Clinical analysis of abnormal muscle response monitoring for hemifacial spasm during microvascular decompression: a retrospective study.

BACKGROUND: Microvascular decompression (MVD) is a widely recognized therapeutic approach for the treatment of hemifacial spasm (HFS). Abnormal muscle response (AMR) is a distinctive electromyographic finding exclusively in patients with HFS. The purpose of our investigation was to determine the correlation between changes in intraoperative AMR and surgical efficacy, as well as the incidence of postoperative complications in patients with HFS after undergoing MVD. METHODS: In this retrospective study, we evaluated 145 patients with HFSs treated with MVD, which was maintained for 1 year postoperatively. The subjects were divided into two groups based on the persistence or disappearance of AMR. Continuous monitoring of AMR during surgery provided data on persistence. All patients were followed up 1 day, 30 days, and 1 year after MVD. A range of potential predictive factors, such as patient demographics, symptom duration, and morphology and latency of AMR, were analyzed using binary logistic regression to assess their relationship with postoperative non-cure and delayed cure rates. RESULTS: The 1 day postoperative cure rate was 77.9%, with a 1 year postoperative cure rate of 94.59% and 1 day postoperative relief rate of 87.6%. A marked distinction was noted between preoperative and 1 year postoperative Cohen grades (P < 0.05). Moreover, 1 day after surgery, the outcome demonstrated significant variability, as shown by the binary logistic regression model (χ2 = 62.913, P < 0.05). The results suggested that factors such as age, symptom duration, disappearance of AMR, and preoperative carbamazepine treatment markedly influence outcomes 1 day after surgery. The binary logistic regression model for delayed cure at 1 year showed significant variability (χ2 = 54.883, P < 0.05). Furthermore, analysis using generalized estimating equations revealed that the duration of postoperative follow-up significantly impacted Cohen grades, as did the disappearance of AMR, with the grade of AMR disappearance being only 10% of that of non-AMR disappearance (P < 0.05). CONCLUSION: Our findings suggest that MVD is an effective intervention for HFS. Our findings also indicate that factors such as patient age, duration of symptoms, disappearance of AMR, and preoperative carbamazepine therapy are significant predictors of 1 day postoperative cure rate. Major predictors for delayed cure at 1 year include age, symptom duration, AMR disappearance, preoperative carbamazepine and botulinum neurotoxin administration, single morphology AMR, and offending vertebral artery.

Delineating structural and metabolic abnormalities in amygdala and hippocampal subfields for different seizure-onset patterns via stereotactic electroencephalography.

AIMS: We aimed to investigate mesial temporal lobe abnormalities in mesial temporal lobe epilepsy (MTLE) patients with hypersynchronous (HYP) and low-voltage fast rhythms (LVF) onset identified by stereotactic electroencephalography (SEEG) and evaluate their diagnostic and prognostic value. METHODS: Fifty-one MTLE patients were categorized as HYP or LVF by SEEG. High-resolution MRI volume-based analysis and 18F-FDG-PET standard uptake values of hippocampal and amygdala subfields were quantified and compared with 57 matched controls. Further analyses were conducted to delineate the distinct pathological characteristics differentiating the two groups. Diagnostic and prognostic prediction performance of these biomarkers were assessed using receiver operating characteristic curves. RESULTS: LVF-onset individuals demonstrated ipsilateral amygdala enlargement (p = 0.048) and contralateral hippocampus hypermetabolism (p = 0.042), pathological results often accompany abnormalities in the temporal lobe cortex, while HYP-onset subjects had significant atrophy (p < 0.001) and hypometabolism (p = 0.013) in ipsilateral hippocampus and its subfields, as well as amygdala atrophy (p < 0.001), pathological results are highly correlated with hippocampal sclerosis. Severe fimbria atrophy was observed in cases of HYP-onset MTLE with poor prognosis (AUC = 0.874). CONCLUSION: Individuals with different seizure-onset patterns display specific morphological and metabolic abnormalities in the amygdala and hippocampus. Identifying these subfield abnormalities can improve diagnostic and prognostic precision, guiding surgical strategies for MTLE.

