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    Academic career progression in AANS/CNS Spine Section award recipients

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    OBJECTIVE: The American Association of Neurological Surgeons (AANS)/Congress of Neurological Surgeons (CNS) Joint Spine Section awards highlight outstanding abstracts submitted to the AANS/CNS Section on Disorders of the Spine and Peripheral Nerves by trainees interested in spine surgery, although the academic trajectory of awardees has not been studied. The aim of this study was to assess the academic career progression of prior recipients of the Journalistic and Academic Neurosurgical Excellence (JANE), Mayfield, and Kuntz research awards. METHODS: Prior JANE, Mayfield, and Kuntz award recipients were identified using awardee records accrued between 1984 and February 2022. Awardee sex, country of residence, specialty, subspecialty focus, and current academic appointment status (if applicable) were searched online. Awardee h-indices and number of peer-reviewed publications were assessed via Google Scholar profiles (or Scopus if unavailable) and PubMed, respectively. Receipt of federal research funding as principal investigator (PI) was determined using the websites of the National Institutes of Health, the National Science Foundation, and the Department of Defense Congressionally Directed Medical Research Programs. The abstract-to-publication rate was assessed. RESULTS: A total of 7 JANE awards, 57 Mayfield awards, and 149 Kuntz awards were identified. Of the JANE awardees, all recipients were male. Of the 4 unique JANE awardees who completed training, 2 (50.0%) held academic appointments at the time of the study. All of the JANE abstracts were published in peer-reviewed journals. The mean h-index of all JANE awardees was 28 and the mean number of publications was 126. None of the awardees have received federal research funding. Of the Mayfield awards, 98.2% were awarded to males. Of the 43 unique Mayfield awardees who completed training, 20 (46.5%) held faculty appointments at academic medical centers. All of the Mayfield abstracts since 2011 were published in peer-reviewed journals. The mean h-index of all Mayfield awardees was 26 and the mean number of publications was 82. Five Mayfield awardees received National Institutes of Health funding as PI, and 7 awardees received Department of Defense funding as PI. Of the Kuntz awards, 95.3% were awarded to males. Most awards were given to current residents and fellows (46.3%). Of the 55 unique Kuntz awardees who completed training, 31 (56.4%) held faculty appointments at academic medical centers. The abstract-to-publication rate of the total Kuntz abstracts was 70.5%. The mean h-index of all Kuntz awardees was 15 and the mean number of publications was 58. Five Kuntz awardees (3.4%) received federal research funding as PI. CONCLUSIONS: Many recipients of the JANE, Mayfield, and Kuntz Joint Spine Section awards have successfully translated award abstracts into peer-reviewed publications. Furthermore, approximately one-third of the awardees are active in academic neurosurgery, with some having secured federal research funding

    Factors influencing geographic gender disparity in neurosurgery: a nationwide geospatial clustering analysis

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    OBJECTIVE: Women neurosurgeons (WNs) continue to remain a minority in the specialty despite significant initiatives to increase their representation. One domain less explored is the regional distribution of WNs, facilitated by the hiring practices of neurosurgical departments across the US. In this analysis, the authors coupled the stated practice location of WNs with regional geospatial data to identify hot spots and cold spots of prevalence and examined regional predictors of increases and decreases in WNs over time. METHODS: The authors examined the National Provider Identifier (NPI) numbers of all neurosurgeons obtained via the National Plan and Provider Enumeration System (NPPES), identifying the percentage of WNs in each county for which data were appended with data from the US Census Bureau. Change in WN rates was identified by calculating a regression slope for all years included (2015-2022). Hot spots and cold spots of WNs were identified through Moran\u27s clustering analysis. Population and surgeon features were compared for hot spots and cold spots. RESULTS: WNs constituted 10.73% of all currently active neurosurgical NPIs, which has increased from 2015 (8.81%). Three hot spots were found-including the Middle Atlantic and Pacific divisions-that contrasted with scattered cold spots throughout the East Central regions that included Memphis as a major city. Although relatively rapidly growing, hot spots had significant gender inequality, with a median WN percentage of 11.38% and a median of 0.61 WNs added to each respective county per year. CONCLUSIONS: The authors analyzed the prevalence of WNs by using aggregated data from the NPPES and US Census Bureau. The authors also show regional hot spots of WNs and that the establishment of WNs in a region is a predictor of additional WNs entering the region. These data suggest that female neurosurgical mentorship and representation may be a major driver of acceptance and further gender diversity in a given region

