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Hydrocephalus is a common complication of aneurysmal subarachnoid hemorrhage (aSAH) that often requires acute placement of an external ventricular drain (EVD). The current systems available for determining which patients will require long-term cerebrospinal fluid diversion remain subjective. We investigated the ventricular volume change (ΔVV) after EVD clamping as an objective predictor of shunt dependence in patients with aSAH.We performed a retrospective medical record review and image analysis of patients treated for aSAH at a single academic institution who had required EVD placement for acute hydrocephalus and had undergone 1 EVD weaning trial. Head computed tomography (CT) scans obtained before and after EVD clamping were analyzed using a custom semiautomated MATLAB program (MathWorks, Natick, Massachusetts, USA), which segments each CT scan into 5 tissue types using k-means clustering. Differences in the pre- and postclamp ventricular volumes were calculated.A total of 34 patients with an indwelling shunt met the inclusion criteria and were sex- and age-matched to 34 controls without a shunt. The mean ΔVV was 19.8 mL in the shunt patients and 3.8 mL in the nonshunt patients (P 0.0001). The area under the receiver operating characteristic curve was 0.84. The optimal ΔVV threshold was 11.4 mL, with a sensitivity of 76.5% and specificity of 88.2% for predicting shunt dependence. The mean ΔVV was significantly greater for the patients readmitted for shunt placement compared with the patients not requiring cerebrospinal fluid diversion (18.69 mL vs. 3.84 mL; P = 0.005). Finally, 70% of the patients with delayed shunt dependence had ΔVV greater than the identified threshold.The ΔVV volume between head CT scans taken before and after EVD clamping was predictive of early and delayed shunt dependence.

OBJECTIVE Decompression with instrumented fusion is commonly employed for spinal metastatic disease. Arthrodesis is typically sought despite limited knowledge of fusion outcomes, high procedural morbidity, and poor prognosis. This study aimed to describe survival, fusion, and hardware failure after decompression and fusion for spinal metastatic disease. METHODS The authors retrospectively examined a prospectively collected, single-institution database of adult patients undergoing decompression and instrumented fusion for spinal metastases. Patients were followed clinically until death or loss to follow-up. Fusion was assessed using CT when performed for oncological surveillance at 6-month intervals through 24 months postoperatively. Estimated cumulative incidences for fusion and hardware failure accounted for the competing risk of death. Potential risk factors were analyzed with univariate Fine and Gray proportional subdistribution hazard models. RESULTS One hundred sixty-four patients were identified. The mean age ± SD was 62.2 ± 10.8 years, 61.6% of patients were male, 98.8% received allograft and/or autograft, and 89.6% received postoperative radiotherapy. The Kaplan-Meier estimate of median survival was 11.0 months (IQR 3.5–37.8 months). The estimated cumulative incidences of any fusion and of complete fusion were 28.8% (95% CI 21.3%–36.7%) and 8.2% (95% CI 4.1%–13.9%). Of patients surviving 6 and 12 months, complete fusion was observed in 12.5% and 16.1%, respectively. The estimated cumulative incidence of hardware failure was 4.2% (95% CI 1.5–9.3%). Increasing age predicted hardware failure (HR 1.2, p = 0.003). CONCLUSIONS Low rates of complete fusion and hardware failure were observed due to the high competing risk of death. Further prospective, case-control studies incorporating nonfusion instrumentation techniques may be warranted.

