Intraosseous venous malformation of the frontal bone with extension into the frontal sinus and orbit.

We present a novel case of intraosseous venous malformation of the frontal bone with dehiscence of the inner table of the frontal calvarium and extension into the frontal sinus and orbit. This case report discusses the surgical management of this intraosseous lesion achieved with a multidisciplinary approach involving otolaryngology and neurosurgical teams. We also present a review of the literature of the pathophysiology of venous malformations, the imaging modalities that aid in diagnosis of these lesions and the management options.

Biomarkers of immunotherapy in glioblastoma.

Glioblastoma (GBM) is the most common primary brain cancer, comprising half of all malignant brain tumors. Patients with GBM have a poor prognosis, with a median survival of 14-15 months. Current therapies for GBM, including chemotherapy, radiotherapy, and surgical resection, remain inadequate. Novel therapies are required to extend patient survival. Although immunotherapy has shown promise in other cancers, including melanoma and non-small lung cancer, its efficacy in GBM has been limited to subsets of patients. Identifying biomarkers of immunotherapy response in GBM could help stratify patients, identify new therapeutic targets, and develop more effective treatments. This article reviews existing and emerging biomarkers of clinical response to immunotherapy in GBM. The scope of this review includes immune checkpoint inhibitor and antitumoral vaccination approaches, summarizing the variety of molecular, cellular, and computational methodologies that have been explored in the setting of anti-GBM immunotherapies.

Device use trends in neuroendovascular procedures in the United States from 2015 to 2020.

BACKGROUND: Neuroendovascular therapies involve an everchanging landscape of new technologies. Understanding the real-world timeframe of adaptation of such technologies can provide further guidance on mechanisms that could be employed to shorten the duration necessary for the widespread use of proven therapies. In this study, we aim to investigate the trends in the use of neuroendovascular technologies, utilizing the sales of neuroendovascular devices, as a proxy for procedural volume. METHODS: Utilizing a device sales data registry from the Decision Resources Group, a healthcare research and consulting company, we examined trends in the sales of devices utilized in cerebrovascular thrombectomy, cerebral aneurysm treatment, and carotid stenting from the same 407 reporting hospitals in the United States between January 1, 2015, and January 1, 2020. Device sales per year were plotted as both the total number of devices sold per year as well as the percent of total device sales when compared against at least one other device. The Cochran-Armitage test for trend was performed when comparing at least two devices to each other. Analyses were performed using RStudio Version 1.1.456 (https://rstudio.com). RESULTS: Between 2015 and 2020, there was a significant increase in the use of flow-diverting stents as well as nondiverting stents utilized for coil assistance. However, the total number of coils utilized over the years has declined. In terms of stroke therapy, between 2015 and 2020, there was a trend of increased use of both aspiration catheters as well as stent retrievers, which plateaued in 2020. The number of stents used for carotid procedures has also been gradually increasing over time. CONCLUSION: Our study demonstrates an increase in the use of flow-diverting stents, nondiverting stents, carotid stents, and reperfusion devices for acute ischemic stroke intervention between 2015 and 2020. Coil use for aneurysmal treatment has declined.

102 AI-Based Molecular Classification of Diffuse Gliomas using Rapid, Label-Free Optical Imaging.

INTRODUCTION: Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. Access to timely molecular diagnostic testing for brain tumor patients is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. METHODS: By combining stimulated Raman histology (SRH), a rapid, label-free, non-consumptive, optical imaging method, and deep learning-based image classification, we are able to predict the molecular genetic features used by the World Health Organization (WHO) to define the adult-type diffuse glioma taxonomy, including IDH-1/2, 1p19q-codeletion, and ATRX loss. We developed a multimodal deep neural network training strategy that uses both SRH images and large-scale, public diffuse glioma genomic data (i.e. TCGA, CGGA, etc.) in order to achieve optimal molecular classification performance. RESULTS: One institution was used for model training (University of Michigan) and four institutions (NYU, UCSF, Medical University of Vienna, and University Hospital Cologne) were included for patient enrollment in the prospective testing cohort. Using our system, called DeepGlioma, we achieved an average molecular genetic classification accuracy of 93.2% and identified the correct diffuse glioma molecular subgroup with 91.5% accuracy within 2 minutes in the operating room. DeepGlioma outperformed conventional IDH1-R132H immunohistochemistry (94.2% versus 91.4% accuracy) as a first-line molecular diagnostic screening method for diffuse gliomas and can detect canonical and non-canonical IDH mutations. CONCLUSIONS: Our results demonstrate how artificial intelligence and optical histology can be used to provide a rapid and scalable alternative to wet lab methods for the molecular diagnosis of brain tumor patients during surgery.

Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging.

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a rapid (<90 seconds), artificial-intelligence-based diagnostic screening system to streamline the molecular diagnosis of diffuse gliomas. DeepGlioma is trained using a multimodal dataset that includes stimulated Raman histology (SRH); a rapid, label-free, non-consumptive, optical imaging method; and large-scale, public genomic data. In a prospective, multicenter, international testing cohort of patients with diffuse glioma (n = 153) who underwent real-time SRH imaging, we demonstrate that DeepGlioma can predict the molecular alterations used by the World Health Organization to define the adult-type diffuse glioma taxonomy (IDH mutation, 1p19q co-deletion and ATRX mutation), achieving a mean molecular classification accuracy of 93.3 ± 1.6%. Our results represent how artificial intelligence and optical histology can be used to provide a rapid and scalable adjunct to wet lab methods for the molecular screening of patients with diffuse glioma.

The MedConnect Program: Symptomatology, Return Visits, and Hospitalization of COVID-19 Outpatients Following Discharge From the Emergency Department.

Background and objective Although hospitalization is required for only a minority of those infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the high rates of morbidity and mortality among these patients have led researchers to focus on the predictors of admission and adverse outcomes in the inpatient population. However, there is scarce data on the clinical trajectory of individuals symptomatic enough to present for emergency care, but not sick enough to be admitted. In light of this, we aimed to examine the symptomatology, emergency department (ED) revisits, and hospitalization of coronavirus disease 2019 (COVID-19) outpatients after discharge from the ED. Methods Adult patients with COVID-19 infection were prospectively enrolled after discharge from the ED between May and December 2020. Patients were followed up longitudinally for 14 days via phone interviews designed to provide support and information and to track symptomatology, ED revisits, and hospitalization. Results A volunteer, medical student-run program enrolled 199 COVID-19 patients discharged from the ED during the first nine months of the pandemic. Of the 176 patients (88.4%) who completed the 14-day protocol, 29 (16.5%) had a second ED visit and 17 (9.6%) were admitted, 16 (9%) for worsening COVID-19 symptoms. Age, male sex, comorbid illnesses, and self-reported dyspnea, diarrhea, chills, and fever were associated with hospital admission for patients with a subsequent ED visit. For those who did not require admission, symptoms generally improved following ED discharge. Age >65 years and a history of cardiovascular disease (CVD) were associated with a longer duration of cough, but generally, patient characteristics and comorbidities did not significantly affect the overall number or duration of symptoms. Conclusions Nearly one in five patients discharged from the ED with COVID-19 infection had a second ED evaluation during a 14-day follow-up period, despite regular phone interactions aimed at providing support and information. More than half of them required admission for worsening COVID-19 symptoms. Established risk factors for severe disease and self-reported persistence of certain symptoms were associated with hospital admission, while those who did not require hospitalization had a steady improvement in symptoms over the 14-day period.

Ventricular Volume Change as a Predictor of Shunt-Dependent Hydrocephalus in Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: The ΔVV volume between head CT scans taken before and after EVD clamping was predictive of early and delayed shunt dependence.

Thrombus Histology as It Relates to Mechanical Thrombectomy: A Meta-Analysis and Systematic Review.

BACKGROUND: Appropriate thrombus-device interaction is critical for recanalization. Histology can serve as a proxy for mechanical properties, and thus inform technique selection. OBJECTIVE: To investigate the value of histologic characterization, we conducted a systematic review and meta-analysis on the relationship between thrombus histology and recanalization, technique, etiology, procedural efficiency, and imaging findings. METHODS: In this meta-analysis, we identified studies published between March 2010 and March 2020 reporting findings related to the histologic composition of thrombi in large vessel occlusion stroke. Studies with at least 10 patients who underwent mechanical thrombectomy using stent retriever or aspiration were considered. Only studies in which retrieved thrombi were histologically processed were included. Patient-level data were requested when data could not be directly extracted. The primary outcome assessed was the relationship between thrombus histology and angiographic outcome. RESULTS: A total of 22 studies encompassing 1623 patients met inclusion criteria. Clots associated with good angiographic outcome had higher red blood cell (RBC) content (mean difference [MD] 9.60%, 95% CI 3.85-15.34, P = .008). Thrombi retrieved by aspiration had less fibrin (MD -11.39, 95% CI -22.50 to -0.27, P = .046) than stent-retrieved thrombi. Fibrin/platelet-rich clots were associated with longer procedure times (MD 13.20, 95% CI 1.30-25.10, P = .037). Hyperdense artery sign was associated with higher RBC content (MD 14.17%, 95% CI 3.07-25.27, P = .027). No relationship was found between composition and etiology. CONCLUSION: RBC-rich thrombi were associated with better recanalization outcomes and shorter procedure times, suggesting that preinterventional compositional characterization may yield important prognostic and therapeutic guidance.

