With its high positioning accuracy, transcranial magnetic stimulation (TMS) has become an important means of non-invasive neuromodulation technique. This article analyzes the current status and challenges of precise positioning navigation technology, points out that the current navigation equipment is expensive and caliper-based simplified precision positioning method is difficult to monitor head movements in real time, and proposes the necessity of developing low-cost, high-precision navigation technology. Focus on the precise positioning technology of TMS and its application in clinical treatment and cognitive function positioning. Finally, the application prospects of precise positioning TMS in clinical treatment and cognitive function positioning are discussed, and it is pointed out that future research directions should focus on comparative studies of precise positioning and non - precise positioning treatment, as well as in - depth exploration of the precise positioning TMS treatment mechanism guided by fiber connections.

The rapid development of neurosurgery robots and navigation systems has significantly enhanced surgical precision and safety. Neurosurgery robots, based on stereotactic technology, achieve submillimeter-level positioning through multi-modal image fusion and non-invasive registration techniques. Equipped with high-degree-of-freedom robotic arms and integrated sensors, they precisely perform complex procedures such as stereo-electroencephalography (SEEG) electrode implantation, deep brain stimulation (DBS) device placement, and magnetic resonance-guided laser interstitial thermal therapy (MRgLITT). Navigation systems employ optical or electromagnetic tracking technologies combined with multi-modal imaging to assist surgeons in tracking important structures and target lesion tissue precisely. Future advancements may autonomously generate personalized surgical plans to reduce human error, while flexible robotic arms and novel endoscope-holding robots could expand endoscopic applications. Furthermore, the integration of multiple technologies will broaden neurosurgical applications. These innovations not only minimize complication risks and shorten treatment periods, but also propel the field toward intelligent, minimally invasive neurosurgery.

Non-invasive neuromodulation techniques have achieved remarkable advancements in the field of neuroscience in recent years, emerging as a crucial tool for researching and treating numerous neuropsychiatric disorders. The primary methods of non-invasive neuromodulation techniques, including transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have increasingly been incorporated into clinical practice and demonstrated impressive outcomes in depression, anxiety, and chronic pain. However, the application of non-invasive neuromodulation techniques still encounter several challenges, such as significant individual response variations, limited duration of therapeutic effects, and issues with standardizing stimulation parameters. This paper provides a comprehensive review of the primary non-invasive neuromodulation techniques and their current applications in brain functional diseases, analyzes the efficacy evaluation and future development direction to provide reference for further exploring their expanded applications in brain functional diseases and neural functions.

High performance computing (HPC) is transforming the field of large-scale brain simulation by enabling the integration of multi-scale computational modeling with massive neuroscience data. With advanced HPC resources, researchers can simulate neural activities from ion-channel dynamics to whole-brain network interactions, thereby illuminating the mechanisms underlying cognition, neural disorders, and emerging neuromorphic intelligence. This review examines the theoretical principles and technical foundations of supercomputer brain simulation, including distributed parallel algorithms, graphics processing unit (GPU)-based acceleration, and multimodal data management. It also surveys prominent simulation platforms such as NEST, NEURON, and The Virtual Brain (TVB), highlighting their strengths in modeling spiking neuronal network (SNN), multicompartmental neurons, and large-scale functional connectivity, respectively. Furthermore, we discuss the practical applications of these simulations in elucidating disease mechanisms in Alzheimer's disease (AD), Parkinson's disease (PD), autism spectrum disorder (ASD), schizophrenia, and epilepsy. Special emphasis is placed on how supercomputer brain simulation assists in virtual drug screening, optimizing deep brain stimulation parameters, and supporting digital twin approaches for personalized medicine. Finally, we address the critical challenges and future directions in this rapidly evolving domain, including the trade-off between computational cost and biological realism, data integration and validation, and the necessity for interdisciplinary collaboration. The advent of exascale supercomputers and the convergence of neuroinformatics and machine learning (ML) are poised to propel brain simulation research toward unprecedented clinical and scientific breakthroughs.

Intracranial pressure (ICP) monitoring serves as a critical component in the management of neurocritical care patients. Hydraulic-coupled intracranial pressure monitoring via external ventricular drainage (EVD-ICP) monitoring offers a clinically practical approach that enables both dynamic physiological assessment and therapeutic intervention, and has gained widespread adoption. However, the significant variability persists across healthcare institutions regarding the procedural standardization and the implementation of systematic management protocols. Building upon evidence-based medical principles and multidisciplinary expert consensus, this "Chinese expert consensus on the management of hydraulic-coupled intracranial pressure monitoring via external ventricular drainage" synthesizes key aspects of EVD-ICP monitoring, including clinical indications, procedural workflows, trouble shooting strategies, monitoring duration, complication prevention and management. The expert consensus aims to standard the technique and management of EVD-ICP monitoring, enhance diagnostic and therapeutic outcomes in the neurocritical care patients, and promote the standardized, precise and efficient application of this technology across clinical settings.

Intraoperative ultrasound (iUS) is a low-cost, portable and user-friendly auxiliary tool in brain tumor surgery, yet there is a lack of standardized operational guidelines. This review begins with the ultrasound physics and summarizes the workflow of iUS, followed by a grading system for ultrasonographic visibility of intracerebral lesions, iUS in assessing brain tumor resection, the limitations of iUS-guided brain tumor resection, multimodal ultrasound imaging, and the application of artificial intelligence (AI) in iUS. This review shows the clinical practice of iUS in brain tumor surgery from multiple perspectives and proposes practical standards.

The monitoring, evaluation and critical care management of neurological complications after endovascular treatment for acute ischemic stroke are essential components in optimizing patient outcomes and reducing both disability and mortality rates. Neurological complications, such as hemorrhagic transformation, vessel reocclusion, malignant brain edema and post-stroke epilepsy, which occur after endovascular treatment can significantly influence the overall effectiveness of the treatment. However, current critical care management of neurological complications are often hindered by inconsistencies in management standards and lack of standardized protocols. This expert consensus, grounded in evidence-based medicine and incorporating the clinical insights of professionals from multiple disciplines, provides a systematic approach to key areas including the identification of risk factors, appropriate monitoring and evaluation, and effective critical care management strategies for the most common postoperative neurological complications. Together, these elements form a comprehensive and standardized management framework. The primary goal of this consensus is to deliver scientifically sound and clinically applicable guidance for neurological complications management after endovascular treatment in patients with acute ischemic stroke.

