphere insular glioma. Using graph theoretical analysis, differences were found in visual, sensorimotor, and default mode networks (p < 0.05). When the glioma located in the left hemisphere, the degree centrality was reduced in the GE group compared to the GnE group. When the glioma located in the right insula, the degree centrality, nodal efficiency, nodal local efficiency, and nodal clustering coefficient of the GE group were lower than those of the GnE group. CONCLUSION: The impact of insular glioma itself and GRE on the brain network is widespread. The networks altered by insular GRE differ depending on the hemisphere location. GRE reduces the nodal properties of brain networks than that in insular glioma.
Subject(s)
Brain Neoplasms , Epilepsy , Glioma , Magnetic Resonance Imaging , Humans , Glioma/diagnostic imaging , Glioma/physiopathology , Glioma/complications , Male , Female , Adult , Brain Neoplasms/diagnostic imaging , Brain Neoplasms/complications , Brain Neoplasms/physiopathology , Middle Aged , Epilepsy/diagnostic imaging , Epilepsy/physiopathology , Nerve Net/diagnostic imaging , Nerve Net/physiopathology , Insular Cortex/diagnostic imaging , Young Adult , Cerebral Cortex/diagnostic imaging , Cerebral Cortex/physiopathologyABSTRACT
OBJECTIVE: To evaluate the diagnostic capabilities of modifying the standard MRI protocol as part of an interdisciplinary presurgical examination of patients with epileptogenic substrates of unknown etiology. MATERIAL AND METHODS: The results of dynamic MRI of 8 patients with a referral diagnosis of focal cortical dysplasia (FCD) were analyzed. In 7 patients, epilepsy was the reason for a standard MRI of the brain; in another patient with myasthenia, MRI was performed as part of a comprehensive examination. All patients, in addition to standard MRI, underwent a modification of the real-time scanning protocol to include contrast, tractography (DTI), and perfusion techniques (ASL/DSC). In 1 case, with questionable results, the results of a modification of the standard MRI protocol, high-resolution MRI (HR MRI) and hybrid positron emission CT with 11C-methionine (PET/CT with 11C-MET) were combined. RESULTS: Seven patients underwent epileptic surgery and 1 patient was operated on for a tumor. In 4 out of 8 patients, based on the results of a modification of the standard MRI protocol, radiological signs of a neoplastic process were identified, which suggested a low-grade tumor. One of them needed PET/CT to confirm the assumption. The results of pathomorphological examination correlated with the direct diagnosis for surgical treatment. One of the 4 patients was suspected to have dysembryoplastic neuroepithelial tumor (DNET) based on the results of the protocol modification, which was also confirmed by pathological examination. In another 4 patients in whom it was possible to narrow the differential between FCD type II and DNET based on the results of the modification, FCD IIb was pathomorphologically verified. CONCLUSION: The proposed modification of the standard MRI protocol can significantly facilitate the differential diagnosis between the neoplastic and dysplastic origin of an epileptogenic substrate of unknown etiology, which in turn affects the patient's management tactics.
Subject(s)
Epilepsy , Magnetic Resonance Imaging , Humans , Magnetic Resonance Imaging/methods , Female , Male , Diagnosis, Differential , Adult , Epilepsy/diagnostic imaging , Epilepsy/diagnosis , Epilepsy/etiology , Malformations of Cortical Development/diagnostic imaging , Adolescent , Young Adult , Brain/diagnostic imaging , Brain/pathology , Middle Aged , Positron Emission Tomography Computed Tomography , Brain Neoplasms/diagnostic imaging , ChildABSTRACT
The blood-brain barrier (BBB) is a barrier protecting the brain and a milieu of continuous exchanges between blood and brain. There is emerging evidence that the BBB plays a major role in epileptogenesis and drug-resistant epilepsy, through several mechanisms, such as water homeostasis dysregulation, overexpression of drug transporters, and inflammation. Studies have shown abnormal water homeostasis in epileptic tissue and altered aquaporin-4 water channel expression in animal epilepsy models. This review focuses on abnormal water exchange in epilepsy and describes recent non-invasive MRI methods of quantifying water exchange. PLAIN LANGUAGE SUMMARY: Abnormal exchange between blood and brain contribute to seizures and epilepsy. The authors describe why correct water balance is necessary for healthy brain functioning and how it is impacted in epilepsy. This review also presents recent MRI methods to measure water exchange in human brain. These measures would improve our understanding of factors leading to seizures.
