Search

Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

Mesial temporal lobe epilepsy (MTLE) is a common cause of seizures, and hippocampal sclerosis (HS) is the predominant subtype. BRAFV600E mutations in MTLE-HS have only been reported infrequently. Herein, we illustrate the neurologic, radiological, and histopathological details of a patient with MTLE-HS and BRAFV600E mutant neurons. A 31-year-old male with medically refractory epilepsy presented with magnetic resonance imaging (MRI) and electroencephalography (EEG) findings typical of mesial temporal sclerosis without a mass lesion. The surgical specimens showed ILAE Type 1 HS with neurons immunopositive for BRAFV600E mutant protein distributed along the Cornu Ammonis (CA) curvature. Instead of the normal mostly perpendicular orientation of pyramidal neurons relative to the hippocampal surface, the BRAF mutant neurons were often oriented in a parallel manner. On CD34 immunostaining, sparse clusters or nodules of CD34+ stellate cells and single immunopositive stellate cells were identified. BRAFV600E or CD34 immunopositive cells were less than 1 % of total cells. The patient responded well to surgery with no further seizures after 2 years and occasional auras. Hippocampal BRAF mutant non-expansive lesion (HBNL) has been used to describe such lesions with preserved cytoarchitecture and without overt tumor mass. Others may argue for the dual pathology of HS with early ganglioglioma. Whether pre-neoplastic lesions or early tumors, these cases are important for understanding early glioneuronal tumorigenesis and suggest that BRAFV600E studies should be routinely performed on MTLE-HS cases in the setting of clinical trials. With next-generation sequencing, a FANCL deletion was detected in almost half of the alleles in our case, suggesting that many of the histologically normal-appearing cells of the hippocampus contain this alteration. FANCL mutations can result in cytogenetic anomalies and defective DNA repair and therefore may underlie the development of a low frequency BRAF alteration.

We describe a case of a young patient with a recurrent pleomorphic xanthoastrocytoma (PXA) showing unusual cell-in-cell (CiC) phenomena. We observed mostly viable but also necrotic neutrophils engulfed within tumor cells. The recurrent tumor was immunopositive for BRAFV600E mutant protein and showed CDKN2 homozygous deletions typical of PXA. Both genetic alterations were also reported in the original primary tumor. Unlike the original tumor that was GFAP and Olig-2 immunopositive, the recurrent neoplasm was largely negative for GFAP and Olig-2 suggesting dedifferentiation. The large malignant cells that contained the neutrophils were negative for histiocytic and lymphohematopoietic markers. Whereas CDKN2 homozygous deletion is common in PXA, its presence is rare in histiocytic neoplasms. Both reactive astrocytes and glial neoplasms very rarely may engulf neutrophils in a process resembling emperipolesis or cellular cannibalism. Future work may clarify which type of CiC pathway is involved.

Craniopharyngiomas are tumors that arise from the remnants of Rathkes pouch along the nasopharynx to the diencephalon. Current standard of care includes maximal surgical resection versus adjuvant radiation if a maximal resection is unfeasible. Pharmacological therapy with MAPK targeted agents is an emerging therapeutic option for tumors with BRAF V600E mutations. We report a 45-year-old male with a strictly third ventricle papillary craniopharyngioma with a BRAF V600E mutation. After initial surgery with subtotal resection, the patient demonstrated durable response to targeted BRAF and MEK inhibitor therapy with vemurafenib and cobimetinib. Our report suggests that targeted therapy may reduce the need for radiation and impact surgical interventions in select cases.

The presence of a normal large blood vessel (LBV) in a tumor region can impact the evaluation of quantitative dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) parameters and tumor classification. Hence, there is a need for automatic removal of LBVs from brain tissues including intratumoral regions for achieving an objective assessment of tumors. This retrospective study included 103 histopathologically confirmed brain tumor patients who underwent MRI, including DCE‐MRI data acquisition. Quantitative DCE‐MRI analysis was performed for computing various parameters such as wash‐out slope (Slope‐2), relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), blood plasma volume fraction (Vp), and volume transfer constant (Ktrans). An approach based on data‐clustering algorithm, morphological operations, and quantitative DCE‐MRI maps was proposed for the segmentation of normal LBVs in brain tissues, including the tumor region. Here, three widely used data‐clustering algorithms were evaluated on two types of quantitative maps: (a) Slope‐2, and (b) a new proposed combination of rCBV and Slope‐2 maps. Fluid‐attenuated inversion recovery‐MRI hyperintense lesions were also automatically segmented using deep learning‐based architecture. The accuracy of LBV segmentation was qualitatively assessed blindly by two experienced observers, and Likert scoring was also obtained from each individual and compared using Cohen's Kappa test, and multiple statistical features from quantitative DCE‐MRI parameters were obtained in the segmented tumor. t‐test and receiver operating characteristic (ROC) curve analysis were performed for comparing the effect of removal of LBVs on parameters as well as on tumor grading. k‐means clustering exhibited better accuracy and computational efficiency. Tumors, in particular high‐grade gliomas (HGGs), showed a high contrast compared with normal tissues (relative % difference = 18.5%) on quantitative maps after the removal of LBVs. Statistical features (95th percentile values) of all parameters in the tumor region showed a statistically significant difference (p < 0.05) between with and without LBV maps. Similar results were obtained for the ROC curve analysis for differentiation between low‐grade gliomas and HGGs. Moreover, after the removal of LBVs, the rCBV, rCBF, and Vp maps show better visualization of tumor regions. [ABSTRACT FROM AUTHOR]

Applications of radiomics for clinical management of medulloblastomas are expanding. This systematic review aims to aggregate and overview the current role of radiomics in the diagnosis, subtyping, and prognostication of medulloblastomas. The present systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed/MEDLINE were searched using a standardized search term. Articles found within the database from the inception until November 2022 were considered for screening. Retrieved records were screened independently by two authors based on their titles and abstracts. The full text of selected articles was reviewed to finalize the eligibility. Due to the heterogeneity of included studies, no formal data synthesis was conducted. Of the 249 screened citations, 21 studies were included and analyzed. Radiomics demonstrated promising performance for discriminating medulloblastomas from other posterior fossa tumors, particularly ependymomas and pilocytic astrocytomas. It was also efficacious in determining the subtype (i.e., WNT+, SHH+, group 3, and group 4) of medulloblastomas non-invasively. Regarding prognostication, radiomics exhibited some ability to predict overall survival and progression-free survival of patients with medulloblastomas. Our systematic review revealed that radiomics represents a promising tool for diagnosis and prognostication of medulloblastomas. Further prospective research measuring the clinical value of radiomics in this setting is warranted. [ABSTRACT FROM AUTHOR]

Here, we report a case of antineutrophil cytoplasmic antibody (ANCA)‐associated central nervous system (CNS) vasculitis that mimicked a brain tumor. The patient presented with progressive right upper arm weakness. Brain magnetic resonance imaging (MRI) revealed large tumor‐like lesions in the left frontal and parietal lobes, with patchy and irregular enhancement with gadolinium and edema. Based on the clinical course and radiological findings, a brain tumor was suspected, and stereotactic brain biopsy was performed. Brain histopathology revealed necrotic tissue and lymphocyte infiltration around small vessels and blood vessel walls. Although the patient's clinical course and pathological findings suggested primary angiitis of CNS (PACNS), double staining for myeloperoxidase (MPO) and CD31 (a neutrophil marker) revealed infiltration of MPO‐positive neutrophils in the blood vessel walls. Therefore, we diagnosed the patient with ANCA‐associated CNS vasculitis. Because CNS vasculitis, including PACNS, presents nonspecific clinical findings and can depict brain tumor‐like MRI findings, CNS vasculitis should be carefully differentiated from brain tumors. Additionally, double staining for MPO and CD31 might be useful for evaluating the pathogenesis of CNS vasculitis. [ABSTRACT FROM AUTHOR]