The high heterogeneity and resistance of glioma present significant challenges in clinical treatment. The rapid development of multi-omics technologies has greatly advanced the understanding of the molecular mechanisms, resistance characteristics, and potential new drug targets in glioma. Building on this, multi-omics data is now being used for drug screening, mechanism exploration, and clinical trial guidance, thereby accelerating the translation of novel therapies and precision medicine strategies into clinical applications for the treatment of glioma. This review focuses on the latest advancements in the application of multi-omics technologies in glioma drug research and development, highlighting how insights into genetic mutations, gene expression, protein functions, and metabolic reprogramming can aid in understanding the molecular mechanisms, resistance, and complexity of the tumor microenvironment. Furthermore, it provides critical support for the identification of new drug targets, the development of personalized treatment plans, and drug screening, thus advancing the field of personalized and precision medicine in the treatment of glioma.

In 2024, significant advancements were made in the diagnosis, treatment, and research of glioma in China, reflecting a comprehensive innovation in basic research, diagnostic technologies, surgical techniques, targeted therapies, immunotherapies, and integrated management. This development showcases China's increasing capabilities in translating basic research into clinical applications, advancing the precision and intelligence of glioma care. Key achievements include the major academic organizations had played pivotal roles in glioma research and clinical practice. Notably, the establishment of the Glioma MDT Specialist Alliance under the National Center for Neurological Disorders had enhanced resource integration, promoted multidisciplinary collaboration, and accelerated knowledge sharing and clinical translation. The approval of mesenchymal - epithelial transition (MET) inhibitors for glioma harboring the PTPRZ1-MET fusion gene marked a milestone in precision oncology. Artificial intelligence (AI) has been widely adopted in glioma research. Breakthroughs in rapid intraoperative molecular diagnostics, combined with AI-powered imaging analysis and clustered regularly interspaced short palindromic repeats (CRISPR), were poised to revolutionize precision diagnosis and treatment. These developments underscore China's growing leadership in integrating cutting-edge technologies to address complex challenges in neuro-oncology.

Objective: To explore the influencing factors for subcutaneous effusion (SCE) after cranioplasty. Methods: Total of 111 patients with skull defect who underwent cranioplasty from January 2019 to June 2024 in Beijing Rehabilitation Hospital, Capital Medical University were analyzed retrospectively. All the patients were devided into SCE group (n = 29) and non-SCE group (n = 82) according to whether they had SCE after cranioplasty. Univariate and multivariate Logistic regression analyses were applied to explore the influencing factors for SCE after cranioplasty. Results: Among 111 patients, 29 had SCE after cranioplasty, with an incidence of 26.13%. All the 29 patients recovered and there was no bleeding, scalp damage, implant exposure, poor wound healing and intracranial infection after the treatment. Logistic regression analysis showed that age increase (OR = 1.075, 95%CI: 1.027-1.126; P = 0.002), polyether-ether-ketone (PEEK) repair material (OR = 7.673, 95%CI: 2.227-26.435; P = 0.001) and 24 h drainage increase before drain removal (OR = 1.026, 95%CI: 1.008-1.044; P = 0.004) were risk factors for SCE after cranioplasty. Conclusions: Age increase, PEEK repair material and 24 h drainage increase before drain removal were risk factors for SCE after cranioplasty. Timely and effective interventions should be taken according to individual condition.

Functional tic-like behaviors (FTLBs) is a kind of rare clinical phenotype of functional neurological disorder (FND), its etiology and pathogenesis have not been fully defined, and the clinical understanding of it is not comprehensive. This paper systematically reviews the relevant studies of FTLBs in recent years, and analyzes and summarizes its clinical characteristics, influencing factors, comorbidities, diagnosis, treatment and prognosis, aiming to provide theoretical reference for the subsequent diagnosis and treatment of FTLBs.

Objective: To explore the efficacy and prognosis of endovascular treatment for severe cerebral venous sinus thrombosis (CVST), providing new insights for the treatment of CVST. Methods: The clinical course of 31 severe CVST patients admitted to The First Hospital of China Medical University and Shengjing Hospital of China Medical University from October 2017 to December 2024 was analyzed retrospectively. The condition of venous sinus recanalization was assessed through immediately postoperative DSA examination, and the prognosis was evaluated based on criteria such as perioperative complication rate, mortality rate during follow‐up, and modified Rankin Scale (mRS) score at the last follow‐ up. Results: A combination of multiple endovascular treatment techniques was used. Immediately after the operation, 7 patients (22.58%) achieved complete recanalization of the venous sinus and 24 patients (77.42%) achieved partial recanalization. The incidence of perioperative complication rate was 6.45% (2/31), and there was no new cerebral infarction. The average follow ‐ up period was (6.60 ± 3.40) months. No deaths were reported during the follow ‐ up period. At the last follow ‐ up, 28 patients (90.32%) had a good prognosis (mRS score ≤ 2). Conclusions: Endovascular treatment can effectively reduce the mortality rate and improve the prognosis of patients with severe CVST, but individualized assessment is required, and indications must be strictly controlled.

Neurosurgery is entering an era of intelligent and personalized precision. The new generation of neurosurgeons needs not only superb surgical skills, but also the ability to master computer technology, imaging technology and neuromodulation. The application of artificial intelligence (AI) technology in neurosurgery includes machine learning (ML), deep learning (DL) and large language model (LLM). This article introduces specific cases in neurological tumors, spinal diseases, epilepsy and cerebrovascular diseases. Digit-intelligent neurosurgery focuses on the deep integration of digitalization and intelligentization in the field of neurosurgery. Digit-intelligent neurosurgery should establish a technical system of intelligent perception, intelligent cognition, intelligent decision-making and intelligent operation. With the deep integration of digitalization and intelligentization, neurosurgery will usher in unprecedented technological changes.

Objective: To summarize the clinical, electrophysiological and genetic characteristics of a pedigree with myotonic dystrophy (DM). Methods and Results: The 25-year-old male proband exhibited an occult onset, characterized by a distinctive "hatchet face" and alopecia, limb muscle weakness, amyotrophy, and damages of various systems, including the endocrine system and heart damage. Notably, the third aunt, the fourth uncle and the first brother of proband also exhibited similar clinical symptoms. Gene detection revealed both the proband, his aunt and his cousin had CTG repeats exceeding 100 times in the DMPK gene. Electromyography (EMG) studies conducted on the proband, his aunt and his cousin showed the coexistence of myotonic potential and myogenic damage. In the proband, the amplitude of the motor nerve conduction velocity of the left common peroneal nerve was decreased with a slight reduction in velocity, while the sensory nerve conduction velocity was also slowed. The proband, his aunt and his cousin were diagnosed with myotonic dystrophy type 1 (MD1). It was evident that the pedigree has myotonic dystrophy. Conclusions: Myotonic dystrophy is a rare autosomal dominant inheritance disorder characterized by myasthenia, myotonia and amyotrophy, which affects multiple systems. The clinical manifestations of this disease are diverse and relatively uncommon. In clinical practice, it is crucial to pay attention to the patient's family history, clinical signs and electrophysiological data, with particular emphasis on the identification of myotonic potential. Gene detection is of great significance for the diagnosis and differential diagnosis of myotonic dystrophy.

