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. The primary objective was to assess the proficiency of nn-2D-IOUS in generating satisfactory image quality, identifying residual tumor tissue, and its influence on the extent of resection. To validate these results, early postoperative MRI data served as the reference standard. RESULTS: The nn-2D-IOUS exhibited a high level of effectiveness, successfully generating good quality images in 79% of the patients evaluated. With a sensitivity rate of 68% and a perfect specificity of 100%, nn-2D-IOUS unequivocally demonstrated its utility in intraoperative residual tumor detection. Notably, when total tumor removal was the surgical objective, a resection exceeding 95% of the initial tumor volume was achieved in 86% of patients. Additionally, patients in whom residual tumor was not detected by nn-2D-IOUS, the mean volume of undetected tumor tissue was remarkably minimal, averaging at 0.29 cm3. CONCLUSION: Our study supports nn-2D-IOUS's invaluable role in glioma surgery. The results highlight the utility of traditional technologies for enhanced surgical outcomes, even when compared to advanced alternatives. This is particularly relevant for resource-constrained settings and emphasizes optimizing existing tools for efficient patient care. NCT05873946 - 24/05/2023 - Retrospectively registered.

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. The dataset features expert-corrected segmentations of tumor subregions, offering valuable ground truth data for developing algorithms for postoperative and follow-up MRI scans.

Posterior cervical triangle approach for carotid endarterectomy: Technical note and results / El triángulo cervical posterior como abordaje en la endarterectomía carotídea: nota técnica y resultados

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. The surgical technique used was explained, and the complications and evolution of the patients were analysed. Results We found 7 CEAs performed through this approach, of which 2 presented transient trapezius paresis. There were no cases of severe complications in this series. Conclusion The PCT approach for performing CEA represents a useful and easy technique that avoids the need for mandibular mobilisation or osteotomies for lesions located in anatomically high carotid bifurcations (AU)

Introducción La endarterectomía carotídea (ECA) se suele realizar utilizando el triángulo cervical anterior como corredor quirúrgico, pero el espacio retromandibular dificulta en algunos casos la disección de estructuras de localización superior. El triángulo cervical posterior (TCP) puede ser útil en estos casos complejos. Métodos Se ha realizado un estudio retrospectivo de los casos atendidos en nuestra unidad utilizando el TCP como abordaje en ECA desde julio de 2013 hasta noviembre de 2019. Se explica la técnica quirúrgica empleada y se han revisado las complicaciones y evolución de los pacientes. Resultados Se realizaron 7 ECA a través de este abordaje. Dos pacientes presentaron paresia transitoria del trapecio. No hubo casos de complicaciones graves en esta serie. Conclusión El abordaje por el TCP para la realización de ECA representa una técnica útil y técnicamente simple, que evita procedimientos de movilización mandibular para lesiones localizadas en bifurcaciones carotídeas anatómicamente altas (AU)

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. This multi-institutional study included a retrospective analysis of patients diagnosed with glioblastoma who underwent surgery with complete resection of the enhancing tumor. Fifty-five patients met the selection criteria. The study sample was split into training (N = 40) and testing (N = 15) datasets. Follow-up MRI was used for ground truth definition, and postoperative structural multiparametric MRI was used to extract voxel-based radiomic features. Deformable coregistration was used to register the MRI sequences for each patient, followed by segmentation of the peritumoral region in the postoperative scan and the enhancing tumor in the follow-up scan. Peritumoral voxels overlapping with enhancing tumor voxels were labeled as recurrence, while non-overlapping voxels were labeled as nonrecurrence. Voxel-based radiomic features were extracted from the peritumoral region. Four machine learning-based classifiers were trained for recurrence prediction. A region-based evaluation approach was used for model evaluation. The Categorical Boosting (CatBoost) classifier obtained the best performance on the testing dataset with an average area under the curve (AUC) of 0.81 ± 0.09 and an accuracy of 0.84 ± 0.06, using region-based evaluation. There was a clear visual correspondence between predicted and actual recurrence regions. We have developed a method that accurately predicts the region of future tumor recurrence in MRI scans of glioblastoma patients. This could enable the adaptation of surgical and radiotherapy treatment to these areas to potentially prolong the survival of these patients.

