Recent scientific research has shown that the ketogenic diet may have potential benefits in a variety of medical fields, which has led to the diet receiving a substantial amount of attention. Clinical and experimental research on brain tumors has shown that the ketogenic diet has a satisfactory safety profile. This safety profile has been established in a variety of applications, including the management of obesity and the treatment of drug-resistant epileptic cases. However, in human studies, the impact of ketogenic therapy on the growth of tumors and the life expectancy of patients has not provided results that are well characterized. Consequently, our purpose is to improve the comprehension of these features by succinctly presenting the developments and conclusions that have been gained from the most recent study that pertains to this non-pharmacological technique. According to the findings of our study, patients with brain tumors who stick to a ketogenic diet are more likely to experience improved survival rates. However, it is required to conduct additional research on humans in order to more accurately define the anti-tumor efficiency of this diet as well as the underlying processes that support the therapeutic effects of this dieting regimen.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor dysfunctions that severely compromise patients’ quality of life. While pharmacological treatments provide symptomatic relief in the early stages, advanced PD often requires neurosurgical interventions, such as deep brain stimulation (DBS) and focused ultrasound (FUS), for effective symptom management. A significant challenge in optimizing these therapeutic strategies is the early identification and recruitment of suitable candidates for clinical trials. This review explores the role of artificial intelligence (AI) in advancing neurosurgical and neuroscience interventions for PD, highlighting the ways in which AI-driven platforms are transforming clinical trial design and patient selection. Machine learning (ML) algorithms and big data analytics enable precise patient stratification, risk assessment, and outcome prediction, accelerating the development of novel therapeutic approaches. These innovations improve trial efficiency, broaden treatment options, and enhance patient outcomes. However, integrating AI into clinical trial frameworks presents challenges such as data standardization, regulatory hurdles, and the need for extensive validation. Addressing these obstacles will require collaboration among neurosurgeons, neuroscientists, AI specialists, and regulatory bodies to establish ethical and effective guidelines for AI-driven technologies in PD neurosurgical research. This paper emphasizes the transformative potential of AI and technological innovation in shaping the future of PD neurosurgery, ultimately enhancing therapeutic efficacy and patient care.

Background: 5-Aminolevulinic acid (5-ALA) serves as a precursor in the heme biosynthesis pathway, resulting in the selective accumulation of protoporphyrin IX (PpIX) within glioma cells. This property facilitates fluorescence-guided resection (FGR) in high-grade gliomas (HGGs), enhancing surgical precision and oncological results. Nonetheless, its clinical implementation is restricted by factors such as accessibility, cost, and technical limitations. Methods: A systematic review of PubMed literature (2019–2024) was conducted to assess the efficacy of 5-ALA in HGG surgery compared to conventional white light microscopy. Studies focusing on non-neurosurgical applications, pediatric populations, and non-HGG indications were excluded. Results: Nineteen articles met the criteria. Recent studies indicate that 5-ALA-guided resection significantly enhances gross total resection (GTR) rates compared to white light surgery (75.4% vs. 54.3%, p < 0.001). Patients receiving 5-ALA-assisted resection exhibit enhanced progression-free survival (PFS) at 6 months (median 8.1 months compared to 5.4 months, p = 0.002) and overall survival (OS) (median 15.2 months versus 12.3 months, p = 0.008). The necessity for specialized neurosurgical microscopes equipped with blue light filters restricts accessibility, especially in low-resource environments. Recent advancements in fluorescence-enhancing technologies, particularly loupe-based systems, have demonstrated increases in fluorescence intensity by up to tenfold through direct emission. Sodium fluorescein, originally designed for ophthalmological use, has been adapted for enhancing contrast in intracranial tumors; however, its non-specific binding to serum albumin restricts its accuracy in glioma resection. Conclusions: Recent publications demonstrate that 5-ALA fluorescence-guided surgery significantly improves gross total resection rates and survival outcomes in patients with high-grade gliomas. Although it offers clinical advantages, cost and equipment constraints continue to pose substantial obstacles to broad implementation. Additional research is required to enhance fluorescence-guided techniques and increase accessibility in resource-constrained environments.

