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The widespread use of pesticides, particularly in combinations, has resulted in enhanced hazardous health effects. However, little is known about their molecular mechanism of interactions. The aim of this study was to assess the neurotoxicity effect of pesticides in mixtures by adopting a 3D in vitro developed neurospheroid model, followed by treatment by increased concentrations of pesticides for 24 h and analysis by a shotgun proteomic-based approach with high-resolution tandem mass spectrometry. Three proteins, namely, glyceraldehyde-3-phosphate-dehydrogenase (GAPDH), α-enolase, and phosphoglycerate-kinase-1, were selected as key targets in the metabolic process. Only high doses of pesticides mitigated cell-density proliferation with the occurrence of apoptotic cells, which unlikely makes any neurological alterations in environmental regulatory exposures. The proteomic analysis showed that majority of altered proteins were implicated in cell metabolism. De novo peptide sequencing revealed ion losses and adduct formation, namely, a trityl-post-translational modification in the active site of 201-GAPDH protein. The study also highlights the plausible role of pyrethroids to be implicated in the deleterious effects of pesticides in a mixture. To the best of our knowledge, our finding is the first in toxicoproteomics to deeply elucidate pesticides' molecular interactions and their ability to adduct proteins as a pivotal role in the neurotoxicity mechanism.

Background: The gift of postmortem tissue donation is critical to pediatric central nervous system (CNS) research. As a "Center of Excellence" for the Gift from a Child Program, our institution has a well-established postmortem tissue donation program. Our objective was to determine if differences exist between patients who participated in and those that declined research-based autopsy., Procedure: We performed a single-institution retrospective chart review of pediatric patients with CNS malignancies who died from their disease between January 1, 2021 and December 31, 2022. Individual clinical, demographic, and socioeconomic data were assessed. Population-level data were estimated using Zip Code Tabulation Areas. Descriptive statistics were used to compare categorical data., Results: Among the 23 patient families approached during the study time frame, 8/23 (35%) consented to participation. In the consented (C) versus declined (D) group, there was a higher percentage of White, non-Hispanic/Latino patients by self-reported race (C: 88% vs. D: 55%), and no patients who identified as Asian or Hispanic/Latino (C: 0% and 0% vs. D: 13% and 27%). Of all patients approached, two required interpreters (9%), and both families declined participation. The rate of private insurance was higher in the consented group (C: 75% vs. D: 47%) compared to Medicaid as primary insurance in the declined group (C: 13% vs. D: 53%).  CONCLUSIONS: Future research should aim to understand and improve identified disparities to ensure research advancements benefit all children with CNS malignancies. One area we plan to address is improved communication with non-English-speaking families by partnering with our interpreter services., (© 2024 Wiley Periodicals LLC.)

Treating neurological illnesses is challenging because the blood-brain barrier hinders therapeutic medications from reaching the brain. Recent advances in polymeric nanocarriers (PNCs), which improve medication permeability across the blood-brain barrier, may influence therapy strategies for neurological diseases. PNCs have several ways to deliver medications to the nervous system. This review article provides a summary of the parts and manufacturing methods involved in making PNCs. Additionally, it highlights the elements that result in PNCs having enhanced blood-brain barrier penetration. A combination of passive and active targeting strategies is used by PNCs intended to overcome the blood-brain barrier. Among these are micellar structures, nanogels, nanoparticles, cubosomes, and dendrimers. These nanocarriers, which are functionalized with certain ligands that target BBB transporters, enable the direct delivery of drugs to the brain. Mainly, the BBB prevents medications from entering the brain. Understanding the BBB's physiological and anatomical characteristics is necessary to get over this obstacle. Preclinical and clinical research demonstrates the safety and effectiveness of these PNCs, and their potential use in the treatment of neurological illnesses, including brain tumors, Parkinson's disease, and Alzheimer's disease, is discussed. Concerns that PNCs may have about their biocompatibility and possible toxicity are also covered in this review article. This study examines the revolutionary potential of PNCs in CNS drug delivery, potential roadblocks, ongoing research, and future opportunities for PNC design progress. PNCs open the door to more focused and efficient treatment for neurological illnesses by comprehending the subtleties of BBB penetration., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The application of chimeric antigen receptor T-cell therapy in central nervous system tumors has significantly advanced; however, challenges pertaining to the blood-brain barrier, immunosuppressive microenvironment, and antigenic heterogeneity continue to be encountered, unlike its success in hematological malignancies such as acute lymphoblastic leukemia and diffuse large B-cell lymphomas. This review examined the research progress of chimeric antigen receptor T-cell therapy in gliomas, medulloblastomas, and lymphohematopoietic tumors of the central nervous system, focusing on chimeric antigen receptor T-cells targeting antigens such as EGFRvIII, HER2, B7H3, GD2, and CD19 in preclinical and clinical studies. It synthesized current research findings to offer valuable insights for future chimeric antigen receptor T-cell therapeutic strategies for central nervous system tumors and advance the development and application of this therapeutic modality in this domain., (© 2024. The Author(s).)

Objective: The objective of this study was to develop a murine system for the delivery of laser interstitial thermotherapy (LITT) with probe-based thermometry as a model for human glioblastoma treatment to investigate thermal diffusion in heterogeneous brain tissue., Methods: First, the tissue heating properties were characterized using a diode-pumped solid-state near-infrared laser in a homogeneous tissue model. The laser was adapted for use with a repurposed stereotactic surgery frame utilizing a micro laser probe and Hamilton syringe. The authors designed and manufactured a stereotactic frame attachment to work as a temperature probe stabilizer. Application of this novel design was used as a precise method for real-time thermometry at known distances from the thermal ablative center mass during murine LITT studies., Results: Temperature measurements were achieved during LITT that verified the direct thermometry capability of the system without the need for MR-based thermal monitoring. Application of multiple stereotactic design iterations led to an accurately reproducible surgical laser ablation procedure. Histological staining confirmed precise thermal ablation and controllable lesion size based on time and temperature control. Treatment of a syngeneic intracranial glioma model highly resistant to conventional therapy resulted in a modest survival benefit., Conclusions: The authors have successfully developed a murine model system of LITT with direct in situ thermometry for investigation into the effects of thermal ablation and combinatorial treatments in murine brain tumor models.