    Ophthalmology Surgical Assessment of Tube Shunt Glaucoma Surgery

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    PURPOSE: To develop an internationally standardized and validated tool to assess skill in performing tube shunt surgery. DESIGN: A panel of 6 glaucoma surgeons developed a tool for assessing tube shunt surgery using a modified Dreyfus scale for skill acquisition. The tool was reviewed by a panel of 10 international content experts, and their comments were incorporated into the final rubric. PARTICIPANTS: A different panel of 8 international glaucoma specialists independently graded videos of surgical procedures performed by 6 surgeons at various levels of ophthalmic training. MAIN OUTCOME MEASURES: Inter-rater reliability for each step in the rubric was calculated. RESULTS: The tube shunt rubric contained 13 steps specific to tube shunt surgery and 7 global indices. The Cronbach α statistic, a measure of internal reliability, ranged from 0.75 to 0.97, indicating strong internal reliability for all 13 steps. CONCLUSIONS: The tube shunt assessment tool has face validity, content validity, and interobserver reliability, and can be used to assess tube shunt surgery skills. Further studies are required to determine predictive and construct validity

    Response to: Multiple Cerebral Hemorrhages in a Patient Receiving Lecanemab and Treated with t-PA for Stroke

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    Molecular Signaling in Stroke

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    We have reached the end of the Special Issue on Molecular Signaling in Stroke in [...]

    Publication Speed Across Neurosurgery Journals: A Bibliometric Analysis

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    OBJECTIVE: Many factors influence an author\u27s choice for journal submission, including journal impact factor and publication speed. These and other bibliometric data points have not been assessed in journals dedicated to neurosurgery. METHODS: Eight leading neurosurgery journals were analyzed to identify original articles and reviews, collected via randomized, stratified sampling per published issue per year from 2016 to 2020. Bibliometric data on publication speed were gathered for each article. Journal impact factor, article processing fees, and open access availability were determined using Clarivate Journal Citation Reports. Correlation analysis and a linear regression model were used to estimate the effect of impact factor and publication year on publication speed. RESULTS: Across the 8 neurosurgery journals, 1617 published articles were reviewed. The mean (standard deviation) time from submission to acceptance (SA) was 131 (101) days, from acceptance to online publication was 77 (61) days, and from submission to online publication was 207 (123) days. Higher impact factors correlated with longer publication times for all metrics. Later years of publication correlated with longer times from SA and submission to online publication. For each point increase in a journal\u27s impact factor, multivariate regression modeling estimated a 19.2-day increase in time from SA, a 19.7-day increase in time from acceptance to online publication, and a 38.9-day increase in time from submission to online publication (P \u3c 0.001 for all). CONCLUSIONS: Publication speeds vary widely among neurosurgery journals and appear to be associated with the journal impact factor. Time to publication increased over the study period

    Identification of single-dose, dual-echo based CBV threshold for fractional tumor burden mapping in recurrent glioblastoma

