OBJECTIVE: Acute Physiology and Chronic Health Evaluation II (APACHE II) is based on the data of intensive care unit (ICU) patients and often correlates with disease severity and prognosis. However, no prognostic predictors exist based on ICU admission data for patients with brain tumors, and no studies have reported an association between APACHE II and prognosis in patients with brain tumors. The Japanese Intensive Care Patients Database (JIPAD) was established to improve the quality of care delivered in intensive care medicine in Japan. We used JIPAD to examine factors associated with in-hospital mortality based on available data of postoperative patients with brain tumors admitted to the ICU.
METHODS: Patients aged ≥16 years enrolled in JIPAD between April 2015 and March 2018 after surgical brain tumor resection or biopsy of brain tumors. We examined factors related to outcomes at discharge based on blood tests and medical procedures performed during ICU admission, tumor type, and APACHE II score.
RESULTS: Among the 1454 patients (male:female ratio: 1:1.1, mean age: 62 years) in the study, 32 (2.2 %) died during hospital stay. In multivariate analysis, male sex (odds ratio [OR] 2.70, [95 % confidence interval, CI 1.22-6.00]), malignant tumor (OR 2.51 [95 % CI 1.13-5.55]), and APACHE II score ≥15 (OR 2.51 [95 % CI 3.08-14.3]) were significantly associated with in-hospital mortality.
CONCLUSIONS: By picking up cases with a high risk of in-hospital death at an early stage, it is possible to improve methods of treatment and support for the patient\'s family.

OBJECTIVE: Outpatient surgery and same-day discharge are developing fields that align with the evolving needs of modern healthcare, presenting a notable advantage by reducing patient susceptibility to nosocomial infections, thromboembolic complications, and medical errors. When paired with enhanced recovery after surgery protocols, they hold promise in safely transitioning certain patients undergoing cranial surgery to outpatient care. This study aimed to evaluate discharge on the same day of surgery after intracranial tumor resection and endoscopic third ventriculostomy (ETV) and to investigate potential associations with anesthesia methods, complications, and readmission rates.
METHODS: A retrospective analysis of patients scheduled for planned discharge on the same day of surgery between August 2020 and October 2023 was conducted. Data included patient demographic characteristics, preoperative clinical deficits, diagnosis, findings on preoperative and postoperative MRI, lesion characteristics, complications, and readmission rates.
RESULTS: A total of 202 patients were included in the study. The mean age was 56.8 years and 117 (57.9%) patients were female. Patients were admitted the evening before surgery to obtain preoperative clearance and undergo MRI. The most common diagnoses were metastasis (23.3%), meningioma (20.8%), glioblastoma (12.4%), and low-grade glioma (10.4%). Craniotomy (46.5%), stereotactic needle biopsy (35.1), and ETV (6.9%) were the most common procedures performed. Thirteen (6.4%) patients underwent awake craniotomy, and 189 (93.6%) surgical procedures were conducted under general anesthesia. Complications occurred in 1.5% of patients, with no permanent complications observed during a mean follow-up of 9.3 months. In total, 179 (88.6%) patients were successfully discharged on the same day of surgery. The median length of hospitalization was 26.8 hours, with the median length of postoperative stay being 7 hours. Twenty-three (11.4%) patients were deemed ineligible for discharge on postoperative day 0 and instead discharged on postoperative day 1. The reasons for these delays included further clinical monitoring (n = 12), social factors (n = 4), and patient preference (n = 7). Age was positively correlated with length of hospitalization (p = 0.006). In total, 6.4% of patients were readmitted within 1-30 days after discharge, with 2.5% readmitted to the department of neurosurgery.
CONCLUSIONS: This study demonstrates the safety and feasibility of discharge on the same day of surgery, with a high success rate and low complication rates. Early discharge did not increase morbidity or readmission rates. Implementation of clear discharge protocols and thorough patient education are crucial for successful same-day discharge programs in neurosurgery.

OBJECTIVE: This study aimed to investigate the efficacy of fine-tuned large language models (LLM) in classifying brain MRI reports into pretreatment, posttreatment, and nontumor cases.
METHODS: This retrospective study included 759, 284, and 164 brain MRI reports for training, validation, and test dataset. Radiologists stratified the reports into three groups: nontumor (group 1), posttreatment tumor (group 2), and pretreatment tumor (group 3) cases. A pretrained Bidirectional Encoder Representations from Transformers Japanese model was fine-tuned using the training dataset and evaluated on the validation dataset. The model which demonstrated the highest accuracy on the validation dataset was selected as the final model. Two additional radiologists were involved in classifying reports in the test datasets for the three groups. The model\'s performance on test dataset was compared to that of two radiologists.
RESULTS: The fine-tuned LLM attained an overall accuracy of 0.970 (95% CI: 0.930-0.990). The model\'s sensitivity for group 1/2/3 was 1.000/0.864/0.978. The model\'s specificity for group1/2/3 was 0.991/0.993/0.958. No statistically significant differences were found in terms of accuracy, sensitivity, and specificity between the LLM and human readers (p ≥ 0.371). The LLM completed the classification task approximately 20-26-fold faster than the radiologists. The area under the receiver operating characteristic curve for discriminating groups 2 and 3 from group 1 was 0.994 (95% CI: 0.982-1.000) and for discriminating group 3 from groups 1 and 2 was 0.992 (95% CI: 0.982-1.000).
CONCLUSIONS: Fine-tuned LLM demonstrated a comparable performance with radiologists in classifying brain MRI reports, while requiring substantially less time.