Recently, deep learning has known a remarkable mutation in computer vision, which has been optimally exploited to solve various complex tasks and improve their results in the medical image analysis field, especially medical image segmentation (MIS). In this regard, convolution neural networks, particularly U-Net-based architectures, have been widely proposed to create several automatic systems for MIS. However, they are still constrained by certain limitations in terms of long-range context information because of the limited kernel size of the convolution layer, sensitivity to rotation and affine transformation, and the discard of the positional information due to the pooling operation. To address these limitations, transformers and capsule neural network have been utilized to model long-range contextual information based on the self-attention mechanism on the one hand and better representation learning based on dynamic routing algorithm on the other hand. To this end, we proposed a deep learning architecture for brain tumor segmentation called Swin transformer capsule pyramid U-Net. Indeed, the encoder consists of four hierarchical features extracted based on shifted window multi-head self-attention used in Swin transformers (ST) blocks. Next, the features are introduced to the proposed residual inception capsule pyramid network (RICapsPN) to encode each spatial relation of features in each encoder depth. Depending on the top-down connection between layers, this network builds a high-level semantic feature at all scales. Furthermore, RICapsPN used inception capsule blocks to test several capsule kernels and optimize the number of parameters. Additionally, the residual connection employed aims to consider the features extracted at each ST depth to enhance feature representation from the encoder part. Finally, the output of RICapsPN has been introduced to the ST decoder to get the final segmentation of different sub-regions of the brain tumor. The experiment results of our method showed a compelling performance on the BraTS 2020 dataset compared with the state-of-the-art methods by achieving 92.80 % , 85.63 % , and 80.14 % of dice similarity coefficient for the whole tumor, core tumor, and enhancing tumor sub-regions, respectively. Ablation experiments also indicate the effectiveness of the designed modules. [ABSTRACT FROM AUTHOR]

Objective: Brain tumors represent some of the most treatment refractory cancers, and there is a clinical need for additional treatments for these tumors. Domesticated dogs are the only other mammalian species which commonly develop spontaneous brain tumors, making them an ideal model for investigating novel therapies. Histotripsy is a non-thermal ultrasonic ablation method that emulsifies tissue through acoustic cavitation. The primary objectives of this prospective study were to assess the feasibility and safety of histotripsy to ablate naturally occurring canine brain tumors. Secondary endpoints included characterization of magnetic resonance imaging (MRI) responses to histotripsy treatment, and exploratory immunogenomic tumor response analyses. Methods: The study design utilized a treat and resect paradigm, where tumors were approached using craniotomy, partially ablated with histotripsy delivered through the cranial defect, imaged with MRI, and then resected. Dogs were evaluated with clinical, brain MRI, immunopathologic, and genomic examinations before treatment, intraoperatively, and 1, 14, and 42 days post-treatment. Here we report the results of the three dogs with meningiomas, all of which were treated with a custom eight element 1 MHz histotripsy transducer at a pulse repetition frequency of 100 Hz and a treatment dosage of 400 pulses/point. Results: Histotripsy was successfully delivered to all dogs, resulting in histopathologic evidence of ablations that were sharply demarcated from untreated tumor, with measured treatments approximating planned volumes in 2/3 dogs. One dog experienced an adverse event consisting of transient cerebral edema that was possibly attributable to histotripsy. Histotripsy ablations could be grossly visualized and identified on MRI, with features consistent with hemorrhage and necrosis. Significant expression or upregulation of the damage associated molecular pattern HMGB1, cytokine-cytokine receptor interaction, and NF-κb signaling pathways were observed in histotripsy treated tumors. Conclusion: Ablation of canine meningiomas with histotripsy through an open cranial window was feasible and clinically well tolerated. [ABSTRACT FROM AUTHOR]

Hyperlactatemia is common during tumor craniotomy, but the underlying pathophysiology is unclear. This study measured simultaneous arterial and jugular‐bulb lactate concentrations in patients undergoing brain tumor craniotomy to investigate the hypothesis that hyperlactatemia was associated with a net cerebrovascular lactate input. In 20 patients, arterial and jugular‐bulb blood was collected hourly from the start of surgery to 6 h postoperatively for measurement of lactate, glucose, and oxygen concentration. For each marker, data were analyzed using a linear mixed‐effects model with jugular‐bulb concentration as dependent variable, arterial concentration as fixed effect, and patient as random effect. Furthermore, we generated regression lines between arterial and jugular‐bulb concentrations. The slope of the regression line between arterial and jugular‐bulb lactate was 0.95 (95% CI 0.93–0.97, R2 = 0.98), indicating that increasing arterial lactate levels were associated with an increasingly positive net cerebrovascular balance (net input). The line crossed the identity line at 2.86 (95% CI 0.57–5.16) mmol/L, indicating that lower levels of lactate were associated with a negative net cerebrovascular balance (net output). This suggests a switch from net lactate output during normolactatemia towards net input during hyperlactatemia. Hyperlactatemia in tumor‐craniotomy patients probably does not originate from the brain. [ABSTRACT FROM AUTHOR]

Introduction: The authors conducted meta-analyses regarding the association between cellular and mobile phone use and brain tumor development by applying various radiofrequency-electromagnetic radiation (RF-EMR) exposure subcategories. With changing patterns of mobile phone use and rapidly developing Wireless Personal Area Network (WPAN) technology (such as Bluetooth), this study will provide insight into the importance of more precise exposure subcategories for RF-EMR. Methods: The medical librarian searched MEDLINE (PubMed), EMBASE, and the Cochrane Library until 16 December 2020. Results: In these meta-analyses, 19 case-control studies and five cohort studies were included. Ipsilateral users reported a pooled odds ratio (OR) of 1.40 (95% CI 1.21–1.62) compared to non-regular users. Users with years of use over 10 years reported a pooled OR of 1.27 (95% CI 1.08–1.48). When stratified by each type of brain tumor, only meningioma (OR 1.20 (95% CI 1.04–1.39)), glioma (OR 1.45 (95% CI 1.16–1.82)), and malignant brain tumors (OR 1.93 (95% CI 1.55–2.39)) showed an increased OR with statistical significance for ipsilateral users. For users with years of use over 10 years, only glioma (OR 1.32 (95% CI 1.01–1.71)) showed an increased OR with statistical significance. When 11 studies with an OR with cumulative hours of use over 896 h were synthesized, the pooled OR was 1.59 (95% CI 1.25–2.02). When stratified by each type of brain tumor, glioma, meningioma, and acoustic neuroma reported the pooled OR of 1.66 (95% CI 1.13–2.44), 1.29 (95% CI 1.08–1.54), and 1.84 (95% CI 0.78–4.37), respectively. For each individual study that considered cumulative hours of use, the highest OR for glioma, meningioma, and acoustic neuroma was 2.89 (1.41–5.93) (both side use, > 896 h), 2.57 (1.02–6.44) (both side use, > 896 h), and 3.53 (1.59–7.82) (ipsilateral use, > 1640 h), respectively. For five cohort studies, the pooled risk ratios (RRs) for all CNS tumors, glioma, meningioma, and acoustic neuroma, were statistically equivocal, respectively. However, the point estimates for acoustic neuroma showed a rather increased pooled RR for ever-use (1.26) and over 10 years of use (1.61) compared to never-use, respectively. Discussion: In this meta-analysis, as the exposure subcategory used became more concrete, the pooled ORs demonstrated higher values with statistical significance. Although the meta-analysis of cohort studies yielded statistically inconclusive pooled effect estimates, (i) as the number of studies included grows and (ii) as the applied exposure subcategories become more concrete, the pooled RRs could show a different aspect in future research. Additionally, future studies should thoroughly account for changing patterns in mobile phone use and the growing use of earphones or headphones with WPAN technology. [ABSTRACT FROM AUTHOR]