TRanscranial AlterNating current stimulation FOR patients with mild Alzheimer's Disease (TRANSFORM-AD): a randomized controlled clinical trial.

BACKGROUND: The mechanistic effects of gamma transcranial alternating current stimulation (tACS) on hippocampal gamma oscillation activity in Alzheimer's Disease (AD) remains unclear. This study aimed to clarify beneficial effects of gamma tACS on cognitive functioning in AD and to elucidate effects on hippocampal gamma oscillation activity. METHODS: This is a double-blind, randomized controlled single-center trial. Participants with mild AD were randomized to tACS group or sham group, and underwent 30 one-hour sessions of either 40 Hz tACS or sham stimulation over consecutive 15 days. Cognitive functioning, structural magnetic resonance imaging (MRI), and simultaneous electroencephalography-functional MRI (EEG-fMRI) were evaluated at baseline, the end of the intervention and at 3-month follow-up from the randomization. RESULTS: A total of 46 patients were enrolled (23 in the tACS group, 23 in the sham group). There were no group differences in the change of the primary outcome, 11-item cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-Cog) score after intervention (group*time, p = 0.449). For secondary outcomes, compared to the control group, the intervention group showed significant improvement in MMSE (group*time, p = 0.041) and MoCA scores (non-parametric test, p = 0.025), which were not sustained at 3-month follow-up. We found an enhancement of theta-gamma coupling in the hippocampus, which was positively correlated with improvements of MMSE score and delayed recall. Additionally, fMRI revealed increase of the local neural activity in the hippocampus. CONCLUSION: Effects on the enhancement of theta-gamma coupling and neural activity within the hippocampus suggest mechanistic models for potential therapeutic mechanisms of tACS. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03920826; Registration Date: 2019-04-19.

Single-cell, single-nucleus and xenium-based spatial transcriptomics analyses reveal inflammatory activation and altered cell interactions in the hippocampus in mice with temporal lobe epilepsy.

BACKGROUND: Temporal lobe epilepsy (TLE) is among the most common types of epilepsy and often leads to cognitive, emotional, and psychiatric issues due to the frequent seizures. A notable pathological change related to TLE is hippocampal sclerosis (HS), which is characterized by neuronal loss, gliosis, and an increased neuron fibre density. The mechanisms underlying TLE-HS development remain unclear, but the reactive transcriptomic changes in glial cells and neurons of the hippocampus post-epileptogenesis may provide insights. METHODS: To induce TLE, 200 nl of kainic acid (KA) was stereotactically injected into the hippocampal CA1 region of mice, followed by a 7-day postinjection period. Single-cell RNA sequencing (ScRNA-seq), single-nucleus RNA sequencing (SnRNA-seq), and Xenium-based spatial transcriptomics analyses were employed to evaluate the changes in mRNA expression in glial cells and neurons. RESULTS: From the ScRNA-seq and SnRNA-seq data, 31,390 glial cells and 48,221 neuronal nuclei were identified. Analysis of the differentially expressed genes (DEGs) revealed significant transcriptomic alterations in the hippocampal cells of mice with TLE, affecting hundreds to thousands of mRNAs and their signalling pathways. Enrichment analysis indicated notable activation of stress and inflammatory pathways in the TLE hippocampus, while pathways related to axonal development and neural support were suppressed. Xenium analysis demonstrated the expression of all 247 genes across mouse brain sections, revealing the spatial distributions of their expression in 27 cell types. Integrated analysis of the DEGs identified via the three sequencing techniques revealed that Spp1, Trem2, and Cd68 were upregulated in all glial cell types and in the Xenium data; Penk, Sorcs3, and Plekha2 were upregulated in all neuronal cell types and in the Xenium data; and Tle4 and Sipa1l3 were downregulated in all glial cell types and in the Xenium data. CONCLUSION: In this study, a high-resolution single-cell transcriptomic atlas of the hippocampus in mice with TLE was established, revealing potential intrinsic mechanisms driving TLE-associated inflammatory activation and altered cell interactions. These findings provide valuable insights for further exploration of HS development and epileptogenesis.