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. The surgical technique used was explained, and the complications and evolution of the patients were analysed. RESULTS: We found 7 CEAs performed through this approach, of which 2 presented transient trapezius paresis. There were no cases of severe complications in this series. CONCLUSION: The PCT approach for performing CEA represents a useful and easy technique that avoids the need for mandibular mobilisation or osteotomies for lesions located in anatomically high carotid bifurcations.

Efficacy of percutaneous pedicle screws for thoracic and lumbar spine fractures compared with open technique.

BACKGROUND: The objective of this study is to compare percutaneous techniques (MIS) with the open technique in terms of angle correction, long-term maintenance and clinical results. METHODS: The authors collected a prospective database of thoraco-lumbar fractures treated with posterior stabilization without fusion from 2013 to 2019. The statistical analysis has been carried out retrospectively. The patients were classified into Open and MIS group. To compare the two population, samples, treatments and mitigate the differences between the groups, the propensity score (PS) matching was used. RESULTS: One hundred and eight patients with thoraco-lumbar fractures were included. After performing the PS, 21 patients were obtained in the open group and 28 in the MIS group. For operative and perioperative parameters there were no differences in number of patients with posterior decompression, number of instrumented segments, number of total screws, operative time and complications. Postoperative hemoglobin was similar in both groups. However, in the open group a greater loss of hemoglobin was observed; as well as, higher analgesia requirements and length of stay. No statistically significant differences were observed in neurological status in both groups in the preoperative, postoperative period and at follow-up. The Cobb angle showed no differences at admission comparing both groups. A similar angle correction was observed with both surgeries, but in open surgery there was a statistically significant loss of correction. CONCLUSIONS: We observed in this study that the MIS technique for the treatment of thoracolumbar fractures is as effective as the open technique in terms of angle correction; and demonstrated that is better in its maintenance over time. Clinical results were at least as good as with the open technique.

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. METHODS: We conducted a retrospective multicentric study of a consecutive cohort of patients with SAH. Demographic, clinical and radiological variables were analyzed. Preprocessed baseline CT scan images were used as the input for training using the AUCMEDI framework. Our model's architecture leveraged a DenseNet121 structure, employing transfer learning principles. The output variable was mortality in the first three months. RESULTS: Images from 219 patients were processed; 175 for training and validation and 44 for the model's evaluation. Of the patients, 52% (115/219) were female and the median age was 58 (SD = 13.06) years. In total, 18.5% (39/219) had idiopathic SAH. The mortality rate was 28.5% (63/219). The model showed good accuracy at predicting mortality in SAH patients when exclusively using the images of the initial CT scan (accuracy = 74%, F1 = 75% and AUC = 82%). CONCLUSION: Modern image processing techniques based on AI and CNN make it possible to predict mortality in SAH patients with high accuracy using CT scan images as the only input. These models might be optimized by including more data and patients, resulting in better training, development and performance on tasks that are beyond the skills of conventional clinical knowledge.

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

Background and Objectives: 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. In this article, we reviewed and discussed the most significant available research on survival estimation for GBM through advanced non-invasive methods. Materials and Methods: PubMed database was queried for articles reporting on survival prognosis for GBM through advanced image and data management methods. Articles including in their title or abstract the following terms were initially screened: ((glioma) AND (survival)) AND ((artificial intelligence) OR (radiomics)). Exclusively English full-text articles, reporting on humans, published as of 1 September 2022 were considered. Articles not reporting on overall survival, evaluating the effects of new therapies or including other tumors were excluded. Research with a radiomics-based methodology were evaluated using the radiomics quality score (RQS). Results: 382 articles were identified. After applying the inclusion criteria, 46 articles remained for further analysis. These articles were thoroughly assessed, summarized and discussed. The results of the RQS revealed some of the limitations of current radiomics investigation on this field. Limitations of analyzed studies included data availability, patient selection and heterogeneity of methodologies. Future challenges on this field are increasing data availability, improving the general understanding of how AI handles data and establishing solid correlations between image features and tumor's biology. Conclusions: Radiomics and AI methods of data processing offer a new paradigm of possibilities to tackle the question of survival prognosis in GBM.