Background Objectives Animals Methods Results Conclusion and Clinical Importance Cerebral microbleeds (CMBs) are a possible sequela in human brain tumor patients treated with radiation therapy (RT). No such association is reported in dogs.To investigate whether CMBs occur in dogs after radiotherapy, and if there is an association between number and dose, and an increase over time.Thirty‐four client‐owned dogs irradiated for primary intracranial neoplasia. ≥2 magnetic resonance imaging (MRI) scans including susceptibility‐weighted imaging (SWI) were required.Retrospective, observational, single‐center study. Cerebral microbleeds identified on 3 T SWI were counted within the entire brain, and within low‐ (<20 Gy), intermediate‐ (20‐30 Gy), and high‐ (>30 Gy) dose regions. A generalized linear mixed‐effects model was used to analyze the relationship between the CMBs count and the predictor variables (irradiation dose, time after treatment).Median follow‐up time was 12.6 months (range, 1.8‐37.6 months). Eighty‐three MR scans were performed. In 4/15 dogs (27%, 95% CI, 10%‐52%) CMBs were present at baseline. ≥1 CMBs after RT were identified in 21/34 dogs (62%, 95% CI, 45%‐77%). With each month, the number of CMBs increased by 14% (95% CI, 11%‐16%; P < .001). The odds of developing CMBs in the high‐dose region are 4.7 times (95% CI, 3.9‐5.6; P < .001) greater compared with the low‐dose region.RT is 1 possible cause of CMBs formation in dogs. Cerebral microbleeds are most likely to occur in the peritumoral high‐dose volume, to be chronic, and to increase in number over time. Their clinical relevance remains unknown. [ABSTRACT FROM AUTHOR]

Brain tumors, a severe health concern across all age groups, present challenges for accurate grading in health monitoring and automated diagnosis. Choosing MRI scans for their superior quality and comprehensive anatomical insight, this study navigates the complexities of brain tumor classification. Deep learning (DL) algorithms revolutionize this field, empowering radiologists with enhanced diagnostic precision. Despite the pivotal role of extensive training data in DL success, medical image datasets often suffer from limitations in diversity and quantity. Transfer learning emerges as a solution, bridging gaps between similar yet distinct areas. The inadequacy of general pre-trained models on ImageNet for medical imaging characteristics prompts our recommendation for RadImageNet. This tailored solution aligns pre-trained models with the specific demands of medical imaging datasets, addressing the current mismatch. Our dataset includes 7023 MR images of Normal brain, Glioma, Meningioma, and Pituitary tumors. We employ two approaches: 'Feature Ensemble,' combining 2-top features, and 'Stacking Ensemble,' utilizing SVM, k-NN, Extra Trees, and MLP as base learners, and Logistic Regression (LR) as a meta-learner. In our initial approach with ResNet-50 and DenseNet121 features guided by MLP, we attained an impressive 97.71% accuracy and a remarkable Area Under the Curve (AUC) of 99.87%. Shifting to the Stacking Ensemble method, where DenseNet121 serves as the optimal feature extractor, we secured a commendable 97.40% accuracy, accompanied by an exceptional AUC of 99.83%. These outcomes highlight the efficacy of our ensemble learning strategies in enhancing both accuracy and the overall discriminative power of the model. [ABSTRACT FROM AUTHOR]

Originally devised for cancer control, mRNA vaccines have risen to the forefront of medicine as effective instruments for control of infectious disease, notably their pivotal role in combating the COVID-19 pandemic. This review focuses on fundamental aspects of the development of mRNA vaccines, e.g., tumor antigens, vector design, and precise delivery methodologies, - highlighting key technological advances. The recent, promising success of personalized mRNA vaccines against pancreatic cancer and melanoma illustrates the potential value for other intractable, immunologically resistant, solid tumors, such as glioblastoma, as well as the potential for synergies with a combinatorial, immunotherapeutic approach. The impact and progress in human cancer, including pancreatic cancer, head and neck cancer, bladder cancer are reviewed, as are lessons learned from first-in-human CAR-T cell, DNA and dendritic cell vaccines targeting glioblastoma. Going forward, a roadmap is provided for the transformative potential of mRNA vaccines to advance cancer immunotherapy, with a particular focus on the opportunities and challenges of glioblastoma. The current landscape of glioblastoma immunotherapy and gene therapy is reviewed with an eye to combinatorial approaches harnessing RNA science. Preliminary preclinical and clinical data supports the concept that mRNA vaccines could be a viable, novel approach to prolong survival in patients with glioblastoma. [ABSTRACT FROM AUTHOR]

Glioblastomas (GBMs) are the most common and aggressive malignant brain tumors, presenting significant challenges for treatment due to their invasive nature and localization in critical brain regions. Standard treatment includes surgical resection followed by radiation and adjuvant chemotherapy with temozolomide (TMZ). Recent advances in immunotherapy, including the use of mRNA vaccines, offer promising alternatives. This review focuses on the emerging use of mRNA vaccines for GBM treatment. We summarize recent advancements, evaluate current obstacles, and discuss notable successes in this field. Our analysis highlights that while mRNA vaccines have shown potential, their use in GBM treatment is still experimental. Ongoing research and clinical trials are essential to fully understand their therapeutic potential. Future developments in mRNA vaccine technology and insights into GBM-specific immune responses may lead to more targeted and effective treatments. Despite the promise, further research is crucial to validate and optimize the effectiveness of mRNA vaccines in combating GBM. [ABSTRACT FROM AUTHOR]

Background/Objectives: Functional MRI (fMRI) is widely used to assess language lateralization, but its application in patients with brain tumors can be hindered by cognitive impairments, compensatory neuroplasticity, and artifacts due to patient movement or severe aphasia. Gray matter volume (GMV) analysis via voxel-based morphometry (VBM) in language-related brain regions may offer a stable complementary approach. This study investigates the relationship between GMV and fMRI-derived language lateralization in healthy individuals and patients with left-hemisphere brain tumors, aiming to enhance accuracy in complex cases. Methods: The MRI data from 22 healthy participants and 28 individuals with left-hemisphere brain tumors were analyzed. Structural T1-weighted and functional images were obtained during three language tasks. Language lateralization was assessed based on activation in predefined regions of interest (ROIs), categorized as typical (left) or atypical (right or bilateral). The GMV in these ROIs was measured using VBM. Linear regressions explored GMV-lateralization associations, and logistic regressions predicted the lateralization based on the GMV. Results: In the healthy participants, typical left-hemispheric language dominance correlated with higher GMV in the left pars opercularis of the inferior frontal gyrus. The brain tumor participants with atypical lateralization showed increased GMV in six right-hemisphere ROIs. The GMV in the language ROIs predicted the fMRI language lateralization, with AUCs from 80.1% to 94.2% in the healthy participants and 78.3% to 92.6% in the tumor patients. Conclusions: GMV analysis in language-related ROIs effectively complements fMRI for assessing language dominance, particularly when fMRI is challenging. It correlates with language lateralization in both healthy individuals and brain tumor patients, highlighting its potential in preoperative language mapping. Further research with larger samples is needed to refine its clinical utility. [ABSTRACT FROM AUTHOR]