Comparative Efficacy of Neuromodulatory Strategies for Drug-Resistant Epilepsy: A Systematic Review and Meta-Analysis.

OBJECTIVE: The study aims to evaluate the efficacy of neuromodulatory strategies for people who have drug-resistant epilepsy (DRE). METHODS: We searched electronic repositories, including PubMed, Web of Science, Embase, and the Cochrane Library, for randomized controlled trials, their ensuing open-label extension studies, and prospective studies focusing on surgical or neuromodulation interventions for people with DRE. We used seizure frequency reduction as the primary outcome. A single-arm meta-analysis synthesized data across all studies to assess treatment effectiveness at multiple time points. A network meta-analysis evaluated the efficacy of diverse therapies in randomized controlled trials. Grading of Recommendations, Assessment, Development, and Evaluations was applied to evaluate the overall quality of the evidence. RESULTS: Twenty-eight studies representing 2936 individuals underwent 10 treatments were included. Based on the cumulative ranking in the network meta-analysis, the top 3 neuromodulatory options were deep brain stimulation (DBS) with 27% probability, responsive neurostimulation (RNS) with 22.91%, and transcranial direct current stimulation with 24.31%. In the single-arm meta-analysis, in the short-to-medium term, seizure control is more effective with RNS than with invasive vagus nerve stimulation (inVNS), which in turn is slightly more effective than DBS, though the differences are minimal. However, in the long term, inVNS appears to be less effective than both DBS and RNS. Trigeminal nerve stimulation, transcranial magnetic stimulation, and transcranial alternating current stimulation did not demonstrate significant seizure frequency reduction. CONCLUSIONS: Regarding long-term efficacy, RNS and DBS outperformed inVNS. While transcranial direct current stimulation and transcutaneous auricular VNS showed promise for treating DRE, further studies are needed to confirm their long-term efficacy.

Unveiling the hidden connection: the blood-brain barrier's role in epilepsy.

Epilepsy is characterized by abnormal synchronous electrical activity of neurons in the brain. The blood-brain barrier, which is mainly composed of endothelial cells, pericytes, astrocytes and other cell types and is formed by connections between a variety of cells, is the key physiological structure connecting the blood and brain tissue and is critical for maintaining the microenvironment in the brain. Physiologically, the blood-brain barrier controls the microenvironment in the brain mainly by regulating the passage of various substances. Disruption of the blood-brain barrier and increased leakage of specific substances, which ultimately leading to weakened cell junctions and abnormal regulation of ion concentrations, have been observed during the development and progression of epilepsy in both clinical studies and animal models. In addition, disruption of the blood-brain barrier increases drug resistance through interference with drug trafficking mechanisms. The changes in the blood-brain barrier in epilepsy mainly affect molecular pathways associated with angiogenesis, inflammation, and oxidative stress. Further research on biomarkers is a promising direction for the development of new therapeutic strategies.

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

Objective: 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. Methods: 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. Results: 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). Conclusion: 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.

EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis.

Background: At the intersection of neural monitoring and decoding, event-related potential (ERP) based on electroencephalography (EEG) has opened a window into intrinsic brain function. The stability of ERP makes it frequently employed in the field of neuroscience. However, project-specific custom code, tracking of user-defined parameters, and the large diversity of commercial tools have limited clinical application. Methods: We introduce an open-source, user-friendly, and reproducible MATLAB toolbox named EPAT that includes a variety of algorithms for EEG data preprocessing. It provides EEGLAB-based template pipelines for advanced multi-processing of EEG, magnetoencephalography, and polysomnogram data. Participants evaluated EEGLAB and EPAT across 14 indicators, with satisfaction ratings analyzed using the Wilcoxon signed-rank test or paired t-test based on distribution normality. Results: EPAT eases EEG signal browsing and preprocessing, EEG power spectrum analysis, independent component analysis, time-frequency analysis, ERP waveform drawing, and topological analysis of scalp voltage. A user-friendly graphical user interface allows clinicians and researchers with no programming background to use EPAT. Conclusion: This article describes the architecture, functionalities, and workflow of the toolbox. The release of EPAT will help advance EEG methodology and its application to clinical translational studies.

