In situ brain tumor detection using a Raman spectroscopy system-results of a multicenter study.

Safe and effective brain tumor surgery aims to remove tumor tissue, not non-tumoral brain. This is a challenge since tumor cells are often not visually distinguishable from peritumoral brain during surgery. To address this, we conducted a multicenter study testing whether the Sentry System could distinguish the three most common types of brain tumors from brain tissue in a label-free manner. The Sentry System is a new real time, in situ brain tumor detection device that merges Raman spectroscopy with machine learning tissue classifiers. Nine hundred and seventy-six in situ spectroscopy measurements and colocalized tissue specimens were acquired from 67 patients undergoing surgery for glioblastoma, brain metastases, or meningioma to assess tumor classification. The device achieved diagnostic accuracies of 91% for glioblastoma, 97% for brain metastases, and 96% for meningiomas. These data show that the Sentry System discriminated tumor containing tissue from non-tumoral brain in real time and prior to resection.

Bibliometric and trend analysis of the top 100 most-cited articles on lateral interbody fusion (LIF).

PURPOSE: Lateral interbody fusion (LIF) is an increasingly popular minimally-invasive spine procedure. This study identifies notable trends in LIF literature and provides a detailed review of the bibliometric aspects of the top 100 most-cited articles. METHODS: Articles were queried from the Web of Science database. Inclusion criteria consisted of peer-reviewed articles, full-text availability, and LIF focus. Network analysis including co-authorship mapping and bibliographic coupling were complemented by trend analysis to determine prominent contributors and themes. Analyses were conducted using VOSviewer and Bibliometrix (RStudio). RESULTS: There has been a rapid increase in LIF publication and citation count since 1998. Leading journals were Spine (n = 24), Journal of Neurosurgery Spine (n = 22), and European Spine Journal (n = 12). NuVasive funded the most publications (n = 17), followed by DePuy Synthes Spine (n = 4). The United States was the most represented country (n = 81); however, trend analysis suggests a steadily growing international contribution. The most prolific author was J.S. Uribe (n = 16), followed by a tie in second place by E. Dakwar and L. Pimenta (n = 8). The most frequent keywords, "complication" (n = 34), "surgery" (n = 30), and "outcomes" (n = 24), demonstrated a patient-centric theme. CONCLUSIONS: This bibliometric analysis provides in-depth insights into the evolution and trends of LIF over the last two decades. The trends and themes identified demonstrate the innovative, collaborative, and patient-focused characteristics of this subfield. Future researchers can use this as a foundation for understanding the past and present state of LIF research while designing investigations.

Return to play after head injury in adolescent sports: evaluating football versus other sports.

OBJECTIVE: Increased adolescent sports participation has raised concerns about higher rates of concussions, a prevalent injury among young athletes with potential long-term effects. Discrepancies in concussion recovery and management protocols across various sports underscore a critical issue in youth athletics. This study aimed to examine the relationship between sport type and the number of games missed following a concussion to inform targeted management strategies. METHODS: Data from 7445 postinjury ImPACT tests for athletes aged 12-22 years, collected from 2009 to 2019, were analyzed across different sports: baseball, basketball, cheerleading, football, ice hockey, lacrosse, soccer, softball, swimming, track and field, volleyball, and wrestling. The number of days and normalized missed games (NMG), a metric accounting for the different number of games in a season for different sports, were used to evaluate the effect of concussions across different sports. ANOVA, t-tests, and linear regression analyses were performed to model the effect of sport type on games missed in a season while controlling for sex, age, concussion history, diagnosed learning disability (DLD), and attention-deficit/hyperactivity disorder (ADHD). RESULTS: Multivariable linear regression analysis demonstrated that football participation significantly increased NMG (ß 1.681, 95% CI 0.807-2.554; p < 0.001) and days missed (ß 1.637, 95% CI 1.044-2.231; p < 0.001) after head injury. Concussion diagnoses were also found to significantly increase NMG (ß 2.344, 95% CI 1.629-3.059; p < 0.001) and days missed (ß 1.560, 95% CI 1.074-2.045; p < 0.001), as well as history of prior concussion (NMG: ß 7.791, 95% CI 7.368-8.215; p < 0.001; days missed: ß 5.232, 95% CI 4.945-5.520; p < 0.001). In contrast, factors such as age, sex, DLD, ADHD, and concussions causing loss of consciousness did not significantly affect NMG or days missed. ANOVA with Tukey Honest Significant Difference indicated that compared with football, ice hockey (mean difference [MD] 5.4 days, p = 0.011) and track and field (MD 4.1 days, p = 0.006) were associated with significantly more days being missed after head injury. Conversely, basketball (MD -3.0, p < 0.001) and volleyball (MD -2.6, p = 0.005) were associated with fewer missed games. CONCLUSIONS: Adolescents playing football missed fewer days and games after concussion than other contact and noncontact sports, including ice hockey and track and field, raising questions about variations in return-to-play protocols and cultural attitudes within sports. Further research is needed to determine the factors affecting games missed across sport types in adolescent athletics and return-to-play protocols.

Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion.

BACKGROUND: The frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400% since 2011, underscoring the need to preoperatively anticipate adverse postoperative outcomes given the procedure's expanding use. Our study aims to accomplish two goals: firstly, to develop a suite of explainable machine learning (ML) models capable of predicting adverse postoperative outcomes following ACDF surgery, and secondly, to embed these models in a user-friendly web application, demonstrating their potential utility. METHODS: We utilized data from the National Surgical Quality Improvement Program database to identify patients who underwent ACDF surgery. The outcomes of interest were four short-term postoperative adverse outcomes: prolonged length of stay (LOS), non-home discharges, 30-day readmissions, and major complications. We utilized five ML algorithms - TabPFN, TabNET, XGBoost, LightGBM, and Random Forest - coupled with the Optuna optimization library for hyperparameter tuning. To bolster the interpretability of our models, we employed SHapley Additive exPlanations (SHAP) for evaluating predictor variables' relative importance and used partial dependence plots to illustrate the impact of individual variables on the predictions generated by our top-performing models. We visualized model performance using receiver operating characteristic (ROC) curves and precision-recall curves (PRC). Quantitative metrics calculated were the area under the ROC curve (AUROC), balanced accuracy, weighted area under the PRC (AUPRC), weighted precision, and weighted recall. Models with the highest AUROC values were selected for inclusion in a web application. RESULTS: The analysis included 57,760 patients for prolonged LOS [11.1% with prolonged LOS], 57,780 for non-home discharges [3.3% non-home discharges], 57,790 for 30-day readmissions [2.9% readmitted], and 57,800 for major complications [1.4% with major complications]. The top-performing models, which were the ones built with the Random Forest algorithm, yielded mean AUROCs of 0.776, 0.846, 0.775, and 0.747 for predicting prolonged LOS, non-home discharges, readmissions, and complications, respectively. CONCLUSIONS: Our study employs advanced ML methodologies to enhance the prediction of adverse postoperative outcomes following ACDF. We designed an accessible web application to integrate these models into clinical practice. Our findings affirm that ML tools serve as vital supplements in risk stratification, facilitating the prediction of diverse outcomes and enhancing patient counseling for ACDF.

Recent Developments in Magnetic Hyperthermia Therapy (MHT) and Magnetic Particle Imaging (MPI) in the Brain Tumor Field: A Scoping Review and Meta-Analysis.

Magnetic hyperthermia therapy (MHT) is a promising treatment modality for brain tumors using magnetic nanoparticles (MNPs) locally delivered to the tumor and activated with an external alternating magnetic field (AMF) to generate antitumor effects through localized heating. Magnetic particle imaging (MPI) is an emerging technology offering strong signal-to-noise for nanoparticle localization. A scoping review was performed by systematically querying Pubmed, Scopus, and Embase. In total, 251 articles were returned, 12 included. Articles were analyzed for nanoparticle type used, MHT parameters, and MPI applications. Preliminary results show that MHT is an exciting treatment modality with unique advantages over current heat-based therapies for brain cancer. Effective application relies on the further development of unique magnetic nanoparticle constructs and imaging modalities, such as MPI, that can enable real-time MNP imaging for improved therapeutic outcomes.

Effects of hours of sleep on ImPACT concussion testing: comparing baseline with postinjury scores.