The application and development of digital intelligence technology in the field of neuroscience have provided powerful tools for fundamental research on brain functions, as well as for the diagnosis, treatment and rehabilitation of neurological disorders. This article reviews the latest advancements in the application of digital intelligence technology in basic brain function research, neurosurgery, neurology and neurorehabilitation, while also addressing the challenges and future development trends in the field. The aim is to provide new insights for the advancement of digital intelligence technology in neurology.

Hemorrhagic transformation (HT) is one of the severe complications of ischemic stroke, which may occur either during the natural course or as a consequence of treatments such as thrombolysis and thrombectomy. HT is associated with poor prognosis after ischemic stroke and influences clinical treatment decisions. Disruption of blood-brain barrier (BBB) has been demonstrated as the main mechanism underlying HT. Inflammatory responses contribute to this process by activating endothelial cells, recruiting immune cells such as neutrophils and macrophages, and releasing inflammatory mediators including proteases and reactive oxygen species, which further exacerbate vascular injury and BBB permeability, thereby promoting HT. Blood inflammatory markers may reflect these pathological processes and offer valuable biological information for early identification and risk stratification of HT. Classical inflammatory markers, such as matrix metalloproteinase-9 (MMP-9) and ferritin, have been demonstrated predictive value for HT. Recently increasing attention has been paid to investigate the mechanism and predictive potential of novel markers, such as neutrophil gelatinase-associated lipocalin (NGAL), high-mobility group box 1 (HMGB1) and nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome, for predicting HT. This review focuses on the novel blood inflammatory markers and systematically describes their correlation with HT, with the aim of providing a scientific basis for the mechanism investigation, accurate prediction and individualized therapeutic strategies of HT.

Cerebral small vessel disease (CSVD) is a major cause of stroke and dementia, with its treatment paradigm shifting from conventional risk factor management to targeted pathophysiological interventions. This article reviews the current landscape and key challenges in CSVD treatment research, focusing on patient selection, optimization of study endpoints, and development of targeted therapeutic strategies. Additionally, it explores the FINESSE framework, which aims to refine CSVD clinical trial design and accelerate advancements in treatment.

Objective: To summarize the clinical experience of supratentorial tumor resection using a wireless head - mounted display (HMD) - based holographic mixed reality navigation system (MRN). Methods: A analysis was performed on 5 patients undergoing supratentorial tumor resection using holographic MRN at Zhuhai People's Hospital from March to September 2024. Preoperative imaging data were imported into 3D Slicer software to generate holograms of lesions, anatomical landmarks, and adjacent structures, which were subsequently integrated into the holographic MRN and projected onto the patient's head for preoperative incision planning and intraoperative tumor resection guidance. The convenience and stability of holographic MRN were evaluated by assessing navigation registration time, navigation application time, and registration attempts. Accuracy, efficacy, and safety of holographic MRN were analyzed through evaluation of bone window extent, tumor - to - surrounding structure relationships, modeling time tumor localization, Karnofsky Performance Status (KPS) scores, and surgical indicators. Results: Preoperative modeling was all successfully completed, with an average modeling time (25.20 ± 1.60) min, and average registration time (3.20 ± 0.05) min. The mean preoperative and intraoperative navigation application times were (12.74 ± 1.09) and (8.17 ± 0.81) min, respectively. All registrations were successful on the first attempt. All lesions were entirely within the planned bone window boundaries, with no under - or over - exposure. Holographic projections of tumors fully overlapped with actual intraoperative lesions. All 5 cases achieved Simpson grade Ⅰ resection. The average KPS score at 72 h after surgery was 94.00 ± 4.90. Conclusions: This study confirms the convenience, stability, accuracy, efficacy, and safety of holographic MRN in clinical practice, demonstrating its value as an adjunctive tool for supratentorial tumor craniotomy.

Cerebral venous system diseases can lead to idiopathic intracranial hypertension (IIH), cerebral venous thrombosis (CVT) and pulsatile tinnitus (PT), and accurate evaluation of cerebral venous sinus hemodynamics is very important for the diagnosis and treatment of these diseases. In recent years, with the rapid development of hemodynamics research software and brain imaging technology, computational fluid dynamics (CFD), 4D Flow MRI, vitro simulation and transcranial Doppler ultrasonography (TCD) provide a multi-dimensional tool for the study of hemodynamics. In this paper, we will comprehensively introduce the research progress of above methods in the field of cerebral venous sinus hemodynamics, and provide innovative solutions for subsequent research of cerebral venous system diseases.

The pathogenesis of Rasmussen encephalitis (RE) remains unclear. Current theories suggest that viral infection, antibody-mediated humoral immune mechanisms, T lymphocytes mediated cellular immunity, and microglia mediated neurodegeneration may all be involved in disease onset and progression. In the early stage of disease, immunotherapy targeting induced by T lymphocytes and microglia could slow down disease progression of some patients. This review summarizes the latest research on the main pathogenic hypotheses and treatment strategies for RE, aiming to enhance clinical understanding of the disease and provide guidance for therapeutic interventions.

Objective: To investigate the short -term efficacy, long -term outcome and safety of recanalization treatment in patients with acute ischemic stroke presenting with large infarct core caused by intracranial atherosclerotic stenosis (ICAS) versus cardiac embolism (CE). Methods: A total of 96 acute ischemic stroke patients with large infarct core who underwent recanalization treatment at The People's Hospital of Anyang City from January 2022 to January 2023 were enrolled. Based on etiology, patients were divided into ICAS group (n = 52) and CE group (n = 44). Short-term efficacy was assessed using the National Institutes of Health Stroke Scale (NIHSS) at 14 d postoperatively, while long -term outcome was evaluated using the modified Rankin Scale (mRS) at 90 d postoperatively. Safety outcome included rate of symptomatic intracranial hemorrhage (sICH), intracranial hemorrhage, cerebral herniation within 24 h postoperatively, and fatality rate at 90 d postoperatively. Results: A statistically significant difference in NIHSS score was observed between the ICAS group and the CE group (F = 5.821, P = 0.023), with the CE group having higher NIHSS score than the ICAS group at admission (t = -2.324, P = 0.022). Both groups showed significant differences in NIHSS score between admission and 14 d postoperatively (F = 589.322, P = 0.000), with the CE group demonstrating lower NIHSS score at 14 d postoperatively compared to admission (t = 4.173, P = 0.001). The ICAS group exhibited a higher rate of favorable outcome at 90 d postoperatively [44.23% (23/52) vs. 25% (11/44); χ² = 3.853, P = 0.050]. No significant differences were observed between the 2 groups in sICH, intracranial hemorrhage, cerebral herniation rate, or 90 d fatality rate (P > 0.05, for all). Conclusions: Recanalization treatment for acute ischemic stroke patients with large infarct core caused by CE demonstrates more pronounced short-term efficacy, while ICAS presenting with better long-term outcome, and there is no significant difference in safety between the 2 groups.

