Journal of Korean Neurosurgical Society最新文献

{"title":"Comparative Evaluation of Imatinib and Nilotinib in a Streptozotocin-Induced Rat Model of Alzheimer's Disease : Neuroprotective, Anti-inflammatory, and Cognitive Outcomes.","authors":"Gokhan Gurkan, Burkay Akdag, Mumin Alper Erdogan, Oytun Erbas","doi":"10.3340/jkns.2025.0110","DOIUrl":"10.3340/jkns.2025.0110","url":null,"abstract":"<p><strong>Objective: </strong>Alzheimer's disease is a progressive neurodegenerative disorder characterized by amyloid-beta (Aβ) peptide aggregation, representing a major therapeutic target. Emerging evidence suggests certain chemotherapeutic agents may attenuate Aβ pathology.</p><p><strong>Methods: </strong>This study investigated the effects of imatinib, a tyrosine kinase inhibitor with limited blood-brain barrier (BBB) penetration, and nilotinib, with enhanced BBB permeability, in an intracerebroventricular streptozotocin (ICV-STZ) rat model of Alzheimer's disease. Outcomes included behavioral assessments (learning latency), hippocampal CA1 and CA3 neuronal counts, and brain concentrations of tumor necrosis factor (TNF)-α, nuclear factor kappa B (NF-κB), brain-derived neurotrophic factor (BDNF), and neuregulin-1 (NRG-1).</p><p><strong>Results: </strong>ICV-STZ administration significantly elevated TNF-α and NF-κB levels and reduced BDNF and NRG-1 expression. Both imatinib and nilotinib mitigated these alterations, with imatinib demonstrating greater efficacy despite its limited BBB permeability. Imatinib and nilotinib reduced TNF-α and NF-κB levels, increased BDNF and NRG-1 expression, and significantly improved cognitive performance, with latency periods extending from 69.8 seconds in the disease model to 193.5 and 183.1 seconds, respectively.</p><p><strong>Conclusion: </strong>Imatinib and nilotinib ameliorated neuroinflammation, restored neurotrophic support, and improved cognitive deficits in a preclinical Alzheimer's disease model. These findings highlight the therapeutic potential of tyrosine kinase inhibitors, warranting further translational research in human studies.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":" ","pages":"421-432"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172787/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145487837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Prediction of Prevertebral Soft Tissue Swelling after Single-Level Anterior Cervical Surgery : A Proof-of-Concept Study.","authors":"Joon Hyun Hwang, Sang Mook Kang, Byeong Jin Ha, Yu Deok Won, Myung-Hoon Han, Jin Hwan Cheong, Shin-Woong Ko, Je Il Ryu","doi":"10.3340/jkns.2025.0252","DOIUrl":"10.3340/jkns.2025.0252","url":null,"abstract":"<p><strong>Objective: </strong>Prevertebral soft tissue swelling (PSTS) is a significant complication of anterior cervical spine surgery (ACSS) that causes dysphagia, dysphonia, and possibly life-threatening airway obstruction. This study aims to develop and internally validate an interpretable machine learning model to predict significant PSTS after single-level ACSS using a small, single-center dataset.</p><p><strong>Methods: </strong>We retrospectively analyzed data from 62 patients who underwent single-level ACSS in our center, from January 2014 to December 2022. Postoperative swelling over 7.0 mm (above 75th percentile) was defined as significant PSTS. We developed an elastic net regularized logistic regression model over 1000 iterations with nested 5-fold cross validation for hyperparameter tuning and bootstrap validation. The model's interpretability was assessed using SHapley Additive exPlanations (SHAP) approach, and its clinical utility by decision curve analysis.</p><p><strong>Results: </strong>A total of 16 (25.8%) out of 62 patients developed significant PSTS. Our model achieved a bootstrap-validated area under the ROC curve value of 0.84 (95% confidence interval, 0.73-0.92) with good calibration (Hosmer-Lemeshow p=0.42). According to our results, important predictors of PSTS included 1) low preoperative serum albumin (SHAP importance, 0.42), 2) upper level surgery above C5 (0.38), and 3) male sex (0.31). Decision curve analysis demonstrated net benefit across probability thresholds of 15-45%.</p><p><strong>Conclusion: </strong>Our machine learning model effectively predicted risk of significant PSTS following single-level ACSS despite small sample size. Such findings offer new opportunities for risk stratification and prevention strategies. This study is a proof of concept for artificial intelligence (AI)-based risk stratification strategy; further external validation could improve its relevance in the clinical setting.