OBJECTIVENormal percentile growth charts for head circumference, length, and weight are well-established tools for clinicians to detect abnormal growth patterns. Currently, no standard exists for evaluating normal size or growth of cerebral ventricular volume. The current standard practice relies on clinical experience for a subjective assessment of cerebral ventricular size to determine whether a patient is outside the normal volume range. An improved definition of normal ventricular volumes would facilitate a more data-driven diagnostic process. The authors sought to develop a growth curve of cerebral ventricular volumes using a large number of normal pediatric brain MR images.METHODSThe authors performed a retrospective analysis of patients aged 0 to 18 years, who were evaluated at their institution between 2009 and 2016 with brain MRI performed for headaches, convulsions, or head injury. Patients were excluded for diagnoses of hydrocephalus, congenital brain malformations, intracranial hemorrhage, meningitis, or intracranial mass lesions established at any time during a 3- to 10-year follow-up. The volume of the cerebral ventricles for each T2-weighted MRI sequence was calculated with a custom semiautomated segmentation program written in MATLAB. Normal percentile curves were calculated using the lambda-mu-sigma smoothing method.RESULTSVentricular volume was calculated for 687 normal brain MR images obtained in 617 different patients. A chart with standardized growth curves was developed from this set of normal ventricular volumes representing the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. The charted data were binned by age at scan date by 3-month intervals for ages 0–1 year, 6-month intervals for ages 1–3 years, and 12-month intervals for ages 3–18 years. Additional percentile values were calculated for boys only and girls only.CONCLUSIONSThe authors developed centile estimation growth charts of normal 3D ventricular volumes measured on brain MRI for pediatric patients. These charts may serve as a quantitative clinical reference to help discern normal variance from pathologic ventriculomegaly.

Given the serious nature of many neurosurgical pathologies, it is common for hospitalized patients to elect comfort care (CC) over aggressive treatment. Few studies have evaluated the incidence and risk factors of CC trends in patients admitted for neurosurgical emergencies. To analyze all neurosurgical patients admitted to a tertiary care academic referral center via the emergency department (ED) to determine incidence and characteristics of those who initiated CC measures during their initial hospital admission. We performed a prospective, cohort analysis of all consecutive adult patients admitted to the neurosurgical service via the ED between October 2018 and May 2019. The primary outcome was the initiation of CC measures during the patient’s hospital admission. CC was defined as cessation of life-sustaining measures and a shift in focus to maintaining the comfort and dignity of the patient. Of the 428 patients admitted during the 7-month period, 29 (6.8%) initiated CC measures within 4.0 ± 4.0 days of admission. Patients who entered CC were significantly more likely to have a medical history of cerebrovascular disease (58.6% vs. 33.3%, p = 0.006), dementia (17.2% vs. 1.5%, p = 0.0004), or cancer with metastatic disease (24.1% vs. 7.0%, p = 0.001). Patients with a presenting pathology associated with cerebrovascular disease were significantly more likely to initiate CC (62.1% vs. 35.3, p = 0.04). Patients who underwent emergent surgery were significantly more likely to enter CC compared with those who had elective surgery (80.0% vs. 42.7%, p = 0.02). Only 10 of the 29 (34.5%) patients who initiated CC underwent a neurosurgical operation (p = 0.002). Twenty of the 29 (69.0%) patients died within 0.8 ± 0.8 days after the initiation of CC measures. CC measures were initiated in 6.8% of patients admitted to the neurosurgical service via the ED, with the majority of patients entering CC before an operation and presenting with a cerebrovascular pathology.

The after-hours effect on postoperative complications has been poorly studied in the neurosurgical literature. A recent retrospective analysis showed that patients with a surgical start time (SST) between 09:01 pm and 07:00 am had a greater risk of complications. This study used a prospective registry to examine the relationship between SST and postoperative complications in a large neurosurgical population.We performed a prospective longitudinal cohort analysis of all consecutive adult patients admitted to our neurosurgery service between October 1, 2018 and May 1, 2019. Complications were prospectively recorded and classified as surgical or medical. Univariate and multivariate logistic regressions were used to analyze these data.Eighty-five surgical complications (6.6%) and 110 medical complications (8.6%) resulted from 1285 operations on 1145 patients. Later SST was predictive of complications in the emergent population (odds ratio [OR], 2.28; 95% confidence interval [CI], 1.01-5.15; P = 0.048) but not in the elective population. Extubation in the neurosurgical intensive care unit (NICU) versus the operating room strongly predicted medical complications (OR, 6.91; 95% CI, 3.33-14.34; P0.0001). Patients with a later SST were significantly more likely to be extubated in the NICU (P0.0001).Patients undergoing emergent operations with a later SST were significantly more likely to have a postoperative complication. Patients who were extubated in the NICU versus the operating room were significantly more likely to have a medical complication. Patients were more likely to be extubated in the NICU if they had a later SST; therefore, SST may indirectly be associated with an increase in medical complications.