Trends in interventional stroke device utilization during the COVID-19 pandemic.

OBJECTIVES: The collateral effect of the COVID-19 pandemic on interventional stroke care is not well described. We studied this effect by utilizing stroke device sales data as markers of interventional stroke case volume in the United States. METHODS: Using a real-time healthcare device sales registry, this observational study examined trends in the sales of thrombectomy devices and cerebral aneurysm coiling from the same 945 reporting hospitals in the U.S. between January 22 and June 31, 2020, and for the same months in 2018 and 2019 to allow for comparison. We simultaneously reviewed daily reports of new COVID-19 cases. The strength of association between the cumulative incidence of COVID-19 and procedural device sales was measured using Spearman rank correlation coefficient (CC). RESULTS: Device sales decreased for thrombectomy (- 3.7%) and cerebral aneurysm coiling (- 8.5%) when comparing 2019-2020. In 2020, thrombectomy device sales were negatively associated with the cumulative incidence of COVID-19 (CC - 0.56, p < 0.0001), with stronger negative correlation during April (CC - 0.97, p < 0.0001). The same negative correlation was observed with aneurysm treatment devices (CC - 0.60, p < 0.001), with stronger correlation in April (CC - 0.97, p < 0.0001). CONCLUSIONS: The decline in sales of stroke interventional equipment underscores a decline in associated case volumes. Future pandemic responses should consider strategies to mitigate such negative collateral effects.

Trends in acute ischemic stroke treatments and mortality in the United States from 2012 to 2018.

OBJECTIVE: The establishment of mechanical thrombectomy (MT) as a first-line treatment for select patients with acute ischemic stroke (AIS) and the expansion of stroke systems of care have been major advancements in the care of patients with AIS. In this study, the authors aimed to identify temporal trends in the usage of tissue-type plasminogen activator (tPA) and MT within the AIS population from 2012 to 2018, and the relationship to mortality. METHODS: Using a nationwide private health insurance database, 117,834 patients who presented with a primary AIS between 2012 and 2018 in the United States were identified. The authors evaluated temporal trends in tPA and MT usage and clinical outcomes stratified by treatment and age using descriptive statistics. RESULTS: Among patients presenting with AIS in this population, the mean age was 69.1 years (SD ± 12.3 years), and 51.7% were female. Between 2012 and 2018, the use of tPA and MT increased significantly (tPA, 6.3% to 11.8%, p < 0.0001; MT, 1.6% to 5.7%, p < 0.0001). Mortality at 90 days decreased significantly in the overall AIS population (8.7% to 6.7%, p < 0.0001). The largest reduction in 90-day mortality was seen in patients treated with MT (21.4% to 14.1%, p = 0.0414) versus tPA (11.8% to 7.0%, p < 0.0001) versus no treatment (8.3% to 6.3%, p < 0.0001). Age-standardized mortality at 90 days decreased significantly only in patients aged 71-80 years (11.4% to 7.8%, p < 0.0001) and > 81 years (17.8% to 11.6%, p < 0.0001). Mortality at 90 days stagnated in patients aged 18 to 50 years (3.0% to 2.2%, p = 0.4919), 51 to 60 years (3.8% to 3.9%, p = 0.7632), and 61 to 70 years (5.5% to 5.2%, p = 0.2448). CONCLUSIONS: From 2012 to 2018, use of tPA and MT increased significantly, irrespective of age, while mortality decreased in the entire AIS population. The most dramatic decrease in mortality was seen in the MT-treated population. Age-standardized mortality improved only in patients older than 70 years, with no change in younger patients.

Risk factors and morbidity associated with surgical site infection subtypes following adult neurosurgical procedures.

