Glioblastoma, the most common and aggressive primary brain tumor in adults, presents a formidable challenge due to its rapid progression, treatment resistance, and poor survival outcomes. Standard care typically involves maximal safe surgical resection, followed by fractionated external beam radiation therapy and concurrent temozolomide chemotherapy. Despite these interventions, median survival remains approximately 12–15 months, with a five-year survival rate below 10%. Prognosis is influenced by factors such as patient age, molecular characteristics, and the extent of resection. Patients with IDH-mutant tumors or methylated MGMT promoters generally have improved survival, while recurrent glioblastoma is associated with a median survival of only six months, as therapies in these cases are often palliative. Innovative treatments, including TTFields, add incremental survival benefits, extending median survival to around 20.9 months for eligible patients. Symptom management—addressing seizures, headaches, and neurological deficits—alongside psychological support for patients and caregivers is essential to enhance quality of life. Emerging targeted therapies and immunotherapies, though still limited in efficacy, show promise as part of an evolving treatment landscape. Continued research and clinical trials remain crucial to developing more effective treatments. This multidisciplinary approach, incorporating diagnostics, personalized therapy, and supportive care, aims to improve outcomes and provides a hopeful foundation for advancing glioblastoma management.

The evidence base of policies that improve the timeliness of cancer care is under ongoing debate. Pancreatic cancer is frequently diagnosed in a stage when curative therapy is not feasible; hence, it is an important target for timelier healthcare interventions. The objectives of our research were to identify all clinical studies on pancreatic cancer care delays via a systematic literature review, to assess the study methodologies for possible biases, to conclude on the available evidence, and to formulate research recommendations on evidence gaps. Nineteen studies were identified and eight reported multivariate analyses. Although many sources of bias shifted the results towards negative or paradoxical findings, a statistically significant association of shorter delays with better clinical outcomes was demonstrated in the majority of studies reporting multivariate analyses. Noninferiority analyses were not published. Further efforts to provide timely care for pancreatic cancer patients are encouraged, and studies on the associations of delay with patient experience and healthcare resource utilization are warranted.

11C-Methionine (MET) is a widely utilized amino acid tracer in positron emission tomography (PET) imaging of primary brain tumors. 11C-MET PET offers valuable insights for tumor classification, facilitates treatment planning, and aids in monitoring therapeutic response. Its tracer properties allow better delineation of the active tumor volume, even in regions that show no contrast enhancement on conventional magnetic resonance imaging (MRI). This review focuses on the role of MET-PET in brain glioma imaging. The introduction provides a brief clinical overview of the problems of high-grade and recurrent gliomas. It discusses glioma management, radiotherapy planning, and the difficulties of imaging after chemoradiotherapy (pseudoprogression or radionecrosis). The mechanism of MET-PET is described. Additionally, the review encompasses the application of MET-PET in the context of primary gliomas, addressing its diagnostic precision, utility in tumor classification, prognostic value, and role in guiding biopsy procedures and radiotherapy planning.

Background: To determine the usefulness of Diffusion Weighted Imaging (DWI) derived from PET/MRI in discriminating normal from metastatic lymph nodes and the correlation between the metastatic lymph nodes with the grade and the localization of the primary tumor.Methods: Retrospective study of 90 lymph nodes from 90 subjects; 65 patients who had proven histopathological metastatic lymph nodes from (HNSCC) who had undergone¹⁸F- PET/MRI for clinical staging and assessment and twenty-five lymph nodes were chosen from 25 healthy subjects. Apparent Diffusion Coefficient (ADC) map was generated from DWI withbvalues (0 and 800 s/mm²). ADC values of the metastatic lymph nodes were calculated and compared to the normal lymph nodes ADC values, ROC was used to determine the best cut-off values to differentiate between the two group. Metastatic lymph nodes ADC mean values were compared to primary tumor grade and localization.Results: ADCmean value of the metastatic lymph nodes in the overall sample (0.899 ± 0.98*10^− 3 mm²/sec) was significantly lower than the normal lymph nodes’ ADCmean value (1.267 ± 0.88*10^− 3 mm²/sec); (P = 0.001). The area under the curve (AUC) was 98.3%, sensitivity and specificity were 92.3 and 98.6%, respectively, when using a threshold value of (1.138 ± 0.75*10^− 3 mm²/sec) to differentiate between both groups. Significant difference was found between metastatic lymph nodes (short-axis diameter < 10 mm), ADCmean (0.898 ± 0.72*10^− 3 mm²/sec), and the benign lymph nodes ADCmean, (P = 0.001). No significant difference was found between ADCmean of the metastatic lymph nodes < 10 mm and the metastatic lymph nodes > 10 mm, ADCmean (0.899 ± 0.89*10^− 3 mm²/sec), (P = 0.967). No significant differences were found between metastatic lymph nodes ADCmean values and different primary tumor grades or different primary tumor localization, (P > 0.05).Conclusion: DWI-ADC is an effective and efficient imaging technique in differentiating between normal and malignant lymph nodes, and might be helpful to discriminate sub-centimeters lymph nodes.Trial registration: The trial is registered in clinical trials underID:NCT04360993, registration date: 17/04/2020.

Recently, online education has been gaining prominence in university life. Our survey aimed to examine sleep quality and perceived stress levels among students at the University of Pécs Faculty of Health Sciences. A cross-sectional, quantitative, descriptive survey was conducted between February and March 2023. The online survey included the Hungarian versions of the internationally validated Athens Insomnia Scale (AIS) and Perceived Stress Scale (PSS). Statistical analysis involved descriptive statistics, independent t-tests, analysis of variance (ANOVA), and Mann–Whitney and Kruskal–Wallis tests (p < 0.05). We analyzed 304 responses, and females dominated (n = 270; 88.8%). Students in a relationship had significantly higher AIS scores (t = −2.470; p = 0.014). Medium average (2.50–3.49) students and those who rarely/never exercise showed significantly higher AIS and PSS (p ≤ 0.05). Students on the phone/watching a series during online education, daily laptop/TV use for more than 2 h, and pre-sleep use of smart devices for more than 60 min also negatively affected AIS and PSS scores (p ≤ 0.05). Nursing, physiotherapy, and radiography students were the most affected regarding insomnia and perceived stress (p ≤ 0.05). Our survey shows that excessive smart device use and lack of exercise are associated with higher stress levels and poorer sleep quality.