A disease warranting attention from neurosurgeons: primary central nervous system post-transplant lymphoproliferative disorder.

Background: Primary central nervous system post-transplant lymphoproliferative disorder (PCNS-PTLD) is a rare condition, posing diagnostic and treatment challenges, with histological biopsy essential for diagnosis. Standardized treatment protocols are lacking. This disease requires urgent attention due to the increasing number of organ transplant surgeries and the use of immunosuppressive agents. Methods: From 2020 to 2023, our center diagnosed five patients with PCNS-PTLD. We reviewed their clinical records and conducted a comprehensive analysis of 22 literatures on PCNS-PTLD cases following renal transplantation or allogeneic hematopoietic stem cell transplantation (HSCT). Results: Four patients had previously received a kidney transplant, one had undergone allogeneic HSCT. The median time from the last transplant surgery to the diagnosis of PCNS-PTLD differs between kidney transplant (21.5 years) and allogeneic HSCT (9 months). Common symptoms included motor weakness (n = 4), headache (n = 2), confusion (n = 2), and nausea (n = 2), with ring-enhancing (n = 5), typically solitary (n = 3) and supratentorial (n = 3) lesions on imaging. Diagnosis involved robot-assisted stereotactic brain biopsy (n = 4) or craniotomy (n = 1), all showing Epstein-Barr virus and CD20 positivity. Most cases (n = 4) were monomorphic diffuse large B-cell lymphoma. Treatment included rituximab (n = 3), surgical resection (n = 2), zanubrutinib (n = 1), whole-brain radiation (n = 1), and methotrexate (n = 1). At the last follow-up, the median duration of follow-up for all patients was 19 months. During this time, 3 patients had died and 2 patients were still alive. Conclusion: In patients with a history of kidney transplantation or allogeneic HSCT who are on long-term immunosuppressive therapy, any neurological symptoms, particularly the presence of supratentorial ring-enhancing masses in the brain on imaging, whether solitary or multiple, should raise high suspicion for this disease, warranting a timely brain biopsy. Additionally, we found that besides reducing immunosuppressants, zanubrutinib may be a potential, safe, and effective treatment for this condition. Moreover, post-surgical administration of rituximab in conjunction with whole-brain radiotherapy also appears to be a potentially safe and effective approach.

Aberrant individual structure covariance network in patients with mesial temporal lobe epilepsy.

Objective: Mesial temporal lobe epilepsy (mTLE) is a complex neurological disorder that has been recognized as a widespread global network disorder. The group-level structural covariance network (SCN) could reveal the structural connectivity disruption of the mTLE but could not reflect the heterogeneity at the individual level. Methods: This study adopted a recently proposed individual structural covariance network (IDSCN) method to clarify the alternated structural covariance connection mode in mTLE and to associate IDSCN features with the clinical manifestations and regional brain atrophy. Results: We found significant IDSCN abnormalities in the ipsilesional hippocampus, ipsilesional precentral gyrus, bilateral caudate, and putamen in mTLE patients than in healthy controls. Moreover, the IDSCNs of these areas were positively correlated with the gray matter atrophy rate. Finally, we identified several connectivities with weak associations with disease duration, frequency, and surgery outcome. Significance: Our research highlights the role of hippo-thalamic-basal-cortical circuits in the pathophysiologic process of disrupted whole-brain morphological covariance networks in mTLE, and builds a bridge between brain-wide covariance network changes and regional brain atrophy.

Wearable sensor devices can automatically identify the ON-OFF status of patients with Parkinson's disease through an interpretable machine learning model.