Subject(s)
Blood-Brain Barrier , Epilepsy , Neuroimaging , Blood-Brain Barrier/metabolism , Humans , Epilepsy/metabolism , Epilepsy/diagnostic imaging , Epilepsy/physiopathology , Animals , Water/metabolism , Magnetic Resonance Imaging , Brain/metabolism , Brain/diagnostic imaging , Brain/physiopathologyABSTRACT
The International League Against Epilepsy (ILAE) is an organization of 120 national chapters providing the most widely accepted and updated guidelines on epilepsy. In 2022, the ILAE Task Force revised the prior (2011) classification of focal cortical dysplasias to incorporate and update clinicopathologic and genetic information, with the aim to provide an objective classification scheme. New molecular-genetic information has led to the concept of "integrated diagnosis" on the same lines as brain tumors, with a multilayered diagnostic model providing a phenotype-genotype integration. Major changes in the new update were made to type II focal cortical dysplasias, apart from identification of new entities, such as mild malformations of cortical development and cortical malformation with oligodendroglial hyperplasia. No major changes were made to type I and III focal cortical dysplasias, given the lack of significant new genetic information. This review provides the latest update on changes to the classification of focal cortical dysplasias with discussion about the new entities. The ILAE in 2017 updated the classification of seizure and epilepsy with 3 levels of diagnosis, including seizure type, epilepsy type, and epilepsy syndrome, which are also briefly discussed here.
Subject(s)
Epilepsy , Malformations of Cortical Development , Phenotype , Humans , Malformations of Cortical Development/diagnostic imaging , Malformations of Cortical Development/genetics , Malformations of Cortical Development/classification , Epilepsy/diagnostic imaging , Epilepsy/genetics , Epilepsy/classification , Neuroimaging/methods , Focal Cortical DysplasiaABSTRACT
OBJECTIVES: This study aimed to identify clinical characteristics that could predict the response to perampanel (PER) and determine whether structural connectivity is a predictive factor. METHODS: We enrolled patients with epilepsy who received PER and were followed-up for a minimum of 12 months. Good PER responders, who were seizure-free or presented with more than 50 % seizure reduction, were classified separately from poor PER responders who had seizure reduction of less than 50 % or non-responders. A graph theoretical analysis was conducted based on diffusion tensor imaging to calculate network measures of structural connectivity among patients with epilepsy. RESULTS: 106 patients with epilepsy were enrolled, including 26 good PER responders and 80 poor PER responders. Good PER responders used fewer anti-seizure medications before PER administration compared to those by poor PER responders (3 vs. 4; p = 0.042). Early PER treatment was more common in good PER responders than poor PER responders (46.2 vs. 21.3 %, p = 0.014). Regarding cortical structural connectivity, the global efficiency was higher and characteristic path length was lower in good PER responders than in poor PER responders (0.647 vs. 0.635, p = 0.006; 1.726 vs. 1,759, p = 0.008, respectively). For subcortical structural connectivity, the mean clustering coefficient and small-worldness index were higher in good PER responders than in poor PER responders (0.821 vs. 0.791, p = 0.009; 0.597 vs. 0.560, p = 0.009, respectively). CONCLUSION: This study demonstrated that early PER administration can predict a good PER response in patients with epilepsy, and structural connectivity could potentially offer clinical utility in predicting PER response.