OBJECTIVE: Studies on surgical site infection (SSI) in adult neurosurgery have presented all subtypes of SSIs as the general 'SSI'. Given that SSIs constitute a broad range of infections, we hypothesized that clinical outcomes and management vary based on SSI subtype. METHODS: A retrospective analysis of all neurosurgical SSI from 2012-2019 was conducted at a tertiary care institution. SSI subtypes were categorized as deep and superficial incisional SSI, brain, dural or spinal abscesses, meningitis or ventriculitis, and osteomyelitis. RESULTS: 9620 craniotomy, shunt, and fusion procedures were studied. 147 procedures (1.5%) resulted in postoperative SSI. 87 (59.2%) of these were associated with craniotomy, 36 (24.5%) with spinal fusion, and 24 (16.3%) with ventricular shunting. Compared with superficial incisional primary SSI, rates of reoperation to treat SSI were highest for deep incisional primary SSI (91.2% vs 38.9% for superficial, p < 0.001) and second-highest for intracranial SSI (90.9% vs 38.9%, p = 0.0001). Postoperative meningitis was associated with the highest mortality rate (14.9%). Compared with superficial incisional SSI, the rate of readmission for intracranial SSI was highest (57.6% vs 16.7%, p = 0.022). CONCLUSION: Deep incisional and organ space SSI demonstrate a greater association with morbidity relative to superficial incisional SSI. Future studies should assess subtypes of SSI given these differences.

Length of Stay Beyond Medical Readiness in a Neurosurgical Patient Population and Associated Healthcare Costs.

BACKGROUND: Length of stay beyond medical readiness (LOS-BMR) leads to increased expenses and higher morbidity related to hospital-acquired conditions. OBJECTIVE: To determine the proportion of admitted neurosurgical patients who have LOS-BMR and associated risk factors and costs. METHODS: We performed a prospective, cohort analysis of all neurosurgical patients admitted to our institution over 5 mo. LOS-BMR was assessed daily by the attending neurosurgeon and neuro-intensivist with a standardized criterion. Univariate and multivariate logistic regressions were performed. RESULTS: Of the 884 patients admitted, 229 (25.9%) had a LOS-BMR. The average LOS-BMR was 2.7 ± 3.1 d at an average daily cost of $9 148.28 ± $12 983.10, which resulted in a total cost of $2 076 659.32 over the 5-mo period. Patients with LOS-BMR were significantly more likely to be older and to have hemiplegia, dementia, liver disease, renal disease, and diabetes mellitus. Patients with a LOS-BMR were significantly more likely to be discharged to a subacute rehabilitation/skilled nursing facility (40.2% vs 4.1%) or an acute/inpatient rehabilitation facility (22.7% vs 1.7%, P < .0001). Patients with Medicare insurance were more likely to have a LOS-BMR, whereas patients with private insurance were less likely (P = .048). CONCLUSION: The most common reason for LOS-BMR was inefficient discharge of patients to rehabilitation and nursing facilities secondary to unavailability of beds at discharge locations, insurance clearance delays, and family-related issues.

Neurosurgical patients admitted via the emergency department initiating comfort care measures: a prospective cohort analysis.

BACKGROUND: 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. OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Rapid, label-free detection of diffuse glioma recurrence using intraoperative stimulated Raman histology and deep neural networks.

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 (<60 sec per 1 × 1 mm2) to image a cohort of patients (n = 35) with suspected recurrent gliomas who underwent biopsy or resection. The SRH images were then used to train a convolutional neural network (CNN) and develop an inference algorithm to detect viable recurrent glioma. Following network training, the performance of the CNN was tested for diagnostic accuracy in a retrospective cohort (n = 48). 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.

Evaluating the role of methicillin-resistant Staphylococcus aureus (MRSA)-specific antibiotic prophylaxis for neurosurgical patients.

