Meningiomas are common primary central nervous system tumors derived from the meninges, with management most frequently entailing serial monitoring or a combination of surgery and/or radiation therapy. Although often considered benign lesions, meningiomas can not only be surgically inaccessible but also exhibit aggressive growth and recurrence. In such cases, adjuvant radiation and systemic therapy may be required for tumor control. In this review, we briefly describe the current WHO grading scale for meningioma and provide demonstrative cases of treatment-resistant meningiomas. We also summarize frequently observed molecular abnormalities and their correlation with intracranial location and recurrence rate. We then describe how genetic and epigenetic features might supplement or even replace histopathologic features for improved identification of aggressive lesions. Finally, we describe the role of surgery, radiotherapy, and ongoing systemic therapy as well as precision medicine clinical trials for the treatment of recurrent meningioma.

BACKGROUND: Machine learning models can help anesthesiology clinicians assess patients and make clinical and operational decisions, but well-designed human-computer interfaces are necessary for machine learning model predictions to result in clinician actions that help patients. Therefore, the goal of this study was to apply a user-centered design framework to create a user interface for displaying machine learning model predictions of postoperative complications to anesthesiology clinicians. METHODS: Twenty-five anesthesiology clinicians (attending anesthesiologists, resident physicians, and certified registered nurse anesthetists) participated in a 3-phase study that included (phase 1) semistructured focus group interviews and a card sorting activity to characterize user workflows and needs; (phase 2) simulated patient evaluation incorporating a low-fidelity static prototype display interface followed by a semistructured interview; and (phase 3) simulated patient evaluation with concurrent think-aloud incorporating a high-fidelity prototype display interface in the electronic health record. In each phase, data analysis included open coding of session transcripts and thematic analysis. RESULTS: During the needs assessment phase (phase 1), participants voiced that (a) identifying preventable risk related to modifiable risk factors is more important than nonpreventable risk, (b) comprehensive patient evaluation follows a systematic approach that relies heavily on the electronic health record, and (c) an easy-to-use display interface should have a simple layout that uses color and graphs to minimize time and energy spent reading it. When performing simulations using the low-fidelity prototype (phase 2), participants reported that (a) the machine learning predictions helped them to evaluate patient risk, (b) additional information about how to act on the risk estimate would be useful, and (c) correctable problems related to textual content existed. When performing simulations using the high-fidelity prototype (phase 3), usability problems predominantly related to the presentation of information and functionality. Despite the usability problems, participants rated the system highly on the System Usability Scale (mean score, 82.5; standard deviation, 10.5). CONCLUSIONS: Incorporating user needs and preferences into the design of a machine learning dashboard results in a display interface that clinicians rate as highly usable. Because the system demonstrates usability, evaluation of the effects of implementation on both process and clinical outcomes is warranted. (Anesth Analg 2024;138:804-13) KEY POINTS• Question: What design considerations are necessary to create a machine learning dashboard that anesthesiology clinicians find useful and usable to help them in order to estimate patient risk for postoperative complications? • Findings: A user interface with electronic health record integration, explanations that permit identification of modifiable predictors, and a simple layout can result in high usability rating...

Vestibular schwannomas (VS) are benign tumors that lead to significant neurologic and otologic morbidity. How VS heterogeneity and the tumor microenvironment (TME) contribute to the pathogenesis of these tumors remains poorly understood. We performed scRNA-seq on 15 VS samples, with paired scATAC-seq in six samples. We identified diverse Schwann cell (SC), stromal, and immune populations in the VS TME and found that repair-like and MHC-II antigen presenting subtype SCs are associated with increased myeloid cell infiltrate, implicating a nerve injury-like process. Deconvolution analysis of RNA-expression data from 175 tumors revealed Injury-like tumors are associated with larger tumor size, and scATAC-seq identified transcription factors associated with nerve repair among SCs from Injury-like tumors. Ligand-receptor analysis and functional in vitro experiments suggested that SCs recruit monocytes. Our study indicates that Injury-like SCs may cause tumor growth via myeloid cell recruitment and identifies molecular pathways that may be targeted to prevent tumor progression.