OBJECTIVE: The influence of sleep on baseline and postconcussion neurocognitive performance prior to Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) is poorly understood. Since ImPACT is widely used in youth sport to assess neurocognitive performance before and after head injury, it is important to delineate factors that affect testing performance. While some have reported correlations between fewer hours of sleep and lower scores on baseline tests, others have not observed any such associations. Therefore, the authors sought to compare the relationship between sleep and neurocognitive performance on ImPACT at both baseline and postinjury. METHODS: The authors queried a database of 25,815 ImPACT tests taken from 2009 to 2019 by athletes aged 12-22 years. There were 11,564 baseline concussion tests and 7446 postinjury concussion ImPACT tests used in the analysis. Linear regression was used to model the effect of sleep on baseline and postconcussion ImPACT scores adjusting for sex, age, learning disability, attention-deficit/hyperactivity disorder, number of prior concussions, number of games missed, and strenuous exercise before testing. RESULTS: Mean composite scores expectedly were all significantly lower in the post-head injury group compared with the baseline group. In the multivariable analysis, at baseline, hours of sleep significantly affected symptom scores (ß = -1.050, 95% CI -1.187 to -0.9138; p < 0.0001). In the postinjury multivariable analysis, verbal memory (ß = 0.4595, 95% CI 0.2080-0.7110; p = 0.0003), visual memory (ß = 0.3111, 95% CI 0.04463-0.5777; p = 0.0221), impulse control (ß = -0.2321, 95% CI -0.3581 to -0.1062; p = 0.0003), and symptom scores (ß = -0.9168, 95% CI -1.259 to -0.5750; p < 0.0001) were all affected by hours of sleep. CONCLUSIONS: Hours of sleep did not alter neurocognitive metrics at baseline but did have an impact on post-head injury metrics. These findings suggest that individuals may be able to compensate for lack of sleep at baseline but not immediately after concussion. Concussions may reduce cognitive reserve or detract from the brain's resources, making sleep even more important for proper neurocognitive functioning postconcussion. Future work will analyze the effects of sleep on postconcussion test performance.

An Interpretable Machine Learning Approach to Predict Survival Outcomes in Spinal and Sacropelvic Chordomas.

STUDY DESIGN: Retrospective, population-based cohort study. OBJECTIVE: This study aimed to develop machine learning (ML) models to predict five-year and 10-year mortality in spinal and sacropelvic chordoma patients and integrate them into a web application for enhanced prognostication. SUMMARY OF BACKGROUND DATA: Past research has uncovered factors influencing survival in spinal chordoma patients. While identifying individual predictors is important, personalized survival predictions are equally vital. Though prior efforts have resulted in nomograms aiming to serve this purpose, they cannot capture complex interactions within data and rely on statistical assumptions that may not fit real-world data. METHODS: Adult spinal and sacropelvic chordoma patients were identified from the National Cancer Database. Sociodemographic, clinicopathologic, diagnostic, and treatment-related variables were utilized as predictive features. Five supervised ML algorithms (TabPFN, CatBoost, XGBoost, LightGBM, and Random Forest) were implemented to predict mortality at five and 10 years postdiagnosis. Model performance was primarily evaluated using the area under the receiver operating characteristic (AUROC). SHapley Additive exPlanations (SHAP) values and partial dependence plots provided feature importance and interpretability. The top models were integrated into a web application. RESULTS: From the NCDB, 1206 adult patients diagnosed with histologically confirmed spinal and sacropelvic chordomas were retrieved for the five-year mortality outcome [423 (35.1%) with five-year mortality] and 801 patients for the 10-year mortality outcome [588 (73.4%) with 10-year mortality]. Top-performing models for both of the outcomes were the models created with the CatBoost algorithm. The CatBoost model for five-year mortality predictions displayed a mean AUROC of 0.801, and the CatBoost model predicting 10-year mortality yielded a mean AUROC of 0.814. CONCLUSIONS: This study developed ML models that can accurately predict five-year to 10-year survival probabilities in spinal chordoma patients. Integrating these interpretable, personalized prognostic models into a web application provides quantitative survival estimates for a given patient. The local interpretability enables transparency into how predictions are influenced. Further external validation is warranted to support generalizability and clinical utility.