Background Detection of glioma recurrence remains a challenge in modern neuro-oncology. Noninvasive radiographic imaging is unable to definitively differentiate true recurrence versus pseudoprogression. Even in biopsied tissue, it can be challenging to differentiate recurrent tumor and treatment effect. We hypothesized that intraoperative stimulated Raman histology (SRH) and deep neural networks can be used to improve the intraoperative detection of glioma recurrence. Methods We used fiber laser–based SRH, a label-free, nonconsumptive, high-resolution microscopy method ( Results Using patch-level CNN predictions, the inference algorithm returns a single Bernoulli distribution for the probability of tumor recurrence for each surgical specimen or patient. The external SRH validation dataset consisted of 48 patients (recurrent, 30; pseudoprogression, 18), and we achieved a diagnostic accuracy of 95.8%. Conclusion SRH with CNN-based diagnosis can be used to improve the intraoperative detection of glioma recurrence in near-real time. Our results provide insight into how optical imaging and computer vision can be combined to augment conventional diagnostic methods and improve the quality of specimen sampling at glioma recurrence.

Objective The HOSPITAL score (HS) and LACE index (LI) are 2 validated methods for quantifying the risk of 30-day unplanned readmission after discharge. However, neither score has been validated in the neurosurgical population. This study evaluated the HS and LI in the neurosurgical population as effective predictors for 30-day unplanned readmission. Methods We performed a prospective, cohort analysis of all consecutive adult patients admitted to the neurosurgical service between October 1, 2018 and May 1, 2019. Patient medical records were used to calculate HS and LI. HS defined groups as low risk (0–4), intermediate (5–6), and high (7–12); LI defined risk as low (1–4), moderate (5–9), and high (10–19). Data analysis used univariate and multivariate logistic regressions. Results The 1242 patients included 626 women (50.4%). The average age was 57.9 years, and most patients (86.5%) underwent surgery during their admission. In multivariate logistic regression, intermediate-risk HS was not predictive of 30-day readmission (odds ratio [OR], 1.04; 95% confidence interval [CI], 0.57–1.88; P = 0.53), whereas high-risk HS did predict readmission (OR, 2.87; 95% CI, 1.49–5.54; P = 0.002). Likewise, moderate-risk LI was not predictive of 30-day unplanned readmission or mortality (OR, 1.59; 95% CI, 0.88–2.85; P = 0.12); however, high-risk LI did predict unplanned readmission or mortality (OR, 2.58; 95% CI, 1.16–5.73; P = 0.02). Both HS and LI showed poor to moderate discrimination (C = 0.62 and 0.60, respectively). Conclusions A high-risk HS and high-risk LI were predictive of 30-day unplanned readmission. Although neither score is ideal for predicting moderate risk for 30-day unplanned readmission in neurosurgical patients, both have some predictiveness that may be clinically valuable.

Background: Prostate cancer (PCa) is characterized by significant heterogeneity in its molecular, genomic, and immunologic characteristics. Methods: Whole transcriptome RNAseq data from The Cancer Genome Atlas of prostate adenocarcinomas (n = 492) was utilized. The immune microenvironment was characterized using the CIBERSORTX tool to identify immune cell type composition. Unsupervised hierarchical clustering was performed based on immune cell type content. Analyses of progression-free survival (PFS), distant metastases, and overall survival (OS) were performed using Kaplan&ndash, Meier estimates and Cox regression multivariable analyses. Results: Four immune clusters were identified, largely defined by plasma cell, CD4+ Memory Resting T Cells (CD4 MR), and M0 and M2 macrophage content (CD4 MRHighPlasma CellHighM0LowM2Mid, CD4 MRLowPlasma CellHighM0LowM2Low, CD4 MRHighPlasma CellLowM0HighM2Low, and CD4 MRHighPlasma CellLowM0LowM2High). The two macrophage-enriched/plasma cell non-enriched clusters (3 and 4) demonstrated worse PFS (HR 2.24, 95% CI 1.46&ndash, 3.45, p = 0.0002) than the clusters 1 and 2. No metastatic events occurred in the plasma cell enriched, non-macrophage-enriched clusters. Comparing clusters 3 vs. 4, in patients treated by surgery alone, cluster 3 had zero progression events (p &lt, 0.0001). However, cluster 3 patients had worse outcomes after post-operative radiotherapy (p = 0.018). Conclusion: Distinct tumor immune clusters with a macrophage-enriched, plasma cell non-enriched phenotype and reduced plasma cell enrichment independently characterize an aggressive phenotype in localized prostate cancer that may differentially respond to treatment.