Objectives: This study aimed to assess the diagnostic management and follow-up imaging for glioma patients across Belgian hospitals by calculating process indicators., Methods: Patients with newly diagnosed glioma in Belgium (2016-2019) were selected from the Belgian Cancer Registry. The National Social Security Number served as unique patient identifier, linking the Registry to vital status and reimbursement data. Nine measurable process related to diagnosis and follow-up imaging were identified, with reformulations for 7 due to data limitations. For each indicator, technical documentation sheets, containing all required details (rationale, numerator and denominator, target, limitations, benchmarking, subgroup analyses) were developed, reviewed by a multidisciplinary expert panel, and validated in six pilot hospitals. Per indicator, patients were assigned to the most relevant hospital per indicator using allocation algorithms., Results: Results for process indicators assessing MRI use in glioma diagnosis and follow-up aligned with predefined targets (90%), except for early postoperative MRI (48.5% vs. target 90%). Mandatory reporting of the WHO performance status (89.3% vs. target 100%) and performance of full-spine (43.6% vs. target 90%) and follow-up MRI (73.5% vs. target 90%) in ependymoma were suboptimal. The largest variability across centers was noted for the indicator on early postoperative MRI., Conclusion: This calculation of process indicators identified opportunities for improvement in diagnosis and follow-up imaging for glioma patients in Belgium. Monitoring indicator results and providing individual feedback reports to the Belgian hospitals invites neuro-oncology care teams and hospital managements to reflect on their results and to take measures to continuously improve care for glioma., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Background: Proton beam radiation therapy (PBRT) is an advanced cancer treatment modality that utilizes the distinctive physical properties of protons to precisely deliver radiation to tumor targets while sparing healthy tissue. This cannot be obtained with photon radiation. In this systematic review and meta-analysis, we aimed to comprehensively assess the risk of brainstem toxicity in pediatric brain tumor patients undergoing PBRT. Methods: With adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a predetermined search strategy was used to identify eligible articles from PubMed, Web of Science, Scopus, and Cochrane Library through July 2024. Results: The current study included a total of 11 eligible articles. The pooled prevalence of patients who suffered from brainstem toxicity was 1.8% (95% CI: 1%, 2.6%). The pooled prevalences of patients with Grade 1 to Grade 5 brainstem toxicity were found to be 10.6% (95% CI: 8.8%, 30%), 1.5% (95% CI: 0.6%, 2.5%), 0.7% (95% CI: 0.3%, 1.1%), 0.4% (95% CI: 0.1%, 0.7%), and 0.4% (95% CI: 0.1%, 0.8%), respectively, with an overall pooled prevalence of 0.7% (95% CI: 0.4%, 1%). Conclusions: This study revealed a relatively low incidence of symptomatic brainstem toxicity and its related mortality in the pediatric population undergoing PBRT. However, further research is encouraged to study the broader effects of PBRT and to explore various factors that may influence the risk of brainstem toxicity in patients treated with PBRT.

Objective: Sexual functioning is a multifaceted aspect of human life that can be profoundly affected in patients with glioma. Most frequent symptoms include reduced sexual desire, difficulties in sexual arousal, or low satisfaction. Such symptoms may cause distress or interpersonal difficulties, inevitably resulting in negative outcomes on different domains of patients' quality of life. Despite this, sexuality is rarely addressed by medical staff and remains understudied. An important question still unanswered is whether sexual dysfunctions in glioma patients correlate with features of the tumor itself, with its treatment, or with the secondary effects of the tumor on the patient's psychological status. To answer this question, the present study aims to investigate the incidence of sexual life impairments in a very large population of patients with low- and high-grade gliomas, focusing on demographic, clinical, and treatment factors associated with their occurrence and developments., Methods: A total of 148 patients treated for glioma were evaluated for sexual functioning, i.e., sexual dysfunction (SD), relationship status (RS), intercourse frequency (IF), and sexual satisfaction (SS), by using a specific anonymous questionnaire. Descriptive statistics were utilized to investigate participant characteristics and to evaluate the occurrence of sexual problems. Chi-squared tests were performed to detect the association between "SS" or "IF" and different clinical/demographic factors as well as between "SS" or "IF" and the "subjective-personal skills judgment"., Results: Results showed no difference between male and female patients, a very low frequency (1.4%) of SD, but a consistent percentage (25%) of subjective deterioration in sexual wellbeing. Notably, 24% of patients reported to have interrupted their relationship after the diagnosis. Chi-squared analyses reveal an association between adjuvant treatments (chemotherapy and radiotherapy) and reduction of IF. Interestingly, "SS" or "IF" was not associated with demographic, clinical, or histomolecular factors., Conclusion: Our study showed that sexual problems in glioma patients are not uncommon, and they are especially linked to SS, RS, and IF. Specifically, intercourse frequency reduction is associated with the adjuvant treatments. Results highlight the need for improved assessment strategies and interventions tailored to the unique needs of brain tumor patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Leonetti, Puglisi, Rossi, Viganò, Conti Nibali, Gay, Sciortino, Fornia, Cerri and Bello.)

Adolescents and young adults (AYAs; ages 15-39 years) are a vulnerable population facing challenges in oncological care, including access to specialized care, transition of care, unique tumor biology, and poor representation in clinical trials. Brain tumors are the second most common tumor type in AYA, with malignant brain tumors being the most common cause of cancer-related death. The 2021 WHO Classification for central nervous system (CNS) Tumors highlights the importance of integrated molecular characterization with histologic diagnosis in several tumors relevant to the AYA population. In this position paper from the Society for Neuro-Oncology (SNO), the diagnosis and management of CNS tumors in AYA is reviewed, focusing on the most common tumor types in this population, namely glioma, medulloblastoma, ependymoma, and CNS germ cell tumor. Current challenges and future directions specific to AYA are also highlighted. Finally, possible solutions to address barriers in the care of AYA patients are discussed, emphasizing the need for multidisciplinary and collaborative approaches that span the pediatric and adult paradigms of care, and incorporating advanced molecular testing, targeted therapy, and AYA-centered care., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Background: As the Internet becomes an increasingly vital source of medical information, the quality and reliability of brain tumor-related short videos on platforms such as TikTok and Bilibili have not been adequately evaluated. Therefore, this study aims to assess these aspects and explore the factors influencing the dissemination of such videos., Methods: A cross-sectional analysis was conducted on the top 100 brain tumor-related short videos from TikTok and Bilibili. The videos were evaluated using the Global Quality Score and the DISCERN reliability instrument. An eXtreme Gradient Boosting algorithm was utilized to predict dissemination outcomes. The videos were also categorized by content type and uploader., Results: TikTok videos scored relatively higher on both the Global Quality Score (median 2, interquartile range [2, 3] on TikTok vs. median 2, interquartile range [1, 2] on Bilibili, p  = 1.51E-04) and the DISCERN reliability instrument (median 15, interquartile range [13, 18.25] on TikTok vs. 13.5, interquartile range [11, 16] on Bilibili, p  = 1.66E-04). Subgroup analysis revealed that videos uploaded by professional individuals and institutions had higher quality and reliability compared to those uploaded by non-professional entities. Videos focusing on disease knowledge exhibited the highest quality and reliability compared to other content types. The number of followers emerged as the most important variable in our dissemination prediction model., Conclusion: The overall quality and reliability of brain tumor-related short videos on TikTok and Bilibili were unsatisfactory and did not significantly influence video dissemination. Future research should expand the scope to better understand the factors driving the dissemination of medical-themed videos., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Zhang, Jie, Guo, Liu, Yang, Li and Guo.)

Background: Brain tumors are highly complex, making their detection and classification a significant challenge in modern medical diagnostics. The accurate segmentation and classification of brain tumors from MRI images are crucial for effective treatment planning. This study aims to develop an advanced neural network architecture that addresses these challenges. Methods: We propose L-net, a novel architecture combining U-net for tumor boundary segmentation and a convolutional neural network (CNN) for tumor classification. These two units are coupled such a way that the CNN classifies the MRI images based on the features extracted by the U-net while segmenting the tumor, instead of relying on the original input images. The model is trained on a dataset of 3064 high-resolution MRI images, encompassing gliomas, meningiomas, and pituitary tumors, ensuring robust performance across different tumor types. Results: L-net achieved a classification accuracy of up to 99.6%, surpassing existing models in both segmentation and classification tasks. The model demonstrated effectiveness even with lower image resolutions, making it suitable for diverse clinical settings. Conclusions: The proposed L-net model provides an accurate and unified approach to brain tumor segmentation and classification. Its enhanced performance contributes to more reliable and precise diagnosis, supporting early detection and treatment in clinical applications.

The present situation of neuropathology practice in the Central American region has not been addressed in the past. These are low middle-income countries, and therefore, many do not have a basic immunohistochemistry panel. Cytogenetics and molecular studies are not available in most of Central America. Pediatric brain tumors are diagnosed either by anatomical pathologists or by pediatric pathologists. Access to a weakly Latin American Tumor Board is available to consult cases, but most countries do not participate in these expert meetings. The most recent World Health Organization brain tumor book has a very broad molecular classification of pediatric brain tumors. All these factors make it very difficult to properly diagnose pediatric brain tumors in the region, and this impacts the treatment and overall survival of children with brain tumors., Competing Interests: The authors declare that the article was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Delgado.)