Intraoperative Evaluation of Brain-Tumor Microvascularization through MicroV IOUS: A Protocol for Image Acquisition and Analysis of Radiomic Features.

Microvascular Doppler (MicroV) is a new-generation Doppler technique developed by Esaote (Esaote s.p.a., Genova, Italy), which is able to visualize small and low-flow vessels through a suppression of interfering signals. MicroV uses advanced filters that are able to differentiate tissue artifacts from low-speed blood flows; by exploiting the space-time coherence information, these filters can selectively suppress tissue components, preserving the signal coming from the microvascular flow. This technique is clinically applied to the study of the vascularization of parenchymatous lesions, often with better diagnostic accuracy than color/power Doppler techniques. The aim of this paper is to develop a reproducible protocol for the recording and collection of MicroV intraoperative ultrasound images by the use of a capable intraoperative ultrasound machine and post-processing aimed at evaluation of brain-tumor microvascularization through the analysis of radiomic features. The proposed protocol has been internally validated on eight patients and will be firstly applied to patients affected by WHO grade IV astrocytoma (glioblastoma-GBM) candidates for craniotomy and lesion removal. In a further stage, it will be generally applied to patients with primary or metastatic brain tumors. IOUS is performed before durotomy. Tumor microvascularization is evaluated using the MicroV Doppler technique and IOUS images are recorded, stored, and post-processed. IOUS images are remotely stored on the BraTIoUS database, which will promote international cooperation and multicentric analysis. Processed images and texture radiomic features are analyzed post-operatively using ImageJ, a free scientific image-analysis software based on the Sun-Java platform. Post-processing protocol is further described in-depth. The study of tumor microvascularization through advanced IOUS techniques such as MicroV could represent, in the future, a non-invasive and real-time method for intraoperative predictive evaluation of the tumor features. This evaluation could finally result in a deeper knowledge of brain-tumor behavior and in the on-going adaptation of the surgery with the improvement of surgical outcomes.

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. Methods: The literature was searched by using PubMed and Google Scholar databases. Eligibility criteria were randomized or quasi-experimental studies including at least five cases per arm and reporting duration of follow-up and number of lost cases. The end points were: angiographic success, final neurological outcome, and the need for retreatments. Results: We could only analyze four quasi-experimental studies with 398 uMCAAs. All of them compared clipping vs. coiling. Clipping showed better results than coiling in all analyzed end points. We could not conduct the proposed NMA because of the absence of randomized or quasi-experimental studies. Instead, a systematic review is further discussed. Conclusions: There is an urgent need for comparative studies on the treatment of 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. However, the ability of preoperative WM simulations to predict a surgical injury has not been thoroughly evaluated. Our objective was to assess the reliability of preoperatively simulated WM injuries for conventional neurosurgical procedures. METHODS: WM surgical damage was preoperatively simulated by creating a 3-dimensional volume representing the endoscope or the surgical trajectory. This volume was used as an additional region of interest in the fascicle reconstruction to be subtracted from the original fascicle. Simulated, injured fascicles were compared in terms of the number of fibers and volume to those created from postoperative DTI studies. Reliability was assimilated into the correlation between the simulation and the postoperative reconstruction; evaluated using the intraclass correlation coefficient or Lin's Concordance correlation coefficient (CCC), and represented on Bland-Altman plots. RESULTS: The preoperative and postoperative DTI studies of 30 patients undergoing various neurosurgical approaches were processed. The correlation between simulated injuries and postoperative studies was high in terms of fibers (Concordance correlation coefficient = Rho.C = 0.989 [95% confidence interval = 0.979-0.995]) and volume (intraclass correlation coefficient = 0.95 [95% CI = 0.89-0.97]). Bland-Altman plots demonstrated that the great majority of cases fell within the mean ± 2 Standard deviations. CONCLUSIONS: Presurgical simulation of WM fascicles based on DTI is consistent with postoperative DTI studies. These findings require further validation by neurophysiological and clinical correlation.