Subject(s)
Anticonvulsants , Diffusion Tensor Imaging , Epilepsy , Nitriles , Pyridones , Humans , Pyridones/therapeutic use , Pyridones/administration & dosage , Female , Male , Anticonvulsants/therapeutic use , Anticonvulsants/administration & dosage , Adult , Epilepsy/drug therapy , Epilepsy/diagnostic imaging , Young Adult , Treatment Outcome , Adolescent , Middle Aged , Brain/diagnostic imaging , Brain/drug effects , Brain/pathologyABSTRACT
OBJECTIVE: Temporally extended signal space separation (tSSS) is a powerful method for artifact suppression in magnetoencephalography (MEG). Because tSSS first separates MEG signals coming from inside and outside a certain sphere, definition of the sphere origin is important. For this study, we explored the influence of origin choice on tSSS performance in spontaneous and evoked activity from epilepsy patients. METHODS: Interictal epileptiform discharges (IEDs) and somatosensory evoked fields (SEFs) were processed with two tSSSs: one with the default origin of (0, 0, 40 mm) in the head coordinate, and the other with an individual origin estimated using each patient's anatomical magnetic resonance imaging (MRI). Equivalent current dipoles (ECDs) were calculated for the data. The ECD location and quality of estimation were compared across conditions. RESULTS: MEG data from 21 patients revealed marginal differences in ECD location, but the estimation quality inferred from goodness of fit (GOF) and confidence volume (CV) was better for the tSSS with individual origins. This choice affected IEDs more than it affected SEFs. CONCLUSIONS: Individual sphere model resulted in better GOF and CV. SIGNIFICANCE: Application of tSSS using an individual origin would be more desirable when available. This parameter might influence spontaneous activity more strongly.
Subject(s)
Epilepsy , Evoked Potentials, Somatosensory , Magnetoencephalography , Humans , Magnetoencephalography/methods , Male , Female , Adult , Epilepsy/physiopathology , Epilepsy/diagnostic imaging , Evoked Potentials, Somatosensory/physiology , Young Adult , Middle Aged , Artifacts , Magnetic Resonance Imaging/methods , Adolescent , Brain/physiopathology , Brain/diagnostic imagingABSTRACT
Accurately studying structural connectivity requires precise tract segmentation strategies. The U-Net network has been widely recognized for its exceptional capacity in image segmentation tasks and provides remarkable results in large tract segmentation when high-quality diffusion-weighted imaging (DWI) data are used. However, short tracts, which are associated with various neurological diseases, pose specific challenges, particularly when high-quality DWI data acquisition within clinical settings is concerned. Here, we aimed to evaluate the U-Net network ability to segment short tracts by using DWI data acquired in different experimental conditions. To this end, we conducted three types of training experiments involving 350 healthy subjects and 11 white matter tracts, including the anterior, posterior, and hippocampal commissure, fornix, and uncinated fasciculus. In the first experiment, the model was exclusively trained with high-quality data of the Human Connectome Project (HCP) dataset. The second experiment focused on images of healthy subjects acquired from a local hospital dataset, representing a typical clinical routine acquisition. In the third experiment, a hybrid training approach was employed, combining data of the HCP and local hospital datasets. Then, the best model was also tested in unseen DWIs of 10 epilepsy patients of the local hospital and 10 healthy subjects acquired on a scanner from another company. The outcomes of the third experiment demonstrated a notable enhancement in performance when contrasted with the preceding trials. Specifically, the short tracts within the local hospital dataset achieved Dice scores ranging between 0.60 and 0.65. Similar intervals were obtained with HCP data in the first experiment, and a substantial improvement compared to the scores between 0.37 and 0.50 obtained with the local hospital dataset at the same experiment. This improvement persisted when the method was applied to diverse scenarios, including different scanner acquisitions and epilepsy patients. These results indicate that combining datasets from different sources, coupled with resolution standardization strengthens the neural network ability to generalize predictions across a spectrum of datasets. Nevertheless, short tract segmentation performance is intricately linked to the training composition, to validation, and to testing data. Moreover, curved tracts have intricate structural nature, which adds complexities to their segmenting. Although the network training approach tested herein has provided promising results, caution must be taken when extrapolating its application to datasets acquired under distinct experimental conditions, even in the case of higher-quality data or analysis of long or short tracts.