Background: Low-grade glioma is the most common brain tumor in children with different modes of treatment and a high overall survival. Low-grade glioma is considered a chronic disease, since residual tumor is present in many children. The tumor and its treatment lead to acquired brain injury with diverse consequences for later life based on factors like the diverse tumor locations, treatment(s) applied, neurofibromatosis type 1, and age at diagnosis. Methods: An overview of affected domains is provided based upon cohort studies from literature and partially based on clinical experience with a practical approach regarding each domain of functioning in order to provide insight in the requirements for long-term care assistance after childhood low-grade glioma. Results: The diverse domains that can potentially be affected are described as follows: motor function, speech, eating and swallowing, sensory functions, seizures, neuropathy, organ function after systemic treatment, late effects due to cranial radiation (vascular changes and secondary tumors, endocrine and hypothalamic function, sleep and energy, neuro-cognition and education, psychosocial effects, and quality of life. Conclusion: Insight in affected domains guides advices for medical follow-up, diagnostics, supportive instructions, and assistive measures per domain of functioning and provide insight in the requirements for long-term care assistance after childhood low-grade glioma. [ABSTRACT FROM AUTHOR]

Pediatric brain tumors, particularly those affecting the brainstem, present a significant challenge due to their intricate anatomical location and diverse classification. This review explores the classification, anatomical considerations, and surgical approaches for pediatric brainstem tumors, focusing on recent updates from the World Health Organization (WHO) classification. Brainstem tumors encompass a spectrum from diffuse gliomas to focal intrinsic and exophytic types, each presenting unique clinical and surgical challenges. Surgical strategies have evolved with advancements in neuroimaging and surgical techniques, emphasizing approaches such as neuroendoscopy and tailored incisions to minimize damage to critical structures. Despite the complexities involved, recent developments offer promising outcomes in tumor resection and patient management, highlighting ongoing advancements in neurosurgical care for pediatric brain tumors. [ABSTRACT FROM AUTHOR]

Introduction: 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. Findings: 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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

The relationship between meningiomas and gonadal steroid hormones has been the subject of debate, and there is limited understanding of the connection between patient, tumor characteristics, and progesterone receptor (PGR) status. This retrospective observational study aims to explore the prognostic correlation between PGR+ and PGR-meningiomas in terms of various clinical, radiological, and surgical predictors. The analysis included 270 patients, divided into 2 groups: group A (PGR-, 194 patients), and group B (PGR+, 76 patients). The analysis showed no significant differences in terms of age, sex, clinical debut, postsurgical complications, total resection, and grading between the 2 groups. However, a significant difference was observed in the mean Karnofsky performance status at all stages of follow-up. Peritumoral edema measured in preoperative magnetic resonance imaging significantly influences the value of Karnofsky performance status in both preoperative (ANOVA, P = 0.05) and postoperative evaluation (postoperative ANOVA, P = 0.014) only in group A. In the multivariate analysis, there are no significant factors related to the clinical, biological, and surgical parameters previously examined for each measurement time (P = 0.826). The study found that PGR + meningioma patients tend to have better postoperative recovery and earlier clinical debut without any association with age prevalence or grading. [ABSTRACT FROM AUTHOR]

Serum albumin reflects nutritional status and is associated with postoperative complications and mortality. Delta albumin (ΔAlb), defined as the difference between preoperative and lowest postoperative levels, could predict complications and mortality, even with postoperative levels above 30 g/L prompting albumin infusions. This study aimed to assess how ΔAlb relates to outcomes in craniotomy patients with brain tumors. This retrospective study screened patients diagnosed with a brain tumor who underwent cerebral surgery from a single Chinese hospital between December 2010 and April 2021. Patients were divided into 4 groups based on their ΔAlb levels: <5 g/L (normal), 5–9.9 g/L (mild ΔAlb), 10–14.9 g/L (moderate ΔAlb), and ≥15 g/L (severe ΔAlb). The primary outcome was postoperative 30-day mortality. Among the 9660 patients undergoing craniotomy for brain tumors, the median ΔAlb level after craniotomy was 7.3 g/L. ΔAlb was associated with increased postoperative 30-day mortality; odds ratios for mild, moderate, and severe ΔAlb were 1.93 (95% confidence interval [CI], 1.17–3.18, P = 0.01), 2.21 (95% CI, 1.28–3.79, P = 0.004), and 7.26 (95% CI, 4.19–12.58, P < 0.01), respectively. Significantly, ΔAlb >5 g/L was found to have a strong association with a higher risk of mortality, even when the nadir Alb remained greater than 30 g/L (odds ratio, 1.84; 95% CI, 1.13–3.00, P = 0.014). Among patients undergoing craniotomy for brain tumor resection, a mild degree of ΔAlb was associated with increased 30-day mortality, even if the nadir Alb remained greater than 30 g/L. Moreover, ΔAlb was associated with postoperative complications and longer lengths of stay. [ABSTRACT FROM AUTHOR]

We aimed to identify socioeconomic gaps in the administration of adjuvant radiotherapy (RT) for patients with atypical meningioma (AM) and secondarily to determine differences in survival between patients receiving radiation and those not receiving radiation at 12 and 60 months. The National Cancer Database was queried for patients receiving AM surgery between 2004 and 2019. Statistical analyses were performed to assess the association between receipt of adjuvant radiation and social determinants. Secondarily, Kaplan-Meir curves were used to compare overall patient survival between those that received radiation and those that did not. Adjuvant radiation was less likely to be administered to patients over 65 (95% confidence interval [CI] = 0.53–22 0.77) and more likely to be administered to males (95% CI = 1.07–1.38). Compared to the Southern USA, patients were more likely to receive RT in the Northeastern (95% CI 24 = 1.40–2.05), Midwestern (95% CI = 1.06–1.54), and Western parts of the USA (95% 25 CI = 1.31–2.00). Patients residing furthest from their facility were less likely to receive radiation (95% CI = 0.65–0.98). Insured patients were more likely to receive radiation (P = 0.048) than uninsured patients. On multivariate analysis, no differences were found between racial groups regarding adjuvant radiation. For patients unstratified, radiation was shown to improve survival at 12 and 60 months. Disparities exist in the administration of adjuvant RT for AM. Patients over 65, women, those residing in the Southern USA, those living further from their facilities and uninsured patients are less likely to receive radiation than their counterparts. [ABSTRACT FROM AUTHOR]

In recent years, various drug delivery systems circumventing the blood–brain barrier have emerged for treating brain tumors. This study aimed to improve the efficacy of brain tumor treatment in boron neutron capture therapy (BNCT) using cerebrospinal fluid (CSF) circulation to deliver boronophenylalanine (BPA) to targeted tumors. Previous experiments have demonstrated that boron accumulation in the brain cells of normal rats remains comparable to that after intravenous (IV) administration, despite BPA being administered via CSF at significantly lower doses (approximately 1/90 of IV doses). Based on these findings, BNCT was conducted on glioma model rats at the Kyoto University Research Reactor Institute (KUR), with BPA administered via CSF. This method involved implanting C6 cells into the brains of 8-week-old Wistar rats, followed by administering BPA and neutron irradiation after a 10-day period. In this study, the rats were divided into four groups: one receiving CSF administration, another receiving IV administration, and two control groups without BPA administration, with one subjected to neutron irradiation and the other not. In the CSF administration group, BPA was infused from the cisterna magna at 8 mg/kg/h for 2 h, while in the IV administration group, BPA was intravenously administered at 350 mg/kg via the tail vein over 1.5 h. Thermal neutron irradiation (5 MW) for 20 min, with an average fluence of 3.8 × 1012/cm2, was conducted at KUR's heavy water neutron irradiation facility. Subsequently, all of the rats were monitored under identical conditions for 7 days, with pre- and post-irradiation tumor size assessed through MRI and pathological examination. The results indicate a remarkable therapeutic efficacy in both BPA-administered groups (CSF and IV). Notably, the rats treated with CSF administration exhibited diminished BPA accumulation in normal tissue compared to those treated with IV administration, alongside maintaining excellent overall health. Thus, CSF-based BPA administration holds promise as a novel drug delivery mechanism in BNCT. [ABSTRACT FROM AUTHOR]