Brain tumors, a significant health burden, rank as the second leading cause of cancer among adolescents and young adults and the eighth most common cancer in older adults. Despite treatment advances, outcomes for many brain tumor types, especially glioblastoma multiforme (GBM), remain poor. Precision population cancer medicine (PPCM) offers promising avenues for improving outcomes in brain tumor management. This comprehensive review delves into the current landscape of brain tumor diagnosis and treatment, with a primary focus on the potential of PPCM to enhance care. The review explores several key areas where PPCM approaches show promise. In genetics and molecular biology, the genetic heterogeneity of brain tumors poses challenges and opportunities for targeted therapies. Understanding genetic patterns can guide treatment strategies and improve prognostication. Epigenetic modifications are crucial in brain tumor development and progression. Deoxyribonucleic acid (DNA) methylation patterns, particularly of the O6-methylguanine-DNA methyltransferase (MGMT) gene promoter, serve as essential biomarkers for treatment response and prognosis in GBM. Targeting epigenetic mechanisms could lead to novel therapeutic approaches. Non-invasive liquid biopsy techniques show potential for diagnosis, monitoring, and prognostication in brain tumors. Analysis of circulating tumor DNA and microRNAs may provide valuable information about tumor characteristics and treatment response. Advanced imaging techniques, including radiomics and radiogenomics, combined with artificial intelligence (AI) algorithms, are enhancing tumor detection, characterization, and treatment planning. These technologies can contribute to more personalized treatment approaches. In addition, emerging nanotherapeutic platforms, which involve the use of nanoparticles to deliver drugs directly to tumors, and theranostic approaches, which combine therapy and diagnostics in a single platform, offer new possibilities for targeted drug delivery and real-time treatment monitoring in brain tumors. The review also addresses socioeconomic and demographic factors influencing brain tumor incidence and outcomes. It highlights the stark disparities in care access and survival rates among different racial and ethnic groups, emphasizing the urgent need for PPCM strategies to address these inequities. Challenges in implementing PPCM for brain tumors include the blood-brain barrier, which limits drug delivery, and the need for more extensive clinical trials to validate new approaches. The authors stress the importance of interdisciplinary collaboration and data sharing to advance the field, making the audience feel united and part of a larger team. While PPCM holds great promise, the review emphasizes that it should complement, not replace, population-level interventions and standard-of-care treatments. The authors advocate for a balanced approach that leverages cutting-edge personalized strategies while ensuring broad access to effective treatments. In conclusion, PPCM represents a powerful tool in the fight against brain tumors, offering the potential for more targeted, effective, and less toxic treatments. However, realizing its full potential will require ongoing research, clinical validation, and policy interactions to address disparities in care access., Competing Interests: Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Velu et al.)

In the pediatric age group, brain neoplasms are the second most common tumor category after leukemia, with an annual incidence of 6.13 per 100,000. Conventional MRI sequences, complemented by CT whenever necessary, are fundamental for the initial diagnosis and surgical planning as well as for post-operative evaluations, assessment of response to treatment, and surveillance; however, they have limitations, especially concerning histopathologic or biomolecular phenotyping and grading. In recent years, several advanced MRI sequences, including diffusion-weighted imaging, diffusion tensor imaging, arterial spin labelling (ASL) perfusion, and MR spectroscopy, have emerged as a powerful aid to diagnosis as well as prognostication; furthermore, other techniques such as diffusion kurtosis, amide proton transfer imaging, and MR elastography are being translated from the research environment to clinical practice. Molecular imaging, especially PET with amino-acid tracers, complement MRI in several aspects, including biopsy targeting and outcome prediction. Finally, radiomics with radiogenomics are opening entirely new perspectives for a quantitative approach aiming at identifying biomarkers that can be used for personalized, precision management strategies., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Significant progress has been made recently with the contribution of technological advances in studies on brain cancer. Regarding this, identifying and correctly classifying tumors is a crucial task in the field of medical imaging. The disease-related tumor classification problem, on which deep learning technologies have also become a focus, is very important in the diagnosis and treatment of the disease. The use of deep learning models has shown promising results in recent years. However, the sparsity of ground truth data in medical imaging or inconsistent data sources poses a significant challenge for training these models. The utilization of StyleGANv2-ADA is proposed in this paper for augmenting brain MRI slices to enhance the performance of deep learning models. Specifically, augmentation is applied solely to the training data to prevent any potential leakage. The StyleGanv2-ADA model is trained with the Gazi Brains 2020, BRaTS 2021, and Br35h datasets using the researchers' default settings. The effectiveness of the proposed method is demonstrated on datasets for brain tumor classification, resulting in a notable improvement in the overall accuracy of the model for brain tumor classification on all the Gazi Brains 2020, BraTS 2021, and Br35h datasets. Importantly, the utilization of StyleGANv2-ADA on the Gazi Brains 2020 Dataset represents a novel experiment in the literature. The results show that the augmentation with StyleGAN can help overcome the challenges of working with medical data and the sparsity of ground truth data. Data augmentation employing the StyleGANv2-ADA GAN model yielded the highest overall accuracy for brain tumor classification on the BraTS 2021 and Gazi Brains 2020 datasets, together with the BR35H dataset, achieving 75.18%, 99.36%, and 98.99% on the EfficientNetV2S models, respectively. This study emphasizes the potency of GANs for augmenting medical imaging datasets, particularly in brain tumor classification, showcasing a notable increase in overall accuracy through the integration of synthetic GAN data on the used datasets., (© 2024. The Author(s).)