Subject(s)
Connectome , Epilepsy , Image Processing, Computer-Assisted , White Matter , Humans , Male , Female , Image Processing, Computer-Assisted/methods , Adult , Epilepsy/diagnostic imaging , White Matter/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Diffusion Tensor Imaging/methods , Magnetic Resonance Imaging/methods , AlgorithmsABSTRACT
BACKGROUND AND OBJECTIVES: Tailoring epilepsy surgery using intraoperative electrocorticography (ioECoG) has been debated, and modest number of epilepsy surgery centers apply this diagnostic method. We assessed the current evidence to use ioECoG-tailored epilepsy surgery for improving postsurgical outcome. METHODS: PubMed and Embase were searched for original studies reporting on ≥10 cases who underwent ioECoG-tailored surgery for epilepsy, with a follow-up of at least 6 months. We used a random-effects model to calculate the overall rate of patients achieving favorable seizure outcome (FSO), defined as Engel class I, ILAE class 1, or seizure-free status. Meta-regression was used to investigate potential sources of heterogeneity. We calculated the odds ratio (OR) for estimating variables on FSO:ioECoG vs non-ioECoG-tailored surgery (if included studies contained patients with non-ioECoG-tailored surgery), ioECoG-tailored epilepsy surgery in children vs adults, temporal (TL) vs extratemporal lobe (eTL), MRI-positive vs MRI-negative, and complete vs incomplete resection of tissue that generated interictal epileptiform discharges (IEDs). A Bayesian network meta-analysis was conducted for underlying pathologies. We assessed the evidence certainty using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). RESULTS: Eighty-three studies (82 observational studies, 1 trial) comprising 3,631 patients with ioECoG-tailored surgery were included. The overall pooled rate of patients who attained FSO after ioECoG-tailored surgery was 74% (95% CI 71-77) with significant heterogeneity, which was predominantly attributed to pathologies and seizure outcome classifications. Twenty-two studies contained non-ioECoG-tailored surgeries. IoECoG-tailored surgeries reached a higher rate of FSO than non-ioECoG-tailored surgeries (OR 2.10 [95% CI 1.37-3.24]; p < 0.01; very low certainty). Complete resection of tissue that displayed IEDs in ioECoG predicted FSO better compared with incomplete resection (OR 3.04 [1.76-5.25]; p < 0.01; low certainty). We found insignificant difference in FSO after ioECoG-tailored surgery in children vs adults, TL vs eTL, or MRI-positive vs MRI-negative. The network meta-analysis showed that the odds of FSO was lower for malformations of cortical development than for tumors (OR 0.47 95% credible interval 0.25-0.87). DISCUSSION: Although limited by low-quality evidence, our meta-analysis shows a relatively good surgical outcome (74% FSO) after epilepsy surgery with ioECoG, especially in tumors, with better outcome for ioECoG-tailored surgeries in studies describing both and better outcome after complete removal of IED areas.
Subject(s)
Electrocorticography , Epilepsy , Intraoperative Neurophysiological Monitoring , Seizures , Humans , Electrocorticography/methods , Epilepsy/surgery , Epilepsy/diagnostic imaging , Epilepsy/physiopathology , Intraoperative Neurophysiological Monitoring/methods , Seizures/surgery , Seizures/physiopathology , Treatment Outcome , Neurosurgical Procedures/methodsABSTRACT
INTRODUCTION: Seizures are a common complication of subarachnoid hemorrhage (SAH) in both acute and late stages: 10-20 % acute symptomatic seizures, 12-25 % epilepsy rate at five years. Our aim was to identify early electroencephalogram (EEG) and computed tomography (CT) findings that could predict long-term epilepsy after SAH. MATERIAL AND METHODS: This is a multicenter, retrospective, longitudinal study of adult patients with aneurysmal SAH admitted to two tertiary care hospitals between January 2011 to December 2022. Routine 30-minute EEG recording was performed in all subjects during admission period. Exclusion criteria were the presence of prior structural brain lesions and/or known epilepsy. We documented the presence of SAH-related cortical involvement in brain CT and focal electrographic abnormalities (epileptiform and non-epileptiform). Post-SAH epilepsy was defined as the occurrence of remote unprovoked seizures ≥ 7 days from the bleeding. RESULTS: We included 278 patients with a median follow-up of 2.4 years. The mean age was 57 (+/-12) years, 188 (68 %) were female and 49 (17.6 %) developed epilepsy with a median latency of 174 days (IQR 49-479). Cortical brain lesions were present in 189 (68 %) and focal EEG abnormalities were detected in 158 patients (39 epileptiform discharges, 119 non-epileptiform abnormalities). The median delay to the first EEG recording was 6 days (IQR 2-12). Multiple Cox regression analysis showed higher risk of long-term epilepsy in those patients with CT cortical involvement (HR 2.6 [1.3-5.2], p 0.009), EEG focal non-epileptiform abnormalities (HR 3.7 [1.6-8.2], p 0.002) and epileptiform discharges (HR 6.7 [2.8-15.8], p < 0.001). Concomitant use of anesthetics and/or antiseizure medication during EEG recording had no influence over its predictive capacity. ROC-curve analysis of the model showed good predictive capability at 5 years (AUC 0.80, 95 %CI 0.74-0.87). CONCLUSIONS: Focal electrographic abnormalities (both epileptiform and non-epileptiform abnormalities) and cortical involvement in neuroimaging predict the development of long-term epilepsy. In-patient EEG and CT findings could allow an early risk stratification and facilitate a personalized follow-up and management of SAH patients.
