Early prediction of recurrence in high-grade glioma (HGG) is critical due to its aggressive nature and poor prognosis. Distinguishing true recurrence from treatment-related changes, such as radionecrosis, is a major diagnostic challenge. Machine learning (ML) offers a novel approach, leveraging advanced algorithms to analyze complex imaging data with high precision. A comprehensive search of PubMed, Embase, Scopus, Web of Science, and Google Scholar identified eligible studies. The sensitivity, specificity, accuracy, precision, F1 score, and the (area under the curve) AUC items were extracted from the included studies. After screening 1077 records, seven studies met the eligibility criteria for the systematic review, of which five were included in the meta-analysis. ML algorithm, particularly Support Vector Machines (SVM), demonstrated promising performance. A meta-analysis of five studies revealed a pooled sensitivity of 0.95 (95% CI: 0.84-0.99) and specificity of 0.80 (95% CI: 0.69-0.88). Additionally, the positive diagnostic likelihood ratio (DLR) was 4.75 (95% CI: 2.91-7.76), the negative DLR was 0.06 (95% CI: 0.02-0.21), and the diagnostic odds ratio was 80.97 (95% CI: 17.5-374.61). The diagnostic score was calculated as 4.39 (95% CI: 2.86-5.93), and the AUC was 0.86 (95% CI: 0.83-0.89). Subgroup analyses showed SVM-based models with higher sensitivity (0.98 vs. 0.87) and specificity (0.82 vs. 0.77) than non-SVM (p = 0.13). Comparing glioblastoma and Grade 3 tumors, sensitivities were 94 % vs. 97 %, and specificities were 79 % vs. 83 %, with no significant heterogeneity. These findings suggest that ML models, particularly SVM, offer promising diagnostic performance in distinguishing true tumor recurrence from treatment-related changes.

Background: OPG accounts for 3–5% of childhood central nervous system (CNS) tumors and about 2% of pediatric glial lesions. Methods: Article selection was performed by searching PubMed, Web of Science, and Cochrane databases. Results: The pooled mortality rate was 0.12 (95%CI 0.09–0.14). Due to the unrepresentative data, improved and not changed outcomes were classified as favorable outcomes and worsened as unfavorable. Meta-analyses were performed to determine the rate of clinical and radiological favorable outcomes. In terms of visual assessment, the pooled rate of a favorable outcome in chemotherapy, radiotherapy, and surgery was 0.74, 0.81, and 0.65, respectively, and the overall pooled rate of the favorable outcome was 0.75 (95%CI 0.70–0.80). In terms of radiological assessment, the rate of a favorable outcome following chemotherapy, radiotherapy, and surgery was 0.71, 0.74, and 0.67, respectively, and the overall pooled rate of the favorable outcome is 0.71 (95%CI 0.65–0.77). The subgroup analysis revealed no significant difference in the rate of clinical and radiological favorable outcomes between the different treatment modalities (p > 0.05). Conclusion: Our analyses showed that each therapeutic modality represents viable treatment options to achieve remission for these patients.

The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), is responsible for an array of extrapulmonary manifestations, including direct and indirect neurological complications. Currently, all published cases noting pituitary apoplexy in patients with COVID-19 have discovered underlying pituitary macroadenomas. Herein, we describe the first documented case, to our knowledge, of pituitary apoplexy attributed solely to COVID-19 in the absence of other identifiable causes. While much remains to be discovered and understood regarding COVID-19, we discuss the potential pathophysiology of COVID-19-associated pituitary apoplexy and raise awareness of this clinical complication.

Background: Laser interstitial thermal therapy (LITT) has emerged as a treatment option for deep-seated primary and metastatic brain lesions; however, hardly any data exist regarding LITT for lesions of the posterior fossa. Methods: A quantitative systematic review was performed. Article selection was performed by searching MEDLINE (using PubMed), Scopus, and Cochrane electronic bibliographic databases. Inclusion criteria were studies assessing LITT on posterior fossa tumors. Results: 16 studies comprising 150 patients (76.1% female) with a mean age of 56.47 years between 2014 and 2021 were systematically reviewed for treatment outcomes and efficacy. Morbidity and mortality data could be extracted for 131 of the 150 patients. Death attributed to treatment failure, disease progression, recurrence, or postoperative complications occurred in 6.87% (9/131) of the pooled sample. Procedure-related complications, usually including new neurologic deficits, occurred in approximately 14.5% (19/131) of the pooled sample. Neurologic deficits improved with time in most cases, and 78.6% (103/131) of the pooled sample experienced no complications and progression-free survival at the time of last follow-up. Conclusions: LITT for lesions of the posterior fossa continues to show promising data. Future clinical cohort studies are required to further direct treatment recommendations.