Typical longitudinal radiographic assessment of brain tumors relies on side-by-side qualitative visualization of serial magnetic resonance images (MRIs) aided by quantitative measurements of tumor size. However, when assessing slowly growing tumors and/or complex tumors, side-by-side visualization and quantification may be difficult or unreliable. Whole-brain, patient-specific "digital flipbooks" of longitudinal scans are a potential method to augment radiographic side-by-side reads in clinical settings by enhancing the visual perception of changes in tumor size, mass effect, and infiltration across multiple slices over time. In this approach, co-registered, consecutive MRI scans are displayed in a slide deck, where one slide displays multiple brain slices of a single timepoint in an array (eg, 3 × 5 "mosaic" view of slices). The flipbooks are viewed similarly to an animated flipbook of cartoons/photos so that subtle radiographic changes are visualized via perceived motion when scrolling through the slides. Importantly, flipbooks can be created easily with free, open-source software. This article describes the step-by-step methodology for creating flipbooks and discusses clinical scenarios for which flipbooks are particularly useful. Example flipbooks are provided in Supplementary Material., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Radiopharmaceutical theranostic treatments have grown exponentially worldwide, and internal dosimetry has attracted attention and resources. Despite some similarities with chemotherapy, radiopharmaceuticals treatments are essentially radiotherapy treatments, as the release of radiation into tissues is the determinant of the observed clinical effects. Therefore, absorbed dose calculations are key to explain dose-effect correlations and to individualize radiopharmaceutical treatments. The present article introduces the basic principles of internal dosimetry and provides an overview of available locoregional and systemic radiopharmaceutical treatments for CNS tumors. The specific characteristics of dosimetry as applied to these treatments are highlighted, along with their limitations and most relevant results. Dosimetry is performed with higher precision and better reproducibility than in the past, and dosimetric data should be systematically collected, as treatment planning and verification may help exploit the full potential of theranostic of CNS tumors., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Despite considerable improvements in understanding the biology of glioblastoma (GB), it still remains the most lethal type of brain tumor in adults. The role of innate immune cells in the development of GB was recently described. In particular, the tumor-immune cell interactions are thought to be critical in enabling tumor tolerance and even protection against therapeutics. Interestingly, the GB cells express proteins belonging to the family of intracellular pattern-recognition receptors, namely the NOD-like receptors (NLRs). Their activation may trigger the formation of the inflammasome complex leading to the secretion of mature IL-1β and IL-18 and thus resulting in cell death. Intrudingly, the expression of most NLRs was found to be correlated with tumor progression and poor prognosis. We speculate that recognizing the role of NOD-like receptors in GB has the potential to improve the effectiveness of diagnostic tools and prognosis, while also encouraging the development of novel precision medicine-based therapies., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Brain tumors are a threat to life for every other human being, be it adults or children. Gliomas are one of the deadliest brain tumors with an extremely difficult diagnosis. The reason is their complex and heterogenous structure which gives rise to subjective as well as objective errors. Their manual segmentation is a laborious task due to their complex structure and irregular appearance. To cater to all these issues, a lot of research has been done and is going on to develop AI-based solutions that can help doctors and radiologists in the effective diagnosis of gliomas with the least subjective and objective errors, but an end-to-end system is still missing. An all-in-one framework has been proposed in this research. The developed end-to-end multi-task learning (MTL) architecture with a feature attention module can classify, segment, and predict the overall survival of gliomas by leveraging task relationships between similar tasks. Uncertainty estimation has also been incorporated into the framework to enhance the confidence level of healthcare practitioners. Extensive experimentation was performed by using combinations of MRI sequences. Brain tumor segmentation (BraTS) challenge datasets of 2019 and 2020 were used for experimental purposes. Results of the best model with four sequences show 95.1% accuracy for classification, 86.3% dice score for segmentation, and a mean absolute error (MAE) of 456.59 for survival prediction on the test data. It is evident from the results that deep learning-based MTL models have the potential to automate the whole brain tumor analysis process and give efficient results with least inference time without human intervention. Uncertainty quantification confirms the idea that more data can improve the generalization ability and in turn can produce more accurate results with less uncertainty. The proposed model has the potential to be utilized in a clinical setup for the initial screening of glioma patients., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Brain tumors such as glioblastomas are resistant to immune checkpoint blockade therapy, largely due to limited T cell infiltration in the tumors. Here, we show that mice bearing intracranial tumors exhibit systemic immunosuppression and T cell sequestration in bone marrow, leading to reduced T cell infiltration in brain tumors. Elevated plasma corticosterone drives the T cell sequestration via glucocorticoid receptors in tumor-bearing mice. Immunosuppression mediated by glucocorticoid-induced T cell dynamics and the subsequent tumor growth promotion can be abrogated by adrenalectomy, the administration of glucocorticoid activation inhibitors or glucocorticoid receptor antagonists, and in mice with T cell-specific deletion of glucocorticoid receptor. CCR8 expression in T cells is increased in tumor-bearing mice in a glucocorticoid receptor-dependent manner. Additionally, chemokines CCL1 and CCL8, the ligands for CCR8, are highly expressed in bone marrow immune cells in tumor-bearing mice to recruit T cells. These findings suggested that brain tumor-induced glucocorticoid surge and CCR8 upregulation in T cells lead to T cell sequestration in bone marrow, impairing the anti-tumor immune response. Targeting the glucocorticoid receptor-CCR8 axis may offer a promising immunotherapeutic approach for the treatment of intracranial tumors., (© 2024. The Author(s), under exclusive licence to CSI and USTC.)

Glioblastoma (GBM) is the most frequent and aggressive primary brain cancer. The Src inhibitor, TAT-Cx43 266-283 , exerts antitumor effects in in vitro and in vivo models of GBM. Because addressing the mechanism of action is essential to translate these results to a clinical setting, in this study we carried out an unbiased proteomic approach. Data-independent acquisition mass spectrometry proteomics allowed the identification of 190 proteins whose abundance was modified by TAT-Cx43 266-283 . Our results were consistent with the inhibition of Src as the mechanism of action of TAT-Cx43 266-283 and unveiled antitumor effectors, such as p120 catenin. Changes in the abundance of several proteins suggested that TAT-Cx43 266-283 may also impact the brain microenvironment. Importantly, the proteins whose abundance was reduced by TAT-Cx43 266-283 correlated with an improved GBM patient survival in clinical datasets and none of the proteins whose abundance was increased by TAT-Cx43 266-283 correlated with shorter survival, supporting its use in clinical trials., (Copyright © 2024. Published by Elsevier Inc.)

Background: Radionecrosis is a common complication in radiation oncology, while mechanisms and risk factors have yet to be fully explored. We therefore conducted a systematic review to understand the pathogenesis and identify factors that significantly affect the development., Methods: We performed a systematic literature search based on the PRISMA guidelines using PubMed, Ovid, and Web of Science databases. The complete search strategy can be found as a preregistered protocol on PROSPERO (CRD42023361662)., Results: We included 83 studies, most involving healthy animals (n = 72, 86.75 %). High doses of hemispherical irradiation of 30 Gy in rats and 50 Gy in mice led repeatedly to radionecrosis among different studies and set-ups. Higher dose and larger irradiated volume were associated with earlier onset. Fractionated schedules showed limited effectiveness in the prevention of radionecrosis. Distinct anatomical brain structures respond to irradiation in various ways. White matter appears to be more vulnerable than gray matter. Younger age, more evolved animal species, and genetic background were also significant factors, whereas sex was irrelevant. Only 13.25 % of the studies were performed on primary brain tumor bearing animals, no studies on brain metastases are currently available., Conclusion: This systematic review identified various factors that significantly affect the induction of radionecrosis. The current state of research neglects the utilization of animal models of brain tumors, even though patients with brain malignancies constitute the largest group receiving brain irradiation. This latter aspect should be primarily addressed when developing an experimental radionecrosis model for translational implementation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

As in previous years, including 2023, a major focus in the neurooncological area of neuropathology was put on more precise and constantly faster diagnostic procedures, even reaching the level of ultra-fast intraoperative diagnostics based on methylation profiling. Neuropathological diagnostic precision and clinical follow-up treatment has been further increased by combining DNA methylation profiling with targeted panel sequencing. A few new, molecularly defined tumor subtypes have been proposed, among others, a glioneuronal tumor with ATRX alteration, kinase fusion and anaplastic features (in its abbreviated form named GTAKA) and the de novo replication repair deficient glioblastoma, IDH-wildtype both having either distinct prognostic or therapeutic implications. Regarding the understanding of brain tumor development and progression, several novel mechanisms have been presented which might also be considered as treatment targets in the future, such as a) autonomous rhythmical Ca 2+ oscillations in interconnected glioma cell networks driving tumor growth; b) transfer of mitochondria from normal astrocytes to glioma cells enhancing proliferation and self-renewal; c) brain endothelial cell remodeling upon matrix-metalloprotease 9 secretion by tumor cells metastasizing into the CNS and d) anti-tumor activity of microglia in CNS metastasis of breast cancer. Finally, in contrast to previous years, several very promising neurooncological treatment studies have been conducted, focusing on specific targets such as H3K27M or IDH1/2 mutations for which a proper neuropathological assessment is key. The continuous translation of potential new treatment targets using faster and precise diagnostic procedures will further pave the way for better individualized clinical care of neurooncological patients., Competing Interests: The author does not have any conflict of interest to declare.

