International practice variation in perioperative laboratory testing in glioblastoma patients-a retrospective cohort study.

Purpose: Although standard-of-care has been defined for the treatment of glioblastoma patients, substantial practice variation exists in the day-to-day clinical management. This study aims to compare the use of laboratory tests in the perioperative care of glioblastoma patients between two tertiary academic centers-Brigham and Women's Hospital (BWH), Boston, USA, and University Medical Center Utrecht (UMCU), Utrecht, the Netherlands.

Methods: All glioblastoma patients treated according to standard-of-care between 2005 and 2013 were included.

Orally Administered 5-aminolevulinic Acid for Isolation and Characterization of Circulating Tumor-Derived Extracellular Vesicles in Glioblastoma Patients.

In glioblastoma (GB), tissue is required for accurate diagnosis and subtyping. Tissue can be obtained through resection or (stereotactic) biopsy, but these invasive procedures provide risks for patients. Extracellular vesicles (EVs) are small, cell-derived vesicles that contain miRNAs, proteins, and lipids, and possible candidates for liquid biopsies.

Survival prediction of glioblastoma patients-are we there yet? A systematic review of prognostic modeling for glioblastoma and its clinical potential.

Glioblastoma is associated with a poor prognosis. Even though survival statistics are well-described at the population level, it remains challenging to predict the prognosis of an individual patient despite the increasing number of prognostic models. The aim of this study is to systematically review the literature on prognostic modeling in glioblastoma patients.

Does Artificial Intelligence Outperform Natural Intelligence in Interpreting Musculoskeletal Radiological Studies? A Systematic Review.

Background: Machine learning (ML) is a subdomain of artificial intelligence that enables computers to abstract patterns from data without explicit programming. A myriad of impactful ML applications already exists in orthopaedics ranging from predicting infections after surgery to diagnostic imaging. However, no systematic reviews that we know of have compared, in particular, the performance of ML models with that of clinicians in musculoskeletal imaging to provide an up-to-date summary regarding the extent of applying ML to imaging diagnoses.

Preoperative functional MRI use in neurooncology patients: a clinician survey.

Objective: Functional MRI (fMRI) is increasingly being investigated for use in neurosurgical patient care. In the current study, the authors characterize the clinical use of fMRI by surveying neurosurgeons' use of and attitudes toward fMRI as a surgical planning tool in neurooncology patients.

Methods: A survey was developed to inquire about clinicians' use of and experiences with preoperative fMRI in the neurooncology patient population, including example case images.

An Online Calculator for the Prediction of Survival in Glioblastoma Patients Using Classical Statistics and Machine Learning.

Background: Although survival statistics in patients with glioblastoma multiforme (GBM) are well-defined at the group level, predicting individual patient survival remains challenging because of significant variation within strata.

Objective: To compare statistical and machine learning algorithms in their ability to predict survival in GBM patients and deploy the best performing model as an online survival calculator.

Methods: Patients undergoing an operation for a histopathologically confirmed GBM were extracted from the Surveillance Epidemiology and End Results (SEER) database (2005-2015) and split into a training and hold-out test set in an 80/20 ratio.

Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement.

Background: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitating tumor volumes as well as the product of maximum bidimensional diameters according to the Response Assessment in Neuro-Oncology (RANO) criteria (AutoRANO).

Methods: Two cohorts of patients were used for this study.

Trends in High-Impact Neurosurgical Randomized Controlled Trials Published in General Medical Journals: A Systematic Review.

Background: The neurosurgery literature lacks a comprehensive report of neurosurgical randomized controlled trials (RCTs) published in general medical journals. RCTs published in these journals have high visibility and impact on decision-making by general medical practitioners and health care policymakers.

Methods: A systematic review of neurosurgical RCTs in the New England Journal of Medicine, The Lancet, Journal of the American Medical Association, The BMJ, and Annals of Internal Medicine was completed.

Natural Language Processing for Automated Quantification of Brain Metastases Reported in Free-Text Radiology Reports.

Purpose: Although the bulk of patient-generated health data are increasing exponentially, their use is impeded because most data come in unstructured format, namely as free-text clinical reports. A variety of natural language processing (NLP) methods have emerged to automate the processing of free text ranging from statistical to deep learning-based models; however, the optimal approach for medical text analysis remains to be determined. The aim of this study was to provide a head-to-head comparison of novel NLP techniques and inform future studies about their utility for automated medical text analysis.

Routine Blood Tests Do Not Predict Survival in Patients with Glioblastoma-Multivariable Analysis of 497 Patients.

Background: Multiple reports have attributed a prognostic value to routine blood tests results for patients with glioblastoma. However, these studies have reported conflicting results and have often had small sample sizes. We sought to validate the prognostic value of the described tests in an independent glioblastoma patient population.

Randomized controlled trials comparing surgery to non-operative management in neurosurgery: a systematic review.

Background: A randomized controlled trial (RCT) remains the pinnacle of clinical research design. However, RCTs in neurosurgery, especially those comparing surgery to non-operative treatment, are rare and their relevance and applicability have been questioned. This study set out to assess trial design and quality and identify their influence on outcomes in recent neurosurgical trials that compare surgery to non-operative treatment.

Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas.

Purpose: Isocitrate dehydrogenase (IDH) and 1p19q codeletion status are importantin providing prognostic information as well as prediction of treatment response in gliomas. Accurate determination of the IDH mutation status and 1p19q co-deletion prior to surgery may complement invasive tissue sampling and guide treatment decisions.

Methods: Preoperative MRIs of 538 glioma patients from three institutions were used as a training cohort.

International practice variation in postoperative imaging of chronic subdural hematoma patients.

Objective: The value of CT scanning after burr hole surgery in chronic subdural hematoma (CSDH) patients is unclear, and practice differs between countries. At the Brigham and Women's Hospital (BWH) in Boston, Massachusetts, neurosurgeons frequently order routine postoperative CT scans, while the University Medical Center Utrecht (UMCU) in the Netherlands does not have this policy. The aim of this study was to compare the use of postoperative CT scans in CSDH patients between these hospitals and to evaluate whether there are differences in clinical outcomes.

Treatment and survival of osteosarcoma and Ewing sarcoma of the skull: a SEER database analysis.

Background: Common primary bone tumors include osteosarcomas (OSC) and Ewing sarcomas (EWS). The skull is a rare site, and literature about their treatment and survival is scarce. Using the Surveillance, Epidemiology, and End Results (SEER) database, this study aims to assess the treatment and survival of skull OSC and skull EWS, as well as predictors for survival.

Behavior and attitudes among European neurosurgeons - An international survey.

Background: A recent survey showed that potentially hazardous levels of certain attitudes have been associated with worse patient outcomes in orthopedic surgery, based on a questionnaire that was adopted from aviation. This questionnaire aims to evaluate the prevalence of potentially hazardous levels of machismo, impulsiveness, anxiety, antiauthority, resignation, and invulnerability in attitudes and was adopted for use among neurosurgeons.

Methods: All individual members of the European Association of Neurosurgical Societies (EANS) were invited to fill-out an online questionnaire.

Information-Based Medicine in Glioma Patients: A Clinical Perspective.

Glioma constitutes the most common type of primary brain tumor with a dismal survival, often measured in terms of months or years. The thin line between treatment effectiveness and patient harm underpins the importance of tailoring clinical management to the individual patient. Randomized trials have laid the foundation for many neuro-oncological guidelines.

Timing of surgery in traumatic brachial plexus injury: a systematic review.

Objective: Ideal timeframes for operating on traumatic stretch and blunt brachial plexus injuries remain a topic of debate. Whereas on the one hand spontaneous recovery might occur, on the other hand, long delays are believed to result in poorer functional outcomes. The goal of this review is to assess the optimal timeframe for surgical intervention for traumatic brachial plexus injuries.

Length of Thromboprophylaxis in Patients Operated on for a High-Grade Glioma: A Retrospective Study.

Objective: High-grade gliomas are associated with venous thromboembolism (VTE). This retrospective study with a parallel cohort design investigated influence of continuing prophylactic anticoagulation after discharge on rate of VTE and intracranial hemorrhage (ICH) in patients operated on for high-grade glioma.

Methods: Consecutive adult patients who underwent subtotal or gross total resection for high-grade glioma at a single institution were included.

A nationwide analysis of 30-day adverse events, unplanned readmission, and length of hospital stay after peripheral nerve surgery in extremities and the brachial plexus.

Background: Little is known on adverse events and their timing after peripheral nerve surgery in extremities. The aim of this study is to identify predictors and typical timing of complications, unplanned readmission, and length of hospital stay for patients undergoing peripheral nerve surgery in the extremities.

Methods: Data were extracted from the National Surgical Quality Improvement Program (NSQIP) registry from 2005 to 2015.

Thirty-Day Outcomes After Craniotomy for Primary Malignant Brain Tumors: A National Surgical Quality Improvement Program Analysis.

Background: Despite improved perioperative management, the rate of postoperative morbidity and mortality after brain tumor resection remains considerably high.

Objective: To assess the rates, causes, timing, and predictors of major complication, extended length of stay (>10 d), reoperation, readmission, and death within 30 d after craniotomy for primary malignant brain tumors.

Methods: Patients were extracted from the National Surgical Quality Improvement Program registry (2005-2015) and analyzed using multivariable logistic regression.

Residual Convolutional Neural Network for the Determination of Status in Low- and High-Grade Gliomas from MR Imaging.

Isocitrate dehydrogenase () mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the status of gliomas from MR imaging by applying a residual convolutional neural network to preoperative radiographic data. Preoperative imaging was acquired for 201 patients from the Hospital of University of Pennsylvania (HUP), 157 patients from Brigham and Women's Hospital (BWH), and 138 patients from The Cancer Imaging Archive (TCIA) and divided into training, validation, and testing sets.

An introduction and overview of machine learning in neurosurgical care.

Background: Machine learning (ML) is a branch of artificial intelligence that allows computers to learn from large complex datasets without being explicitly programmed. Although ML is already widely manifest in our daily lives in various forms, the considerable potential of ML has yet to find its way into mainstream medical research and day-to-day clinical care. The complex diagnostic and therapeutic modalities used in neurosurgery provide a vast amount of data that is ideally suited for ML models.