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":" ","pages":"451-458"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172777/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neurosurgical Application of Artificial Intelligence in Pediatric Neuro-Oncology.","authors":"Joo Whan Kim","doi":"10.3340/jkns.2026.0085","DOIUrl":"10.3340/jkns.2026.0085","url":null,"abstract":"<p><p>Pediatric neuro-oncology is a critical field of neurosurgery, representing the leading cause of disease-related mortality in children. Despite its rarity, it encompasses over 100 diverse disease entities, which significantly complicates preoperative differential diagnosis and surgical planning. This review examines how artificial intelligence (AI) can address these unmet clinical challenges throughout the perioperative period. Preoperatively, AI-driven radiogenomic models extract pixel-level features to enable non-invasive molecular subtyping, such as predicting B-Raf proto-oncogene alteration status in pediatric low-grade gliomas (pLGGs). Such insights are vital for determining the extent of resection (EOR) with consideration of availability of targeted therapies. Furthermore, AI facilitates automated tumor segmentation, allowing for meticulous surgical planning and more accurate assessment of surgical risks. Intraoperatively, AI significantly accelerates diagnostic turnaround times, which is essential for real-time decision-making. Emerging technologies, including Oxford Nanopore sequencing with neural network classifiers or stimulated Raman histology, allow for the rapid identification of tumor characteristics in operation time window. These tools directly inform the optimal EOR, particularly in cases like medulloblastoma where molecular subgroups dictate surgical aggressiveness. Additionally, AI integration into intraoperative neurophysiological monitoring enhances the preservation of critical neurological functions. Postoperatively, multimodal deep learning models integrate clinical, imaging, and genomic data to improve prognostic accuracy and standardize response assessment via AI integration. While challenges such as data scarcity and the \"black box\" nature of algorithms persist, innovative strategies offer potential solutions to AI application. AI serves as a transformative tool for personalized precision management, potentially bridging diagnostic disparities and optimizing clinical outcomes for children with central nervous system tumors.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":" ","pages":"338-348"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172791/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147581583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editors' Pick in May 2026.","authors":"Hee-Jin Yang","doi":"10.3340/jkns.2026.0119","DOIUrl":"10.3340/jkns.2026.0119","url":null,"abstract":"","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":"69 3","pages":"323-325"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172782/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147874412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Model for Recurrent Lumbar Disc Herniation after Lumbar Discectomy.","authors":"Seung Yeop Kang, Soo Jin Lee, Suhyeon Kim, Sung Hyeon Noh","doi":"10.3340/jkns.2025.0120","DOIUrl":"10.3340/jkns.2025.0120","url":null,"abstract":"<p><strong>Objective: </strong>Recurrent lumbar disc herniation (RLDH) is a significant challenge following lumbar discectomy, with recurrence rates of 5-15%. Established risk factors include male gender, diabetes mellitus, smoking, and obesity, but the role of paraspinal muscles in recurrence is unclear. This study was conducted to identify key risk factors for RLDH, including the volume of paraspinal muscles with machine learning.</p><p><strong>Methods: </strong>We used data from 126 patients who underwent lumbar discectomy between January 2003 and September 2023 and had follow-up outpatient visits for more than 6 months at a single institution. Variables selected for the model, comprising demographic and clinical variables, medical history, LDH operation-related variables, and magnetic resonance imaging (MRI) measurements for RLDH. Based on clinical symptoms and radiologic results, the patients were classified into RLDH and non-RLDH groups, and RLDH was defined at the same surgical level on follow-up MRI.</p><p><strong>Results: </strong>Totally, 38 patients were included in the RLDH group and 88 in the non-RLDH group. The volume of quadratus lumborum was identified as a risk factor for RLDH (odds ratio, 7.894; p=0.001). Among the five different machine learning algorithms, extreme gradient boosting achieved the best result with an accuracy of 0.794 and area under the curve of 0.811. In terms of Shapley Additive exPlanations value analysis, the weight, volume of quadratus lumborum, psoas major, and vertebra were key features for predicting RLDH.