Subject(s)
Electroencephalography , Epilepsy , Subarachnoid Hemorrhage , Humans , Subarachnoid Hemorrhage/complications , Subarachnoid Hemorrhage/physiopathology , Female , Male , Middle Aged , Longitudinal Studies , Retrospective Studies , Aged , Epilepsy/etiology , Epilepsy/diagnosis , Epilepsy/diagnostic imaging , Epilepsy/physiopathology , Adult , Tomography, X-Ray Computed , Neuroimaging , Brain/diagnostic imaging , Brain/physiopathologyABSTRACT
SATB1 (MIM #602075) is a relatively new gene reported only in recent years in association with neurodevelopmental disorders characterized by variable facial dysmorphisms, global developmental delay, poor or absent speech, altered electroencephalogram (EEG), and brain abnormalities on imaging. To date about thirty variants in forty-four patients/children have been described, with a heterogeneous spectrum of clinical manifestations. In the present study, we describe a new patient affected by mild intellectual disability, speech disorder, and non-specific abnormalities on EEG and neuroimaging. Family studies identified a new de novo frameshift variant c.1818delG (p.(Gln606Hisfs*101)) in SATB1. To better define genotype-phenotype associations in the different types of reported SATB1 variants, we reviewed clinical data from our patient and from the literature and compared manifestations (epileptic activity, EEG abnormalities and abnormal brain imaging) due to missense variants versus those attributable to loss-of-function/premature termination variants. Our analyses showed that the latter variants are associated with less severe, non-specific clinical features when compared with the more severe phenotypes due to missense variants. These findings provide new insights into SATB1-related disorders.
Subject(s)
Brain , Electroencephalography , Epilepsy , Matrix Attachment Region Binding Proteins , Humans , Matrix Attachment Region Binding Proteins/genetics , Epilepsy/genetics , Epilepsy/diagnostic imaging , Epilepsy/physiopathology , Brain/diagnostic imaging , Brain/pathology , Brain/physiopathology , Male , Female , Loss of Function Mutation , Intellectual Disability/genetics , Intellectual Disability/diagnostic imaging , Intellectual Disability/pathology , Neuroimaging/methods , Child , Frameshift Mutation/genetics , Phenotype , Child, PreschoolABSTRACT
Las variantes normales de aspecto epileptiforme, o variantes epileptiformes benignas, son un reto diagnóstico en la interpretación de los electroencefalogramas que requiere su conocimiento y una amplia experiencia por parte de los responsables del informe electroencefalográfico. Incluyen un grupo heterogéneo de hallazgos, algunos muy infrecuentes, que inicialmente se relacionaron con epilepsia y patologías neurológicas diversas. En la actualidad, la mayoría se consideran variantes sin significado patológico, y su sobreinterpretación habitualmente acarrea diagnósticos erróneos y tratamientos innecesarios. Los datos de prevalencia de estas variantes son muy diversos y proceden habitualmente de poblaciones seleccionadas, por lo que son difícilmente extrapolables a población sana. No obstante, estudios con electrodos invasivos y series más recientes vuelven a asociar algunas de estas variantes con epilepsia. Nuestro objetivo es revisar las características y la prevalencia de las principales variantes epileptiformes benignas y actualizar su significado clínico. (AU)
Subject(s)
Humans , Electrocardiography , Diagnosis, Differential , Diagnostic Errors , Epilepsy/diagnostic imaging , Epilepsy/diagnosisABSTRACT