Background: Gamma Knife Radiosurgery (GKRS), a specific type of Stereotactic Radiosurgery (SRS), has developed as a significant modality in the treatment of glioblastoma, particularly in conjunction with standard chemotherapy. The goal of this study is to evaluate the efficacy of combining GKRS with surgical resection and chemotherapy in enhancing therapeutic effects for glioblastoma patients aged 55 years and older. Methods: This prospective clinical study, conducted in accordance with the STROBE guidelines, involved 49 glioblastoma patients aged 55 years and older, treated between January 2013 and January 2023. Data were collected prospectively, and strict adherence to the STUPP protocol was maintained. Only patients who conformed to the STUPP protocol were included in the analysis. Due to concerns regarding the cognitive impairment associated with conventional radiotherapy, and at the patients’ request, a radiosurgery plan was offered. Radiosurgery was administered for 4–8 weeks following surgical resection. Any patients who had not received previous radiotherapy received open surgical tumor removal, followed by GKRS along with adjuvant chemotherapy. Results: In this prospective clinical study of 49 glioblastoma patients aged 55 years and older, the average lifespan post-histopathological diagnosis was established at 22.3 months (95% CI: 12.0–28.0 months). The median time before disease progression was 14.3 months (95% CI: 13.0–29.7 months). The median duration until the first recurrence after treatment was 15.2 months, with documented cases varying between 4 and 33 months. The Gamma Knife Radiosurgery (GKRS) treatment involved a median marginal recommended dose of 12.5 Gy, targeting an average volume of 5.7 cm³ (range: 1.6–39 cm³). Local recurrence occurred in 21 patients, while distant recurrence was identified in 8 patients. Within the cohort, 34 patients were subjected to further therapeutic approaches, including reoperation, a second GKRS session, the administration of bevacizumab and irinotecan, and PCV chemotherapy. A cognitive function assessment revealed that the patients treated with GKRS experienced significantly less cognitive decline compared to the historical controls, who were treated with conventional radiotherapy. The median MMSE scores declined by 1.9 points over 12 months, and the median MoCA scores declined by 2.9 points. Conclusion: This study demonstrates that Gamma Knife Radiosurgery (GKRS), when integrated with surgical resection and adjuvant chemotherapy, offers a substantial benefit for glioblastoma patients aged 55 years and older. The data reveal that GKRS not only prolongs overall survival and progression-free survival but also significantly reduces cognitive decline compared to conventional radiotherapy. These findings underscore the efficacy and safety of GKRS, advocating for its incorporation into standard treatment protocols for older glioblastoma patients. The potential of GKRS to improve patient outcomes while preserving cognitive function is compelling and warrants further research to optimize and confirm its role in glioblastoma management.

Background: Disparities in neuro-oncological care between high-income and low- and middle-income countries (LMICs) are well documented, yet region-specific data from Latin America remain limited. This review evaluates epidemiologic trends, access to care, and systemic challenges in brain tumor management across Latin American LMICs, using Argentina as a case study. Methods: A systematic review of peer-reviewed literature was conducted focusing on brain tumor incidence, mortality, risk factors, and availability of diagnostics and treatments in Latin America. Socioeconomic, cultural, and systemic barriers were also analyzed. Results: Latin America exhibits some of the highest global brain tumor mortality rates, with Brazil reporting age-standardized rates exceeding 4.5 per 100,000. Glioblastomas are frequently diagnosed at younger ages, often in the fifth decade of life, compared to the global average. Meningioma incidence has increased by 15–20% over the last decade, yet region-wide data remain fragmented. Access to neuroimaging, neurosurgery, radiotherapy, and chemotherapy is limited, with up to 60% of patients relying solely on under-resourced public health systems. Less than 30% of hospitals in rural areas have MRI availability, and continuous professional training is infrequent. Innovative adaptations, such as awake craniotomy, are used in some LMIC centers in response to equipment scarcity. Conclusions: Brain tumor care in Latin America is hindered by limited epidemiological data, restricted access to diagnostics and treatment, and insufficient workforce training. Targeted investments in healthcare infrastructure, international educational collaborations, and policy-level reforms are critical to reducing disparities and improving outcomes in neuro-oncology across the region.