The treatment of brain tumors is significantly hindered by the Blood-Brain Barrier (BBB), a selective barrier that restricts the passage of therapeutic agents to the brain. Recent advancements in BBB-targeting therapies offer promising strategies to overcome this challenge, providing new avenues for the effective treatment of brain cancer. This article reviews innovative approaches, including Convection-Enhanced Delivery (CED) and RNA-based therapeutics, which enhance drug delivery directly to tumor sites, bypassing the BBB and reducing systemic toxicity. Additionally, the use of theranostic nanoparticles and CRISPR-Cas9 gene editing presents novel opportunities for real-time monitoring and precision-targeted therapy, respectively. Techniques such as magnetic nanoparticles, intranasal drug administration, and focused ultrasound with microbubbles are also being refined to improve drug penetration across the BBB. Furthermore, peptide-based delivery systems and small molecules designed to mimic endogenous transport pathways are accelerating the discovery of more effective therapies. The exploration of combination therapies that synergize BBB-penetrant drugs with conventional chemotherapeutic agents or immunotherapies holds the potential to enhance treatment efficacy and patient outcomes. Continued research and interdisciplinary collaboration are essential to develop predictive models, personalized treatment strategies, and alternative delivery methods that ensure the long-term safety and effectiveness of these novel therapies. Advancements in BBB-targeting therapeutics are poised to transform the landscape of brain cancer treatment, offering renewed hope for improved survival rates and quality of life for patients., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Implementation of standardized protocols in neurooncology during the surgical resection of brain tumors is needed to advance the clinical treatment paradigms that use tissue for diagnosis, prognosis, bio-banking, and treatment. Currently recommendations on intraoperative tissue procurement only exist for diffuse gliomas but management of other brain tumor subtypes can also benefit from these protocols. Fresh tissue from surgical resection can now be used for intraoperative diagnostics and functional precision medicine assays. A multidisciplinary neuro-oncology perspective is critical to develop the best avenues for practical standardization. This perspective from the multidisciplinary Oncology Tissue Advisory Board (OTAB) discusses current advances, future directions, and the imperative of adopting standardized protocols for diverse brain tumor entities. There is a growing need for consistent operating room practices to enhance patient care, streamline research efforts, and optimize outcomes., Competing Interests: The authors, except WJS, are members of an advisory board sponsored by Nico Corporation. However, Nico Corporation was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. CB is a consultant for Depuy-Synthes, Bionaut Labs, Haystack Oncology and Privo Technologies. CB is a co-founder of OrisDx and Belay Diagnostics. HB is a chairman of the Medical Advisory Board for Insightec. Insightec is developing focused ultrasound treatments for brain tumors. This arrangement has been reviewed and approved by the Johns Hopkins University in accordance with its conflict-of-interest policies. HB has consultation agreements with Insightec, Candel Therapeutics, Inc., Catalio Nexus Fund II, LLC, LikeMinds, Inc*, and Nurami Medical*, Intragel *includes equity or options. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Rodriguez, Ahluwalia, Bettegowda, Brem, Carter, Chang, Das, Eberhart, Garzon-Muvdi, Hadjipanayis, Hawkins, Jacques, Khalessi, McDermott, Mikkelsen, Orr, Phillips, Rosenblum, Shelton, Solomon, von Deimling, Woodworth and Rutka.)

This comprehensive review paper examines the most updated state of research on glioblastoma, an aggressive brain tumor with limited treatment options. By analyzing 76 recent studies, from translational and basic sciences, to clinical trials, we highlight various aspects of glioblastoma and shed light on potential therapeutic strategies. The interplay between tumor cells, neural progenitor cells, and the tumor microenvironment is explored. Targeting the PI3K-Akt-mTOR pathway through extracellular-vesicle (EV)-mediated signaling emerges as a potential therapeutic strategy. Personalized modeling approaches utilizing patient-specific MRI data offer promise for optimizing treatment strategies. The response of glioblastoma stem cells (GSCs) to different treatment modalities is examined, emphasizing the need to inhibit the transformation of proneural (PN) GSCs into resistant mesenchymal (MES) GSCs. Metabolic therapy and combination therapies show potential in reversing treatment resistance and inhibiting both PN and MES GSCs. Immunotherapy, targeted approaches, and molecular dynamics in gliomas are discussed, providing insights into early-stage diagnosis and treatment. Additionally, the potential use of Zika virus as an oncolytic agent is explored. Analysis of phase 0 to 3 clinical trials reveal promising outcomes for various experimental treatments, highlighting the importance of combination therapies, predictive signatures, and patient selection strategies. Specific compounds demonstrate potential therapeutic benefits and tolerability. Phase 3 trials indicate the efficacy of DCVax-L in improving survival rates and depatux-m in prolonging progression-free survival. These findings emphasize the importance of personalized treatment approaches and continued exploration of targeted therapies, immunotherapies, and tumor biology understanding in shaping the future of glioblastoma treatment., Competing Interests: All authors declare that they have no potential conflicts of interest that may have influenced the review process or the interpretation of the findings. This includes financial interests, employment affiliations, or any other personal or professional relationships that could be perceived as influencing the objectivity of the review., (© 2024 The Authors.)

Introduction: Brain tumors are characterized by abnormal cell growth within or around the brain, posing severe health risks often associated with high mortality rates. Various imaging techniques, including magnetic resonance imaging (MRI), are commonly employed to visualize the brain and identify malignant growths. Computer-aided diagnosis tools (CAD) utilizing Convolutional Neural Networks (CNNs) have proven effective in feature extraction and predictive analysis across diverse medical imaging modalities., Methods: This study explores a CNN trained and evaluated with nine activation functions, encompassing eight established ones from the literature and a modified version of the soft sign activation function., Results: The latter demonstrates notable efficacy in discriminating between four types of brain tumors in MR images, achieving an accuracy of 97.6%. The sensitivity for glioma is 93.7%; for meningioma, it is 97.4%; for cases with no tumor, it is 98.8%; and for pituitary tumors, it reaches 100%., Discussion: In this manuscript, we propose an advanced CNN architecture that integrates a newly developed activation function. Our extensive experimentation and analysis showcase the model's remarkable ability to precisely distinguish between different types of brain tumors within a substantial and diverse dataset. The findings from our study suggest that this model could serve as an invaluable supplementary tool for healthcare practitioners, including specialized medical professionals and resident physicians, in the accurate diagnosis of brain tumors., Competing Interests: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Kaifi.)