Germ cell tumors (GCTs) are categorized as gonadal or extra‐gonadal, based on the origin. Extra‐gonadal GCTs predominantly manifest within the central nervous system (CNS), mediastinum, retroperitoneum, and sacrococcygeal region. These malignancies are most frequently diagnosed in the pediatric, adolescent, and young adult demographics. Incidences of GCT within the nasal cavity are notably scarce, with only six cases documented. This report details the case of a 70‐year‐old man who presented with a left nasal mass ultimately diagnosed as immature teratoma. A remarkable aspect of this case was the detection of SMARCA4 (BRG1) loss through immunohistochemical analysis. In addition, methylation profiling aligned this case with CNS GCTs, specifically those classified as non‐germinomatous GCTs. This molecular characterization informed a tailored therapeutic strategy incorporating carboplatin and etoposide, alongside localized irradiation. This individualized treatment regimen achieved favorable outcomes, with the patient remaining recurrence free for over three years. This highlights the need for precise therapeutic approaches in the management of extragonadal GCTs, particularly those arising in atypical anatomical locations. The present case accentuates the significance of thorough diagnostic evaluations and customized treatment plans for rare GCT presentations. Further empirical and clinical investigations are warranted to enhance our understanding of and refine therapeutic protocols for such exceptional cases. [ABSTRACT FROM AUTHOR]

Nerves and blood vessels must be protected during brain tumor surgery, which has traditionally relied on microscopes. In the 2000s, endoscopes and related equipment were developed for neurosurgery. In this review, we aim to outline the role of endoscopes in brain tumor surgery and discuss the emerging use of exoscopes. The primary use of endoscopes in brain tumor surgery is in endoscopic endonasal surgery for pituitary tumors. By using the space within the sphenoid sinus, surgeons can insert an endoscope and instruments such as forceps or scissors through the nose to access and remove the tumor. Compared to microscopes, endoscopes can get closer to tumors, nerves, and blood vessels. They enable wide-angle observation of the skull base, making them valuable for skull base tumors as well as pituitary tumors. Endoscopes are also used in cases where a brain tumor is associated with hydrocephalus, allowing surgeons to correct obstructive hydrocephalus and perform tumor biopsies simultaneously. Exoscopy, a newer technique introduced in recent years, involves surgeons wearing special glasses and removing the tumor while viewing a three-dimensional monitor. This approach reduces surgeon fatigue and allows for more natural positioning during lengthy brain tumor surgeries. Future brain tumor surgeries will likely involve robotic surgery, which is already used for other organs. This is expected to make brain tumor removal safer and more accurate. [ABSTRACT FROM AUTHOR]

Background Sleep–wake disturbances are common and disabling in primary brain tumor (PBT) patients but studies exploring longitudinal data are limited. This study investigates the feasibility and relationship between longitudinal patient-reported outcomes (PROs) and physiologic data collected via smart wearables. Methods Fifty-four PBT patients ≥ 18 years wore Fitbit smart-wearable devices for 4 weeks, which captured physiologic sleep measures (eg, total sleep time, wake after sleep onset [WASO]). They completed PROs (sleep hygiene index, PROMIS sleep-related impairment [SRI] and Sleep Disturbance [SD], Morningness-Eveningness Questionnaire [MEQ]) at baseline and 4 weeks. Smart wearable use feasibility (enrollment/attrition, data missingness), clinical characteristics, test consistency, PROs severity, and relationships between PROs and physiologic sleep measures were assessed. Results The majority (72%) wore their Fitbit for the entire study duration with 89% missing < 3 days, no participant withdrawals, and 100% PRO completion. PROMIS SRI/SD and MEQ were all consistent/reliable (Cronbach's alpha 0.74–0.92). Chronotype breakdown showed 39% morning, 56% intermediate, and only 6% evening types. Moderate-severe SD and SRI were reported in 13% and 17% at baseline, and with significant improvement in SD at 4 weeks (P  = .014). Fitbit-recorded measures showed a correlation at week 4 between WASO and SD (r  = 0.35, P  = .009) but not with SRI (r  = 0.24, P  = .08). Conclusions Collecting sleep data with Fitbits is feasible, PROs are consistent/reliable, > 10% of participants had SD and SRI that improved with smart wearable use, and SD was associated with WASO. The skewed chronotype distribution, risk and impact of sleep fragmentation mechanisms warrant further investigation. Trial Registration NCT04 669 574 [ABSTRACT FROM AUTHOR]

Background Minimal clinically important differences (MCIDs) quantify the clinical relevance of quality of life results at the individual patient and group level. The aim of this study was to estimate the MCID for the Brief Fatigue Inventory (BFI) and the Worst and Usual Fatigue items in patients with brain or CNS cancer undergoing curative radiotherapy. Methods Data from a multi-site prospective registry was used. The MCID was calculated using distribution-based and anchor-based approaches. For the anchor-based approach, the fatigue item from the PROMIS-10 served as the anchor to determine if a patient improved, deteriorated, or had no change from baseline to end of treatment (EOT). We compared the unadjusted means on the BFI for the 3 groups to calculate the MCID. For the distribution-based approaches, we calculated the MCID as 0.5 SD of the scores and as 1.96 times the standard error of measurement. Results Three-hundred and fifty nine patients with brain or CNS tumors undergoing curative radiotherapy filled out the 9-item BFI at baseline and EOT. The MCID for the BFI was 1.33 (ranging from 0.99 to 1.70 across the approaches), 1.51 (ranging from 1.16 to 2.02) and 1.76 (ranging from 1.38 to 2.14) for the usual and worst fatigue items, respectively. Conclusions This study provides the MCID ranges for the BFI and Worst and Usual fatigue items, which will allow clinically meaningful conclusions to be drawn from BFI scores. These results can be used to select optimal treatments for patients with brain or CNS cancer or to interpret BFI scores from clinical trials. [ABSTRACT FROM AUTHOR]

An accurate diagnosis of the type of brain tumor is crucial for experts to choose the best course of therapy and increase the patient's lifetime. The manual categorization of brain tumors in Magnetic resonance imaging (MRI) with similar structures or appearances can be complex and relies on expertise. Also, brain MRI contains a significant number of redundant or irrelevant features, and classification algorithms struggle to detect patterns without feature selection. By selecting prominent features, the machine-learning model can produce a high level of predicted accuracy in medical diagnostic problems. In this paper, an improved ant lion optimization approach (IALO) is developed to select the optimal features for wrapper-mode classification. Initially, pre-processing is carried out to remove bias and noise. Tumor segmentation is performed using active contours driven by Laplacian of Gaussian energy and optimal region scalable fitting energy. From the segmented brain images, hand-crafted features are extracted using the Histogram of Oriented Gradient, Gray level co-occurrence matrix, Gray level run length matrix, and deep features are extracted using the ResNet50. The proposed IALO is employed for the selection of the best features from handcrafted and deep features. The final step was to classify brain tumors using Support Vector Machines, Naive Bayes, and Recurrent Neural Networks. The proposed IALO-based RNN exhibited enhanced accuracy of 99.59% for BRATS and 99.18% for J.Cheng brain images respectively. From the experimental results, it is observed that our proposed model outperforms the existing metaheuristic optimization algorithms and effectively removes the least significant features while improving classification accuracy. [ABSTRACT FROM AUTHOR]

