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Background The prognostic factors for survival in patients with ependymoma (EPN) remain controversial. The aim of this study was to establish a prognostic model for 5‐ and 10‐year survival probability nomograms for patients with EPN. Methods Clinical data from the Surveillance, Epidemiology, and End Results (SEER) database were used for patients diagnosed with ependymoma between 2000 and 2018 and were randomized 7:3 into a development set and a validation set. Factors significantly associated with prognosis were screened out using the least absolute shrinkage and selection operator (LASSO) regression. The calibration chart and consistency index (C‐index) are used to evaluate the discrimination and consistency of the prediction model. Decision curve analysis (DCA) was used to further evaluate the established model. Finally, prognostic factors selected by LASSO regression were evaluated using Kaplan–Meier (KM) survival curves. Results A total of 3820 patients were included in the prognostic model. Seven survival predictors were obtained by LASSO regression screening, including age, gender, morphology, location, size, laterality, and resection. The prognostic model of the nomogram showed moderate discriminative ability in the development group and the validation group, with a C‐index of 0.642 and 0.615, respectively. In the development set and validation set survival curves, the prognosis index of high risk was less effective than low risk (p < 0.001). Conclusions Our nomograms may play an important role in predicting 5 and 10‐year outcomes for patients with ependymoma. This will help assist clinicians in personalized medicine. Prognostic factors in patients with ependymoma (EPN) remain controversial. Based on the SEER database, we constructed prognosis models for EPN 5‐year and 10‐year survival rates. It may provide a reference for clinicians to personalized treatment.

The Consortium to Inform Molecular and Practical Approaches to Central Nervous System Tumor Taxonomy (cIMPACT‐NOW) updates provide guidelines for the diagnosis of central nervous system (CNS) tumors and suggestions for future World Health Organization (WHO) classification. Following publication of the fifth edition WHO Classification of CNS Tumors (WHO CNS5) in 2021, the cIMPACT‐NOW working group “Clarification” reviewed WHO CNS5 and prioritized two topics for further elucidation: (a) distinction of Glioblastoma, IDH‐wildtype from Diffuse pediatric‐type high‐grade glioma, H3‐wildtype, and IDH‐wildtype and (b) clarification of subgroups of posterior fossa (PF) ependymal tumors. Recommendations regarding the IDH‐ and H3‐wildtype diffuse high‐grade gliomas include: (1) use caution assigning CNS WHO grade 4 (diagnosis of Glioblastoma, IDH‐wildtype) to a “TERT promoter only”, histologically low‐grade, IDH‐wildtype tumor; (2) EGFR gene amplification and +7/−10 chromosome copy number alterations should not be used as solitary defining features for diagnosing high‐grade gliomas as Glioblastoma, IDH‐wildtype in patients <40 years of age; (3) Diffuse pediatric‐type high‐grade glioma, H3‐wildtype, and IDH‐wildtype should be considered in the differential diagnosis in adults, especially those <40 years of age; (4) PDGFRA alteration, EGFR alteration, or MYCN amplification count as key molecular features of Diffuse pediatric‐type high‐grade glioma, H3‐wildtype, and IDH‐wildtype only in patients <25 years. Guidelines for improved diagnosis of posterior fossa ependymal tumors include: (1) immunohistochemical demonstration of nuclear EZHIP supports classification as PF group A ependymoma; (2) a PF ependymoma with retained nuclear H3 K27me3 expression and no nuclear EZHIP overexpression for which DNA methylation profiling is not performed should be considered as PF ependymoma, “not otherwise specified”; (3) for emerging tumors not included in WHO CNS5, “not elsewhere classified” (NEC) can be added to the diagnosis. Of note, these recommendations are not formal changes to the WHO definitions and diagnostic criteria but are intended to provide diagnostic guidance in advance of WHO CNS6.

To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P  < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10 −3 mm 2  s −1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

Abstract BACKGROUND: Contrast-enhanced ultrasound (CEUS) is a dynamic and continuous modality that offers a real-time, direct view of vascularization patterns and tissue resistance for many organs. Thanks to newer ultrasound contrast agents, CEUS has become a well-established, live-imaging technique in many contexts, but it has never been used extensively for brain imaging. The use of intraoperative CEUS (iCEUS) imaging in neurosurgery is limited. OBJECTIVE: To provide the first dynamic and continuous iCEUS evaluation of a variety of brain lesions. METHODS: We evaluated 71 patients undergoing iCEUS imaging in an off-label setting while being operated on for different brain lesions; iCEUS imaging was obtained before resecting each lesion, after intravenous injection of ultrasound contrast agent. A semiquantitative, offline interobserver analysis was performed to visualize each brain lesion and to characterize its perfusion features, correlated with histopathology. RESULTS: In all cases, the brain lesion was visualized intraoperatively with iCEUS. The afferent and efferent blood vessels were identified, allowing evaluation of the time and features of the arterial and venous phases and facilitating the surgical strategy. iCEUS also proved to be useful in highlighting the lesion compared with standard B-mode imaging and showing its perfusion patterns. No adverse effects were observed. CONCLUSION: Our study is the first large-scale implementation of iCEUS in neurosurgery as a dynamic and continuous real-time imaging tool for brain surgery and provides the first iCEUS characterization of different brain neoplasms. The ability of CEUS to highlight and characterize brain tumor will possibly provide the neurosurgeon with important information anytime during a surgical procedure.