OBJECTIVE: Surgical site infection (SSI) in neurosurgical patients increases morbidity. Despite the rise of methicillin-resistant Staphylococcus aureus (MRSA) colonization, there is little consensus regarding antibiotic prophylaxis for SSI in MRSA-colonized neurosurgical patients. Our objective was to examine the incidence of SSI in MRSA-colonized neurosurgical patients and interrogate whether MRSA-specific antibiotic prophylaxis reduces SSIs. METHODS: We performed a retrospective analysis of adult patients undergoing neurosurgical procedures between 2013 and 2018. The primary outcome was SSI in patients with MRSA colonization receiving MRSA-specific antibiotics. Secondary outcomes included predictors of SSI, including whether broad use of MRSA-specific antibiotics affects SSI rate. RESULTS: Of 9739 procedures, 376 had SSI (3.9 %). Seven hundred forty-four procedures (7.6 %) were performed on patients screened preoperatively for MRSA, including 54 procedures on MRSA-colonized patients. MRSA-colonized patients were more likely than MRSA-non-colonized patients to receive MRSA-specific antibiotics (35.2 % vs. 17.8 %, p = 0.002) for prophylaxis. Nevertheless, MRSA-colonized patients had higher SSI rates compared to MRSA-non-colonized patients (22.2 % vs. 6.4 %, p = 0.00002). MRSA-colonization led to 3.49 greater odds (95 % CI 1.52-7.65, p = 0.002) of SSI relative to MRSA-non-colonization. MRSA-colonized patients receiving MRSA-specific antibiotics, compared to those receiving non-MRSA-specific antibiotics, had lower SSI rates, but this difference was not statistically significant (15.8 % vs. 25.7 %, p = 0.40). In the non-screened population, those receiving MRSA-specific antibiotics, compared to those receiving non-MRSA-specific antibiotics, had significantly higher SSI rates (6.9 % vs. 3.0 %, p = 0.00001). The use of MRSA-specific antibiotic prophylaxis in the non-screened population increased the odds of SSI (OR 1.90, 95 % CI 1.45-2.46, p = 0.0001). CONCLUSION: MRSA-colonized neurosurgical patients had a higher SSI rate compared to MRSA-non-colonized patients. While MRSA-specific antibiotics may benefit those with MRSA colonization, the difference in SSI rate between MRSA-colonized patients receiving MRSA-specific antibiotics vs. non-specific antibiotics requires further investigation. The broader use of MRSA-specific antibiotics may paradoxically confer an increased risk of SSI in a non-screened neurosurgical population.

Automated histologic diagnosis of CNS tumors with machine learning.

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.

Predictive Factors, 30-Day Clinical Outcomes, and Costs Associated with Cerebrospinal Fluid Leak in Pituitary Adenoma Resection.

Cerebrospinal fluid (CSF) leak is a complication of endoscopic endonasal pituitary adenoma resection. Previous studies examining complications of pituitary adenoma resection have not examined associations of an exhaustive list of clinical and financial variables with CSF leak. We designed a retrospective analysis of 334 consecutive patients that underwent endoscopic endonasal pituitary adenoma resection at a single institution over 5 years, analyzing associations between CSF leak and demographic data, operative data, comorbidities, clinical complications and outcomes, costs, charges, and payments. Of the 20 preoperative variables studied, none were positively associated with CSF leak in between-groups comparison, although multivariate analysis revealed an association with a history of radiation to the skull base (odds ratio [OR], 8.67; 95% confidence interval [CI], 0.94-57.03; p < 0.05). CSF leak was associated with a significantly higher rate of postoperative diabetes insipidus (Δ = 33.4%, p = 0.040) and increased length of stay after operation in between-groups comparison. Multivariate analysis on postoperative variables revealed significant associations between CSF leak and intracerebral hemorrhage (OR, 17.44; 95% CI, 0.65-275.3; p < 0.05) and postoperative intracranial infection (OR, 28.73; 95% CI, 2.04-438.7; p < 0.05). Also, CSF leak was associated with significantly higher costs (Δ = $15,643, p < 0.05) and hospital charges (Δ = $46,026, p < 0.05). Operating room time, room and board, and supplies and implants were the strongest cost drivers. This study highlights the difficulty of utilizing preoperative variables to predict CSF leak, the clinical complications and outcomes of leak, and the financial subcategories that drive the costs, charges, and payments associated with this complication.

Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks.

Intraoperative diagnosis is essential for providing safe and effective care during cancer surgery1. The existing workflow for intraoperative diagnosis based on hematoxylin and eosin staining of processed tissue is time, resource and labor intensive2,3. Moreover, interpretation of intraoperative histologic images is dependent on a contracting, unevenly distributed, pathology workforce4. In the present study, we report a parallel workflow that combines stimulated Raman histology (SRH)5-7, a label-free optical imaging method and deep convolutional neural networks (CNNs) to predict diagnosis at the bedside in near real-time in an automated fashion. Specifically, our CNNs, trained on over 2.5 million SRH images, predict brain tumor diagnosis in the operating room in under 150 s, an order of magnitude faster than conventional techniques (for example, 20-30 min)2. In a multicenter, prospective clinical trial (n = 278), we demonstrated that CNN-based diagnosis of SRH images was noninferior to pathologist-based interpretation of conventional histologic images (overall accuracy, 94.6% versus 93.9%). Our CNNs learned a hierarchy of recognizable histologic feature representations to classify the major histopathologic classes of brain tumors. In addition, we implemented a semantic segmentation method to identify tumor-infiltrated diagnostic regions within SRH images. These results demonstrate how intraoperative cancer diagnosis can be streamlined, creating a complementary pathway for tissue diagnosis that is independent of a traditional pathology laboratory.