The Top 100 Cited Articles on Cervical Disc Arthroplasty: A Bibliometric Analysis.

STUDY DESIGN: Bibliometric analysis. OBJECTIVE: Cervical disc arthroplasty (CDA) has emerged as an effective surgical intervention for degenerative cervical disc disease with potential advantages over traditional cervical fusion. This bibliometric analysis aimed to assess the current state of research on CDA by analyzing the relevant literature using bibliometric indicators. SUMMARY OF BACKGROUND DATA: Web of Science Core Collection. METHODS: A comprehensive search was conducted using the Web of Science database, for articles related to CDA published in the last 19 years. The top 100 articles were reviewed using bibliometric analysis. Publication trends, citation patterns, authorship, and collaboration networks were analyzed using VOSviewer and the Bibliometrix package in RStudio. RESULTS: The results revealed a significant increase in the number of publications related to CDA over the past 2 decades, with most of the articles being published in orthopedic and spine surgery journals. The most frequently cited articles were related to clinical outcomes, complications, and biomechanical studies of CDA. Co-authorship analysis identified influential authors and collaborative networks, highlighting the multidisciplinary nature of CDA research involving neurosurgeons, orthopedic surgeons, and engineers. Overall, this bibliometric analysis provides a comprehensive overview of the current state of research on CDA, highlighting the key research themes, influential authors, and collaborative networks in the field. CONCLUSION: These findings can serve as a guide for researchers, clinicians, and policymakers to identify knowledge gaps, research trends, and future directions in the field of CDA.

Development and internal validation of machine learning models for personalized survival predictions in spinal cord glioma patients.

BACKGROUND CONTEXT: Numerous factors have been associated with the survival outcomes in patients with spinal cord gliomas (SCG). Recognizing these specific determinants is crucial, yet it is also vital to establish a reliable and precise prognostic model for estimating individual survival outcomes. OBJECTIVE: The objectives of this study are twofold: first, to create an array of interpretable machine learning (ML) models developed for predicting survival outcomes among SCG patients; and second, to integrate these models into an easily navigable online calculator to showcase their prospective clinical applicability. STUDY DESIGN: This was a retrospective, population-based cohort study aiming to predict the outcomes of interest, which were binary categorical variables, in SCG patients with ML models. PATIENT SAMPLE: The National Cancer Database (NCDB) was utilized to identify adults aged 18 years or older who were diagnosed with histologically confirmed SCGs between 2010 and 2019. OUTCOME MEASURES: The outcomes of interest were survival outcomes at three specific time points postdiagnosis: 1, 3, and 5 years. These outcomes were formed by combining the "Vital Status" and "Last Contact or Death (Months from Diagnosis)" variables. Model performance was evaluated visually and numerically. The visual evaluation utilized receiver operating characteristic (ROC) curves, precision-recall curves (PRCs), and calibration curves. The numerical evaluation involved metrics such as sensitivity, specificity, accuracy, area under the PRC (AUPRC), area under the ROC curve (AUROC), and Brier Score. METHODS: We employed five ML algorithms-TabPFN, CatBoost, XGBoost, LightGBM, and Random Forest-along with the Optuna library for hyperparameter optimization. The models that yielded the highest AUROC values were chosen for integration into the online calculator. To enhance the explicability of our models, we utilized SHapley Additive exPlanations (SHAP) for assessing the relative significance of predictor variables and incorporated partial dependence plots (PDPs) to delineate the influence of singular variables on the predictions made by the top performing models. RESULTS: For the 1-year survival analysis, 4,913 patients [5.6% with 1-year mortality]; for the 3-year survival analysis, 4,027 patients (11.5% with 3-year mortality]; and for the 5-year survival analysis, 2,854 patients (20.4% with 5-year mortality) were included. The top models achieved AUROCs of 0.938 for 1-year mortality (TabPFN), 0.907 for 3-year mortality (LightGBM), and 0.902 for 5-year mortality (Random Forest). Global SHAP analyses across survival outcomes at different time points identified histology, tumor grade, age, surgery, radiotherapy, and tumor size as the most significant predictor variables for the top-performing models. CONCLUSIONS: This study demonstrates ML techniques can develop highly accurate prognostic models for SCG patients with excellent discriminatory ability. The interactive online calculator provides a tool for assessment by physicians (https://huggingface.co/spaces/MSHS-Neurosurgery-Research/NCDB-SCG). Local interpretability informs prediction influences for a given individual. External validation across diverse datasets could further substantiate potential utility and generalizability. This robust, interpretable methodology aligns with the goals of precision medicine, establishing a foundation for continued research leveraging ML's predictive power to enhance patient counseling.