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. Concurrently with the start of massive vaccination in our region, we have observed a fivefold increase in the average incidence of bDAVFs. Our objective is to raise awareness of the potential involvement of COVID-19 vaccines in the pathogenesis of bDAVF. METHODS: A retrospective review of demographic, clinical, radiological, COVID-19 infection and vaccination data of patients diagnosed with bDAVFs between 2011 and 2021 was conducted. Patients were divided into two cohorts according to their belonging to pre- or post-COVID-19 vaccination times. Cohorts were compared for bDAVFs incidences and demographic and clinical features. RESULTS: Twenty-one bDAVFs were diagnosed between 2011 and 2021, 7 of which in 2021. The mean age was 57.7 years, and 62 % were males. All cases except one were treated; of them, 85 % exclusively managed with surgery. All treated cases were successfully occluded. The incidence in 2021 was significantly higher than that in the prevaccination period (1.72 vs 0.35/100,000/year;p = 0.036; 95 %Confidence Interval=0.09-2.66). Cohorts were not different in age, sex, hemorrhagic presentation, dural sinus thrombosis or presence of prothrombotic or cardiovascular risk factors. CONCLUSION: The significant increase in the incidence of bDAVF following general vaccination policies against COVID-19 observed in our region suggests a potential correlation between these two facts. Our findings need confirmation from larger cohorts and further pathogenic research.

Synthetic MRI improves radiomics-based glioblastoma survival prediction.

Glioblastoma is an aggressive and fast-growing brain tumor with poor prognosis. Predicting the expected survival of patients with glioblastoma is a key task for efficient treatment and surgery planning. Survival predictions could be enhanced by means of a radiomic system. However, these systems demand high numbers of multicontrast images, the acquisitions of which are time consuming, giving rise to patient discomfort and low healthcare system efficiency. Synthetic MRI could favor deployment of radiomic systems in the clinic by allowing practitioners not only to reduce acquisition time, but also to retrospectively complete databases or to replace artifacted images. In this work we analyze the replacement of an actually acquired MR weighted image by a synthesized version to predict survival of glioblastoma patients with a radiomic system. Each synthesized version was realistically generated from two acquired images with a deep learning synthetic MRI approach based on a convolutional neural network. Specifically, two weighted images were considered for the replacement one at a time, a T2w and a FLAIR, which were synthesized from the pairs T1w and FLAIR, and T1w and T2w, respectively. Furthermore, a radiomic system for survival prediction, which can classify patients into two groups (survival >480 days and ≤ 480 days), was built. Results show that the radiomic system fed with the synthesized image achieves similar performance compared with using the acquired one, and better performance than a model that does not include this image. Hence, our results confirm that synthetic MRI does add to glioblastoma survival prediction within a radiomics-based approach.

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. Cases with an ioUS strain elastography study were included. The elastograms were processed semiquantitatively, and the mean tissue elasticity (MTE) values were calculated from the histogram of intensities. An analysis was performed to correlate the histopathological groups and the tumor and peritumoral MTE values using the Kruskal-Wallis test and a decision tree classifier. Furthermore, elastogram quality was assessed to discuss possible artifacts and weaknesses of the ultrasound technique. RESULTS: One hundred two patients with the following histopathological diagnoses were analyzed: 43 high-grade gliomas, 11 low-grade gliomas, 28 meningiomas, and 20 metastases. The tumor MTE values were significantly different between the histopathological groups (P < .001). The decision tree classifier showed an area under the curve of 0.73 and a classification accuracy of 72%. The main technical limitations found in our series were the presence of artifacts after dural opening, the variability of the frequency and amplitude of the mechanical pulsations, and the challenge in evaluating deep lesions. CONCLUSION: Tumor stiffness revealed by ioUS strain elastography has a plausible histopathological correlation. Thus, this fast and versatile technique has enormous potential to be exploited in the coming years.

