Benralizumab: Effectiveness in Patients with Uncontrolled Severe Eosinophilic Asthma at 6 and 12 Months at a Third-Level Care Hospital. Capacity for ICS-LABA Therapy Reduction.

Background: Asthma is a health condition with worldwide relevance, evaluated based on the necessary treatment to control symptoms and exacerbations. Severe asthma is uncontrolled despite high doses of ICS-LABA and treatment for triggering factors. Severe eosinophilic asthma is characterized by an increase in eosinophils in the peripheral circulation, walls, and passages of the respiratory tract.

Endovascular treatment of chronic subdural hematoma in a dual-trained neurosurgical unit: Results and proposal of a randomized controlled trial protocol.

Introduction: Chronic subdural hematoma (cSDH) is a prevalent neurosurgical condition with an increasing incidence due to the rising life expectancy and the widespread use of anticoagulant and antiplatelet therapies. Insights into the inflammatory origins of cSDH led to the exploration of Middle Meningeal Artery (MMA) embolization as a therapeutic strategy. In recent years the endovascular treatment of MMA has gained momentum.

A Fully Automated Pipeline Using Swin Transformers for Deep Learning-Based Blood Segmentation on Head Computed Tomography Scans After Aneurysmal Subarachnoid Hemorrhage.

Background: Accurate volumetric assessment of spontaneous aneurysmal subarachnoid hemorrhage (aSAH) is a labor-intensive task performed with current manual and semiautomatic methods that might be relevant for its clinical and prognostic implications. In the present research, we sought to develop and validate an artificial intelligence-driven, fully automated blood segmentation tool for subarachnoid hemorrhage (SAH) patients via noncontrast computed tomography (NCCT) scans employing a transformer-based Swin-UNETR architecture.

Methods: We retrospectively analyzed NCCT scans from patients with confirmed aSAH utilizing the Swin-UNETR for segmentation.

Integrating endovascular techniques into established open neurosurgery practice: a temporal analysis of treatment evolution in a dual-trained neurosurgical unit.

Objetive: In Europe, units with Dual-trained Neurovascular Surgeons (DTNS) skilled in both open neurosurgery (ON) and endovascular neurosurgery (EN) are scarce. For instance, in Spain, our unit is unique within the public health system, where all neurovascular procedures are carried out by DTNS. Our study aims to evaluate the evolution in treating ruptured intracranial aneurysms (rICAs) and assess the impact of this evolution on clinical outcomes.

[Economic burden assessment for the management of asthma patients at Mexico's National Institute for Respiratory Diseases].

Objetivo: Determinar la carga económica anual del asma, desde una perspectiva institucional y con base en la clasificación recomendada por GINA, en una cohorte retrospectiva de adultos atendidos en el Instituto Nacional de Enfermedades Respiratorias (INER) de México.

MÉtodos: Estudio observacional, longitudinal y retrospectivo, llevado a cabo a partir de la información recabada de 247 pacientes femeninas con asma. Se estimaron los costos directos anuales: visitas, pruebas de laboratorio, tratamiento farmacológico y de las crisis o exacerbaciones, para determinar la carga anual de la enfermedad desde una perspectiva institucional, y según la clasificación de la Iniciativa Global para el Asma.

Non-navigated 2D intraoperative ultrasound: An unsophisticated surgical tool to achieve high standards of care in glioma surgery.

Purpose: In an era characterized by rapid progression in neurosurgical technologies, traditional tools such as the non-navigated two-dimensional intraoperative ultrasound (nn-2D-IOUS) risk being overshadowed. Against this backdrop, this study endeavors to provide a comprehensive assessment of the clinical efficacy and surgical relevance of nn-2D-IOUS, specifically in the context of glioma resections.

Methods: This retrospective study undertaken at a single center evaluated 99 consecutive, non-selected patients diagnosed with both high-grade and low-grade gliomas.

Mortality Prediction of Patients with Subarachnoid Hemorrhage Using a Deep Learning Model Based on an Initial Brain CT Scan.

Background: Subarachnoid hemorrhage (SAH) entails high morbidity and mortality rates. Convolutional neural networks (CNN) are capable of generating highly accurate predictions from imaging data. Our objective was to predict mortality in SAH patients by processing initial CT scans using a CNN-based algorithm.

The Río Hortega University Hospital Glioblastoma dataset: A comprehensive collection of preoperative, early postoperative and recurrence MRI scans (RHUH-GBM).

Glioblastoma, a highly aggressive primary brain tumor, is associated with poor patient outcomes. Although magnetic resonance imaging (MRI) plays a critical role in diagnosing, characterizing, and forecasting glioblastoma progression, public MRI repositories present significant drawbacks, including insufficient postoperative and follow-up studies as well as expert tumor segmentations. To address these issues, we present the "Río Hortega University Hospital Glioblastoma Dataset (RHUH-GBM)," a collection of multiparametric MRI images, volumetric assessments, molecular data, and survival details for glioblastoma patients who underwent total or near-total enhancing tumor resection.

Predicting Regions of Local Recurrence in Glioblastomas Using Voxel-Based Radiomic Features of Multiparametric Postoperative MRI.

The globally accepted surgical strategy in glioblastomas is removing the enhancing tumor. However, the peritumoral region harbors infiltration areas responsible for future tumor recurrence. This study aimed to evaluate a predictive model that identifies areas of future recurrence using a voxel-based radiomics analysis of magnetic resonance imaging (MRI) data.

Posterior cervical triangle approach for carotid endarterectomy: Technical note and results.

Introduction: Carotid endarterectomy (CEA) is usually performed using the anterior cervical triangle as a surgical corridor but, when needed, the retromandibular space makes dissection of higher structures difficult in some cases. The posterior cervical triangle (PCT) can be useful in these demanding cases.