Introduction: Accurately and objectively quantifying the clinical features of Parkinson's disease (PD) is crucial for assisting in diagnosis and guiding the formulation of treatment plans. Therefore, based on the data on multi-site motor features, this study aimed to develop an interpretable machine learning (ML) model for classifying the "OFF" and "ON" status of patients with PD, as well as to explore the motor features that are most associated with changes in clinical symptoms. Methods: We employed a support vector machine with a recursive feature elimination (SVM-RFE) algorithm to select promising motion features. Subsequently, 12 ML models were constructed based on these features, and we identified the model with the best classification performance. Then, we used the SHapley Additive exPlanations (SHAP) and the Local Interpretable Model agnostic Explanations (LIME) methods to explain the model and rank the importance of those motor features. Results: A total of 96 patients were finally included in this study. The naive Bayes (NB) model had the highest classification performance (AUC = 0.956; sensitivity = 0.8947, 95% CI 0.6686-0.9870; accuracy = 0.8421, 95% CI 0.6875-0.9398). Based on the NB model, we analyzed the importance of eight motor features toward the classification results using the SHAP algorithm. The Gait: range of motion (RoM) Shank left (L) (degrees) [Mean] might be the most important motor feature for all classification horizons. Conclusion: The symptoms of PD could be objectively quantified. By utilizing suitable motor features to construct ML models, it became possible to intelligently identify whether patients with PD were in the "ON" or "OFF" status. The variations in these motor features were significantly correlated with improvement rates in patients' quality of life. In the future, they might act as objective digital biomarkers to elucidate the changes in symptoms observed in patients with PD and might be used to assist in the diagnosis and treatment of patients with PD.

The Interplay Between Epilepsy and Parkinson's Disease: Gene Expression Profiling and Functional Analysis.

The results of many epidemiological studies suggest a bidirectional causality may exist between epilepsy and Parkinson's disease (PD). However, the underlying molecular landscape linking these two diseases remains largely unknown. This study aimed to explore this possible bidirectional causality by identifying differentially expressed genes (DEGs) in each disease as well as their intersection based on two respective disease-related datasets. We performed enrichment analyses and explored immune cell infiltration based on an intersection of the DEGs. Identifying a protein-protein interaction (PPI) network between epilepsy and PD, and this network was visualised using Cytoscape software to screen key modules and hub genes. Finally, exploring the diagnostic values of the identified hub genes. NetworkAnalyst 3.0 and Cytoscape software were also used to construct and visualise the transcription factor-micro-RNA regulatory and co-regulatory networks, the gene-microRNA interaction network, as well as gene-disease association. Based on the enrichment results, the intersection of the DEGs mainly revealed enrichment in immunity-, phosphorylation-, metabolism-, and inflammation-related pathways. The boxplots revealed similar trends in infiltration of many immune cells in epilepsy and Parkinson's disease, with greater infiltration in patients than in controls. A complex PPI network comprising 186 nodes and 512 edges were constructed. According to node connection degree, top 15 hub genes were considered the kernel targets of epilepsy and PD. The area under curve values of hub gene expression profiles confirmed their excellent diagnostic values. This study is the first to analyse the molecular landscape underlying the epidemiological link between epilepsy and Parkinson's disease. The two diseases are closely linked through immunity-, inflammation-, and metabolism-related pathways. This information was of great help in understanding the pathogenesis, diagnosis, and treatment of the diseases. The present results may provide guidance for further in-depth analysis about molecular mechanisms of epilepsy and PD and novel potential targets.

An EEG motor imagery dataset for brain computer interface in acute stroke patients.

The brain-computer interface (BCI) is a technology that involves direct communication with parts of the brain and has evolved rapidly in recent years; it has begun to be used in clinical practice, such as for patient rehabilitation. Patient electroencephalography (EEG) datasets are critical for algorithm optimization and clinical applications of BCIs but are rare at present. We collected data from 50 acute stroke patients with wireless portable saline EEG devices during the performance of two tasks: 1) imagining right-handed movements and 2) imagining left-handed movements. The dataset consists of four types of data: 1) the motor imagery instructions, 2) raw recording data, 3) pre-processed data after removing artefacts and other manipulations, and 4) patient characteristics. This is the first open dataset to address left- and right-handed motor imagery in acute stroke patients. We believe that the dataset will be very helpful for analysing brain activation and designing decoding methods that are more applicable for acute stroke patients, which will greatly facilitate research in the field of motor imagery-BCI.