Objective: Based on real-world clinical data, the predictive efficacy of the unweighted machine learning (ML) models for the prognosis of acute ischemic stroke with large vessel occlusion in the anterior circulation (AIS-aLVO) patients after mechanical thrombectomy was evaluated. The optimal model was selected, and the impact of class-weighted strategies on the predictive efficacy of this model was assessed. Methods: A total of 191 patients with AIS-aLVO who underwent mechanical thrombectomy from May 2023 to September 2024 in Tianjin Huanhu Hospital were included. Collect their clinical data, such as pre-admission National Institutes of Health Stroke Scale (NIHSS) score, etc. Retrospectively analyze the brain non-contrast CT (NCCT), multi-phase CT angiography (mCTA) and CT perfusion (CTP) examinations of the patients upon admission. The mCTA was used to assess the collateral circulation status; the Alberta Stroke Program Early CT Score (ASPECTS) was used to evaluate the early ischemic changes in the middle cerebral artery (MCA) supply area based on the NCCT; the CTP was used to assess the cerebral perfusion status, and the Mismatch volume, Tmax > 4 s volume, Tmax > 6 s volume, Tmax > 8 s volume and Tmax > 10 s volume were obtained. The 90-day modified Rankin Scale (mRS) score after surgery was used as the prognostic evaluation index, and the score > 2 was determined as poor prognosis. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Logistic regression (LR), random forest (RF), support vector machine (SVM), decision tree (DT), k-nearest neighbor (KNN), and eXtreme Gradient Boosting (XGBoost) algorithms were used to construct unweighted models. The predictive efficacy of the models was evaluated using the receiver operating characteristic (ROC) curve, area under the curve (AUC), calibration curve (Brier score), and decision curve analysis (DCA). The optimal model was selected, and the Shapley additive explanation (SHAP) method was used to analyze the feature importance of this model. At the same time, the impact of the class-weighted strategy on the predictive performance of the model was evaluated. Results: The optimal regularization parameter (λ = 0.064) of LASSO regression was determined by the ten-fold cross-validation minimum deviation criterion. Four feature variables were selected: ASPECTS score, Tmax > 10 s volume, pre-admission NIHSS score, and poor collateral circulation status. Stratified sampling was used to randomly allocate the subjects to the training set (n = 133) and the test set (n = 58), and unweighted models was established. In the unweighted model, except for the overfitting RF and XGBoost models, the Delong test showed that the pairwise comparison of the AUC values of the remaining models had no statistical significance (P > 0.05, for all); however, the unweighted SVM model had the lowest Brier score (0.16), and its calibration ability was the strongest. Within the 15%-30% threshold range, the DCA curve of the unweighted SVM model was the highest, suggesting the highest clinical applicability. There was no statistically significant difference in the AUC values, sensitivity, specificity, accuracy, positive predictive value and negative predictive value between the class-weighted and unweighted SVM models (P > 0.05, for all); however, compared with the unweighted SVM model, the Brier score of the class-weighted SVM model was higher (0.17 vs. 0.16), and its calibration ability was weakened. Conclusions: In a real-world cohort of AIS-aLVO cohort, the unweighted SVM model can accurately predict poor functional outcomes after mechanical thrombectomy without relying on class-weighted, and this method has high clinical translational potential.

Objective: To summarize the clinical manifestations and genetic characteristics of patients with Charcot-Marie-Tooth disease (CMT) caused by ARSs gene variation. Methods and Results: A total of 12 probands with clinical diagnosis of CMT were selected from The First Affiliated Hospital of Fujian Medical University from January 1997 to February 2024 and included in the clinical registration cohort of the hospital. Clinical symptoms: 10 patients had normal proximal limb muscle strength, while the distal limb muscle strength was seriously involved. Most muscular atrophy occurred below ankle joint and wrist joint. Two patients had subjective numbness of limbs, and one patient had reduced symmetry sensation on superficial sensory examination. Tendon reflexes were normal in only one patient. EMG characteristics: for the 11 probands, the median nerve motor nerve conduction velocity (MNCV) ranged from 0 to 65.70 m/s, with an average of 36.67 m/s, and the median nerve compound muscle action potential (CMAP) ranged from 0 to 19.50 mV, with an average of 5.42 mV. ARSs gene variation analysis: there were 4 ARSs gene variants, including GARS1, YARS1, AARS1 and SARS1. Among the 8 GARS1 gene mutation sites (c.1235G > A, c.598G > C, c.362G > A, c.1415A > G, c.637C > T, c.374A > G, c.722G > T, c.1000A > T), c. 598G > C and c. 722G > T had not been reported at home and abroad. EMG showed 5 probands were intermediate CMT (ICMT) and 3 were CMT₂. Among the 2 YARS1 gene mutation sites (c. 1333A > G, c. 787T > C), C. 787T > C has not been reported at home and abroad, and the 2 probands were CMT1 and ICMT. One proband with AARS1 gene mutation (c.896C > T), the EMG showed CMT₂; and there was one proband with SARS1 gene mutation (c.1187C > T), and the EMG showed ICMT. Conclusions: CMT caused by ARSs gene variation mainly causes hereditary motor neuropathy with or without sensory involvement, and the main clinical phenotypes are CMT₂ and ICMT. Different ARSs gene variation-related CMT patients have different clinical manifestations, and gene detection should be performed to confirm the diagnosis. The genetic spectrum of CMT was expanded to provide a basis for disease diagnosis and genetic counseling.

