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.

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.

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Background Existential anxiety is a significant concern for patients with life-threatening illnesses like brain tumors. This study explores the prevalence and impact of existential anxiety among brain tumor patients in Saudi Arabia, examining relationships between demographic, clinical, and psychological variables and death anxiety. Methods A cross-sectional study was conducted with 120 brain tumor patients from inpatient and outpatient settings at King Abdulaziz University Hospital, King Fahad Hospital, and King Abdullah Medical Complex in Saudi Arabia. Data were collected using the Death Anxiety Scale (DAS), Spiritual Well-Being Scale (SWBS), Meaning in Life Questionnaire (MLQ), and the 12-item Short Form Survey (SF-12). Descriptive and inferential statistics analyzed the relationships between variables. Results Females exhibited significantly higher DAS scores (77.9 ± 14.2) compared to males (48.5 ± 19.4) (p < 0.001). Educational attainment was inversely related to DAS, with illiterate patients scoring highest (83 ± 13.5) and those with higher education scoring lowest (47.3 ± 18.2) (p < 0.001). Widowed patients had higher anxiety (68.5 ± 22.1) compared to married (51.4 ± 21.5) and single patients (50 ± 12) (p < 0.001). Monthly income showed an inverse relationship with DAS. Patients with chronic medical conditions reported lower DAS scores compared to those without (p = 0.004). The tumor stage significantly influenced DAS, with third-stage patients showing lower anxiety than those in the first and second stages (p < 0.001). Longer duration since diagnosis was associated with lower DAS scores (p = 0.03). Conclusion This study highlights the significant psychosocial impact of brain tumors on Saudi Arabian patients, emphasizing the need to address demographic factors in managing death anxiety. Findings indicate that chronic medical conditions and advanced tumor stages might be associated with lower anxiety, revealing potential resilience factors. The positive influence of spiritual well-being and meaning in life on quality of life underscores the importance of holistic care approaches. Integrating psychological and spiritual support tailored to individual patient demographics could enhance management strategies and improve patient outcomes. Future research should explore longitudinal changes in existential anxiety, the role of cultural factors, and the effectiveness of holistic interventions in reducing anxiety and improving quality of life.

Background  Patient-reported outcome measures (PROMs) have gained traction in assessing patients\' health around surgery. Among these, the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS-29) is a widely accepted tool for evaluating overall health, yet its applicability in cranial neurosurgery remains uncertain. Objective  This study aimed to evaluate the predictive value of preoperative PROMIS-29 scores for postoperative outcomes in patients undergoing brain tumor resection. Materials and Methods  We identified adult patients undergoing brain tumor resection at a single neurosurgical center between January 2018 and December 2021. We analyzed physical health (PH) summary scores to determine optimal thresholds for predicting length of stay (LOS), discharge disposition (DD), and 30-day readmission. Bivariate analyses were conducted to examine the distribution of PH scores based on patient characteristics. Multivariate logistic regression models were employed to assess the association between preoperative PH scores and short-term postoperative outcomes. Results  Among 157 patients (mean age 55.4 years, 58.0% female), 14.6% exhibited low PH summary scores. Additionally, 5.7% experienced prolonged LOS, 37.6% had nonroutine DDs, and 19.1% were readmitted within 30 days. Bivariate analyses indicated that patients with low PH summary scores, indicating poorer baseline PH, were more likely to have malignant tumors, nonelective admissions, and adverse outcomes. In multivariate analysis, low PH summary scores independently predicted increased odds of prolonged LOS (odds ratio [OR] = 6.09, p  = 0.003), nonroutine DD (OR = 4.25, p  = 0.020), and 30-day readmission (OR = 3.93, p  = 0.020). Conclusion  The PROMIS-29 PH summary score serves as a valuable predictor of short-term postoperative outcomes in brain tumor patients. Integrating this score into clinical practice can enhance the ability to anticipate meaningful postoperative results.

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.

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.

Brain tumors, and, in particular, glioblastoma (GBM), are among the most aggressive forms of cancer. In spite of the advancement in the available therapies, both diagnosis and treatments are still unable to ensure pathology-free survival of the GBM patients for more than 12-15 months. At the basis of the still poor ability to cope with brain tumors, we can consider: (i) intra-tumor heterogeneity; (ii) heterogeneity of the tumor properties when we compare different patients; (iii) the blood-brain barrier (BBB), which makes difficult both isolation of tumor-specific biomarkers and delivering of therapeutic drugs to the brain. Recently, it is becoming increasingly clear that cancer cells release large amounts of extracellular vesicles (EVs) that transport metabolites, proteins, different classes of RNAs, DNA, and lipids. These structures are involved in the pathological process and characterize any particular form of cancer. Moreover, EVs are able to cross the BBB in both directions. Starting from these observations, researchers are now evaluating the possibility to use EVs purified from organic fluids (first of all, blood and saliva), in order to obtain, through non-invasive methods (liquid biopsy), tumor biomarkers, and, perhaps, also for obtaining nanocarriers for the targeted delivering of drugs.

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.

UNASSIGNED: Recent studies have shown that gut microbiota may be related to the occurrence of brain tumors, but direct evidence is lacking. This study used the Mendelian randomization study (MR) method to explore the potential causal link between gut microbiota and brain tumors.
UNASSIGNED: We analyzed the genome-wide association data between 211 gut microbiota taxa and brain tumors, using the largest existing gut microbiota Genome-Wide Association Studies meta-analysis data (n=13266) and combining it with brain tumor data in the IEU OpenGWAS database. We use inverse-variance weighted analysis, supplemented by methods such as Mendelian randomization-Egger regression, weighted median estimator, simple mode, and weighted mode, to assess causality. In addition, we also conducted the Mendelian randomization-Egger intercept test, Cochran\'s Q test, and Mendelian randomization Steiger directionality test to ensure the accuracy of the analysis. Quality control includes sensitivity analysis, horizontal gene pleiotropy test, heterogeneity test, and MR Steiger directionality test.
UNASSIGNED: Our study found that specific gut microbial taxa, such as order Lactobacillales and family Clostridiaceae1, were positively correlated with the occurrence of brain tumors, while genus Defluviitaleaceae UCG011 and genus Flavonifractor were negatively correlated with the occurrence of brain tumors. The Mendelian randomization-Egger intercept test showed that our analysis was not affected by pleiotropy (P>0.05).
UNASSIGNED: This study reveals for the first time the potential causal relationship between gut microbiota and brain tumors, providing a new perspective for the prevention and treatment of early brain tumors. These findings may help develop new clinical intervention strategies and point the way for future research.