Cervical Spine Stenosis Causing Diaphragmatic Paralysis: A Case Study and Narrative Review of Clinical Presentations and Outcomes.

STUDY DESIGN: Case report and narrative review. OBJECTIVE: To explore the therapeutic role of surgical and nonsurgical treatment of diaphragmatic paralysis secondary to spinal cord and nerve root compression. SUMMARY OF BACKGROUND DATA: Phrenic nerve dysfunction due to central or neuroforaminal stenosis is a rare yet unappreciated etiology of diaphragmatic paralysis and chronic dyspnea. Surgical spine decompression, diaphragmatic pacing, and intensive physiotherapy are potential treatment options with varying degrees of evidence. METHODS: The case of a 70-year-old male with progressive dyspnea, reduced hemi-diaphragmatic excursion, and C3-C7 stenosis, who underwent a microscopic foraminotomy is discussed. Literature review (MEDLINE, PubMed, Google Scholar) identified 19 similar reports and discussed alternative treatments and outcomes. RESULTS AND CONCLUSIONS: Phrenic nerve root decompression and improvement in neuromonitoring signals were observed intraoperatively. The patient's postoperative course was uncomplicated, and after 15 months, he experienced significant symptomatic improvement and minor improvement in hemi-diaphragmatic paralysis and pulmonary function tests. All case reports of patients treated with spinal decompression showed symptomatic and/or functional improvement, while one of the 2 patients treated with physiotherapy showed improvement. More studies are needed to further describe the course and outcomes of these interventions, but early identification and spinal decompression can be an effective treatment. OCEBM LEVEL OF EVIDENCE: Level-4.

Clinical and Operative Risk Factors Associated With Prolonged Length of Stay After Endoscopic Pituitary Adenoma Resection.

BACKGROUND AND OBJECTIVES: Pituitary adenomas (PAs) are the most common intrasellar tumor. Clinically relevant adenomas have a prevalence of 1 per 1000 in the general population. Transsphenoidal surgery (TSS) is the most common surgical treatment and is the first-line management for most PAs. Most patients fare well postoperatively, but a subset of patients experience a prolonged length of stay (PLOS). In this article, we aim to identify demographic and clinical factors associated with PLOS after TSS for PA. METHODS: Patients with sellar pathologies surgically treated at a single tertiary center from March 1, 2009, to May 31, 2020, were retrospectively reviewed. All patients older than 18 years receiving nonemergent endoscopic TSS for pituitary adenoma were included. Clinical and demographic characteristics were analyzed using χ2-tests and student t-tests. For those factors with a P-value less than .01, multivariate logistic regression and negative binomial regression models were constructed to estimate the adjusted odds of PLOS across predictive factors. RESULTS: A total of 301 patients were included in the study. This cohort had an average age of 54.65 ± 15.06 years and an average body mass index of 29.47 ± 6.69. The median length of stay was 54.9 hours [25th-75th percentiles: 43.5-72.9]. Postoperative cerebrospinal fluid leak (P < .01), postoperative diabetes insipidus (DI) (P < .01), increased surgery duration (P = .01), and elevated maximal tumor dimension (P = .01) were predictive of PLOS in logistic regression. Increased surgery duration, previous pituitary radiation, intraoperative complications, and postoperative DI (all P < .01) were associated with increased rate of PLOS in negative binomial regression. CONCLUSION: Patients undergoing endoscopic TSS for PA resection demonstrate prolonged lengths of stay if they have higher tumor burden, have lengthier surgeries with intraoperative complications, or develop postoperative complications such as cerebrospinal fluid leak or DI. Careful monitoring of these factors will allow for better resource optimization, reducing costs to both the hospital and the patient.