Radiofrequency electromagnetic fields (RF-EMF, 100 kHz to 300 GHz) are classified by IARC as possibly carcinogenic to humans (Group 2B). This study evaluates the potential association between occupational RF-EMF exposure and brain tumor risk, utilizing for the first time, a RF-EMF job-exposure matrix (RF-JEM) developed in the multi-country INTEROCC case-control study. Cumulative and time-weighted average (TWA) occupational RF-EMF exposures were estimated for study participants based on lifetime job histories linked to the RF-JEM using three different methods: (1) by considering RF-EMF intensity among all exposed jobs, (2) by considering RF-EMF intensity among jobs with an exposure prevalence ≥ the median exposure prevalence of all exposed jobs, and (3) by considering RF-EMF intensity of jobs of participants who reported RF-EMF source use. Stratified conditional logistic regression models were used, considering various lag periods and exposure time windows defined a priori. Generally, no clear associations were found for glioma or meningioma risk. However, some statistically significant positive associations were observed including in the highest exposure categories for glioma for cumulative and TWA exposure in the 1- to 4-year time window for electric fields (E) in the first JEM application method (odds ratios [ORs] = 1.36, 95% confidence interval [95% CI] 1.08, 1.72 and 1.27, 95% CI 1.01, 1.59, respectively), as well as for meningioma for cumulative exposure in the 5- to 9-year time window for electric fields (E) in the third JEM application method (OR = 2.30, 95% CI 1.11, 4.78). We did not identify convincing associations between occupational RF-EMF exposure and risk of glioma or meningioma., (© 2024 The Author(s). International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Background: We sought to analyze, in well-defined clinical setting, the first 100 patients treated at the intraoperative MRI (iMRI) hybrid surgical theatre at our facility in a population-based setting to evaluate which pathologies are best approached with iMRI assisted surgeries, as this is not yet clearly defined., Methods: Patients undergoing surgery in the 3T iMRI hybrid surgical theatre at our neurosurgical department between December 2017 to May 2021 were included after informed consent. Demographic, clinical, surgical, histological, radiological and outcome parameters, as well as variables related to iMRI, were retrospectively collected and analyzed. Patients were subdivided into adult and pediatric cohorts., Results: Various neurosurgical procedures were performed; resection of tumors and epileptic foci, endoscopic skull base procedures including pituitary lesions, deep brain stimulation (DBS) and laser interstitial thermal therapy (LITT). In total, 41 patients were pediatric. An iMRI scan was carried out in 96% of cases and led to continuation of surgery in 50% of cases, mainly due to visualized remaining pathological tissue (95.2%). Median time to iMRI from intubation was 280 min and median total duration of surgery was 445 min. The majority of patients experienced no postoperative complications (70%), 13 patients suffered permanent postoperative deficits, predominantly visual., Conclusion: Herein, we demonstrate the first 100 patients undergoing neurosurgery aided by iMRI at our facility since introduction. Indications for surgery differed between pediatric and adult patients. The iMRI was utilized for tumor surgeries, particularly adult low-grade gliomas and pediatric tumors, as well as for epilepsy surgery and DBS. In this heterogenous population, iMRI led to continuation of surgery in 50%. To establish the benefit in maximizing the extent of resection in these brain pathologies future studies are recommended., Clinical Trial Number: Not applicable., (© 2024. The Author(s).)

Research on the neural imprint of dual-language experience, crucial for understanding how the brain processes dominant and non-dominant languages, remains inconclusive. Conflicting evidence suggests either similarity or distinction in neural processing, with implications for bilingual patients with brain tumors. Preserving dual-language functions after surgery requires considering pre-diagnosis neuroplastic changes. Here, we combine univariate and multivariate fMRI methodologies to test a group of healthy Spanish-Basque bilinguals and a group of bilingual patients with gliomas affecting the language-dominant hemisphere while they overtly produced sentences in either their dominant or non-dominant language. Findings from healthy participants revealed the presence of a shared neural system for both languages, while also identifying regions with distinct language-dependent activation and lateralization patterns. Specifically, while the dominant language engaged a more left-lateralized network, speech production in the non-dominant language relied on the recruitment of a bilateral basal ganglia-thalamo-cortical circuit. Notably, based on language lateralization patterns, we were able to robustly decode (AUC: 0.80 ± 0.18) the language being used. Conversely, bilingual patients exhibited bilateral activation patterns for both languages. For the dominant language, regions such as the cerebellum, thalamus, and caudate acted in concert with the sparsely activated language-specific nodes. In the case of the non-dominant language, the recruitment of the default mode network was notably prominent. These results demonstrate the compensatory engagement of non-language-specific networks in the preservation of bilingual speech production, even in the face of pathological conditions. Overall, our findings underscore the pervasive impact of dual-language experience on brain functional (re)organization, both in health and disease., (© 2024. The Author(s).)

Background: This study assessed the cost-effectiveness of proton beam therapy (PBT) compared to conventional radiotherapy (CRT) for treating patients with brain tumors in Sweden., Methods: Data from a longitudinal non-randomized study performed between 2015 and 2020 was used, and included adult patients with brain tumors, followed during treatment and through a one-year follow-up. Clinical and demographic data were sourced from the longitudinal study and linked to Swedish national registers to get information on healthcare resource use. A cost-utility framework was used to evaluate the cost-effectiveness of PBT vs. CRT. Patients in PBT group (n = 310) were matched with patients in CRT group (n = 40) on relevant observables using propensity score matching with replacement. Costs were estimated from a healthcare perspective and included costs related to inpatient and specialized outpatient care, and prescribed medications. The health outcome was quality-adjusted life-years (QALYs), derived from the EORTC-QLQ-C30. Generalized linear models (GLM) and two-part models were used to estimate differences in costs and QALYs., Results: PBT yielded higher total costs, 14,639 US$, than CRT, 13,308 US$, with a difference of 1,372 US$ (95% CI, -4,914-7,659) over a 58 weeks' time horizon. Further, PBT resulted in non-significantly lower QALYs, 0.746 compared to CRT, 0.774, with a difference of -0.049 (95% CI, -0.195-0.097). The probability of PBT being cost-effective was < 30% at any willingness to pay., Conclusions: These results suggest that PBT cannot be considered a cost-effective treatment for brain tumours, compared to CRT., Trial Registration: Not applicable., (© 2024. The Author(s).)

To meet the needs of automated medical analysis of brain tumor magnetic resonance imaging, this study introduces an enhanced instance segmentation method built upon mask region-based convolutional neural network. By incorporating squeeze-and-excitation networks, a channel attention mechanism, and concatenated attention neural network, a spatial attention mechanism, the model can more adeptly focus on the critical regions and finer details of brain tumors. Residual network-50 combined attention module and feature pyramid network as the backbone network to effectively capture multi-scale characteristics of brain tumors. At the same time, the region proposal network and region of interest align technology were used to ensure that the segmentation area matched the actual tumor morphology. The originality of the research lies in the deep residual network that combines attention mechanism with feature pyramid network to replace the backbone based on mask region convolutional neural network, achieving an improvement in the efficiency of brain tumor feature extraction. After a series of experiments, the precision of the model is 90.72%, which is 0.76% higher than that of the original model. Recall was 91.68%, an increase of 0.95%; Mean Intersection over Union was 94.56%, an increase of 1.39%. This method achieves precise segmentation of brain tumor magnetic resonance imaging, and doctors can easily and accurately locate the tumor area through the segmentation results, thereby quickly measuring the diameter, area, and other information of the tumor, providing doctors with more comprehensive diagnostic information., (© 2024. The Author(s).)