Objective: To report the clinical and typical imaging features of a patient with recurrent cerebral venous thrombosis (CVT) secondary to anemia, and to review the relevant literatures in order to enhance the understanding of recurrent CVT. Methods and Results: A 38 - year - old female patient initially presented with metamorphopsia and reading difficulties. Laboratory tests revealed significant decrease in hemoglobin and increase in platelet count. MRI and MRV showed thrombosis of the left transverse and sigmoid sinuses. She was diagnosed with CVT with secondary venous infarction and severe anemia. After anticoagulation therapy and treatment to correct the anemia, the condition improved. However, she stopped anticoagulation therapy on her own after 3 months. One year later, she experienced a recurrence of CVT. MRI and MRV showed cortical venous thrombosis. Anticoagulation therapy was restarted, and the symptoms improved. Conclusions: In patients with anemia and other hypercoagulable risk factors, CVT should be highly suspected when neurological deficits or epileptic seizures occur. A definitive diagnosis can be made with imaging findings. CVT requires both active etiological treatment and adequate anticoagulation therapy to prevent recurrence.

Objective: To develop a dual-layer feature distillation multiple instance learning (DLFD- MIL) model integrating MRI and whole slide image (WSI) features for precise prediction of IDH1 mutation, 1p/19q codeletion, and World Health Organization (WHO) grading in adult-type diffuse gliomas. Methods: A retrospective cohort of 212 adult-type diffuse gliomas patients from Huashan Hospital, Fudan University (January 2021 to June 2024) and 42 cases from The Cancer Genome Atlas (TCGA) were included. Preoperative T₂-FLAIR and postoperative WSI data were jointly analyzed. The DLFD-MIL model addressed the lack of instance - level labels in weakly supervised WSI learning via a pseudo - bag generation strategy. Multimodal feature fusion was achieved through Concat. Diagnostic performance for molecular subtyping and WHO grading was evaluated by comparing area under the curve (AUC) of receiver operating characteristic (ROC) curve between single - mode (WSI or MRI) and multi - mode. Results: In the IDH1 mutation prediction task, AUC of the multi - mode feature fusion model surpassed single - mode WSI model (Z = 2.752, P = 0.006) and single-mode T₂ -FLAIR model (Z = 5.662, P = 0.000). In the 1p/19q codeletion prediction task, no statistically significant differences in AUC were observed between the multi-mode feature fusion model and either single-mode WSI model (Z = - 0.245, P = 0.806) or T₂-FLAIR model (Z = 0.781, P = 0.435). In the WHO grading prediction task, the multi - mode feature fusion model showed no significant differences in AUC compared to single - mode WSI model (Z = 1.739, P = 0.082), however its AUC was significantly higher than single -mode T₂ -FLAIR model (Z = 4.830, P = 0.000). Conclusions: Multi-mode fusion of macro - and micro - imaging features improves prediction accuracy for IDH1 genotyping and WHO grading in gliomas, providing a reliable artificial intelligence (AI) decision - support tool for personalized clinical management.

Severe cerebral venous thrombosis (CVT) is associated with serious clinical manifestations and poor prognosis, and current therapeutic strategies fail to substantially improve outcomes, necessitating exploration of novel therapeutic approaches. The latest studies have shown that inflammation is closely associated with the severity and poor prognosis of severe CVT, and anti?inflammatory therapy may be a very promising treatment. Despite ongoing debate regarding the role of glucocorticoids in severe CVT, recent studies indicate that short? term glucocorticoids pulse therapy may be a safe and effective intervention in acute/subacute severe CVT, which are likely due to suppression of the inflammatory response. This paper focuses on the latest research progress of glucocorticoids therapy for severe CVT, and points out that anti?inflammatory therapy targeting inflammation has great research potential in improving the prognosis of severe CVT. We wish to provide a novel, accessible, effective and safe anti? inflammatory therapy for patients with severe CVT.

Cerebral venous thrombosis (CVT) is a relatively uncommon but serious cerebrovascular disease. Anticoagulation therapy is the preferred treatment. In recent years, significant progress has been made in venous sinus mechanical thrombectomy. However, there is no consensus on mechanical thrombectomy in clinical practice. Issues such as how to bridge thrombectomy with anticoagulation therapy, the definition of severe CVT, and the determination of the mechanical thrombectomy "time window" need further exploration. This paper reviews the progress on anticoagulantion therapy and mechanical thrombectomy for CVT in recent years, and introduces the concept of the "time window" for mechanical thrombectomy, with the aim of providing some inspiration for future clinical research and practice.

Surgical treatment of spontaneous intracerebral hemorrhage (sICH) is increasingly oriented toward minimally invasive, precise, and safe, with growing emphasis on disease and prognostic assessment, and perioperative monitoring. As a medical image processing software, 3D Slicer has been gradually applied in the diagnosis and treatment of sICH. It enables precise quantification of hematoma-related pathological changes, assists in preoperative trajectory simulation and intraoperative localization, greatly enriching the approaches for sICH evaluation, monitoring, and treatment. This article reviews the use of 3D Slicer software in sICH monitoring and prognostic evaluation, preoperative pathway planning and surgical simulation, intraoperative localization and puncture guidance, and the design and use of postoperative neuroprotective devices, aiming to provide novel insights to advance clinical practice.

Objective: To analyze the distribution characteristics of imaging biomarkers in cerebral small vessel disease (CSVD) in high - altitude plateau, investigate interrelationships among imaging features, and identify influencing risk factors for high CSVD burden. Methods: A total of 131 CSVD patients diagnosed and treated at People's Hospital of Xizang Autonomous Region between January 2021 and December 2022 were enrolled. Clinical data were collected, and brain MRI was performed to assess white matter hyperintensity (WMH), lacunar infarcts (LACI), cerebral microbleeds (CMBs), and enlarged perivascular space (EPVS), with subsequent calculation of the total CSVD burden score. The distribution patterns of CSVD imaging markers were analyzed. Spearman rank correlation analysis was used to investigate the association among imaging biomakers, including WMH, LACI, CMBs and EPVS. Univariate and multivariate Logistic regression analyses were applied to examine risk factors for high CSVD burden. Results: Total 131 patients with CSVD were divided into high CSVD burden group (1-4 points, n = 85) and low CSVD burden group (0 point, n = 46) according to total CSVD burden score. Compared to the low CSVD burden group, the high CSVD burden group exhibited significantly older age (t = - 5.410, P = 0.000) and a higher prevalence of hypertension (χ² = 14.853, P = 0.000). Among patients with CSVD in high-altitude plateau, the prevalence of WMH was 95.42% (125/131); LACI accounted for 34.35% (45/131), and were commonly located in the basal ganglia region; CMBs were predominantly of the mixed type (40.54%, 15/37); the prevalence of EPVS was 54.96% (72/131). Spearman rank correlation analysis revealed that CMBs were positively correlated with WMH (r_s = 0.255, P = 0.003) and LACI (r_s = 0.289, P = 0.001). Logistic regression analysis revealed that older age (OR = 1.056, 95%CI: 1.026- 1.088; P = 0.000) and hypertension (OR = 2.482, 95%CI: 1.071 -5.753; P = 0.034) were risk factors for high CSVD burden. Conclusions: Prevention and management strategies for CSVD in these populations should prioritize elderly individuals and hypertensive patients. While high-altitude environment may exacerbate cerebrovascular pathology, their specific mechanistic roles require further investigation.