Lumbar Vertebral Body Tethering: Single Center Outcomes and Reoperations in a Consecutive Series of 106 Patients.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: To evaluate the outcomes and reoperation rates in patients with adolescent idiopathic scoliosis (AIS) undergoing lumbar anterior vertebral body tethering (AVBT). SUMMARY OF BACKGROUND DATA: Anterior vertebral body tethering (AVBT) is a viable option in growing children. The benefit of motion preservation must be balanced by a higher reoperation rate. A paucity of reports has addressed lumbar AVBT. METHODS: A single-center retrospective study was conducted to identify all patients who underwent lumbar AVBT (lowest instrumented vertebra L3 or L4) with a minimum 2 years of follow-up. Clinical and radiographic parameters, including complications and reoperations, were also collected. Statistical analysis was performed using Student's t-test for qualitative variables. RESULTS: From a dataset of 551 patients, we identified 106 patients (89% female) who underwent a lumbar AVBT (33 lumbar only, 73 bilateral thoracic/lumbar) with mean follow-up of 4.1±1.6 years at which point 85% (90/106) had reached skeletal maturity. Preoperatively, these patients were skeletally immature (age: 12.8±1.3 y, Sanders: 3.3±0.8, R=0.6±0.9) with a lumbar coronal curve angle of 49.6°±11.2 which corrected to 19.9°±11.2 (P <0.0001) at most recent follow-up. At the latest follow-up, 76.4% (81/106) of the patients harbored a coronal curve angle of < 30°. Twenty patients (18.9%) underwent 23 reoperations, with overcorrection being the most common (10/23, 43%). Broken tethers led to reoperation in 3 instances (3/23, 13%). Six patients in the cohort needed a posterior spinal fusion (6/106, 5.4%). CONCLUSIONS: Vertebral body tethering is a viable treatment option for skeletally immature patients with idiopathic scoliosis. This report is the largest to date for lumbar AVBT, highlighting that 84% of patients harbored a curve < 35° at the latest follow-up but with an 18.9% reoperation rate. LEVEL OF EVIDENCE: 3.

The effect of age on baseline neurocognitive performance.

OBJECTIVE: Evaluate the independent effect of age on baseline neurocognitive performance. STUDY DESIGN: Baseline ImPACT scores from tests taken by 7454 athletes aged 12-22 from 2009 to 2019 were split into three age cohorts: 12-14 years (3244), 15-17 years (3732), and 18-22 years (477). Linear regression analyses were used to evaluate the effect of age on ImPACT composite scores while controlling for demographic differences, medication-use, and symptom burden. Significance values have been set at p < 0.05. RESULTS: Linear regression analyses demonstrated that increased age does not significantly affect symptom score (ß = 0.06, p = 0.54) but does improve impulse control (ß = -0.45, p < 0.0001), verbal memory (ß = 0.23, p = 0.03), visualmotor (ß = 0.77, p < 0.0001), and reaction time (ß = -0.008, p < 0.0001) scores.  However, age did not have an effect on visual memory scores (ß = -0.25, p = 0.07). CONCLUSIONS: Age was shown to be an independent modifier of impulse control, verbal memory, visual motor, and reaction time scores but not visual memory or symptom scores.  This underscores the previous literature showing developmental differences as age increases among the adolescent athlete population.  This data also indicates the need for repeat neurocognitive baseline testing every other year as baseline scoring is likely to change as athletes become older.

Bibliometric Analysis of the Top 100 Cited Articles and Author H-Indexes on the Surgical Treatment of Trigeminal Neuralgia.