IDH1 mutation predicts seizure occurrence and prognosis in lower-grade glioma adults.

Epileptic seizures are frequently the first symptom in glioma patients. However, the causal relationship between glioma and epilepsy is not yet fully understood, as it cannot be explained solely by tumor mass effect or peritumoral factors. In this study, we retrospectively enrolled 320 patients with grade 2-4 glioma who received treatment between January 2019 and July 2022, and explored the biomarkers of seizure occurrence and seizure outcome prediction using univariate and multivariate logistic regression analyses. Our results showed that IDH1 R132H mutation was an independent risk factor for seizure occurrence in lower-grade glioma (LGG) patients (OR = 4.915, 95%CI = 1.713 - 14.103, P = 0.003). Additionally, IDH1 R132H mutation predicted higher seizure-free ratios in LGG patients with intact ATRX expression (OR = 6.793, 95%CI = 1.217 - 37.923, P = 0.029) one year after diagnosis. Therefore, our findings suggest that IDH1 mutation can predict seizure occurrence and control in LGG patients, providing further insights into the relationship between glioma and epilepsy.

Structural and functional changes in the brain after chronic complete thoracic spinal cord injury.

This study aimed to investigate whether brain anatomical structures and functional network connectivity are altered after chronic complete thoracic spinal cord injury (cctSCI) and to determine how these changes impact clinical outcomes. Structural and resting-state functional MRI was performed for 19 cctSCI patients (18 for final statistics) and 19 healthy controls. Voxel-based morphometry (VBM) was used to assess gray matter volume (GMV) with differences between cctSCI patients and controls. VBM results were used as seeds for whole-brain functional connectivity (FC) analysis. The relationship between brain changes and clinical variables was investigated. Compared with those of the control group, the left triangular inferior frontal gyrus, middle frontal gyrus, orbital inferior frontal gyrus, precuneus and parietal superior gyrus volumes of SCI patients decreased, while the left superior frontal gyrus and supplementary motor area volumes increased. Additionally, when the regions with increased GMV were used as seeds, the FC of the parahippocampus and thalamus increased. Subsequent partial correlation analysis showed a positive correlation between FC and total sensorimotor score based on the ASIA criteria (p = 0.001, r = 0.746). Overall, the structural and functional changes in the brain after cctSCI occurred in some visual and cognitive areas and sensory or motor control areas. These findings aid in improving our understanding of the underlying brain injury mechanisms and the subsequent structural and functional reorganization to reveal potential therapeutic targets and track treatment outcomes.

Stereo-electroencephalography-guided three-dimensional radiofrequency thermocoagulation for mesial temporal lobe epilepsy with hippocampal sclerosis: A retrospective study with long-term follow-up.

OBJECTIVE: Stereo-electroencephalography-guided three-dimensional radiofrequency thermocoagulation (SEEG-3D RFTC) is a minimally invasive treatment for mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS). This study aimed to investigate the long-term prognosis after SEEG-3D RFTC treatment in patients with MTLE-HS. METHODS: This single-center retrospective study included 28 patients with MTLE-HS treated with SEEG-3D RFTC from January 2016 to May 2018. Postoperative curative effects were evaluated using the Engel classification, and the patients were followed up for 5 years. RESULTS: The proportions of patients categorized as Engel I between 1 and 5 years after surgery were 72.41% (12 months after surgery), 67.86% (18 months after surgery), 62.07% (24 months after surgery), 50.00% (36 months after surgery), 42.86% (48 months after surgery), and 42.86% (60 months after surgery), respectively. Regarding long-term efficacy, based on the Engel classification, SEEG-3D RFTC showed room for improvement. SIGNIFICANCE: This was the first study to evaluate the efficacy of SEEG-3D RFTC for MTLE-HS with long-term follow-up. SEEG-3D RFTC is a promising alternative for patients with MTLE-HS. PLAIN LANGUAGE SUMMARY: This study explored the potential of stereoelectroencephalography-guided three-dimensional radiofrequency thermocoagulation, a minimally invasive approach, for treating medial temporal lobe epilepsy with hippocampal sclerosis. Involving 28 patients, the research tracked the treatment's success over five years using the Engel classification. Initial results were promising, with 72.41% of patients achieving the most favorable outcome (Engel I) at one year. While there was a gradual decrease in this proportion over time, 42.86% of patients maintained this positive outcome at five years, highlighting the treatment's potential for long-term efficacy.

