Magnetic resonance imaging (MRI) is an indispensable tool in neurosurgery, though it sometimes faces challenges such as \"tumor mimicry.\" While intraoperative MRI (iMRI) is widely recognized for its usefulness in achieving maximal safe resection during glioma surgery, instances of tumor mimicry still occur on iMRI. Moreover, reports on tumor mimics observed through iMRI, particularly in low-grade gliomas, remain scarce. In this article, we present a case of oligodendroglioma, where a newly emerged T2 high-signal intensity region on iMRI necessitated differentiation from tumor expansion. A 23-year-old man presented with a newly diagnosed brain tumor and underwent surgical removal. An iMRI taken after tumor removal revealed a newly emerged T2 hyperintense area without diffusion restriction around the resection cavity, which was not observed in the preoperative MRI. Suspecting residual tumor, we performed additional resection. An MRI on the following day confirmed that the T2 hyperintense area identified on the iMRI had been completely resected but also revealed an enlarged T2 high-signal area over a wider region. Histopathology found no tumor cells in the additionally resected area, indicating that the iMRI finding was a tumor mimic. Six months later, the T2 high-signal area around the resection cavity had disappeared on MRI without any additional treatment. This case highlights the challenge of distinguishing between T2 hyperintense mimicry and tumor enlargement during glioma surgery seen on iMRI. Despite the significant value of iMRI, our report underscores the need for careful interpretation in neurosurgical practice, particularly with non-contrast-enhancing tumors.

UNASSIGNED: Epileptic seizures commonly burden low-grade glioma (LGG) patients and negatively impact quality of life, neurocognition, and general patient health. Anti-seizure medications (ASMs) are used to manage seizures but can result in undesired side effects. Our aim was to report our experience in epilepsy in one of the largest case series of LGG patients (reclassified in accordance with the WHO 2021 classification). Furthermore, we evaluate our postoperative seizure frequency difference between LGG patients who use preoperative ASMs and ones with no ASMs.
UNASSIGNED: Data were retrospectively collected from Salford Royal Hospital electronic records and Neuro-Oncology database from 2006 to 2022. Descriptive statistics were performed for demographic analysis, while multivariable analysis was used to determine postoperative seizure-free outcomes.
UNASSIGNED: In total, 257 operations were performed on 206 patients. Postoperatively, 114 patients suffered from seizures, and approximately 45.2% of patients developed seizures at 3-12 months postsurgery, with the odds higher in patients on preoperative ASMs. There was no evidence to suggest a higher postoperative seizure rate in patients undergoing awake craniotomy versus general anesthetic. The extent of resection (EOR) was inversely related to seizure failure, with gross-total resection showing a statistically significant reduction in seizures in comparison to all other surgical resections.
UNASSIGNED: In our experience, there is no evidence to suggest a reduced postoperative seizure outcome when prescribing preoperative ASMs. EOR is an independent prognosticator for postoperative seizure failure with all other variables demonstrating nonsignificance. Overall, a larger study can investigate the role of ASMs in LGG in greater detail.

UNASSIGNED: Radiotherapy (RT) plays an integral role in the management of low-grade gliomas (LGG). Late toxicity from RT can cause progressive neurocognitive dysfunction. Radiation-induced damage to the hippocampus (HCP) plays a considerable role in memory decline. Advancements in photon planning software have resulted in the development of multi-criteria optimization (MCO) and HyperArc technologies which may improve HCP sparing while maintaining planning target volume (PTV) target coverage.
UNASSIGNED: Three planning methods for hippocampal sparing (HS) were compared, volumetric modulated arc therapy (VMAT) without HS (VMAT_noHS), VMAT with HS (VMAT_HS), MCO with HS (MCO_HS), and HyperArc with HS (HyperArc_HS).
UNASSIGNED: Twenty-five patients were identified. The contralateral HCP was spared in 16 patients and bilateral HCP in 9 patients with superiorly located tumors. All 3 HS planning techniques showed significant reductions in dose to the spared HCP in contralateral cases but only VMAT_HS and MCO_HS achieved this in bilateral cases (P < .008). Only MCO_HS was superior to VMAT_HS in lowering the dose to both contralateral HCP and bilateral HCP in all measured metrics (P < .008). PTV and OAR (organ at risk) dose constraints were achieved for all plans.
UNASSIGNED: This retrospective dosimetric study demonstrated the feasibility of HS for low-grade glioma. All 3 HS planning techniques achieved significant dose reductions to the spared contralateral hippocampus, but only MCO_HS and VMAT_HS achieved this in bilateral cases. MCO was superior to other planning techniques for sparing both bilateral and contralateral hippocampi.