INTRODUCTION: Medically refractory cases of trigeminal neuralgia often require treatment escalation. Surgical options include microvascular decompression and percutaneous ablation. This paper provides a bibliometric analysis of the most influential articles on the surgical management of trigeminal neuralgia. METHODS: The Web of Science database was queried to identify the top 100 cited articles concerning surgical treatment of trigeminal neuralgia. The search terms used included ALL=(("trigeminal neuralgia" OR "tic douloureux" OR "Fothergill's disease" OR "Trifacial neuralgia") AND ("surgical treatment" OR "surgical management" OR "surgery" OR "neurosurgery") NOT ("radiosurgery" OR "gamma knife")). The extracted variables included the first and senior author names, journal, publication year, institution, and surgical modality. RESULTS: Our bibliometric search yielded 2104 studies, with 41,502 citations overall. Within the top 100 articles, Zakrzewska had the most first author papers (n = 5), and Burchiel had the most senior author papers (n = 6). The Massachusetts General Hospital was the most represented institution (n = 5). The United States was the most represented country (51%). Microvascular decompression was the most studied surgical strategy (51%), followed by percutaneous radiofrequency coagulation (9%), balloon/nerve compression (7%), and glycerol rhizolysis (7%). Some studies assessed multiple treatment modalities (22%). The types of studies included retrospective articles (58%), prospective articles (26%), reviews (10%), anatomic studies (2%), and basic science (1%). Neurosurgery (35%) and the Journal of Neurosurgery (33%) were the most represented journals. CONCLUSIONS: The current literature consists of retrospective reviews and mostly describes microvascular decompression for trigeminal neuralgia. Future studies should include further characterization of other surgical modalities such as percutaneous radiofrequency thermocoagulation, glycerol injection, and balloon compression.

Exoscopic resection of a parasagittal atypical meningioma.

This video demonstrates use of the Synaptive 3D exoscope to enhance complex meningioma resection. The patient was a 58-year-old female who presented with new-onset seizures. Workup revealed a parasagittal meningioma over the bilateral cortices. She was started on 750 mg of Keppra twice daily and tapered dexamethasone and discharged. MR venography demonstrated segmental occlusion of the superior sagittal sinus. She then underwent a diagnostic angiogram and tumor Onyx embolization of the bilateral middle meningeal artery feeders. She then underwent a craniotomy for meningioma resection using 3D exoscope guidance. She awoke with a stable examination in the intensive care unit and worked with physical therapy on postoperative day 1. The video can be found here: https://stream.cadmore.media/r10.3171/2023.10.FOCVID23164.

5-Aminolevulinic Acid Fluorescence-Guided Surgery in Head and Neck Squamous Cell Carcinoma.

OBJECTIVES: To determine the utility of 5-aminolevulinic acid (5-ALA) fluorescence for resection of head and neck carcinoma. METHODS: In this prospective pilot trial, 5-ALA was administered as an oral suspension 3-5 h prior to induction of anesthesia for resection of head and neck squamous cell carcinoma (HNSCC). Following resection, 405 nm blue light was applied, and fluorescence of the tumor as well as the surgical bed was recorded. Specimen fluorescence intensity was graded categorically as none (score = 0), mild (1), moderate (2), or robust (3) by the operating surgeon intraoperatively and corroborated with final pathologic diagnosis. RESULTS: Seven patients underwent resection with 5-ALA. Five (83%) were male with an age range of 33-82 years (mean = 60). Sites included nasal cavity (n = 3), oral cavity (n = 3), and the larynx (n = 1). All specimens demonstrated robust fluorescence when 5-ALA was administered 3-5 h preoperatively. 5-ALA fluorescence predicted the presence of perineural invasion, a positive margin, and metastatic lymphadenopathy. Two patients had acute photosensitivity reactions, and one patient had a temporary elevation of hepatic enzymes. CONCLUSIONS: 5-ALA induces robust intraoperative fluorescence of HNSCC, capable of demonstrating a positive margin, perineural invasion, and metastatic nodal disease. Although no conclusions are there about the safety of this drug in the head and neck cancer population, our study parallels the extensive safety data in the neurosurgical literature. Future applications may include intraoperative assessment of margin status, diagnostic accuracy, and impacts on survival. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:741-748, 2024.

From Text to Insight: A Natural Language Processing-Based Analysis of Topics and Trends in Neurosurgery.