Despite enormous efforts being invested in the development of novel therapies for brain malignancies, there remains a dire need for effective treatments, particularly for pediatric glioblastomas. Their poor prognosis has been attributed to the fact that conventional therapies target tumoral cells, but not glioblastoma stem cells (GSCs). GSCs are characterized by self-renewal, tumorigenicity, poor differentiation, and resistance to therapy. These characteristics represent the fundamental tools needed to recapitulate the tumor and result in a relapse. The mechanisms by which GSCs alter metabolic cues and escape elimination by immune cells are discussed in this article, along with potential strategies to harness effector immune cells against GSCs. As cellular immunotherapy is making significant advances in a variety of cancers, leveraging this underexplored reservoir may result in significant improvements in the treatment options for brain malignancies., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: High-grade gliomas in infants and very young children (less than 3 to 5 years old) pose significant challenges due to the limited scientific literature available and high risks associated with treatments. This study aims to investigate their characteristics, treatment, and outcomes., Methods: A cohort study was conducted at Children's Cancer Hospital, Egypt. Cases included children aged < 5 years old with confirmed CNS high-grade glioma. Baseline clinical and radiological characteristics, besides potential prognostic factors were assessed., Results: In total, 76 cases were identified, 7 of them were < 1 year old. Gross- or near-total resection (GTR/NTR) was achieved in 32.9% of all cases. Of the tested cases, H3K27M-alteration was present in 5 subjects only. The 3-year OS and EFS for all cases were 26.9% and 15.4%, respectively. Extent of resection was the most important prognostic factor, as those achieving GTR/NTR experienced more than double the survival compared to those who do not (p = 0.05). Age had a "bimodal" effect on EFS, with those aged 1 to 3 years old faring better than younger and older age groups. Subjects with midline tumors had worse survival compared to non-midline tumors (1-year EFS = 18.5% vs 35%, respectively, p = 0.02)., Conclusion: This study in a large cohort of HGG in infants and very young children offers insights into the characteristics and treatment challenges. Extent of resection, age group, and tumor localization are important prognostic factors. Further research with larger sample size is warranted to refine treatment approaches and improve outcomes., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: The incidence of brain tumors has increased in elderly population overtime. Their eligibility to a major surgery remains a questionable subject. This study evaluated prognostic factors and 30-days morbidity and mortality in octogenarian population who underwent craniotomy for resection of brain tumor., Materials and Methods: A total of 154 patients were divided into two different groups: patients above 80 years old and patients below 65 years old. In both groups, patients were stratified based on diagnosis with benign tumors [meningioma] and malignant tumors [high-grade gliomas and metastases]. Multivariable logistic regression model with backward elimination method was utilized to identify the independent risk factors for 30-days readmission and post-operative complications., Results: The analysis revealed no significant difference in 30-day readmission ( p  = 0.7329), 30-day mortality (0.6854) or in post-operative complication ( p  = 0.3291) between age ≥ 80 and age ≤ 65 groups. A longer length of stay (LOS) was observed in the older patients ( p  = 0.0479). There was a significant difference in the pre-post KPS between the two groups ( p  < 0.0001). ASA ( p  = 0.0315) and KPS ( p  = 0.071) were found as important prognostic factors associated with post-operative mortality in both groups., Conclusion: Octogenarians can withstand craniotomy without any significant increase in 30-day readmission, 30-day mortality and post-operative complications as compared to patients younger than age 65. The ASA score (>3) and/or KPS (<70) were the most important prognostic factors for 30-days readmission and mortality.

Background: Alopecia causes significant distress for patients and negatively impacts quality of life for low-grade glioma (LGG) patients. We aimed to compare and evaluate variations in dose distribution for scalp-sparing in LGG patients with proton therapy and photon therapy, namely intensity-modulated proton therapy (IMPT), intensity-modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT), and helical tomotherapy (HT)., Methods: This retrospective study utilized a dataset comprising imaging data from 22 patients with LGG who underwent postoperative radiotherapy. Treatment plans were generated for each patient with scalp-optimized (SO) approaches and scalp-non-optimized (SNO) approaches using proton techniques and photons techniques; all plans adhered to the same dose constraint of delivering a total radiation dose of 54.04 Gy to the target volume. All treatment plans were subsequently analyzed., Results: All the plans generated in this study met the dose constraints for the target volume and OARs. The SO plans resulted in reduced maximum scalp dose (D max ), mean scalp dose (D mean ), and volume of the scalp receiving 30 Gy (V 30 ) and 40 Gy (V 40 ) compared with SNO plans in all radiation techniques. Among all radiation techniques, the IMPT plans exhibited superior performance compared to other plans for dose homogeneity as for SO plans. Also, IMPT showed lower values for D mean and D max than all photon radiation techniques., Conclusion: Our study provides evidence that the SO approach is a feasible technique for reducing scalp radiation dose. However, it is imperative to conduct prospective trials to assess the benefits associated with this approach., (© 2024. Springer-Verlag GmbH Germany, part of Springer Nature.)

Chemotherapy in brain tumors is tailored based on tumor type, grade, and molecular markers, which are crucial for predicting responses and survival outcomes. This review summarizes the role of chemotherapy in gliomas, glioneuronal and neuronal tumors, ependymomas, choroid plexus tumors, medulloblastomas, and meningiomas, discussing standard treatment protocols and recent developments in targeted therapies.Furthermore, the studies reporting the integration of MRI-based radiomics and deep learning models for predicting treatment outcomes are reviewed. Advances in MRI-based radiomics and deep learning models have significantly enhanced the prediction of chemotherapeutic benefits, survival prediction following chemotherapy, and differentiating tumor progression with psuedoprogression. These non-invasive techniques offer valuable insights into tumor characteristics and treatment responses, facilitating personalized therapeutic strategies. Further research is warranted to refine these models and expand their applicability across different brain tumor types., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Significance: Accurate identification between pathologic (e.g., tumors) and healthy brain tissue is a critical need in neurosurgery. However, conventional surgical adjuncts have significant limitations toward achieving this goal (e.g., image guidance based on pre-operative imaging becomes inaccurate up to 3 cm as surgery proceeds). Hyperspectral imaging (HSI) has emerged as a potential powerful surgical adjunct to enable surgeons to accurately distinguish pathologic from normal tissues., Aim: We review HSI techniques in neurosurgery; categorize, explain, and summarize their technical and clinical details; and present some promising directions for future work., Approach: We performed a literature search on HSI methods in neurosurgery focusing on their hardware and implementation details; classification, estimation, and band selection methods; publicly available labeled and unlabeled data; image processing and augmented reality visualization systems; and clinical study conclusions., Results: We present a detailed review of HSI results in neurosurgery with a discussion of over 25 imaging systems, 45 clinical studies, and 60 computational methods. We first provide a short overview of HSI and the main branches of neurosurgery. Then, we describe in detail the imaging systems, computational methods, and clinical results for HSI using reflectance or fluorescence. Clinical implementations of HSI yield promising results in estimating perfusion and mapping brain function, classifying tumors and healthy tissues (e.g., in fluorescence-guided tumor surgery, detecting infiltrating margins not visible with conventional systems), and detecting epileptogenic regions. Finally, we discuss the advantages and disadvantages of HSI approaches and interesting research directions as a means to encourage future development., Conclusions: We describe a number of HSI applications across every major branch of neurosurgery. We believe these results demonstrate the potential of HSI as a powerful neurosurgical adjunct as more work continues to enable rapid acquisition with smaller footprints, greater spectral and spatial resolutions, and improved detection., (© 2024 The Authors.)

While MR imaging is the main imaging modality to assess brain tumors, PET imaging has a specific role. Among the many tracers that have been proposed and are still being developed, 2-[ 18 F]fluoro-2-deoxy-d-glucose ([ 18 F]FDG) and O-(2-[ 18 F]-fluoroethyl)-l-tyrosine ([ 18 F]FET) PET remain the most solidly established in the clinics. In particular, [ 18 F]FET has gained increased acceptance due to its higher sensitivity. In this paper, we present an overview of the current clinical status of brain tumor imaging, with emphasis on PET imaging., Competing Interests: Disclosure The authors received no financial support for the study, authorship, and/or publication of this article., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Brain tumors exert their clinical effects in a variety of ways. Mass effect, edema, seizures, and a vicious cycle of cause and effect are often the focus of therapeutic interventions employed to improve clinical signs and increase survival time. Obstructive hydrocephalus is a common sequela of certain types of brain tumors and is often the major driver of clinical signs seen in tumors arising within the ventricular system. This study outlines the application of ventriculoperitoneal shunting for obstructive hydrocephalus secondary to brain tumors as part of an overall management program to help increase patients' lifespan and quality of life., Competing Interests: Disclosure The authors declare that this chapter was written in the absence of any commercial or financial relationsips that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

External beam radiation therapy (RT) has become the standard of care for non-resectable or post-operative incompletely excised brain tumors in dogs and cats due to its relatively low side effect profile and increasing availability. This article reviews the indications for, expected outcomes of and possible toxicities associated with RT, follow-up care recommendations after RT, and publications about specific tumor types in dogs and cats with brain tumors., Competing Interests: Disclosure Dr T.L. Gieger does not have relevant commercial or financial conflicts of interest, or funding sources which are relevant to this article., (Copyright © 2024 Elsevier Inc. All rights reserved.)