BACKGROUND: In epilepsy, the ictal phase leads to cerebral hyperperfusion while hypoperfusion is present in the interictal phases. Patients with Alzheimer's disease (AD) have an increased prevalence of epileptiform discharges and a study using intracranial electrodes have shown that these are very frequent in the hippocampus. However, it is not known whether there is an association between hippocampal hyperexcitability and regional cerebral blood flow (rCBF). The objective of the study was to investigate the association between rCBF in hippocampus and epileptiform discharges as measured with ear-EEG in patients with Alzheimer's disease. Our hypothesis was that increased spike frequency may be associated with increased rCBF in hippocampus. METHODS: A total of 24 patients with AD, and 15 HC were included in the analysis. Using linear regression, we investigated the association between rCBF as measured with arterial spin-labelling MRI (ASL-MRI) in the hippocampus and the number of spikes/sharp waves per 24 h as assessed by ear-EEG. RESULTS: No significant difference in hippocampal rCBF was found between AD and HC (p-value = 0.367). A significant linear association between spike frequency and normalized rCBF in the hippocampus was found for patients with AD (estimate: 0.109, t-value = 4.03, p-value < 0.001). Changes in areas that typically show group differences (temporal-parietal cortex) were found in patients with AD, compared to HC. CONCLUSIONS: Increased spike frequency was accompanied by a hemodynamic response of increased blood flow in the hippocampus in patients with AD. This phenomenon has also been shown in patients with epilepsy and supports the hypothesis of hyperexcitability in patients with AD. The lack of a significant difference in hippocampal rCBF may be due to an increased frequency of epileptiform discharges in patients with AD. TRIAL REGISTRATION: The study is registered at clinicaltrials.gov (NCT04436341).
Subject(s)
Alzheimer Disease , Epilepsy , Humans , Alzheimer Disease/complications , Alzheimer Disease/diagnostic imaging , Hippocampus/diagnostic imaging , Temporal Lobe , Cerebrovascular Circulation , Epilepsy/diagnostic imagingABSTRACT
BACKGROUND AND OBJECTIVES: Although commonly used in the evaluation of patients for epilepsy surgery, the association between the detection of localizing 18fluorine fluorodeoxyglucose PET (18F-FDG-PET) hypometabolism and epilepsy surgery outcome is uncertain. We conducted a systematic review and meta-analysis to determine whether localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery. METHODS: A systematic literature search was undertaken. Eligible publications included evaluation with 18F-FDG-PET before epilepsy surgery, with ≥10 participants, and those that reported surgical outcome at ≥12 months. Random-effects meta-analysis was used to calculate the odds of achieving a favorable outcome, defined as Engel class I, International League Against Epilepsy class 1-2, or seizure-free, with localizing 18F-FDG-PET hypometabolism, defined as concordant with the epilepsy surgery resection zone. Meta-regression was used to characterize sources of heterogeneity. RESULTS: The database search identified 8,916 studies, of which 98 were included (total patients n = 4,104). Localizing 18F-FDG-PET hypometabolism was associated with favorable outcome after epilepsy surgery for all patients with odds ratio (OR) 2.68 (95% CI 2.08-3.45). Subgroup analysis yielded similar findings for those with (OR 2.64, 95% CI 1.54-4.52) and without epileptogenic lesion detected on MRI (OR 2.49, 95% CI 1.80-3.44). Concordance with EEG (OR 2.34, 95% CI 1.43-3.83), MRI (OR 1.69, 95% CI 1.19-2.40), and triple concordance with both (OR 2.20, 95% CI 1.32-3.64) was associated with higher odds of favorable outcome. By contrast, diffuse 18F-FDG-PET hypometabolism was associated with worse outcomes compared with focal hypometabolism (OR 0.34, 95% CI 0.22-0.54). DISCUSSION: Localizing 18F-FDG-PET hypometabolism is associated with favorable outcome after epilepsy surgery, irrespective of the presence of an epileptogenic lesion on MRI. The extent of 18F-FDG-PET hypometabolism provides additional information, with diffuse hypometabolism associated with worse surgical outcome than focal 18F-FDG-PET hypometabolism. These findings support the incorporation of 18F-FDG-PET into routine noninvasive investigations for patients being evaluated for epilepsy surgery to improve epileptogenic zone localization and to aid patient selection for surgery.