The motor network is a key system in the central nervous system responsible for motor control and coordination, and its dysfunction is closely associated with various nervous system diseases. This review summarizes the physiological and pathological characteristics of the motor network, with a focus on its structural and functional changes in nervous system diseases. Additionally, the potential future developments in precision medicine and data integration are discussed.

Objective To report one case with protein C deficiency (PCD) and protein S deficiency (PSD) associated cerebral venous thrombosis (CVT), and to explore diagnostic and therapeutic strategies. Methods and Results A 27-year-old male patient presented with positional headache, worsened in supine position and relieved upon standing. Imaging findings showed thrombosis in the right transverse sinus, sigmoid sinus, and confluence of sinus. Laboratory tests showed significantly reduced protein C and protein S activities (49% and 51%) and elevated cerebrospinal fluid (CSF) pressure (> 330 mm H₂O). Genetic test identified a frameshift mutation in the PROC gene [c.574_577del (p.Val192Serfs*5)] and missense mutation in the PROS1 gene [c. 1915T > G (p. Cys639Gly) and c. 301C > T (p. Arg101Cys)]. After receiving heparin followed by non - vitamin K oral anticoagulants (NOACs), alongside intracranial pressure reduction, neurotrophic therapy, and analgesia treatment, the patient's headache symptom resolved, and at 4-month follow-up reexamination showed CSF pressure normalized (135 mm H₂O), with protein C and protein S activities rising to 53% and 54.10% (still below normal ranges). No headache recurrence was observed. Conclusions PCD and PSD are critical etiological factors for CVT. NOACs effectively improve venous reflux and avoid warfarin - related coagulation dysfunction, representing a preferred therapeutic option. Screening for coagulation protein activity and genetic analysis in young patients is essential to guide precise anticoagulation management.

Objective: To explore the diagnostic value of cerebrospinal fluid (CSF) biomarkers, total tau protein (t-tau), phosphorylated tau protein 181 (p-tau181) and real-time quaking-induced conversion (RT-QuIC) in sporadic Creutzfeldt-Jakob disease (sCJD). Methods: A retrospective study was conducted on 30 patients diagnosed with probable sCJD at Huashan Hospital, Fudan University from April 2020 to November 2022, serving as the sCJD group. Meanwhile, 25 patients diagnosed with rapidly progressive Alzheimer's disease (AD) and 23 patients diagnosed with autoimmune encephalitis (AE), matched for gender and age with the sCJD group, were selected as the AD group and AE group, respectively. CSF t- tau, p-tau181 and t- tau/p-tau181 ratio were collected from the 3 groups. The auxiliary examination data of the sCJD group, including typical manifestations of electroencephalography (EEG) and head MRI, as well as RT- QuIC results, were collected with emphasis. Results: There were statistically significant differences in CSF t-tau (χ² = 38.247, P = 0.000), p-tau181 (χ² = 22.855, P = 0.000) and t-tau/p-tau181 ratio (χ² = 43.780, P = 0.000) among 3 groups. Further pairwise comparisons revealed that the t- tau in the sCJD group was higher than that in the AD group (Z =-4.392, P = 0.000) and AE group (Z =-5.852, P = 0.000); the p-tau181 in the AD group was higher than that in the sCJD group (Z = 2.830, P = 0.014) and AE group (Z = 4.758, P = 0.000); the t-tau/p-tau181 ratio in the sCJD group was higher than that in the AD group (Z =-6.601, P = 0.000) and AE group (Z =-3.339, P = 0.003), and the t-tau/p-tau181 ratio in the AE group was higher than that in the AD group (Z =-2.984, P = 0.009). Among the 30 patients in the sCJD group, 70% (21/30) exhibited abnormal MRI findings in the brain, all displaying the typical cortical "lace sign"; 40% (12/30) showed typical triphasic waves on EEG. In the sCJD group, 7 cases underwent CSF RT-QuIC, and pathogenic prion protein was detected in 5 patients. Conclusions: Elevated CSF t-tau and t-tau/p-tau181 ratio, as well as positive RT-QuIC results, hold certain diagnostic value for sCJD.

Stroke, with its high incidence and disability rate, imposes a heavy burden on patients, families and society, urgently requiring safe and effective new treatment methods. Transcutaneous electrical acupoint stimulation (TEAS) is a non - invasive therapy that combines traditional Chinese meridian theory with modern physical factor therapy. Stimulating specific acupoints can not only improve functional disorders such as movement, swallowing, urination and defecation, but also regulate neuropsychological problems such as post-stroke depression and cognitive impairment. Moreover, TEAS can help prevent and treat complications such as deep vein thrombosis of the lower extremities and post-stroke fatigue. TEAS has unique clinical application value in the rehabilitation treatment of stroke. This article systematically reviews the progress in clinical application and mechanisms of TEAS in stroke rehabilitation treatment, and proposes future research directions to promote the standardized and precise application of TEAS.

Objective: To develop and validate a preoperative prediction model for meningioma brain invasion using radiomics features derived from multiparametric magnetic resonance imaging (MRI) - based brain - tumor interface (BTI). Methods: A total of 656 meningioma patients diagnosed and treated were included at The First Affiliated Hospital of Nanjing Medical University from September 2014 to April 2023. Using stratified random sampling, patients were randomly divided in a 4∶1 ratio into training set (524 cases) and testing set (132 cases). The training set was used for model construction and optimization, and the testing set for evaluating generalization ability. All patients underwent preoperative MRI examination including axial T₁WI, enhanced T₁WI and T₂WI. After image preprocessing and segmentation, the meningioma region of interest was identified, and BTI with thicknesses of 0.80, 1.00 and 1.20 cm were constructed. Radiomics features were extracted from the regions of interest (ROI) across the 3 sequences. Following single - value elimination and interclass correlation coefficient [ICC (2, k) > 0.90] stability screening, features were selected using five - fold cross - validated least absolute shrinkage and selection operator (LASSOCV). Six machine learning (ML) algorithms, including light gradient boosting machine (LightGBM), Logistic regression (LR), multilayer perceptron (MLP), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGBoost) were utilized to build predictive models. The performance of each model was assessed using receiver operating characteristic (ROC) curve and the area under the curve (AUC). The significance of differences between ROC curves were compared using the Delong test. Decision curve analysis (DCA) was performed to evaluate the clinical net benefit of the models across different threshold probabilities. Results: Among the 656 meningioma patients, 152 cases (23.17%) exhibited brain invasion, with 123 cases (23.47%) in the training set and 29 cases (21.97%) in the testing set. Through five - fold cross - validation in the training set and evaluation in the testing set, comparative analysis of the predictive performance of 18 model - thickness combinations (6 ML algorithms × 3 BTI thicknesses) showed that the XGBoost model constructed with a 1.00 cm BTI thickness demonstrated exceptional performance. This model achieved an AUC of 0.913 (95%CI: 0.886-0.937, P = 0.000), accuracy of 0.86, sensitivity of 0.77, and specificity of 0.88 in the training set; and an AUC of 0.897 (95%CI: 0.821- 0.961, P = 0.000), accuracy of 0.90, sensitivity of 0.72, and specificity of 0.95 in the testing set. Further Delong test showed that this model's AUC was significantly higher than all other models (P < 0.05, for all). DCA showed that this model demonstrated the best clinical utility with the highest net benefit area in both the training set (0.087) and the testing set (0.094). Conclusions: The XGBoost model based on 1.00 cm BTI exhibited outstanding predictive performance, providing an accurate and reliable non - invasive method for preoperative evaluation of meningioma brain invasion. This method offers substantial clinical utility in facilitating personalized surgical planning, risk assessment, and prognosis evaluation.