Objective: To examine the efficacy and safety of perampanel (PER) in patients with post‐stroke epilepsy (PSE), brain tumor‐related epilepsy (BTRE), and post‐traumatic epilepsy (PTE) using Japanese real‐world data. Methods: The prospective post‐marketing observational study included patients with focal seizures with or without focal to bilateral tonic–clonic seizures who received PER combination therapy. The observation period was 24 or 52 weeks after the initial PER administration. The safety and efficacy analysis included 3716 and 3272 patients, respectively. This post hoc analysis examined responder rate (50% reduction in seizure frequency), seizure‐free rate (proportion of patients who achieved seizure‐free), and safety in patients included in the post‐marketing study who had PSE, BTRE, and PTE in the 4 weeks prior to the last observation. Results: Overall, 402, 272, and 186 patients were included in the PSE, BTRE, and PTE subpopulations, and 2867 controls in the "Other" population (etiologies other than PSE, BTRE, or PTE). Mean modal dose (the most frequently administered dose) values at 52 weeks were 3.38, 3.36, 3.64, and 4.04 mg/day for PSE, BTRE, PTE, and "Other," respectively; PER retention rates were 56.2%, 54.0%, 52.6%, and 59.7%, respectively. Responder rates (% [95% confidence interval]) were 82% (76.3%–86.5%), 78% (70.8%–83.7%), 67% (56.8%–75.6%), and 50% (47.9%–52.7%) for PSE, BTRE, PTE, and "Other," respectively, and seizure‐free rates were 71% (64.5%–76.5%), 62% (54.1%–69.0%), 50% (40.6%–60.4%), and 28% (25.8%–30.1%), respectively. Adverse drug reactions tended to occur less frequently in the PSE (14.7%), BTRE (16.5%), and PTE (16.7%) subpopulations than in the "Other" population (26.3%). Significance: In real‐world clinical conditions, efficacy and tolerability for PER combination therapy were observed at low PER doses for the PSE, BTRE, and PTE subpopulations. Plain Language Summary: To find out how well the medication perampanel works and whether it is safe for people who have epilepsy after having had a stroke, brain tumor, or head injury, we used information from real‐life medical situations in Japan. We looked at the data of about 3700 Japanese patients with epilepsy who were treated with perampanel. We found that perampanel was used at lower doses and better at controlling seizures, and had fewer side effects for patients with epilepsy caused by these etiologies than the control group. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this prospective, single-centre case series was to investigate feasibility, clinical outcomes, and neural correlates of non-invasive Neuromodulation-Induced Cortical Prehabilitation (NICP) before brain tumor surgery. Previous studies have shown that gross total resection is paramount to increase life expectancy but is counterbalanced by the need of preserving critical functional areas. NICP aims at expanding functional margins for extensive tumor resection without functional sequelae. Invasive NICP (intracranial neuromodulation) was effective but characterized by elevated costs and high rate of adverse events. Non-invasive NICP (transcranial neuromodulation) may represent a more feasible alternative. Nonetheless, up to this point, non-invasive NICP has been examined in only two case reports, yielding inconclusive findings. Methods: Treatment sessions consisted of non-invasive neuromodulation, to transiently deactivate critical areas adjacent to the lesion, coupled with intensive functional training, to activate alternative nodes within the same functional network. Patients were evaluated pre-NICP, post-NICP, and at follow-up post-surgery. Results: Ten patients performed the intervention. Feasibility criteria were met (retention, adherence, safety, and patient's satisfaction). Clinical outcomes showed overall stability and improvements in motor and executive function from pre- to post-NICP, and at follow-up. Relevant plasticity changes (increase in the distance between tumor and critical area) were observed when the neuromodulation target was guided by functional neuroimaging data. Conclusion: This is the first case series demonstrating feasibility of non-invasive NICP. Neural correlates indicate that neuroimaging-guided target selection may represent a valid strategy to leverage neuroplastic changes before neurosurgery. Further investigations are needed to confirm such preliminary findings. [ABSTRACT FROM AUTHOR]

Background: Reliable quantification of the association between hypertension requiring medication and postoperative 30-day mortality in adult patients who undergo craniotomy for tumor resection is limited. We aimed to explore the associations between these factors. Materials and methods: This work was a retrospective cohort study that used propensity score matching (PSM) among 18,642 participants from the American College of Surgeons National Surgical Quality Improvement Program database between 2012 and 2015. Hypertension requiring medication and postoperative 30-day mortality were the independent and dependent target variables, respectively. PSM was conducted via nonparsimonious multivariate logistic regression to balance the confounders. Robust estimation methods were used to investigate the association between hypertension requiring medication and postoperative 30-day mortality. Results: A total of 18,642 participants (52.6% male and 47.4% female) met our inclusion criteria; 7,116 (38.17%) participants with hypertension required medication and had a 3.74% mortality rate versus an overall mortality rate of 2.46% in the adult cohort of patients who underwent craniotomy for tumor resection. In the PSM cohort, the risk of postoperative 30-day mortality significantly increased by 39.0% among patients with hypertension who required medication (OR = 1.390, 95% confidence interval (CI): 1.071-1.804, p = 0.01324) after adjusting for the full covariates. Compared with participants without hypertension requiring medication, those with hypertension requiring medication had a 34.0% greater risk of postoperative 30-day mortality after adjusting for the propensity score (OR = 1.340, 95% CI: 1.040-1.727, p = 0.02366) and a 37.6% greater risk of postoperative 30-day mortality in the inverse probability of treatment weights (IPTW) cohort (OR = 1.376, 95% CI: 1.202, 1.576, p < 0.00001). Conclusion: Among U.S. adult patients undergoing craniotomy for tumor resection, hypertension requiring medication is a notable contributor to 30-day mortality after surgery, with odds ratios ranging from 1.34 to 1.39. [ABSTRACT FROM AUTHOR]

Purpose: To investigate glymphatic system function in patients with brain tumors, including both primary and secondary tumors, using diffusion tensor imaging along perivascular spaces (DTI-ALPS). Methods: We retrospectively analyzed the MR DTI of 24 patients with unilateral brain tumors and compared them with age and sex-matched controls. We compared the DTI-ALPS index of the ipsi- and contralateral brain hemispheres. The region of interest was placed in the periventricular vessels adjacent to the lateral ventricles. Differences between sex, age, and kind of tumor (primary or brain metastasis) were evaluated. Correlations between DTI-ALPS index and age and the tumor's apparent diffusion coefficient (ADC) were also investigated. Results: The DTI-ALPS index was significantly lower (p < 0.05) in the tumor-affected hemisphere (mean = 1.26 ± 0.24) than contralateral (mean = 1.43 ± 0.28). A comparison with healthy controls revealed no significant difference on the matched ipsilateral side. However, the DTI-ALPS index of the contralateral side of the patients was larger than the HC. Additionally, no statistically significant differences were found when analyzing the DTI-ALPS index vs. age, sex, and tumor entity. Additionally, we did not find a correlation between the DTI-ALPS index and patient age or tumor ADC. Conclusion: The decreased DTI-ALPS index in the tumor-affected hemisphere may be related to impaired glymphatic system function. However, cancer is often a systemic disease; thus, the DTI-ALPS index from the contralateral brain hemisphere may not generally be considered as a normal control. Nonetheless, the DTI-ALPS index does not only reflect diffusion in the perivascular spaces but it can also be influenced by factors such as axonal degeneration. Therefore, it does not directly reflect brain waste clearance and changes in the index should be interpreted carefully. [ABSTRACT FROM AUTHOR]