</p><p><strong>Conclusion: </strong>The prediction model would be of great assistance for surgeons to make surgical decisions or establish observation intervals.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":" ","pages":"441-450"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172788/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145345003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Burnout among Korean Neurosurgeons Following a National Trainee Withdrawal during 2024-2025 Medical Crisis in Korea.","authors":"Hyun Gyu Kim, Woo Cheul Cho, Stephen Ahn","doi":"10.3340/jkns.2025.0172","DOIUrl":"10.3340/jkns.2025.0172","url":null,"abstract":"<p><strong>Objective: </strong>The 2024-2025 medical crisis in the Republic of Korea, triggered by mass trainee departures, caused severe staffing shortages in tertiary hospitals. The impact of this disruption on neurosurgeons' workload, lifestyle, and mental health has not been evaluated. In this study, we aimed to determine the prevalence of burnout among neurosurgeons during the crisis, assess associated changes in workload and lifestyle, and identify key factors linked to burnout severity.</p><p><strong>Methods: </strong>We conducted a nationwide, questionnaire-based observational study from April 29 to June 4, 2025, targeting board-certified neurosurgeons in university hospitals across the Republic of Korea. Participants were recruited through departmental professional contacts and completed an online survey capturing baseline characteristics, paired pre-post crisis values for 14 workload and lifestyle variables, and three current-status items. Burnout was assessed using the Copenhagen Burnout Inventory (CBI) as the primary tool and the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) as a supplementary measure.</p><p><strong>Results: </strong>Of 61 respondents, 36 (59.0%) met high-burnout criteria. After the crisis onset, all workload and lifestyle factors shifted unfavorably, with the largest increases in weekend/holiday duty (86.9%), night duty (82.0%), and sleep disturbance call (68.9%), and the largest declines in number of colleagues (-50.8%), leisure time (-47.5%) and family time (-44.3%). High-burnout surgeons had greater workloads, more off-hour duties, and less recovery time than low-burnout peers. Burnout severity correlated with staffing levels, working hours, night duty, time spent with family and leisure activities, job satisfaction, intention to leave, and all MBI subscales.</p><p><strong>Conclusion: </strong>Burnout among Korean neurosurgeons is widespread after the national medical crisis, with substantial deterioration in workload and lifestyle. Coordinated efforts at both hospital and national levels are essential to protect surgeon well-being and maintain the quality of neurosurgical care.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":" ","pages":"482-492"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145345646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wearable Technologies for Clinical Assessment and Monitoring in Pediatric Neurodevelopmental Disorders : A Narrative Review.","authors":"Eun Jae Lee, Woojoong Kim","doi":"10.3340/jkns.2026.0036","DOIUrl":"10.3340/jkns.2026.0036","url":null,"abstract":"<p><p>Pediatric neurodevelopmental disorders (NDDs) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision : intellectual disabilities, communication disorders, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), specific learning disorder, and motor disorders together with closely associated pediatric neurological conditions such as cerebral palsy (CP) and epilepsy, present with symptom fluctuations and variable performance, making longitudinal assessment challenging. Conventional clinical scales, questionnaires, and caregiver diaries are largely subjective and offer limited temporal coverage. This review examines wearable technologies applicable to these conditions, focusing on measurable digital biomarkers and real-world clinical application. A narrative review was performed. Wearable technologies were categorized into motion trackers (accelerometers/gyroscopes, inertial measurement units [IMUs]), physiological monitors (photoplethysmography-derived heart rate and heart rate variability, and electrodermal activity), wearable electroencephalography (EEG)/brain sensors, smart glasses/cameras, and textile-based wearables. IMU and accelerometer based systems achieved posture and gait classification accuracies of approximately 85%, distinguished children with ADHD from controls with 80-90% accuracy, and detected stereotyped behaviors in