UNASSIGNED: WEE1 is a critical kinase in the DNA damage response pathway and has been shown to be effective in treating serous uterine cancer. However, its role in gliomas, specifically low-grade glioma (LGG), remains unclear. The impact of DNA methylation on WEE1 expression and its correlation with the immune landscape in gliomas also need further investigation.
UNASSIGNED: This study used data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) and utilized various bioinformatics tools to analyze gene expression, survival, gene correlation, immune score, immune infiltration, genomic alterations, tumor mutation burden, microsatellite instability, clinical characteristics of glioma patients, WEE1 DNA methylation, prognostic analysis, single-cell gene expression distribution in glioma tissue samples, and immunotherapy response prediction based on WEE1 expression.
UNASSIGNED: WEE1 was upregulated in LGG and glioblastoma (GBM), but it had a more significant prognostic impact in LGG compared to other cancers. High WEE1 expression was associated with poorer prognosis in LGG, particularly when combined with wild-type IDH. The WEE1 inhibitor MK-1775 effectively inhibited the proliferation and migration of LGG cell lines, which were more sensitive to WEE1 inhibition. DNA methylation negatively regulated WEE1, and high DNA hypermethylation of WEE1 was associated with better prognosis in LGG than in GBM. Combining WEE1 inhibition and DNA methyltransferase inhibition showed a synergistic effect. Additionally, downregulation of WEE1 had favorable predictive value in immunotherapy response. Co-expression network analysis identified key genes involved in WEE1-mediated regulation of immune landscape, differentiation, and metastasis in LGG.
UNASSIGNED: Our study shows that WEE1 is a promising indicator for targeted therapy and prognosis evaluation. Notably, significant differences were observed in the role of WEE1 between LGG and GBM. Further investigation into WEE1 inhibition, either in combination with DNA methyltransferase inhibition or immunotherapy, is warranted in the context of LGG.

Glioma, a predominant type of brain tumor, can be fatal. This necessitates an early diagnosis and effective treatment strategies. Current diagnosis is based on biopsy, prompting the need for non invasive neuroimaging alternatives. Diffusion tensor imaging (DTI) is a promising method for studying the pathophysiological impact of tumors on white matter (WM) tissue. Single-shell DTI studies in brain glioma patients have not accounted for free water (FW) contamination due to tumors. This study aimed to (a) assess the efficacy of a two-compartment DTI model that accounts for FW contamination and (b) identify DTI-based biomarkers to classify low-grade glioma (LGG) and high-grade glioma (HGG) patients. DTI data from 86 patients (LGG n = 39, HGG n = 47) were obtained using a routine clinical imaging protocol. DTI metrics of tumorous regions and normal-appearing white matter (NAWM) were evaluated. Advanced stacked-based ensemble learning was employed to classify LGG and HGG patients using both single- and two-compartment DTI model measures. The DTI metrics of the two-compartment model outperformed those of the standard single-compartment DTI model in terms of sensitivity, specificity, and area under the curve of receiver operating characteristic (AUC-ROC) score in classifying LGG and HGG patients. Four features (out of 16 features), namely fractional anisotropy (FA) of the edema and core region and FA and mean diffusivity of the NAWM region, showed superior performance (sensitivity = 92%, specificity = 90%, and AUC-ROC = 90%) in classifying LGG and HGG. This demonstrates that both tumorous and NAWM regions may be differentially affected in LGG and HGG patients. Our results demonstrate the significance of using a two-compartment DTI model that accounts for FW contamination by improving diagnostic accuracy. This improvement may eventually aid in planning treatment strategies for glioma patients.

UNASSIGNED: Glioma resection aims for maximal tumor removal while preserving neurological function. Neuronavigation systems (NS), with intraoperative imaging, have revolutionized this process through precise tumor localization and detailed anatomical navigation.
UNASSIGNED: To assess the efficacy and breadth of neuronavigation and intraoperative imaging in glioma resections, identify operational challenges, and provide educational insights to medical students and non-neurosurgeons regarding their practical applications.
UNASSIGNED: This systematic review analyzed studies from 2012 to 2023 on glioma patients undergoing surgical resection with neuronavigation, sourced from MEDLINE (PubMed), Embase, and Web of Science. A database-specific search strategy was employed, with independent reviewers screening for eligibility using Rayyan and extracting data using the Joanna Briggs Institute (JBI) tool.
UNASSIGNED: The integration of neuronavigation systems with intraoperative imaging modalities such as iMRI, iUS, and 5-ALA significantly enhances gross total resection (GTR) rates and extent of resection (EOR). While advanced technology improves surgical outcomes, it does not universally reduce operative times, and its impact on long-term survival varies. Combinations like NS + iMRI and NS + 5-ALA + iMRI achieve higher GTR rates compared to NS alone, indicating that advanced imaging adjuncts enhance tumor resection accuracy and success. The results underscore the multifaceted nature of successful surgical outcomes.
UNASSIGNED: Integrating intraoperative imaging with neuronavigation improves glioma resection. Ongoing research is vital to refine technology, enhance accuracy, reduce costs, and improve training, considering various factors impacting patient survival.