Brain tumor is a condition due to the expansion of abnormal cell growth. Tumors are rare and can take many forms; it is challenging to estimate the survival rate of a patient. These tumors are found using Magnetic Resonance (MRI) which is crucial for locating the tumor region. Moreover, manual identification is an extensive and difficult method to produce false positives. The research communities have adopted computer-aided methods to overcome these limitations. With the advancement of artificial intelligence (AI), brain tumor prediction relies on MR images and deep learning (DL) models in medical imaging. The suggested layered configurations, i.e., layered network model, are proposed to classify and detect brain tumors accurately. The modified CNN is proposed to automatically detect the important features without any supervision and the convolution layer present in the network model enhances the training feasibility. To improve the quality of the images, some essential preprocessing is used in conjunction with image-enhancing methods. Data augmentation is adopted to expand the number of data samples for our suggested model's training. The Dataset is portioned as based on 70% for training and 30% for testing. The findings demonstrate that the proposed model works well than existing models in classification precision, accuracy, recall, and area under the curve. The layered network model beats other CNN models and achieves an overall accuracy of 99% during prediction. In addition, VGG16, hybrid CNN and NADE, CNN, CNN and KELM, deep CNN with data augmentation, CNN-GA, hybrid VGG16-NADE and ResNet+SE approaches are used for comparison. [ABSTRACT FROM AUTHOR]

Introduction: Although meningiomas are the most common primary brain tumor, there are limited treatment options for recurrent or aggressive lesions. Compared to other brain tumors, meningiomas may be uniquely amenable to immunotherapy by virtue of their location outside the blood–brain barrier. Areas covered: This review describes our current understanding of the immunology of the meninges, as well as immune cell infiltration and immune signaling in meningioma. Current literature on meningioma immunology and immunotherapy was comprehensively reviewed and summarized by a comprehensive search of MEDLINE (1/1/1990-6/1/2024). Further, we describe the current state of immunotherapeutic approaches, as well as potential future targets. Potential immunotherapeutic approaches include immune checkpoint inhibition, CAR-T approaches, tumor vaccine therapy, and immunogenic molecular markers. Expert opinion: Meningioma immunotherapy is in early stages, as no immunotherapies are currently included in treatment guidelines. There is substantial heterogeneity in immune cell infiltration, immunogenicity, and immune escape across tumors, even within tumor grade. Furthering our understanding of meningioma immunology and tumor classification will allow for careful selection of tumors and patient populations that may benefit from primary or adjunctive immunotherapy for meningioma. [ABSTRACT FROM AUTHOR]

Brain tumors pose a serious threat to public health, impacting thousands of individuals directly or indirectly worldwide. Timely and accurate detection of these tumors is crucial for effective treatment and enhancing the quality of patients’ lives. The widely used brain imaging technique is magnetic resonance imaging, the precise identification of brain tumors in MRI images is challenging due to the diverse anatomical structures. This paper introduces an innovative approach known as the ensemble attention mechanism to address this challenge. Initially, the approach uses two networks to extract intermediate- and final-level feature maps from MobileNetV3 and EfficientNetB7. This assists in gathering the relevant feature maps from the different models at different levels. Then, the technique incorporates a co-attention mechanism into the intermediate and final feature map levels on both networks and ensembles them. This directs attention to certain regions to extract global-level features at different levels. Ensemble of attentive feature maps enabling the precise detection of various feature patterns within brain tumor images at both model, local, and global levels. This leads to an improvement in the classification process. The proposed system was evaluated on the Figshare dataset and achieved an accuracy of 98.94%, and 98.48% for the BraTS 2019 dataset which is superior to other methods. Thus, it is robust and suitable for brain tumor detection in healthcare systems. [ABSTRACT FROM AUTHOR]

Introduction: This is a prospective, rigorous inquiry into the systemic immune effects of standard adjuvant chemoradiotherapy, for WHO grade 4, glioblastoma. The purpose is to identify peripheral immunologic effects never yet reported in key immune populations, including myeloid-derived suppressor cells, which are critical to the immune suppressive environment of glioblastoma. We hypothesize that harmful immune-supportive white blood cells, myeloid derived suppressor cells, expand in response to conventionally fractionated radiotherapy with concurrent temozolomide, essentially promoting systemic immunity similar what is seen in chronic diseases like diabetes and heart disease. Methods: 16 patients were enrolled in a single-institution, observational, immune surveillance study where peripheral blood was collected and interrogated by flow cytometry and RNAseq. Tumor tissue from baseline assessment was analyzed with spatial proteomics to link peripheral blood findings to baseline tissue characteristics. Results: We identified an increase in myeloid-derived suppressor cells during the final week of a six-week treatment of chemoradiotherapy in peripheral blood of patients that were not alive at two years after diagnosis compared to those who were living. This was also associated with a decrease in CD8+ T lymphocytes that produced IFNg, the potent anti-tumor cytokine. Discussion: These data suggest that, as in chronic inflammatory disease, systemic immunity is impaired following delivery of adjuvant chemoradiotherapy. Finally, baseline investigation of myeloid cells within tumor tissue did not differ between survival groups, indicating immune surveillance of peripheral blood during adjuvant therapymay be a critical missing link to educate our understanding of the immune effects of standard of care therapy for glioblastoma. [ABSTRACT FROM AUTHOR]

Introduction: Magnetic Resonance Elastography (MRE) allows the non-invasive quantification of tumor biomechanical properties in vivo. With increasing incidence of brain metastases, there is a notable absence of appropriate preclinical models to investigate their biomechanical characteristics. Therefore, the purpose of this work was to assess the biomechanical characteristics of B16 melanoma brain metastases (MBM) and compare it to murine GL261 glioblastoma (GBM) model using multifrequency MRE with tomoelastography post processing. Methods: Intracranial B16 MBM (n = 6) and GL261 GBM (n = 7) mouse models were used. Magnetic Resonance Imaging (MRI) was performed at set intervals after tumor implantation: 5, 7, 12, 14 days for MBM and 13 and 22 days for GBM. The investigations were performed using a 7T preclinical MRI with 20 mm head coil. The protocol consisted of single-shot spin echo-planar multifrequency MRE with tomoelastography post processing, contrast-enhanced T1- and T2- weighted imaging and diffusion-weighted imaging (DWI) with quantification of apparent diffusion coefficient of water (ADC). Elastography quantified shear wave speed (SWS), magnitude of complex MR signal (T2/T2*) and loss angle (j). Immunohistological investigations were performed to assess vascularization, blood-brain-barrier integrity and extent of glucosaminoglucan coverage. Results: Volumetric analyses displayed rapid growth of both tumor entities and softer tissue properties than healthy brain (healthy: 5.17 ± 0.48, MBM: 3.83 ± 0.55, GBM: 3.7 ± 0.23, [m/s]). SWS of MBM remained unchanged throughout tumor progression with decreased T2/T2* intensity and increased ADC on days 12 and 14 (p<0.0001 for both). Conversely, GBM presented reduced j values on day 22 (p=0.0237), with no significant alterations in ADC. Histological analysis revealed substantial vascularization and elevated glycosaminoglycan content in both tumor types compared to healthy contralateral brain. Discussion: Our results indicate that while both, MBM and GBM, exhibited softer properties compared to healthy brain, imaging and histological analysis revealed different underlying microstructural causes: hemorrhages in MBM and increased vascularization and glycosaminoglycan content in GBM, further corroborated by DWI and T2/T2* contrast. These findings underscore the complementary nature of MRE and its potential to enhance our understanding of tumor characteristics when used alongside established techniques. This comprehensive approach could lead to improved clinical outcomes and a deeper understanding of brain tumor pathophysiology. [ABSTRACT FROM AUTHOR]

Glioblastoma is a Grade 4 primary brain tumor defined by therapy resistance, diffuse infiltration, and near-uniform lethality. The underlying mechanisms are unknown, and no treatment has been curative. Using a recently developed creatine kinase inhibitor (CKi), we explored the role of this inhibitor on GBM biology in vitro. While CKi minimally impacted GBM cell proliferation and viability, it significantly affected migration. In established GBM cell lines and patient-derived xenografts, CKi ablated both the migration and invasion of GBM cells. CKi also hindered radiation-induced migration. RNA-seq revealed a decrease in invasion-related genes, with an unexpected increase in glutathione metabolism and ferroptosis protection genes post-CKi treatment. The effects of CKi could be reversed by the addition of cell-permeable glutathione. Carbon-13 metabolite tracing indicated heightened glutathione biosynthesis post-CKi treatment. Combinatorial CKi blockade and glutathione inhibition or ferroptosis activation abrogated cell survival. Our data demonstrated that CKi perturbs promigratory and anti-ferroptotic roles in GBM, identifying the creatine kinase axis as a druggable target for GBM treatment. [ABSTRACT FROM AUTHOR]