children with ASD with sensitivities exceeding 90%. Wearable EEG demonstrated high performance for ASD classification (accuracy, 96%; sensitivity, 100%) and for automated sleep staging in epilepsy(accuracy, 80.8-83.5%), and also enabled seizure-related signal monitoring through detection of ictal fast activity. For tonic-clonic seizures, wearable devices achieved sensitivities of 89-94%, whereas tonic-seizure detection performance remains limited. Smartwatch vibrotactile stimulation reduced stereotyped behaviors and improved task performance, and wrist-worn biosignals enabled prediction of aggressive behavior approximately three minutes before onset. Augmented reality based smart glasses supported social-communication coaching in children with ASD. In children with CP, smart-shoe systems classified daily activities with high accuracy and quantified gait asymmetry. Wearables enable objective and continuous assessment of symptoms and behaviors in children with NDDs and related pediatric neurological conditions across real-world environments and are expanding toward personalized intervention. Remaining challenges include integration into clinical workflows (electronic medical record [EMR] linkage, clinician-friendly data summarisation, and reimbursement pathways), ethical and privacy considerations, and standardisation of validation protocols.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":"69 3","pages":"361-370"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172776/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147874367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Utility of Antiplatelet Assay-Guided Individualized Dual Antiplatelet Therapy in Carotid Artery Stenting for Unstable Plaques.","authors":"Sujong Pak, Shigeta Miyake, Osamu Masuo, Kana Takase, Yoshiaki Tetsuo, Wataru Shimohigoshi, Arisa Umesaki, Taisuke Akimoto, Yasunobu Nakai, Tetsuya Yamamoto","doi":"10.3340/jkns.2025.0170","DOIUrl":"10.3340/jkns.2025.0170","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the efficacy of individualized dual antiplatelet therapy (DAPT) using VerifyNow in reducing periprocedural ischemic complications following carotid artery stenting (CAS), particularly in patients with unstable plaques.</p><p><strong>Methods: </strong>This retrospective, single-center study included 187 patients who underwent elective CAS between January 2018 and September 2024. Patients were divided into two groups : a conventional DAPT (c-DAPT) group treated with aspirin and clopidogrel (n=89), and an individualized DAPT (i-DAPT) group (n=98) where antiplatelet regimens were adjusted based on preoperative platelet reactivity measured by VerifyNow. The primary outcome was the incidence of ischemic lesions on diffusion-weighted imaging (DWI) following CAS. Risk factors and the impact of DAPT personalization on ischemic changes were analyzed using multivariate logistic regression.</p><p><strong>Results: </strong>DWI-positive ischemic lesions were observed in 62.9% of the c-DAPT group and 51% of the i-DAPT group (p=0.07). Although the difference was not statistically significant, there was a trend toward reduced ischemic changes with individualized therapy. Multivariate analysis identified hypertension, diabetes mellitus, and unstable plaque as independent predictors of post-CAS ischemic changes. Subgroup analysis showed that VerifyNow-guided i-DAPT significantly reduced ischemic events in patients with unstable plaques (odds ratio, 0.49; p=0.03), whereas no significant effect was observed in other subgroups.</p><p><strong>Conclusion: </strong>VerifyNow-guided personalization of antiplatelet therapy is a safe and may have the potential to reduce periprocedural ischemic complications in CAS, particularly in patients with unstable plaques. Further multicenter prospective studies are needed to validate these findings and optimize individualized antiplatelet regimens.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":" ","pages":"433-440"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172784/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145345036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Citicoline Loaded PHBA Tubular Grafts on Axonal Regeneration in Sciatic Nerve Injury : An Experimental Approach as an Autograft Alternative.","authors":"Hıdır Özer, Ali Yılmaz, Mürüvvet Akçay Çelik, Yeliz Kaşko Arıcı, Vugar Nabi, Ebru Erdal, Songül Özay, Murat Demirbilek, Mehdi Hekimoğlu","doi":"10.3340/jkns.2025.0202","DOIUrl":"10.3340/jkns.2025.0202","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to evaluate the effects of poly(3-hydroxybutyrate)/alginate (PHBA/ALG) tubular graft containing cytidine 5'-diphosphocholine (citicoline) on axonal regeneration in an experimental rat sciatic nerve injury model and to compare the results of this method with autologous nerve grafting.