Objective: To investigate the correlation between vestibular symptoms and balance/walking function in patients with acute brain stem infarction. Methods: Fifty-one patients with acute brain stem infarction with a Functional Ambulation Category Scale (FAC) grade > 3 admitted to Tianjin Huanhu Hospital between November 2023 and December 2024 were included. The subjective visual vertical skew angle was measured using the Bucket Test. The degree of dizziness/vertigo was evaluated by the Visual Analogue Scales (VAS). The vestibulo-ocular reflex function was assessed by dynamic visual acuity (DVA). The Activities-Specific Balance Confidence Scale (ABC) was used to evaluate the balance confidence during performing various tasks, and the Dynamic Gait Index (DGI) was applied to assess the objective dynamic balance function. Results: Spearman rank correlation analysis showed that the ABC score was negatively correlated with the subjective visual vertical skew angle (r_s = -0.414, P = 0.003) and dizziness/vertigo VAS score (r_s = -0.463, P = 0.000), and the DGI index was negatively correlated with subjective visual vertical skew angle (r_s = -0.347, P = 0.012), dizziness/vertigo VAS score (r_s = -0.472, P = 0.000) and the number of rows lost in the yaw plane of DVA (r_s = -0.326, P = 0.019). Multifactor linear stepwise regression analysis showed that the strength of the effect of dizziness/vertigo VAS score (standardized partial regression coefficient = -0.593, P = 0.000) on ABC score was approximately 2.21 times greater than that of the subjective visual vertical skew angle (standardized partial regression coefficient = -0.268, P = 0.015); the effect of dizziness/vertigo VAS score (standardized partial regression coefficient = -0.666, P = 0.000) was 2.53 times stronger on the DGI index than the number of rows lost in the yaw plane of DVA (standardized partial regression coefficient = -0.263, P = 0.010). Further Spearman rank correlation analysis showed a positive correlation between dizziness/vertigo VAS score and the proportion of the stance phase time of gait parameter (r_s = 0.289, P = 0.039). Conclusions: Dynamic balance function in patients with acute brain stem infarction is mainly affected by the dizziness/vertigo severity. Furthermore, the degree of dizziness/vertigo shows a positive correlation with the proportion of stance phase duration during walking, which warrants heightened attention from both clinicians and rehabilitation therapists.

Objective: To compare the monitoring effect of abnormal muscle response (AMR) combined Z-L response (ZLR) and simple AMR in keyhole microvascular decompression (MVD) for hemifacial spasm (HFS). Methods: Total 258 patients with primary HFS treated with keyhole MVD between January 2014 and April 2024 from The Second Affiliated Hospital of Soochow University were analyzed retrospectively, including 102 patients underwent simple AMR (ARM group) and 156 patients underwent intraoperative monitoring of AMR combined ZLR (AMR + ZLR group). Calculate the surgical efficiency, and record the occurrence of postoperative complications. Results: In the AMR + ZLR group, 145 cases recovered 7 d after surgery, 11 cases were ineffective, and the surgery effective rate was 92.95% (145/156); 151 cases recovered 6 months after surgery, 5 cases was ineffective, and the surgery effective rate was 96.79% (151/156). In the AMR group, 86 cases recovered at 7 d after surgery, 16 cases were ineffective, and the surgery effective rate was 84.31% (86/102); 92 cases recovered 6 months after surgery, 10 cases were ineffective (2 cases relapsed), and the surgery effective rate was 90.20% (92/102). The MVD effective rates in AMR + ZLR group were better than that in AMR group at 7 d and 6 months after surgery (χ² = 4.908, P = 0.027; χ² = 4.904, P = 0.027). On the first day after surgery, 12 cases in the AMR + ZLR group experienced mild facial paralysis, which recovered within 7 d after surgery. In the AMR group, one case had tinnitus and one case had dizziness, both of which recovered within 3 d after surgery, 18 cases experienced mild facial paralysis, which recovered within 7 d after surgery. Conclusions: Intraoperative monitoring of AMR combined ZLR provides more valuable neurosurgical guidance than simple AMR during MVD for HFS. MVD is an effective method for the treatment of HFS, and the MVD rate of keyhole in our center has maintained a high level.

