Background: Pituitary adenomas rank third among adult intracranial tumors, with an incidence of 3.9– 7.4 cases/per 100,000 annually. Transsphenoidal surgery has evolved to include endoscopic endonasal surgery (EEA) in many centers due to technological and surgical advancements over the past two decades. We aim to analyze a 12-year cohort of pituitary adenomas operated through EEA, highlighting the evolution of surgical techniques and outcomes.Methods: A retrospective review of patients undergoing EEA was conducted. A team of an otolaryngologist and neurosurgeon performed surgeries. The cohort was divided into three groups: Phase 1 (P1, 2012–2015), Phase 2 (P2, 2016–2019), and Phase 3 (P3, 2020–2023). Patient demographics, clinical data, and outcomes were collected from electronic medical records and compared over time.Results: The mean age was 54.2 years, with 53.5% being female. The gross total resection rate was 75.6%, increasing from 62.3% in P1 to 76.3% in P3 (P= 0.003). The mean operative duration was 274.61 min, with no significant correlation to case number. Complication rates, excluding cerebrospinal fluid (CSF) leaks, were similar between the groups, with no statistically significant differences observed for complications such as visual deficit, cranial nerve palsy, and epistaxis. However, meningitis decreased significantly from 3.8% to 0.3% (P< 0.001). Intraoperative CSF leaks decreased from 65.1% to 55% (P= 0.003). The need for revision surgery was lower in P3 (8.5% vs. 5.4% vs. 2.1,P< 0.001). Length of hospitalization decreased from 5.3 days to 3.9 days (P< 0.001).Conclusion: Our experience with EEA for pituitary adenomas shows significant improvements in surgical outcomes, reduced complications, and better postoperative management, underscoring the importance of experience, technical refinement, and a multidisciplinary approach.

The insular cortex, a critical hub in the brain’s sensory, cognitive, and emotional networks, remains an intriguing subject of study. In this article, we discuss its intricate functional neuroanatomy, emphasizing its pivotal role in processing olfactory information. Through concise exploration, we delve into the insula’s diverse connectivity and its involvement in sensory integration, particularly in olfaction. Stimulation studies in humans reveal compelling insights into the insula’s contribution to the perception of smell, hinting at its broader implications for cognitive processing. Additionally, we explore an avenue of research in which studying olfactory processing via insular stimulation could unravel higher-level cognitive processes. This innovative approach could help give a fresh perspective on the interplay between sensory and cognitive domains, offering valuable insights into the neural mechanisms underlying cognition and emotion. In conclusion, future research efforts should emphasize a multidisciplinary approach, combining advanced imaging and surgical techniques to explore the intricate functions of the human insula. Moreover, awake craniotomies could offer a unique opportunity for real-time observation, shedding light on its neural circuitry and contributions to higher-order brain functions. Furthermore, olfaction’s direct cortical projection enables precise exploration of insular function, promising insights into cognitive and emotional processes. This multifaceted approach will deepen our understanding of the insular cortex and its significance in human cognition and emotion.

Background: Colloid cysts are intracranial lesions originating from abnormalities in the primitive neuroepithelium folding of the third ventricle. Various surgical approaches have been explored for the management of colloid cysts, each carrying its own set of advantages and limitations. Tubular retractors developed recently alleviate retraction pressure through radial distribution, potentially offering benefits for colloid cyst resection. This study aims to introduce and assess a modified microsurgical method utilizing the tubular retractor for addressing colloid cysts. Methods: The study included a retrospective assessment of patients who had colloid cysts and who were treated between 2015 and 2023 by one experienced surgeon. The demographic, clinical, radiological, histological, and surgical data regarding these patients were evaluated. The patients were assessed using the colloid cyst risk score, indicating a risk for obstructive hydrocephalus. Results: The minimally invasive microsurgical approach was successfully applied to all 22 identified patients. No postoperative surgical complications were reported. Gross total resection was achieved in 21 (95.5%) patients. The early complication rate was 22.7% (n = 5). There were no postoperative seizures, permanent neurological deficits, or venous injuries. The average hospital stay was 3 days. There was no evidence of recurrence at an average follow-up length of 25.9 months. Conclusion: The transtubular approach is an effective, safe method for treating colloid cysts. It achieves complete cyst removal with minimal complications, offering the benefits of less invasiveness, improved visualization, and reduced tissue disruption, strengthening its role in colloid cyst surgery.

Extraosseous Ewing sarcoma is a rare and aggressive malignancy belonging to the Ewing sarcoma family of tumors, primarily affecting soft tissues such as the pelvis, retroperitoneum, and chest wall. Although it predominantly involves these soft tissues, extraosseous Ewing sarcoma can also occur in solid organs, including the pancreas. Here, we present a rare case of a 4-year-old girl diagnosed with primary extraosseous Ewing sarcoma of the pancreas.

Background/Objective: Subarachnoid hemorrhage (SAH) is associated with high morbidity and mortality rates, necessitating prognostic algorithms to guide decisions. Our study evaluates the use of machine learning (ML) models for predicting 1-month and 1-year mortality among SAH patients using national electronic health records (EHR) system. Methods: Retrospective cohort of 29,274 SAH patients, identified through national EHR system from January 2017 to December 2022, was analyzed, with mortality data obtained from central civil registration system in Türkiye. Variables included (n = 102) pre- (n = 65) and post-admission (n = 37) data, such as patient demographics, clinical presentation, comorbidities, laboratory results, and complications. We employed logistic regression (LR), decision trees (DTs), random forests (RFs), and artificial neural networks (ANN). Model performance was evaluated using area under the curve (AUC), average precision, and accuracy. Feature significance analysis was conducted using LR. Results: The average age was 56.23 ± 16.45 years (47.8% female). The overall mortality rate was 22.8% at 1 month and 33.3% at 1 year. One-month mortality increased from 20.9% to 24.57% (p < 0.001), and 1-year mortality rose from 30.85% to 35.55% (p < 0.001) in the post-COVID period compared to the pre-COVID period. For 1-month mortality prediction, the ANN, LR, RF, and DT models achieved AUCs of 0.946, 0.942, 0.931, and 0.916, with accuracies of 0.905, 0.901, 0.893, and 0.885, respectively. For 1-year mortality, the AUCs were 0.941, 0.927, 0.926, and 0.907, with accuracies of 0.884, 0.875, 0.861, and 0.851, respectively. Key predictors of mortality included age, cardiopulmonary arrest, abnormal laboratory results (such as abnormal glucose and lactate levels) at presentation, and pre-existing comorbidities. Incorporating post-admission features (n = 37) alongside pre-admission features (n = 65) improved model performance for both 1-month and 1-year mortality predictions, with average AUC improvements of 0.093 ± 0.011 and 0.089 ± 0.012, respectively. Conclusions: Our study demonstrates the effectiveness of ML models in predicting mortality in SAH patients using big data. LR models’ robustness, interpretability, and feature significance analysis validate its importance. Including post-admission data significantly improved all models’ performances. Our results demonstrate the utility of big data analytics in population-level health outcomes studies.