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    BACKGROUND: Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is widely used to distinguish high grade glioma recurrence from post treatment radiation effects (PTRE). Application of rCBV thresholds yield maps to distinguish between regional tumor burden and PTRE, a biomarker termed the fractional tumor burden (FTB). FTB is generally measured using conventional double-dose, single-echo DSC-MRI protocols; recently, a single-dose, dual-echo DSC-MRI protocol was clinically validated by direct comparison to the conventional double-dose, single-echo protocol. As the single-dose, dual-echo acquisition enables reduction in the contrast agent dose and provides greater pulse sequence parameter flexibility, there is a compelling need to establish dual-echo DSC-MRI based FTB mapping. In this study, we determine the optimum standardized rCBV threshold for the single-dose, dual-echo protocol to generate FTB maps that best match those derived from the reference standard, double-dose, single-echo protocol. METHODS: The study consisted of 23 high grade glioma patients undergoing perfusion scans to confirm suspected tumor recurrence. We sequentially acquired single dose, dual-echo and double dose, single-echo DSC-MRI data. For both protocols, we generated leakage-corrected standardized rCBV maps. Standardized rCBV (sRCBV) thresholds of 1.0 and 1.75 were used to compute single-echo FTB maps as the reference for delineating PTRE (sRCBV \u3c 1.0), tumor with moderate angiogenesis (1.0 \u3c sRCBV \u3c 1.75), and tumor with high angiogenesis (sRCBV \u3e 1.75) regions. To assess the sRCBV agreement between acquisition protocols, the concordance correlation coefficient (CCC) was computed between the mean tumor sRCBV values across the patients. A receiver operating characteristics (ROC) analysis was performed to determine the optimum dual-echo sRCBV threshold. The sensitivity, specificity, and accuracy were compared between the obtained optimized threshold (1.64) and the standard reference threshold (1.75) for the dual-echo sRCBV threshold. RESULTS: The mean tumor sRCBV values across the patients showed a strong correlation (CCC = 0.96) between the two protocols. The ROC analysis showed maximum accuracy at thresholds of 1.0 (delineate PTRE from tumor) and 1.64 (differentiate aggressive tumors). The reference threshold (1.75) and the obtained optimized threshold (1.64) yielded similar accuracy, with slight differences in sensitivity and specificity which were not statistically significant (1.75 threshold: Sensitivity = 81.94%; Specificity: 87.23%; Accuracy: 84.58% and 1.64 threshold: Sensitivity = 84.48%; Specificity: 84.97%; Accuracy: 84.73%). CONCLUSIONS: The optimal sRCBV threshold for single-dose, dual-echo protocol was found to be 1.0 and 1.64 for distinguishing tumor recurrence from PTRE; however, minimal differences were observed when using the standard threshold (1.75) as the upper threshold, suggesting that the standard threshold could be used for both protocols. While the prior study validated the agreement of the mean sRCBV values between the protocols, this study confirmed that their voxel-wise agreement is suitable for reliable FTB mapping. Dual-echo DSC-MRI acquisitions enable robust single-dose sRCBV and FTB mapping, provide pulse sequence parameter flexibility and should improve reproducibility by mitigating variations in preload dose and incubation time

    Toward Automated Detection of Silent Cerebral Infarcts in Children and Young Adults With Sickle Cell Anemia

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    BACKGROUND: Silent cerebral infarcts (SCI) in sickle cell anemia (SCA) are associated with future strokes and cognitive impairment, warranting early diagnosis and treatment. Detection of SCI, however, is limited by their small size, especially when neuroradiologists are unavailable. We hypothesized that deep learning may permit automated SCI detection in children and young adults with SCA as a tool to identify the presence and extent of SCI in clinical and research settings. METHODS: We utilized UNet-a deep learning model-for fully automated SCI segmentation. We trained and optimized UNet using brain magnetic resonance imaging from the SIT trial (Silent Infarct Transfusion). Neuroradiologists provided the ground truth for SCI diagnosis, while a vascular neurologist manually delineated SCI on fluid-attenuated inversion recovery and provided the ground truth for SCI segmentation. UNet was optimized for the highest spatial overlap between automatic and manual delineation (dice similarity coefficient). The optimized UNet was externally validated using an independent single-center prospective cohort of SCA participants. Model performance was evaluated through sensitivity and accuracy (%correct cases) for SCI diagnosis, dice similarity coefficient, intraclass correlation coefficient (metric of volumetric agreement), and Spearman correlation. RESULTS: The SIT trial (n=926; 31% with SCI; median age, 8.9 years) and external validation (n=80; 50% with SCI; age, 11.5 years) cohorts had small median lesion volumes of 0.40 and 0.25 mL, respectively. Compared with the neuroradiology diagnosis, UNet predicted SCI presence with 100% sensitivity and 74% accuracy. In magnetic resonance imaging with SCI, UNet reached a moderate spatial agreement (dice similarity coefficient, 0.48) and high volumetric agreement (intraclass correlation coefficient, 0.76; ρ=0.72; \u3c0.001) between automatic and manual segmentations. CONCLUSIONS: UNet, trained using a large pediatric SCA magnetic resonance imaging data set, sensitively detected small SCI in children and young adults with SCA. While additional training is needed, UNet may be integrated into the clinical workflow as a screening tool, aiding in SCI diagnosis

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