The discovery of a new mass involving the brain or spine typically prompts referral to a neurosurgeon to consider biopsy or surgical resection. Intraoperative decision-making depends significantly on the histologic diagnosis, which is often established when a small specimen is sent for immediate interpretation by a neuropathologist. Access to neuropathologists may be limited in resource-poor settings, which has prompted several groups to develop machine learning algorithms for automated interpretation. Most attempts have focused on fixed histopathology specimens, which do not apply in the intraoperative setting. The greatest potential for clinical impact probably lies in the automated diagnosis of intraoperative specimens. Successful future studies may use machine learning to automatically classify whole-slide intraoperative specimens among a wide array of potential diagnoses.

OBJECTIVEHydrocephalus and seizures greatly impact outcomes of patients with aneurysmal subarachnoid hemorrhage (aSAH); however, reliable tools to predict these outcomes are lacking. The authors used a volumetric quantitative analysis tool to evaluate the association of total aSAH volume with the outcomes of shunt-dependent hydrocephalus and seizures.METHODSTotal hemorrhage volume following aneurysm rupture was retrospectively analyzed on presentation CT imaging using a custom semiautomated computer program developed in MATLAB that employs intensity-based k-means clustering to automatically separate blood voxels from other tissues. Volume data were added to a prospectively maintained aSAH database. The association of hemorrhage volume with shunted hydrocephalus and seizures was evaluated through logistic regression analysis and the diagnostic accuracy through analysis of the area under the receiver operating characteristic curve (AUC).RESULTSThe study population comprised 288 consecutive patients with aSAH. The mean total hemorrhage volume was 74.9 ml. Thirty-eight patients (13.2%) developed seizures. The mean hemorrhage volume in patients who developed seizures was significantly higher than that in patients with no seizures (mean difference 17.3 ml, p = 0.01). In multivariate analysis, larger hemorrhage volume on initial CT scan and hemorrhage volume > 50 ml (OR 2.81, p = 0.047, 95% CI 1.03–7.80) were predictive of seizures. Forty-eight patients (17%) developed shunt-dependent hydrocephalus. The mean hemorrhage volume in patients who developed shunt-dependent hydrocephalus was significantly higher than that in patients who did not (mean difference 17.2 ml, p = 0.006). Larger hemorrhage volume and hemorrhage volume > 50 ml (OR 2.45, p = 0.03, 95% CI 1.08–5.54) were predictive of shunt-dependent hydrocephalus. Hemorrhage volume had adequate discrimination for the development of seizures (AUC 0.635) and shunted hydrocephalus (AUC 0.629).CONCLUSIONSHemorrhage volume is an independent predictor of seizures and shunt-dependent hydrocephalus in patients with aSAH. Further evaluation of aSAH quantitative volumetric analysis may complement existing scales used in clinical practice and assist in patient prognostication and management.