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. METHODS: A retrospective study of surgically treated glioblastomas between March 2018 and November 2019 was performed. Patients with IOUS B-mode and strain elastography were included. After preprocessing, segmentation and extraction of radiomic features were performed with LIFEx software. An evaluation of semantic segmentation was carried out using the Dice similarity coefficient (DSC). Using univariate correlations, radiomic features associated with OS were selected. Subsequently, survival analysis was conducted using Cox univariate regression and Kaplan-Meier curves. RESULTS: Sixteen patients were available for analysis. The DSC revealed excellent agreement for the segmentation of the tumour region. Of the 52 radiomic features, two texture features from B-mode (conventional mean and the grey-level zone length matrix/short-zone low grey-level emphasis [GLZLM_SZLGE]) and one texture feature from strain elastography (grey-level zone length matrix/long-zone high grey-level emphasis [GLZLM_LZHGE]) were significantly associated with OS. After establishing a cut-off point of the statistically significant radiomic features, we allocated patients in high- and low-risk groups. Kaplan-Meier curves revealed significant differences in OS. CONCLUSION: IOUS-based quantitative texture analysis in glioblastomas is feasible. Radiomic tumour region characteristics in B-mode and elastography appear to be significantly associated with OS.

Third Ventricle Volume Predicts Functional Outcome in Chronic Subdural Hematoma.

OBJECTIVES: There is a lack of evidence demonstrating the utility of computed tomography (CT) to predict chronic subdural hematoma (CSDH) clinical outcomes. We aim to analyze the role of tomographic volumetric analysis in patients with CSDH. METHODS: We performed a retrospective study of patients undergoing burr-hole craniostomy (BHC) for CSDH over five years at a tertiary care center. Degree of midline shift, radiographic density, subdural hematoma volume, acute blood volume, and third ventricle (3VV) and fourth ventricle (4VV) volume were estimated using semiautomatic segmentation of preoperative CT. Postoperative functional outcome was measured by two endpoints: National Institute of Health Stroke Scale (NIHSS) at discharge and short-term modified Rankin Scale (mRS) at 6-week follow-up. Univariate and multivariate analyses were performed using nonparametric tests. Discriminative capacity and optimal thresholds of independent variables were calculated by means of receiving-operative curves (ROC). RESULTS: A total of 79 patients were included for analysis with a median age of 78.5 years. Greater preoperative 3VV independently correlated with poor discharge NIHSS (p = .01) and short-term mRS (p = .03). A cutoff value of 0.545 mL demonstrated the highest sensitivity (77.1%) and specificity (88.8%) with an odds ratio for an mRS functional dependence of 9.29 (p = .001). CONCLUSIONS: Greater preoperative tomographic 3VV independently prognosticates poor discharge NIHSS and 6-week mRS. A threshold 3VV of 0.545 mL can be used to identify patients at higher risk of being dependent at first protocolized follow-up.

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. Preoperative structural multiparametric magnetic resonance imaging (mpMRI) sequences were pre-processed, and a total of 15,720 radiomic features were extracted. After feature reduction, machine learning-based classifiers were used to predict early mortality (<6 months). Additionally, a survival analysis was performed using the random survival forest (RSF) algorithm. A total of 203 patients were enrolled in this study. In the classification task, the naive Bayes classifier obtained the best results in the test data set, with an area under the curve (AUC) of 0.769 and classification accuracy of 80%. The RSF model allowed the stratification of patients into low- and high-risk groups. In the test data set, this model obtained values of C-Index = 0.61, IBS = 0.123 and integrated AUC at six months of 0.761. In this study, we developed a reliable predictive model of short-term survival in GBM by applying open-source and user-friendly computational means. These new tools will assist clinicians in adapting our therapeutic approach considering individual patient characteristics.