Background: Neurosurgery developed rapidly with technology advancing. Concept of digit-intelligent neurosurgery becomes mature and augmented reality (AR) technology shows great potential in future neurosurgical operations. The feasibility and applicability of AR assisted technology is currently the most important topic in clinical research. Methods: Four cases engaged from January to December 2024 in Department of Neurosurgery of Beijing Tsinghua Changgung Hospital with vestibular schwannoma (one case), intracranial aneurysm (2 cases) and subclavian artery (SA) occlusion caused vertebral artery steal syndrome (one case) have been conducted tumor resection, internal carotid artery (ICA)-posterior communicating artery (PCoA) aneurysm clipping and common carotid artery (CCA)-SA bypass, respectively. Using presurgical imaging data-based Surgical AR reconstruction on the HoloLens 2 platform, preoperative planning, surgical simulation, and intraoperative display were conducted. These were then compared with surgical practices and postoperative imaging data to qualitatively evaluate their effectiveness in assisting neurosurgery. Results: 1) Vestibular schwannoma resection: compared to the preoperative AR assisted simulation, we fully replicated the procedures of retrosigmoid approach craniotomy, removal of the posterior wall of internal auditory canal, and the exposure and removal of the internal auditory canal tumor during surgical practice. Facial nerve function was preserved intact during the surgery and reached House-Brackmann grade Ⅰ, but effective hearing was not preserved. Postoperative imaging data showed non-significant difference compared to preoperative simulation and surgical practice. The modified Rankin Scale (mRS) assessed postoperatively was 2. 2) ICA-PCoA aneurysm clipping: compared to the presurgical AR assistance, we fully replicate the procedures of lateral supraorbital craniotomy, removal of anterior clinoid process and the exposure and clipping of the neck of aneurysm. Postoperative imaging data showed non-significant difference compared to preoperative simulation. Postoperatively symptoms such as eye pain, ptosis, and double visian were completely relieved and the mRS was 0 after 6 months. 3) Basilar artery apex aneurysm clipping: based on preoperative simulation, we opted for the orbito-zygomatic approach during surgery to provide full exposure of the aneurysm neck and direct visualization of the bilateral P1 segment of posterior cerebral artery (PCA), offering better safety compared to the subtemporal approach. In surgical practice, lateral sulcus was separated, basilar artery and aneurysm was exposed and clipped via carotid spaces. Postoperatively occlomoter nerve was well recovered mRS was 0 after 6 months. 4) CCA- SA bypass: critical muscles and vessels on the neck were located intraoperatively on the body surface with AR assistance. CCA and SA were fully exposed and artificial vessel was anastomosed. Postoperative CTA 3D reconstruction suggested the blood flow was patent. The dizziness did not recur, and the blood pressure in the upper limb on the affected side returned to normal. Postoperative mRS was 0 after 6 months. Conclusions: The application of AR technology in neurosurgical procedures allows for preoperative planning, surgical simulation, and intraoperative display. It aids young surgeons in quickly understanding complex anatomical structures and shortens the learning curve, holding significant clinical value and promising application prospects.

Lobar hemorrhage is an important subtype of cerebral hemorrhage, which is associated with cerebral amyloidosis angiopathy (CAA) and has a high incidence rate, recurrence rate and disability rate. It is of great significance to predict its clinical prognosis using plain CT. Previous studies have found that the volume and morphology (irregular morphology of edges, island sign, spot sign, finger- like projection) of cerebral hemorrhage on CT images, combined with subarachnoid hemorrhage (SAH), CT cerebral small vessel disease (CSVD) score, and CT radiomics, have certain predictive value for early hematoma expansion, neurological deterioration, and long - term poor functional prognosis, and recurrence in lobar hemorrhage. We review the predictive value of the above imaging features for the prognosis in lobar hemorrhage, providing a theoretical basis for precise prognostic stratification and individualized intervention.

Objective: To investigate the predictive value of a modified Acute Stroke Registry and Analysis of Lausanne (ASTRAL) score, in which the triglyceride glucose (TyG) index replaces the glucose parameter of ASTRAL score, for poor prognosis in ischemic stroke patients. Methods: This study was based on the ischemic stroke database of The First Affiliated Hospital of Zhengzhou University. A total of 3393 ischemic stroke patients from January 2019 to December 2021 were enrolled. Baseline information was collected, and the TyG index and ASTRAL score were calculated. Replace the glucose parameter of ASTRAL score with the TyG index to construct ASTRAL-TyG model. Modified Rankin Scale (mRS) score was used to evaluate the functional outcome. Univariate and multivariate Logistic regression analyses were performed to screen for influencing factors of poor prognosis. Receiver operating characteristic (ROC) curve was plotted, and the area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were calculated to evaluate the predictive value of the ASTRAL - TyG model. Results: Based on the mRS score, patients were stratified into a good prognosis group (mRS ≤ 2, n = 2961) and a poor prognosis group (mRS > 2, n = 432). Logistic regression analysis showed that both increased ASTRAL score witnin 24 h of admission (OR = 1.156, 95%CI: 1.133-1.179; P = 0.000) and increased TyG index (OR = 1.731, 95%CI: 1.489-2.013; P = 0.000) were risk factors for poor prognosis (Model 1, TyG index was included as a continuous variable). Increased ASTRAL score within 24 h of admission (OR = 1.156, 95%CI: 1.133-1.179; P = 0.000), TyG index of 8.69-9.08 (OR = 1.445, 95%CI: 1.025-2.039; P = 0.036), and TyG index ≥ 9.55 (OR = 2.103, 95%CI: 1.532-2.888; P = 0.000) were risk factors for poor prognosis (Model 2, TyG index was included as a categorical variable). The ROC curve demonstrated that the AUC for predicting one year poor prognosis was 0.754 (95%CI: 0.728-0.779, P = 0.000) for the ASTRAL score and 0.768 (95%CI: 0.743-0.794, P = 0.000) for the ASTRAL-TyG model. The sensitivity was 65.05% and 65.97%, while the specificity was 74.23% and 78.01%, respectively. The predictive value of the ASTRAL - TyG model was significantly higher than that of the ASTRAL score (Z = 2.084, P = 0.037). Conclusions: The ASTRAL score modified by the TyG index (ASTRAL - TyG model) improved the predictive value for poor prognosis in ischemic stroke patients.

Objective To report one case of chronic cerebral venous thrombosis (CVT) caused by compound heterozygous mutation in MTHFR gene, and to investigate the association between compound heterozygous mutation in MTHFR gene and chronic CVT as well as its pathophysiology mechanism. Methods and Results A 27-year-old male patient presented to the hospital with sudden onset headache. Imaging findings showed chronic thrombosis of the left superior sagittal sinus, inferior sagittal sinus, straight sinus, transverse sinus and confluence of sinus, and laboratory tests revealed hyperhomocysteinemia (homocysteine > 100 μmol/L). Genetic testing showed that the patient had a compound heterozygous mutation of MTHFR gene c. 325C > G (p. Arg109Gly) and c. 277C > T (p. Arg93Ter), and the mother also carried the c. 277C > T (p. Arg93Ter) heterozygous mutation, suggesting a familial predisposition. The clinical diagnosis was chronic CVT caused by a compound heterozygous mutation in MTHFR gene. Following anticoagulation therapy combined with folate acid and vitamin B supplementation, symptoms improved, but homocysteine level remained elevated. Conclusions This paper first reports the association of MTHFR gene c.325C > G (p.Arg109Gly) and c.277C > T (p.Arg93Ter) compound heterozygous mutation with CVT. Compound heterozygous mutation in MTHFR gene play an important role in the chronicity of thrombosis, and the necessity of genetic testing and individualized therapy for patients with hereditary thrombophilia should be emphasized.