IMPORTANCE: Facial flap procedures may be difficult for surgical trainees to conceptualize and challenging for supervising surgeons to allow entrustment early in training. Simulation outside of the operating room may accelerate and enhance the surgical education experience. OBJECTIVE: To design and manufacture a 3-dimensional (3-D)–printed, multilayer, anatomically accurate facial flap model for use in surgical education. DESIGN, SETTING, AND PARTICIPANTS: In this multicenter validation study, a 3-D–printed facial flap simulator was designed from a computed tomographic (CT) scan and manufactured for low-cost, high-fidelity simulation. Expert otolaryngology–head and neck surgeon feedback was acquired through surgical rehearsal and performance of 8 local facial flap procedures on the facial flap simulator by 7 otolaryngologists fellowship trained in facial plastic surgery. MAIN OUTCOMES AND MEASURES: Likert scale surveys were made based on evaluation criteria categorized into domains of realism, experience, and applicability of the simulator. Measures of central tendency, variability, and confidence intervals were generated to evaluate the outcomes. RESULTS: Seven expert otolaryngology–head and neck surgeons completed a Likert scale evaluation survey containing quantitative analysis of 6 questions on physical attributes, 12 questions on realism, 8 questions on experience, and 4 questions on the applicability of the simulator. All expert surgeons were additionally fellowship trained in facial plastic surgery with their mean years in practice being 11.9. Overall evaluation demonstrated valuable ability of the simulator for medical education with suggestions for future directions. Importantly, the simulator was rated on a scale of 1 (no value) to 4 (great value) as 3.86 as a training tool, 3.57 as a competency evaluation tool, and 3.43 as a rehearsal tool. CONCLUSIONS AND REVELANCE: Expert experience with the local facial flap simulator was rated highly for realism, experience, performance, and usefulness. With slight refinement, the model has strong potential for broad use in training in otolaryngology–head and neck surgery and facial plastic surgery. LEVEL OF EVIDENCE: NA.

Intratumoral genomic heterogeneity in glioblastoma (GBM) is a barrier to overcoming radiation (RT) resistance. To discover genotype-independent mediators of RT resistance, we correlated RT resistance with the concentration of approximately 700 metabolites across 23 GBM cell lines. Purine metabolites, especially those containing the base guanine, were most correlated with RT resistance. Similarly, increased abundance of tumor purines was associated with decreased survival in GBM patients treated with RT. This relationship is causal. Purine supplementation protected RT-sensitive GBMs from RT and promoted the repair of RT-induced double strand DNA breaks (DSBs). In vitro and in vivo stable isotope tracing confirmed that GBM cell lines and orthotopic patient-derived xenografts primarily generated purines through the de novo synthetic pathway. RT treatment further increased de novo purine synthesis in GBM through signaling via the DNA damage response. Inhibition of de novo GTP synthesis with mycophenolic acid (MPA) sensitized multiple GBM cell lines and neurospheres to RT by slowing the repair of RT-induced DSBs. MPA-induced radiosensitization was GTP-dependent as it was rescued by nucleoside supplementation. Modulating pyrimidine metabolism affected neither RT resistance nor DSB repair, suggesting these GTP-specific effects are due to active signaling rather than its ability to act as a physical substrate for DNA repair and candidate signaling molecules have been identified. These results were recapitulated in vivo with mycophenolate mofetil (MMF), the orally bioavailable FDA-approved prodrug of MPA. MMF potentiated RT efficacy, reduced tumor guanylates and slowed the repair of RT-induced DSBs across multiple models. Because de novo purine synthesis is activated by many of the oncogenic alterations that drive GBM, its inhibition is a promising genotype-independent strategy to overcome GBM RT resistance. We have now begun a clinical trial to determine whether combining MMF and RT is safe and potentially efficacious in patients with GBM.

PURPOSE: To characterize the patterns of progression across medulloblastoma (MB) clinical risk and molecular subgroups. METHODS AND MATERIALS: 155 pediatric patients with newly diagnosed MB were treated at our institution on a prospective, multi-center phase II trial of adjuvant RT and dose-intense chemotherapy with autologous stem cell transplant. RT included CSI to 23.4 Gy (average risk, AR) or 36-39.6 Gy (high risk, HR) followed by conformal primary site RT with a 1 cm clinical target volume to a cumulative dose of 55.8 Gy. MB subgroup was determined using 450K DNA methylation. Progression was classified by anatomic site (primary site failure (PSF) +/- distant failure (DF), or isolated DF), and RT dosimetry. RESULTS: 32 patients have progressed (median follow-up 9.0 years (range, 0.3 - 14.2 y)). Anatomic failure pattern differed by clinical risk (P=0.0054) and methylation subgroup (P=0.0001). 10-year cumulative incidence (CI) of PSF was 6.2% and 5.6% in AR and HR patients, respectively (P=0.92), and did not differ across subgroups (P=0.16). 10-year CI of DF was 8.2% vs. 28.1% for AR vs. HR (P=0.0007); and 0% for WNT, 18.4% for SHH, 39.5% for G3, and 6.4% for G4 (P