</p><p><strong>Methods: </strong>A total of 24 Wistar-Hannover albino rats were randomly divided into three groups (n=8). In all animals, a 10 mm segment was removed from the right sciatic nerve under microscope. The nerve defect was repaired using autologous nerve graft (group O), PHBA graft only (group T), and PHBA graft containing citicoline (group S). Sixteen weeks later, all animals were euthanized and sciatic nerve samples were taken for histopathological examination. Sections were stained with hematoxylin-eosin and Masson Trichrome.</p><p><strong>Results: </strong>The groups were compared statistically in terms of regenerated axon diameter, number of blood vessels, nerve sheath degeneration, edema, inflammatory cell infiltration, and necrosis. Histopathological evaluation showed that regenerative axons were formed in all three groups. PHBA and citicoline-containing PHBA grafts successfully bridged the damaged area. While the best results were obtained in the autograft group, the results of the PHBA group containing citicoline were statistically significantly better than the PHBA group. In general, the distribution of histopathological parameters showed that citicoline administration showed protective effects on parameters such as inflammation and cell death. Axon diameter : group S had significantly larger axon diameters than group T (p<0.05). Number of blood vessels : the highest values were in the autograft group and the difference between groups O and T was significant (p<0.05).</p><p><strong>Conclusion: </strong>PHBA-based tubular graft with oriented nanofiber structure containing citicoline supports peripheral nerve regeneration. Although our results are not better than autograft, it may be a promising alternative for cases where autologous graft is not available.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":" ","pages":"403-420"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172785/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147443763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Emerging Role of Artificial Intelligence in Pediatric Neuroanesthesia.","authors":"Jung-Bin Park, Young-Eun Jang","doi":"10.3340/jkns.2026.0033","DOIUrl":"10.3340/jkns.2026.0033","url":null,"abstract":"<p><p>Anesthesia for pediatric neurosurgery represents a highly complex and challenging field, characterized by age-dependent physiological variability, heterogeneous patient populations, and the critical need to protect the developing central nervous system. Conventional clinical approaches often rely on adult-derived data, which may inadequately reflect the distinct neurophysiological and hemodynamic characteristics of neonates, infants and children. Recent advances in artificial intelligence (AI) have enabled the integration of multimodal perioperative data, including physiologic signals and neurophysiologic monitoring, with the aim of supporting clinical decision-making in complex surgical settings. This review summarizes the current landscape of AI applications relevant to pediatric anesthesia, with particular attention to preoperative risk assessment, airway management, and real-time prediction of intraoperative adverse events such as hypoxemia and hemodynamic instability. Although AI-based approaches have demonstrated encouraging results in adult populations, their application to pediatric neuroanesthesia remains limited. The integration of AI into this field faces several distinct challenges, including the scarcity of high-quality datasets for rare neurosurgical conditions, substantial heterogeneity across developmental stages, and difficulties in aligning model outputs with clinically interpretable physiologic mechanisms. Addressing these limitations will require the development of explainable, physiology-informed AI frameworks and disease-specific models tailored to conditions such as moyamoya disease or complex craniofacial reconstruction. Ultimately, AI should be positioned as an adjunctive decision-support tool that complements, rather than replaces, anesthesiologists' expertise. Through multidisciplinary collaboration and human-centered implementation, AI may contribute to improved perioperative safety and long-term neurodevelopmental outcomes in vulnerable pediatric neurosurgical patients.</p>","PeriodicalId":16283,"journal":{"name":"Journal of Korean Neurosurgical Society","volume":" ","pages":"392-402"},"PeriodicalIF":1.9,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13172780/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147638571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}