Methods: We retrospectively reviewed cases from July 2013 to November 2019 in which PCT was used as an approach for CEA.

Current Evidence, Limitations and Future Challenges of Survival Prediction for Glioblastoma Based on Advanced Noninvasive Methods: A Narrative Review.

: Survival estimation for patients diagnosed with Glioblastoma (GBM) is an important information to consider in patient management and communication. Despite some known risk factors, survival estimation remains a major challenge. Novel non-invasive technologies such as radiomics and artificial intelligence (AI) have been implemented to increase the accuracy of these predictions.

Treatment of unruptured middle cerebral artery aneurysms: Systematic review in an attempt to perform a network meta-analysis.

Objective: Open surgical clipping has been generally considered the best treatment option for unruptured middle cerebral artery aneurysms (uMCAAs). However, this type of aneurysm is being treated endovascularly with the appearance of new devices. We have carried out a systematic review of randomized and quasi-experimental studies to conduct a network meta-analysis (NMA) to assess the safety and efficacy of the different treatment methods currently used in uMCAAs.

Validation of Presurgical Simulation of White Matter Damage Using Diffusion Tensor Imaging.

Background: The understanding of white matter (WM) was revolutionized by the emergence of tractography based on diffusion tensor imaging (DTI). Currently, DTI simulations are implemented in preoperative planning to optimize surgical approaches. The reliability of these simulations has been questioned and investigated seeking for correlation between neurological performance and anomalies in DTI parameters.

Brain dural arteriovenous fistulas in the COVID-19 Era: A warning and rationale for association.

Objectives: Brain dural arteriovenous fistulas(bDAVFs) are anomalous connections between dural arteries and cerebral veins or sinuses. Cerebral venous thrombosis(CVT) often precedes or coincides with bDAVFs and is considered a risk factor for these vascular malformations. Recently, vaccine-induced thrombotic thrombocytopenia causing CVTs has been associated with COVID-19 vaccines.

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis.

Background: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome.

Methods: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions.

Advantages and Limitations of Intraoperative Ultrasound Strain Elastography Applied in Brain Tumor Surgery: A Single-Center Experience.

Background: Strain elastography is an intraoperative ultrasound (ioUS) modality currently under development with various potential applications in neurosurgery.

Objective: To describe the main technical aspects, usefulness, and limitations of ioUS strain elastography applied in a large case series of brain tumors.

Methods: We retrospectively analyzed patients who underwent craniotomy for a brain tumor between March 2018 and March 2021.

Predicting Short-Term Survival after Gross Total or Near Total Resection in Glioblastomas by Machine Learning-Based Radiomic Analysis of Preoperative MRI.

Radiomics, in combination with artificial intelligence, has emerged as a powerful tool for the development of predictive models in neuro-oncology. Our study aims to find an answer to a clinically relevant question: is there a radiomic profile that can identify glioblastoma (GBM) patients with short-term survival after complete tumor resection? A retrospective study of GBM patients who underwent surgery was conducted in two institutions between January 2019 and January 2020, along with cases from public databases. Cases with gross total or near total tumor resection were included.

Intraoperative magnetic resonance imaging for cerebral cavernous malformations: When is it maybe worth it?

Objective: Intraoperative magnetic resonance imaging (iMRI) can be useful for cerebral cavernous malformations (CCM) surgery. However, literature on this topic is scarce. We aim to investigate its clinical utility and propose criteria for the selection of patients who may benefit the most from iMRI.

Is There a Relationship between the Elasticity of Brain Tumors, Changes in Diffusion Tensor Imaging, and Histological Findings? A Pilot Study Using Intraoperative Ultrasound Elastography.

Intraoperative ultrasound elastography (IOUS-E) is a novel image modality applied in brain tumor assessment. However, the potential links between elastographic findings and other histological and neuroimaging features are unknown. This study aims to find associations between brain tumor elasticity, diffusion tensor imaging (DTI) metrics, and cell proliferation.

Acute changes in diffusion tensor-derived metrics and its correlation with the motor outcome in gliomas adjacent to the corticospinal tract.

Background: This study involves analysis of the relationship between variables obtained using diffusion tensor imaging (DTI) and motor outcome in gliomas adjacent to the corticospinal tract (CST).

Methods: Histologically confirmed glioma patients who were to undergo surgery between January 2018 and December 2019 were prospectively enrolled. All patients had a preoperative magnetic resonance imaging (MRI) study that included DTI, a tumor 2 cm or less from the CST, and postsurgical control within 48 h.

Comparison of Intraoperative Ultrasound B-Mode and Strain Elastography for the Differentiation of Glioblastomas From Solitary Brain Metastases. An Automated Deep Learning Approach for Image Analysis.

Background: The differential diagnosis of glioblastomas (GBM) from solitary brain metastases (SBM) is essential because the surgical strategy varies according to the histopathological diagnosis. Intraoperative ultrasound elastography (IOUS-E) is a relatively novel technique implemented in the surgical management of brain tumors that provides additional information about the elasticity of tissues. This study compares the discriminative capacity of intraoperative ultrasound B-mode and strain elastography to differentiate GBM from SBM.

Relationship between the overall survival in glioblastomas and the radiomic features of intraoperative ultrasound: a feasibility study.

Purpose: Predicting the survival of patients diagnosed with glioblastoma (GBM) is essential to guide surgical strategy and subsequent adjuvant therapies. Intraoperative ultrasound (IOUS) can contain biological information that could be correlated with overall survival (OS). We propose a simple extraction method and radiomic feature analysis based on IOUS imaging to estimate OS in GBM patients.