TTFields is a novel FDA-approved technology utilized for treating glioblastoma multiforme (GBM) within the brain. Presently, the effectiveness of therapy is evaluated through MRI imaging at random two-month intervals. Electrical impedance is an important and effective parameter for reflecting changes in tissue properties. In TTFields treatment for brain tumors, electrodes attached to the scalp deliver electric field energy to the tumor region. We hypothesize that these electrodes can also serve as sensors to detect impedance changes caused by tumor alterations in real time, thus continuously assessing the effectiveness of the treatment. In this work, we propose and scrutinize this hypothesis by conducting an in silico study to confirm the potential feasibility of the proposed concept. Our results indicate that the impedance amplitude change measured between opposing TTFields electrode arrays utilizing voltage and frequency of 50 V and 200 kHz (typical TTFields treatment parameters), has enough resolution (> 1mm) and Signal-to-Noise Ratio (> 40 dB) to evaluate tumor size change in the head. The impedance detection technique may be a significant augmentation to TTFields cancer treatment, enabling the continuous evaluation of safety and efficacy throughout the procedure. [ABSTRACT FROM AUTHOR]

The diagnosis of brain tumors through magnetic resonance imaging (MRI) has become highly significant in the field of medical science. Relying solely on MR imaging for the detection and categorization of brain tumors demands significant time, effort, and expertise from medical professionals. This underscores the need for an autonomous model for brain tumor diagnosis. Our study involves the application of a deep convolutional neural network (DCNN) to diagnose brain tumors from MR images. The application of these algorithms offers several benefits, including rapid brain tumor prediction, reduced errors, and enhanced precision. The proposed model is built upon the state‐of‐the‐art CNN architecture VGG16, employing a data augmentation approach. The dataset utilized in this paper consists of 3000 brain MR images sourced from Kaggle, with 1500 images reported to contain tumors. Through training and testing, the pretrained CNN model achieves a precision and classification accuracy rate of 96%, and the loss is 1%. Moreover, it achieves an average precision, recall, and F1‐score of 98.7%, 97.44%, and 98.06%, respectively. These evaluation metric values demonstrate the effectiveness of the proposed solution. [ABSTRACT FROM AUTHOR]

Background: Intra-axial brain tumors persist as significant clinical challenges. Aggressive surgical resection carries risk of morbidity, and the blood-brain barrier (BBB) prevents optimal pharmacological interventions. There is a clear clinical demand for innovative and less invasive therapeutic strategies for patients, especially those that can augment established treatment protocols. Focused ultrasound (FUS) has emerged as a promising approach to manage brain tumors. Sonodynamic therapy (SDT), a subset of FUS, utilizes sonosensitizers activated by ultrasound waves to generate reactive oxygen species (ROS) and induce tumor cell death. Objective: This review explores the historical evolution and rationale behind SDT, focusing on its mechanisms of action and potential applications in brain tumor management. Method: A systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Preclinical studies have demonstrated the efficacy of various sonosensitizers, including 5-aminolevulinic acid (5-ALA), fluorescein, porphyrin derivatives, and nanoparticles, in conjunction with FUS for targeted tumor therapy and BBB disruption. Clinical trials have shown promising results in terms of safety and efficacy, although further research is needed to fully understand the potential adverse effects and optimize treatment protocols. Challenges such as skull thickness affecting FUS penetration, and the kinetics of BBB opening require careful consideration for the successful implementation of SDT in clinical practice. Future directions include comparative studies of different sonosensitizers, optimization of FUS parameters, and exploration of SDT's immunomodulatory effects. Conclusion: SDT represents a promising frontier in the treatment of aggressive brain tumors, offering hope for improved patient outcomes. [ABSTRACT FROM AUTHOR]

Purpose: Artificial Intelligence (AI) has become increasingly integrated clinically within neurosurgical oncology. This report reviews the cutting-edge technologies impacting tumor treatment and outcomes. Methods: A rigorous literature search was performed with the aid of a research librarian to identify key articles referencing AI and related topics (machine learning (ML), computer vision (CV), augmented reality (AR), virtual reality (VR), etc.) for neurosurgical care of brain or spinal tumors. Results: Treatment of central nervous system (CNS) tumors is being improved through advances across AI—such as AL, CV, and AR/VR. AI aided diagnostic and prognostication tools can influence pre-operative patient experience, while automated tumor segmentation and total resection predictions aid surgical planning. Novel intra-operative tools can rapidly provide histopathologic tumor classification to streamline treatment strategies. Post-operative video analysis, paired with rich surgical simulations, can enhance training feedback and regimens. Conclusion: While limited generalizability, bias, and patient data security are current concerns, the advent of federated learning, along with growing data consortiums, provides an avenue for increasingly safe, powerful, and effective AI platforms in the future. [ABSTRACT FROM AUTHOR]

The disease that causes a large number of deaths annually across the world is brain cancer and it has become an important research topic in the field of medical image processing in recent times. There are various techniques for the detection of brain tumors (BT) but magnetic resonance imaging (MRI) diagnosing techniques show superior performance in the prognosis and examination of brain tumors in the early stages. The manual detection of brain tumors by radiologists leads to many limitations like errors and lack of detection accuracy. Hence, there is a need for computer-aided diagnostic techniques to help radiologists in detecting brain tumors accurately from the MRI images. To make this process more effective, the implementation of an automated technique is a preferred choice. In this paper, an effective detection and classification technique Adaptive convolutional Autoencoder-based Snow Avalanches (ACAE-SA) Algorithm is proposed. This algorithm comprises an Adaptive CNN component and an Autoencoder to detect and categorize BT from the MRI images. To mitigate the computational complexities in these components a Snow Avalanches algorithm is integrated into this work as an optimization technique. For the validation of the proposed architecture two MRI image datasets namely figshare and BraTS 2018 are used. The proposed technique proved its effectiveness in the detection and classification of brain tumors from the MRI images and outperformed the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

Background/Objectives: Brain tumor patients confront numerous challenges arising from diagnosis and treatment, and these impact the patient's physical, mental, and social functions at all levels. Primary informal caregivers assume a pivotal role in home-based patient care. Of particular importance are the coping strategies employed by family caregivers, as they can influence both their own health and the overall quality of home care. This study aimed to explore the associations among family function, caregiving competence, and coping strategies among primary informal caregivers. Methods: This study adopted a cross-sectional correlational design and convenience sampling to survey the primary informal caregivers of 111 brain tumor patients. The study instruments included the Family Assessment Device General Function, Caregiving Competence Scale, and Revised Ways of Coping Checklist. Results: The findings of this study revealed a significant positive correlation between the family function of primary informal caregivers and their employment of emotion-focused coping (r = 0.209, p < 0.05). Furthermore, caregiving competence exhibited a positive association with problem-focused coping (r = 0.242, p < 0.05) and emerged as a significant predictor of problem-focused coping (β = 0.182, p < 0.05). However, neither family function (r = 0.059, p < 0.05) nor caregiving competence (r = 0.031, p < 0.05) demonstrated significant associations with total coping strategies. Conclusions: The findings of this study affirmed that enhancing the caregiving competence of primary informal caregivers of brain tumor patients can facilitate the adoption of problem-focused coping strategies. [ABSTRACT FROM AUTHOR]