OBJECTIVE Although individuals underrepresented in medicine (URM) make up 33% of the United States population, only 12.6% of medical school graduates identify as URM; the same percentage of URM students comprises neurosurgery residency applicants. More information is needed to understand how URM students are making specialty decisions and their perceptions of neurosurgery. The authors aimed to evaluate the differences between URM and non-URM medical students and residents in terms of the factors that contribute to specialty decision-making and perceptions of neurosurgery. METHODS A survey was administered to all medical students and resident physicians at a single Midwestern institution to assess factors influencing medical student specialty decision-making and perceptions of neurosurgery. Likert scale responses converted to numerical values on a 5-point scale (strongly agree was the high score of 5) were analyzed with the Mann-Whitney U-test. The chi-square test was performed on the binary responses to examine associations between categorical variables. Semistructured interviews were conducted and analyzed using the grounded theory method. RESULTS Of 272 respondents, 49.2% were medical students, 51.8% were residents, and 11.0% identified as URM. URM medical students considered research opportunities more than non-URM medical students in specialty decision-making (p = 0.023). When specialty decision-making factors were assessed, URM residents less strongly considered the technical skill required (p = 0.023), their perceived fit in the field (p < 0.001), and seeing people like them in the field (p = 0.010) than their non-URM counterparts when making specialty decisions. Within both medical student and resident respondent cohorts, the authors found no significant differences between URM and non-URM respondents in terms of their specialty decision-making being affected by medical school experiences such as shadowing, elective rotations, family exposure, or having a mentor in the field. URM residents were more concerned about the opportunity to work on health equity issues in neurosurgery than non-URM residents (p = 0.005). The predominant theme that emerged from interviews was the need for more intentional efforts to recruit and retain URM individuals in medicine and specifically neurosurgery. CONCLUSIONS URM students may make specialty decisions differently than non-URM students. URM students were more hesitant toward neurosurgery due to their perceived lack of opportunity for health equity work in neurosurgery. These findings further inform optimization of both new and existing initiatives to improve URM student recruitment and retention in neurosurgery.

OBJECTIVE The objective of this study was to evaluate opportunities for early clinical exposure to neurosurgery at US allopathic medical schools and to assess associations between early exposure and recruitment into neurosurgery. METHODS The authors conducted a standardized review of online curriculum documentation for all US allopathic medical schools, including descriptive review of opportunities for clinical neurosurgical training among medical students. Chi-square analysis was used to compare baseline characteristics of institutions. Logistic regression was performed to assess factors predictive of early exposure to clinical neurosurgery, defined as completion of a formal rotation at least 6 months prior to Electronic Residency Application Service submission. RESULTS Among 155 allopathic US medical schools, 143 are fully accredited by the Liaison Committee on Medical Education. Eleven schools have no affiliated hospitals with a neurosurgery practice, and 26 do not have an American Association of Neurological Surgeons (AANS) medical student chapter. Overall, 94 (60.6%) have a traditional preclinical curriculum lasting 21–25 months, 50 (32.3%) offer an intermediate preclinical period of 15–20 months, and 11 (7.1%) report a short preclinical curriculum of 12–14 months. Early formal exposure to clinical neurosurgery was offered by 113 schools (72.9%). Early clinical exposure to neurosurgery was associated with a short (100%) or intermediate (76%) preclinical curriculum, as compared with a traditional curriculum (68.1%; p = 0.066). Early exposure was significantly associated with a shorter preclinical curriculum (OR 0.784, p = 0.005). AANS medical student chapters were present at a high majority of schools with early exposure (OR 4.114, p = 0.006). Medical schools with a higher percentage of graduating medical students matching into neurosurgery were associated with a shorter preclinical curriculum length (β = −0.287, p < 0.001), were more commonly private medical schools (β = 0.338, p < 0.001), and had early clinical exposure to neurosurgery (β = 0.191, p = 0.032). CONCLUSIONS Early exposure to clinical neurosurgery is available at most US allopathic medical schools and is associated with shorter preclinical curricula and institutions with AANS medical student chapters. Medical schools with a higher proportion of medical students entering neurosurgery had a shorter preclinical curriculum length and early clinical exposure to neurosurgery. Further study is recommended to characterize the impact of early exposure on long-term pedagogical outcomes.