A bibliometric and knowledge-map analysis of the glymphatic system from 2012 to 2022.

Objective: To explore the development context, research hotspots and frontiers in the glymphatic system (GS) field from 2012 to 2022 by bibliometric analysis. Methods: The Web of Science Core Collection (WoSCC) database was searched for articles published between 2012 and 2022. Microsoft Excel was used to manage the data. VOSviewer, CiteSpace, GraphPad Prism, the Web of Science, and an online analysis platform for bibliometrics (http://bibliometric.com/) were used to analyze the countries, institutions, journals, and collaboration networks among authors and the types of articles, developmental directions, references, and top keywords of published articles. Results: A total of 412 articles were retrieved, including 39 countries/regions, 223 research institutes and 171 academic journals. The subject classifications related to the GS were Neuroscience, Clinical Neuroscience and Radiology/Nuclear Medicine/Medical Imaging. The United States has maintained its dominant and most influential position in GS research. Among research institutions and journals, the Univ Rochester and Journal of Cerebral Blood Flow and Metabolism had the highest number of academic articles, respectively. Nedergaard M had the most published article, and Iliff JJ had the most co-citations. The top two keywords with the highest frequency were "glymphatic system" and "cerebrospinal fluid." Conclusion: This research provides valuable information for the study of the GS. The bibliometric analysis of this area will encourage potential collaborations among researchers, defining its frontiers and directions for development.

Short-term surgical outcomes of spontaneous intracerebral hemorrhage in China from 2019 to 2021: a retrospective cohort study.

Background: China has the highest prevalence of spontaneous intracerebral hemorrhage (sICH) worldwide. To date, no national-level report has revealed sICH surgical performance. We aimed to investigate the current status and short-term outcomes of patients who underwent surgical treatment for sICH between 2019 and 2021. Methods: Data from 7451 patients undergoing sICH surgical treatment in China between 2019 and 2021, including demographic information, disease severity, surgical treatments for sICH, complications, and follow-up information, were retrieved from the Bigdata Observatory Platform for Stroke of China. Propensity score matching (PSM) was applied to balance the baseline characteristics. The surgical treatment performance on 3-month mortality and functional outcome were then explored by regression analysis. The influence of stroke center level and region on surgical performance was then explored. Findings: The numbers of sICH patients undergoing open craniotomy (OC), cranial puncture (CP), decompressive craniectomy (DC) and endoscopic evacuation (EE) were 2404 (32.3%), 3030 (40.7%), 1700 (22.8%) and 317 (4.3%), respectively. The 3-month mortality rate was 20.2%. Among the surviving patients, the 3-month poor functional prognosis (mRS 3-5) rate was 46.5%. After PSM, regression analysis showed that DC was associated with a higher mortality risk (OR = 1.31, 95% CI 1.06-1.61) than OC. CP was associated with a lower risk of poor mRS scores than OC (OR = 0.84, 95% CI 0.70-1.01), especially in stroke prevention centers and specific regions. Interpretation: Outcome improvements in Chinese sICH patients undergoing surgical treatment are worth expecting. Inconsistent surgical performance, especially functional outcome, affected by inhomogeneity of the hospital should be addressed. Funding: This work was supported by the Beijing Hospitals Authority Youth Programme (QML20230804), the National Natural Science Foundation of China (81701796, 82030037, 81871009), Capital Health Research and Development of Special Fund (2020-2Z-2019), Science and Technology Innovation 2030-Major Project (2021ZD0201801), and the Translational and Application Project of Brain-inspired and Network Neuroscience on Brain Disorders (11000022T000000444685).