Pediatric high-grade gliomas are a devastating subset of brain tumors, characterized by their aggressive pathophysiology and limited treatment options. Among them, H3 K27-altered diffuse midline gliomas (DMG) of the brainstem stand out due to their distinct molecular features and dismal prognosis. Recent advances in molecular profiling techniques have unveiled the critical role of H3 K27 alterations, particularly a lysine-to-methionine mutation on position 27 (K27M) of the histone H3 tail, in the pathogenesis of DMG. These mutations result in epigenetic dysregulation, which leads to altered chromatin structure and gene expression patterns in DMG tumor cells, ultimately contributing to the aggressive phenotype of DMG. The exploration of targeted therapeutic avenues for DMG has gained momentum in recent years. Therapies, including epigenetic modifiers, kinase inhibitors, and immunotherapies, are under active investigation; these approaches aim to disrupt aberrant signaling cascades and overcome the various mechanisms of therapeutic resistance in DMG. Challenges, including blood-brain barrier penetration and DMG tumor heterogeneity, require innovative approaches to improve drug delivery and personalized treatment strategies. This review aims to provide a comprehensive overview of the evolving understanding of DMG, focusing on the intricate molecular mechanisms driving tumorigenesis/tumor progression and the current landscape of emerging targeted interventions.

UNASSIGNED: Brain tumor segmentation is highly contributive in diagnosing and treatment planning. Manual brain tumor delineation is a time-consuming and tedious task and varies depending on the radiologist\'s skill. Automated brain tumor segmentation is of high importance and does not depend on either inter- or intra-observation. The objective of this study is to automate the delineation of brain tumors from the Fluid-attenuated inversion recovery (FLAIR), T1-weighted (T1W), T2-weighted (T2W), and T1W contrast-enhanced (T1ce) magnetic resonance (MR) sequences through a deep learning approach, with a focus on determining which MR sequence alone or which combination thereof would lead to the highest accuracy therein.
UNASSIGNED: The BraTS-2020 challenge dataset, containing 370 subjects with four MR sequences and manually delineated tumor masks, is applied to train a residual neural network. This network is trained and assessed separately for each one of the MR sequences (single-channel input) and any combination thereof (dual- or multi-channel input).
UNASSIGNED: The quantitative assessment of the single-channel models reveals that the FLAIR sequence would yield higher segmentation accuracy compared to its counterparts with a 0.77 ± 0.10 Dice index. As to considering the dual-channel models, the model with FLAIR and T2W inputs yields a 0.80 ± 0.10 Dice index, exhibiting higher performance. The joint tumor segmentation on the entire four MR sequences yields the highest overall segmentation accuracy with a 0.82 ± 0.09 Dice index.
UNASSIGNED: The FLAIR MR sequence is considered the best choice for tumor segmentation on a single MR sequence, while the joint segmentation on the entire four MR sequences would yield higher tumor delineation accuracy.

Neuroscience is a swiftly progressing discipline that aims to unravel the intricate workings of the human brain and mind. Brain tumors, ranging from non-cancerous to malignant forms, pose a significant diagnostic challenge due to the presence of more than 100 distinct types. Effective treatment hinges on the precise detection and segmentation of these tumors early. We introduce a cutting-edge deep-learning approach employing a binary convolutional neural network (BCNN) to address this. This method is employed to segment the 10 most prevalent brain tumor types and is a significant improvement over current models restricted to only segmenting four types. Our methodology begins with acquiring MRI images, followed by a detailed preprocessing stage where images undergo binary conversion using an adaptive thresholding method and morphological operations. This prepares the data for the next step, which is segmentation. The segmentation identifies the tumor type and classifies it according to its grade (Grade I to Grade IV) and differentiates it from healthy brain tissue. We also curated a unique dataset comprising 6,600 brain MRI images specifically for this study. The overall performance achieved by our proposed model is 99.36%. The effectiveness of our model is underscored by its remarkable performance metrics, achieving 99.40% accuracy, 99.32% precision, 99.45% recall, and a 99.28% F-Measure in segmentation tasks.