This study describes the essential components and the technique of intraoperative ultrasound (IOUS), including probe selection and techniques used to produce quality images. Case examples are given to illustrate the value and the accuracy of IOUS in intracranial surgery of companion animals. IOUS has proven an invaluable addition to intracranial surgery, especially in real-time localization of the mass, identifying borders between mass and normal cerebral tissue, and identifying vascular supply to the mass., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Brain tumors are diseases characterized by abnormal cell growth within or around brain tissues, including various types such as benign and malignant tumors. However, there is currently a lack of early detection and precise localization of brain tumors in MRI images, posing challenges to diagnosis and treatment. In this context, achieving accurate target detection of brain tumors in MRI images becomes particularly important as it can improve the timeliness of diagnosis and the effectiveness of treatment. To address this challenge, we propose a novel approach-the YOLO-NeuroBoost model. This model combines the improved YOLOv8 algorithm with several innovative techniques, including dynamic convolution KernelWarehouse, attention mechanism CBAM (Convolutional Block Attention Module), and Inner-GIoU loss function. Our experimental results demonstrate that our method achieves mAP scores of 99.48 and 97.71 on the Br35H dataset and the open-source Roboflow dataset, respectively, indicating the high accuracy and efficiency of this method in detecting brain tumors in MRI images. This research holds significant importance for improving early diagnosis and treatment of brain tumors and provides new possibilities for the development of the medical image analysis field., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Chen, Lin and Gao.)

Chimeric antigen receptor T cells (CAR-Ts) have shown a remarkable efficacy in hematological malignancies but limited responses in solid tumors. Among solid tumors, CAR-T cell therapy has been particularly explored in brain tumors. CAR-T cells have shown a limited clinical efficacy in various types of brain tumors due to several factors that have hampered their activity, including tumor antigen heterogeneity, the limited access of CAR-T cells to brain tumor cells, limited CAR-T cell trafficking and in vivo persistence and the presence of a highly immunosuppressive tumor microenvironment. Despite these considerations, some recent studies have shown promising antitumor activity of GD2-CAR-T cells on diffuse midline gliomas and neuroblastomas and of CARv3-TEAM-E cells in glioblastomas. However, strategies are required to improve the effect of CAR-T cells in brain tumors, including advanced CAR-T cell design with multiple antigenic targeting and incorporation of combination therapies.

MR-guided Laser Interstitial Thermal Therapy (MRgLITT) is a minimally invasive neurosurgical technique increasingly used for the treatment of drug-resistant epilepsy and brain tumors. Utilizing near-infrared light energy delivery guided by real-time MRI thermometry, MRgLITT enables precise ablation of targeted brain tissues, resulting in limited corridor-related morbidity and expedited postoperative recovery. Since receiving CE marking in 2018, the adoption of MRgLITT has expanded to more than 40 neurosurgical centers across Europe. In epilepsy treatment, MRgLITT can be applied to various types of focal lesional epilepsy, including mesial temporal lobe epilepsy, hypothalamic hamartoma, focal cortical dysplasias, periventricular heterotopias, cavernous malformations, dysembryoplastic neuroepithelial tumors (DNET), low-grade gliomas, tuberous sclerosis, and in disconnective surgeries. In neuro-oncology, MRgLITT is used for treating newly diagnosed and recurrent primary brain tumors, brain metastases, and radiation necrosis. This comprehensive review presents an overview of the current evidence and technical considerations for the use of MRgLITT in treating various pathologies associated with drug-resistant epilepsy and brain tumors., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Background : Diagnosis with a brain tumor is a critical event in the lives of patients and their families due to poor medical prognoses and complex clinical care. Spiritual care interventions have been known to have meaningful effects in morbid diagnoses and palliative medicine, but their role in the neuro-oncologic patient's experience is poorly understood. This systematic review explores the role of spirituality and its relevance to patient care in the diverse setting of brain tumors. Methods : A comprehensive systematic review was conducted following PRISMA-SR guidelines. PUBMED was queried for studies on spirituality and neuro-oncology. Identified studies included RCTs, interviews, surveys, and case reports that examined spirituality in neuro-oncological clinical care, quality of life, and patient experience. Of 214 articles identified, 21 studies met the inclusion criteria, and the results were narratively synthesized. Results : Spirituality may play a significant role in mental well-being by reconciling existential questions faced by both patients and caregivers, and can serve as a valuable resource to improve mental well-being and reduce rates of palliative caregiver burnout. However, the paucity of studies examining the education and integration of spiritual awareness within the clinical literature warrants further study. Conclusions : While spiritual care interventions may improve the quality of life and mental wellness of patients and their caregivers, it is unclear how spiritual awareness and education should best be implemented. Further research is needed to better understand how key components of spiritual awareness can be integrated into medical education to deepen the patient-physician relationship and improve clinical experiences.

Background: Evaluating longitudinal changes in gliomas is a time-intensive process with significant interrater variability. Automated segmentation could reduce interrater variability and increase workflow efficiency for assessment of treatment response. We sought to evaluate whether neural networks would be comparable to expert assessment of pre- and posttreatment diffuse gliomas tissue subregions including resection cavities., Methods: A retrospective cohort of 647 MRIs of patients with diffuse gliomas (average 55.1 years; 29%/36%/34% female/male/unknown; 396 pretreatment and 251 posttreatment, median 237 days post-surgery) from 7 publicly available repositories in The Cancer Imaging Archive were split into training (536) and test/generalization (111) samples. T1, T1-post-contrast, T2, and FLAIR images were used as inputs into a 3D nnU-Net to predict 3 tumor subregions and resection cavities. We evaluated the performance of networks trained on pretreatment training cases (Pre-Rx network), posttreatment training cases (Post-Rx network), and both pre- and posttreatment cases (Combined networks)., Results: Segmentation performance was as good as or better than interrater reliability with median dice scores for main tumor subregions ranging from 0.82 to 0.94 and strong correlations between manually segmented and predicted total lesion volumes (0.94 <  R 2 values < 0.98). The Combined network performed similarly to the Pre-Rx network on pretreatment cases and the Post-Rx network on posttreatment cases with fewer false positive resection cavities (7% vs 59%)., Conclusions: Neural networks that accurately segment pre- and posttreatment diffuse gliomas have the potential to improve response assessment in clinical trials and reduce provider burden and errors in measurement., Competing Interests: The authors I.V., G.M.M., R.X.S., and N.W. are employees at Cortechs.ai. N.W. and A.M.D. are on the board of directors at Cortechs.ai. J.D.R., S.Bas., N.F., S.K. and T.M.S. are on the medical advisory board of Cortechs.ai., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Few T cells infiltrate into primary brain tumors, fundamentally hampering the effectiveness of immunotherapy. We hypothesized that Toxoplasma gondii, a microorganism that naturally elicits a Th1 response in the brain, can promote T cell infiltration into brain tumors despite their immune suppressive microenvironment. Using a mouse genetic model for medulloblastoma, we found that T. gondii infection induced the infiltration of activatable T cells into the tumor mass and led to myeloid cell reprogramming toward a T cell-supportive state, without causing severe health issues in mice. The study provides a concrete foundation for future studies to take advantage of the immune modulatory capacity of T. gondii to facilitate brain tumor immunotherapy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)