In the published article, there was an error in Figure 1. All locations in the figure that mention "TRAF4" are incorrect and should be changed to "TRAF7". The corrected Figure 1 and its caption (unchanged) appear below.The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Vestibular schwannomas (VS) comprise 8% of primary brain tumors, with rising prevalence due to increased detection by imaging. How intertumoral heterogeneity and differences within the tumor microenvironment (TME) contribute to the pathogenesis of VS remains poorly understood. We performed single-cell RNA sequencing (scRNA-seq) on 15 sporadic VS with paired single-nucleus assay of transposase accessible chromatin sequencing (snATAC-seq) on 7 tumors. Dimension reduction analysis revealed diverse Schwann, immune—predominantly macrophage, and stromal cell populations. Schwann cells adopted multiple unique functional states, such as repair-like, myelinating, and hypoxia-response, reflecting undescribed intratumoral heterogeneity within VS-associated Schwann cells. Remarkably, VS-associated Schwann cells were found to be phenotypically similar to Schwann cells in the setting of peripheral nerve injury, which is robustly associated with macrophage recruitment. Indeed, using our scRNA-seq atlas to perform deconvolution analysis of a broader cohort of VS, including newly sequenced (n = 22) and published bulk RNA-sequencing datasets (n = 153), we found variation in proportion of immune cells was strongly correlated with the proportion of macrophage infiltrate (R,2 = 0.86, p &lt; 0.001). Furthermore, we found that macrophage/monocyte lineage cells represent a disproportionately large number of cycling cells in the VS TME, a finding corroborated by immunohistochemistry. Clinically, tumors with high macrophage infiltrate were associated with larger tumor size (Fisher’s exact test p = 0.007). Together, these findings suggest macrophages play an important role in VS pathogenesis. We therefore sought to characterize potential cell-to-cell interactions between Schwann cells and macrophages in our scRNA-seq atlas. Ligand-receptor analysis revealed several cytokines expressed by Schwann cells with cognate receptors expressed by macrophages, including MIF, SPP1, MDK, SEMA3C and IL34, which may be responsible for recruiting macrophages. In summary, we describe previously uncharacterized cellular diversity within VS, highlight an association between macrophage infiltration and clinical phenotypes, and identify potential therapeutic targets for VS treatment.

OBJECTIVE Characterizing changes in the geographic distribution of neurosurgeons in the United States (US) may inform efforts to provide a more equitable distribution of neurosurgical care. Herein, the authors performed a comprehensive analysis of the geographic movement and distribution of the neurosurgical workforce. METHODS A list containing all board-certified neurosurgeons practicing in the US in 2019 was obtained from the American Association of Neurological Surgeons membership database. Chi-square analysis and a post hoc comparison with Bonferroni correction were performed to assess differences in demographics and geographic movement throughout neurosurgeon careers. Three multinomial logistic regression models were performed to further evaluate relationships among training location, current practice location, neurosurgeon characteristics, and academic productivity. RESULTS The study cohort included 4075 (3830 male, 245 female) neurosurgeons practicing in the US. Seven hundred eighty-one neurosurgeons practice in the Northeast, 810 in the Midwest, 1562 in the South, 906 in the West, and 16 in a US territory. States with the lowest density of neurosurgeons included Vermont and Rhode Island in the Northeast; Arkansas, Hawaii, and Wyoming in the West; North Dakota in the Midwest; and Delaware in the South. Overall, the effect size, as measured by Cramér’s V statistic, between training stage and training region is relatively modest at 0.27 (1.0 is complete dependence); this finding was reflected in the similarly modest pseudo R2 values of the multinomial logit models, which ranged from 0.197 to 0.246. Multinomial logistic regression with L1 regularization revealed significant associations between current practice region and residency region, medical school region, age, academic status, sex, or race (p < 0.05). On subanalysis of the academic neurosurgeons, the region of residency training correlated with an advanced degree type in the overall neurosurgeon cohort, with more neurosurgeons than expected holding Doctor of Medicine and Doctor of Philosophy degrees in the West (p = 0.021). CONCLUSIONS Female neurosurgeons were less likely to practice in the South, and neurosurgeons in the South and West had reduced odds of holding academic rather than private positions. The Northeast was the most likely region to contain neurosurgeons who had completed their training in the same locality, particularly among academic neurosurgeons who did their residency in the Northeast.