Immunologic treatment options are uncommon in low-grade gliomas, although such therapies might be beneficial for inoperable and aggressive cases. Knowledge of the immune and stromal cells in low-grade gliomas is highly relevant for such approaches but still needs to be improved. Published gene-expression data from 400 low-grade gliomas and 193 high-grade gliomas were gathered to quantify 10 microenvironment cell populations with a deconvolution method designed explicitly for brain tumors. First, we investigated general differences in the microenvironment of low- and high-grade gliomas. Lower-grade and high-grade tumors cluster together, respectively, and show a general similarity within and distinct differences between these groups, the main difference being a higher infiltration of fibroblasts and T cells in high-grade gliomas. Among the analyzed entities, gangliogliomas and pleomorphic xanthoastrocytomas presented the highest overall immune cell infiltration. Further analyses of the low-grade gliomas presented three distinct microenvironmental signatures of immune cell infiltration, which can be divided into T-cell/dendritic/natural killer cell-, neutrophilic/B lineage/natural killer cell-, and monocytic/vascular/stromal-cell-dominated immune clusters. These clusters correlated with tumor location, age, and histological diagnosis but not with sex or progression-free survival. A survival analysis showed that the prognosis can be predicted from gene expression, clinical data, and a combination of both with a support vector machine and revealed the negative prognostic relevance of vascular markers. Overall, our work shows that low- and high-grade gliomas can be characterized and differentiated by their immune cell infiltration. Low-grade gliomas cluster into three distinct immunologic tumor microenvironments, which may be of further interest for upcoming immunotherapeutic research.

UNASSIGNED: Radiological follow-up of diffuse low-grade gliomas (LGGs) growth is challenging. Approximative visual assessment still predominates over objective quantification due to the complexity of the pathology. The infiltrating character, diffuse borders and presence of surgical cavities demand LGG-based linear measurement rules to efficiently and precisely assess LGG evolution over time.
UNASSIGNED: We compared optimized 1D, 2D, and 3D linear measurements with manual volume segmentation as a reference to assess LGG tumor growth in 36 patients with LGG (340 magnetic resonance imaging scans), using the clinically important mean tumor diameter (MTD) and the velocity diameter expansion (VDE). LGG-specific progression thresholds were established using the high-grade gliomas-based RECIST, Macdonald, and RANO criteria, comparing the sensitivity to identify progression/non-progression for each linear method compared to the ground truth established by the manual segmentation.
UNASSIGNED: 3D linear volume approximation correlated strongly with manually segmented volume. It also showed the highest sensitivity for progression detection. The MTD showed a comparable result, whereas the VDE highlighted that caution is warranted in the case of small tumors with multiple residues. Novel LGG-specific progression thresholds, or the critical change in estimated tumor volume, were increased for the 3D (from 40% to 52%) and 2D methods (from 25% to 33%) and decreased for the 1D method (from 20% to 16%). Using the 3D method allowed a ~5-minute time gain.
UNASSIGNED: While manual volumetric assessment remains the gold standard for calculating growth rate, the 3D linear method is the best time-efficient standardized alternative for radiological evaluation of LGGs in routine use.

Low-grade glioma (LGG) is a grade II-III glioma accompanied by distinct clinical and molecular characteristics and the studies related to its prognosis are still unclear. The objective of this study is to explore the involvement of mitochondrial-related genes SLBP, COMMD7, LSM4, TOMM34, RPP40, FKBP1A, ARPC1A, and TBCA for the prognosis of LGG. We detected differences in the expression of some of the genes by analyzing the bioinformatics dataset and combining it with RT-PCR experiments. Subsequently, a nomogram was constructed and validated for the clinical relevance of risk factors such as age, WHO grade, IDH mutation status, Ch.1p19q co-deletion status, and high and low expression of ARPC1A to predict the 1-, 3-, 5-year overall survival and prognostic relevance of ARPC1A. Gene set enrichment analysis was performed for the relevant datasets pertinent to the expression of ARPC1A to elucidate the cancer-promoting pathways involved in the LGG through KEGG and GO analysis. Transfection assays, CCK-8 assays, and flow cytometry were used to determine the proliferation rate, and apoptosis rate of the HS683 and SW1783 cell lines respectively. Western blotting was used to examine the involvement of the cancer-promoting activity of ARPC1A through MAPK signaling. In this study, the prognostic value of ARPC1A in LGG was found by bioinformatics analysis combined with experimental approach analysis and may be a significant independent risk factor. ARPC1A fosters a higher LGG proliferation rate that may control the MAP kinase signaling and could be a prominent biomarker for LGG. Future studies are warranted to explore its clinical implications.

Tumors may contain billions of cells, including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that are consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.