BACKGROUND: The use of robot assisted laser interstitial thermal therapy (LITT) is emerging as a viable treatment option for brain tumors patients aged between 80-90 years (octogenarians). Correspondingly the aim of this study was to describe the clinical feasibility of octogenarians undergoing LITT procedure for brain tumors at our institution.
METHODS: A retrospective review was conducted of all robot assisted LITT procedures performed at our institution between 2013-2023 for octogenarians. Comparison of continuous variables was by student t-tests, and Kaplan-Meier estimates were used to estimate survival outcomes.
RESULTS: A total of 20/311 (6%) LITT patients in the search cohort were octogenarians. Mean age was 82.6 years (range, 80.1-88.0) with 13 (65%) females. Brain tumor lesions most commonly were located on the left side (65%), and for ablation, all were single trajectories with mean number of 2.3 ablations. No operative complications were seen during hospitalization, with mean length of stay of 1.6 days and most common disposition destination being home (95%). There were no 30- or 90-day readmissions or emergency room presentations. Mean follow-up was 12.4 months without any complications in that time. The most common pathology in our cohort was glioblastoma (GBM, 55%).
CONCLUSIONS: Robot assisted LITT is a safe and effective treatment option for brain tumors in octogenarians with a very low morbidity risk. Therefore, further investigations is required to understand how LITT can translate to therapeutic benefit in patients aged over 80 years old with brain tumors.

Posterior fossa group A (PFA) ependymoma is a lethal brain cancer diagnosed in infants and young children. The lack of driver events in the PFA linear genome led us to search its 3D genome for characteristic features. Here, we reconstructed 3D genomes from diverse childhood tumor types and uncovered a global topology in PFA that is highly reminiscent of stem and progenitor cells in a variety of human tissues. A remarkable feature exclusively present in PFA are type B ultra long-range interactions in PFAs (TULIPs), regions separated by great distances along the linear genome that interact with each other in the 3D nuclear space with surprising strength. TULIPs occur in all PFA samples and recur at predictable genomic coordinates, and their formation is induced by expression of EZHIP. The universality of TULIPs across PFA samples suggests a conservation of molecular principles that could be exploited therapeutically.

OBJECTIVE: People with primary malignant brain tumors experience serious health-related suffering caused by limited prognosis and high symptom burden. Consequently, neuro-oncological healthcare workers can be affected emotionally in a negative way. The aim of this study was to analyze the attitudes and behavior of nurses and physicians when confronted with spiritual distress in these patients.
METHODS: Neurospirit-DE is a qualitative vignette-based, multicenter, cross-sectional online survey that was conducted in Bavaria, Germany. Reflexive thematic analysis was used for data analysis.
RESULTS: A total of 143 nurses and physicians working in neurological and neurosurgical wards in 46 hospitals participated in the survey. The participants questioned if the ability to provide spiritual care can be learned or is a natural skill. Spiritual care as a responsibility of the whole team was highlighted, and the staff reflected on the appropriate way of involving spiritual care experts. The main limitations to spiritual care were a lack of time and not viewing spiritual engagement as part of the professional role. Some were able to personally benefit from spiritual conversations with patients, but many participants criticized the perceived emotional burden while expressing the imminent need for specific training and team reflection.
CONCLUSIONS: Most neuro-oncological nurses and physicians perceive spiritual care as part of their duty and know how to alleviate the patient\'s spiritual distress. Nonetheless, validation of spiritual assessment tools for neuro-oncology and standardized documentation of patients\' distress, shared interprofessional training, and reflection on the professional and personal challenges faced when confronted with spiritual care in neuro-oncology require further improvement and training.

BACKGROUND: The goal of surgical management in pediatric low-grade gliomas (pLGGs) is gross total resection (GTR), as it is considered curative with favorable long-term outcomes. Achieving GTR can be challenging in the setting of eloquent-region gliomas, in which resection may increase risk of neurological deficits. Awake craniotomy (AC) with intraoperative neurofunctional mapping (IONM) offers a promising approach to achieve maximal resection while preserving neurological function. However, its adoption in pediatric cases has been hindered, and barriers to its adoption have not previously been elucidated.
RESULTS: This review includes two complementary investigations. First, a survey study was conducted querying pediatric neurosurgeons on their perceived barriers to the procedure in children with pLGG. Next, these critical barriers were analyzed in the context of existing literature. These barriers included the lack of standardized IONM techniques for children, inadequate surgical and anesthesia experience, concerns regarding increased complication risks, doubts about children\'s ability to tolerate the procedure, and perceived non-indications due to alternative monitoring tools.
CONCLUSIONS: Efforts to overcome these barriers include standardizing IONM protocols, refining anesthesia management, enhancing patient preparation strategies, and challenging entrenched beliefs about pediatric AC. Collaborative interdisciplinary efforts and further studies are needed to establish safety guidelines and broaden the application of AC, ultimately improving outcomes for children with pLGG.