BACKGROUND AND OBJECTIVES: Neurosurgical research is a rapidly evolving field, with new research topics emerging continually. To provide a clearer understanding of the evolving research landscape, our study aimed to identify and analyze the prevalent research topics and trends in Neurosurgery. METHODS: We used BERTopic, an advanced natural language processing-based topic modeling approach, to analyze papers published in the journal Neurosurgery . Using this method, topics were identified based on unique sets of keywords that encapsulated the core themes of each article. Linear regression models were then trained on the topic probabilities to identify trends over time, allowing us to identify "hot" (growing in prominence) and "cold" (decreasing in prominence) topics. We also performed a focused analysis of the trends in the current decade. RESULTS: Our analysis led to the categorization of 12 438 documents into 49 distinct topics. The topics covered a wide range of themes, with the most commonly identified topics being "Spinal Neurosurgery" and "Treatment of Cerebral Ischemia." The hottest topics of the current decade were "Peripheral Nerve Surgery," "Unruptured Aneurysms," and "Endovascular Treatments" while the cold topics were "Chiari Malformations," "Thromboembolism Prophylaxis," and "Infections." CONCLUSION: Our study underscores the dynamic nature of neurosurgical research and the evolving focus of the field. The insights derived from the analysis can guide future research directions, inform policy decisions, and identify emerging areas of interest. The use of natural language processing in synthesizing and analyzing large volumes of academic literature demonstrates the potential of advanced analytical techniques in understanding the research landscape, paving the way for similar analyses across other medical disciplines.

The role of minimally invasive surgery within a multidisciplinary approach for patients with metastatic spine disease over a decade: A systematic review.

BACKGROUND: Metastatic spine disease (MSD) occurs commonly in cancer patients causing pain, spinal instability, devastating neurological compromise, and decreased quality of life. Oncological patients are often medically complex and frail, precluding them form invasive procedures. To address this issue, minimally invasive spinal surgery (MISS) techniques are desirable. The aim of this study is to review published peer-reviewed literature and ongoing clinical trials to provide current state of the art. METHODS: A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, assessing MISS in MSD patients for the period 2013-2023. Innovations under development were assessed by querying and reviewing data from currently enrolling U.S. registered clinical trials. RESULTS: From 3,696 articles, 50 studies on 3,196 patients focused on spinal oncology MISS. The most commonly reported techniques were vertebral augmentation (VA), percutaneous spinal instrumentation, and radiofrequency ablation (RFA). Surgical instrumentation/stabilization techniques were reported in 10/50 articles for a total of 410 patients. The majority of studies focused on pain as a primary outcome measure, with 28/50 studies reporting a significant improvement in pain following intervention. In the United States, 13 therapeutic trials are currently recruiting MSD patients. Their main focus includes radiosurgery, VA and/or RFA, and laser interstitial thermal therapy. CONCLUSIONS: Due to their medical complexity and increased fragility, MSD patients may benefit from minimally invasive approaches. These strategies are effective at mitigating pain and preventing neurological deterioration, while providing other advantages including ease to start/resume systemic/radiotherapy treatment(s).

Clinical Considerations and Outcomes for Spine Surgery Patients with a History of Transplant: A Systematic Scoping Review.

OBJECTIVE: The objective of this study was to investigate the perioperative management and outcomes of patients with a prior history of successful transplantation undergoing spine surgery. METHODS: We searched Medline, Embase, and Cochrane Central Register of Controlled Trials for matching reports in July 2021. We included case reports, cohort studies, and retrospective analyses, including terms for various transplant types and an exhaustive list of key words for various forms of spine surgery. RESULTS: We included 45 studies consisting of 34 case reports (published 1982-2021), 3 cohort analyses (published 2005-2006), and 8 retrospective analyses (published 2006-2020). The total number of patients included in the case reports, cohort studies, and retrospective analysis was 35, 48, and 9695, respectively. The mean 1-year mortality rate from retrospective analyses was 4.6% ± 1.93%, while the prevalence of perioperative complications was 24%. Cohort studies demonstrated an 8.5% ± 12.03% 30-day readmission rate. The most common procedure performed was laminectomy (38.9%) among the case reports. Mortality after spine surgery was noted for 4 of 35 case report patients (11.4%). CONCLUSIONS: This is the first systematic scoping review examining the population of transplant patients with subsequent unrelated spine surgery. There is significant heterogeneity in the outcomes of post-transplant spine surgery patients. Given the inherent complexity of managing this group and elevated mortality and complications compared to the general spine surgery population, further investigation into their clinical care is warranted.