Subject(s)
Epilepsy , Fluorodeoxyglucose F18 , Positron-Emission Tomography , Humans , Epilepsy/surgery , Epilepsy/diagnostic imaging , Epilepsy/metabolism , Treatment Outcome , Radiopharmaceuticals , Brain/diagnostic imaging , Brain/metabolism , Brain/surgeryABSTRACT
Fluorescence sensing is crucial to studying biological processes and diagnosing diseases, especially in the second near-infrared (NIR-II) window with reduced background signals. However, it's still a great challenge to construct "off-on" sensors when the sensing wavelength extends into the NIR-II region to obtain higher imaging contrast, mainly due to the difficult synthesis of spectral overlapped quencher. Here, we present a new fluorescence quenching strategy, which utilizes steric hindrance quencher (SHQ) to tune the molecular packing state of fluorophores and suppress the emission signal. Density functional theory (DFT) calculations further reveal that large SHQs can competitively pack with fluorophores and prevent their self-aggregation. Based on this quenching mechanism, a novel activatable "off-on" sensing method is achieved via bio-analyte responsive invalidation of SHQ, namely the Steric Hindrance Invalidation geNerated Emission (SHINE) strategy. As a proof of concept, the ClO--sensitive SHQ lead to the bright NIR-II signal release in epileptic mouse hippocampus under the skull and high photon scattering brain tissue, providing the real-time visualization of ClO- generation process in living epileptic mice.
Subject(s)
Density Functional Theory , Epilepsy , Fluorescent Dyes , Optical Imaging , Animals , Fluorescent Dyes/chemistry , Epilepsy/diagnostic imaging , Mice , Infrared Rays , Hippocampus/diagnostic imaging , Molecular StructureABSTRACT
OBJECTIVE: Accurate detection of focal cortical dysplasia (FCD) through magnetic resonance imaging (MRI) plays a pivotal role in the preoperative assessment of epilepsy. The integration of multimodal imaging has demonstrated substantial value in both diagnosing FCD and devising effective surgical strategies. This study aimed to enhance MRI post-processing by incorporating positron emission tomography (PET) analysis. We sought to compare the diagnostic efficacy of diverse image post-processing methodologies in patients presenting MRI-negative FCD. METHODS: In this retrospective investigation, we assembled a cohort of patients with negative preoperative MRI results. T1-weighted volumetric sequences were subjected to morphometric analysis program (MAP) and composite parametric map (CPM) post-processing techniques. We independently co-registered images derived from various methods with PET scans. The alignment was subsequently evaluated, and its correlation was correlated with postoperative seizure outcomes. RESULTS: A total of 41 patients were enrolled in the study. In the PET-MAP(p = 0.0189) and PET-CPM(p = 0.00041) groups, compared with the non-overlap group, the overlap group significantly associated with better postoperative outcomes. In PET(p = 0.234), CPM(p = 0.686) and MAP(p = 0.672), there is no statistical significance between overlap and seizure-free outcomes. The sensitivity of using the CPM alone outperformed the MAP (0.65 vs 0.46). The use of PET-CPM demonstrated superior sensitivity (0.96), positive predictive value (0.83), and negative predictive value (0.91), whereas the MAP displayed superior specificity (0.71). CONCLUSIONS: Our findings suggested a superiority in sensitivity of CPM in detecting potential FCD lesions compared to MAP, especially when it is used in combination with PET for diagnosis of MRI-negative epilepsy patients. Moreover, we confirmed the superiority of synergizing metabolic imaging (PET) with quantitative maps derived from structural imaging (MAP or CPM) to enhance the identification of subtle epileptogenic zones (EZs). This study serves to illuminate the potential of integrated multimodal techniques in advancing our capability to pinpoint elusive pathological features in epilepsy cases.