Evaluation of the reporting quality of clinical practice guidelines on gliomas using the RIGHT checklist.

BACKGROUND: The reporting quality of clinical practice guidelines (CPGs) for gliomas has not yet been thoroughly assessed. The International Reporting Items for Practice Guidelines in Healthcare (RIGHT) statement developed in 2016 provides a reporting framework to improve the quality of CPGs. We aimed to estimate the reporting quality of glioma guidelines using the RIGHT checklist and investigate how the reporting quality differs by selected characteristics. METHODS: We systematically searched electronic databases, guideline databases, and medical society websites to retrieve CPGs on glioma published between 2018 and 2020. We calculated the compliance of the CPGs to individual items, domains and the RIGHT checklist overall. We performed stratified analyses by publication year, country of development, reporting of funding, and impact factor (IF) of the journal. RESULTS: Our search revealed 20 eligible guidelines. Mean overall adherence to the RIGHT statement was 54.6%. Eight CPGs reported more than 60% of the items, and five reported less than 50%. All guidelines adhered to the items 1a, 3, 7a, 13a, while no guidelines reported the items 17 or 18b (see http://www.right-statement.org/right-statement/checklist for a description of the items). Two of the seven domains, "Basic information" and "Background", had mean reporting rates above 60%. The "Review and quality assurance" domain had the lowest mean reporting rate, 12.5%. The reporting quality of guidelines published in 2020, guidelines developed in the United States, and guidelines that reported funding tended to be above average. CONCLUSIONS: The reporting quality of CPGs on gliomas is low and needs improvement. Particular attention should be paid on reporting the external review and quality assurance process. The use of the RIGHT criteria should be encouraged to guide the development, reporting and evaluation of CPGs.

Extradural anterior clinoidectomy through endoscopic transorbital approach: laboratory investigation for surgical perspective.

BACKGROUND: The endoscopic transorbital approach (eTOA) is a new mini-invasive procedure used to explore different areas of the skull base. Authors propose an extradural anterior clinoidectomy (AC) through this corridor, defining the anatomical landmarks of the anterior clinoid process (ACP) projection onto the posterior orbit wall and the technical feasibility of this approach. We describe the exposure of the opticocarotid region and the surgical freedom and the angles of attack obtained with this novel approach. METHODS: Five cadaver heads underwent an eTOA at the Laboratory of Surgical Neuroanatomy of the University of Barcelona. A step-by-step description of the extradural endoscopic transorbital clinoidectomy was provided. A volumetric analysis of the morphometrics characteristics of the sphenoid wings was evaluated before and after dissection using CT scans. Pterional approach was performed to ascertain ACP removal. RESULTS: In all the specimens, it was possible to resect the ACP endo-orbitally aiming an optimal optic canal (OC) unroofing. The surface of the triangle corresponding to the ACP projection onto the posterior orbit wall was 0.42 ± 0.20 cm2. The drilled area to perform the extradural clinoidectomy via eTOA was 3.11 ± 2.27 cm2, and the volume of bone removal corresponding to the greater sphenoid wing (GSW) and lesser sphenoid wing (LSW) was 2.55 ± 1.41 and 0.26 ± 0.18 cm3 respectively. The area of surgical freedom provided by the eTOA was (3.11 ± 2.27cm2), and the angles of attack were 21.39 ± 9.13° in the horizontal axel and 30.63 ± 18.51° in the vertical. CONCLUSIONS: The described extradural anterior clinoidectomy by eTOA uses specific landmarks to localize the ACP on the posterior orbit wall. Resection of the ACP is a technically feasible approach, achieving the main goals of any clinoidectomy.