Purpose The overall survival and prognostic factors for children with multiply recurrent posterior fossa ependymoma are not well understood. We aimed to assess prognostic factors associated with survival for relapsed pediatric posterior fossa ependymoma. Methods An institutional database was queried for children with a primary diagnosis of posterior fossa ependymoma from 2000 to 2019. Kaplan–Meier survival analysis and Cox-proportional hazard regression were used to assess the relationship between treatment factors and overall survival. Results There were 60 patients identified; molecular subtype was available for 56, of which 49 (87.5%) were PF-A and 7 (12.5%) were PF-B. Relapse occurred in 29 patients (48%) at a mean time of 24 months following primary resection. Median 50% survival was 12.3 years for all patients and 3.3 years following diagnosis of first relapsed disease. GTR was associated with significantly improved survival following primary resection (HR 0.373, 95% CI 0.14–0.96). Presence of recurrent disease was significantly associated with worse survival (p < 0.0001). At recurrent disease diagnosis, disseminated disease was a negative prognostic factor (HR 11.0 95% CI 2.7–44) while GTR at first relapse was associated with improved survival HR 0.215 (95% CI: 0.048–0.96, p = 0.044). Beyond first relapse, the impact of GTR was not significant on survival, though surgery compared to no surgery was favorable with HR 0.155 (95% CI: 0.04–0.59). Conclusions Disseminated disease at recurrence and extent of resection for first relapsed disease were important prognostic factors. Surgery compared to no surgery was associated with improved survival for the multiply recurrent ependymoma cohort.

Patients with ependymoma exhibit a wide range of clinical outcomes that are currently unexplained by clinical or histological factors. Little is known regarding molecular biomarkers that could predict clinical behavior. Since recent data suggest that these tumors display biological characteristics according to their location (cerebral vs. infratentorial vs. spinal cord), rather than explore a broad spectrum of ependymoma, we focused on molecular alterations in ependymomas arising in the infratentorial compartment. Unsupervised clustering of available g ene expression microarray data revealed two major subgroups of infratentorial ependymoma. Group 1 tumors over expressed genes that were associated with mesenchyme, Group 2 tumors showed no distinct gene ontologies. To assess the prognostic significance of these gene expression subgroups, real-time reverse transcriptase polymerase chain reaction assays were performed on genes defining the subgroups in a training set. This resulted in a 10-gene prognostic signature. Multivariate analysis showed that the 10-gene signature was an independent predictor of recurrence-free survival after adjusting for clinical factors. Evaluation of an external dataset describing subgroups of infratentorial ependymomas showed concordance of subgroup definition, including validation of the mesenchymal subclass. Importantly, the 10-gene signature was validated as a predictor of recurrence-free survival in this dataset. Taken together, the results indicate a link between clinical outcome and biologically identified subsets of infratentorial ependymoma and offer the potential for prognostic testing to estimate clinical aggressiveness in these tumors.

Brainstem ependymomas (EPNs) are rare and aggressive central nervous system tumors with unique anatomical challenges and poor prognosis. Traditional survival estimates offer limited clinical guidance due to their static nature. This study aimed to investigate the dynamic survival patterns of brainstem EPNs using conditional survival (CS) analysis and to develop a web-based nomogram model for individualized, real-time prognostication. Patients diagnosed with primary brainstem EPNs between 2000 and 2021 were identified from the SEER database. CS analysis was performed to assess changes in survival probability over time. Annual hazard rates were calculated to identify high-risk periods. Prognostic variables were selected using best subset regression (BSR) and least absolute shrinkage and selection operator (LASSO) methods. A CS-based nomogram was constructed using multivariable Cox regression and validated through calibration plots, ROC curves, and decision curve analysis (DCA). A risk stratification system and an interactive web calculator were also developed. A total of 697 patients were included and randomly assigned to training (n = 487) and validation (n = 210) cohorts. CS analysis showed that as patients survive longer after diagnosis, their probability of surviving additional years increases steadily. And six variables (age, sex, race, histology, surgery, and radiotherapy) were identified via the LASSO model for nomogram construction. The CS-nomogram demonstrated good calibration and acceptable discrimination, with 1-, 3-, and 5-year AUCs of 0.626, 0.649, and 0.656 in the training cohort, and 0.688, 0.692, and 0.687 in the validation cohort, respectively. DCA confirmed the clinical utility of the model. A risk classification system effectively stratified patients into high- and low-risk groups with significantly different survival outcomes. A web-based calculator was created to facilitate real-world application. This study presents a novel CS-based nomogram that dynamically predicts survival in patients with brainstem EPNs. By capturing time-dependent survival probabilities and integrating key clinical factors, the model offers a practical tool to support individualized prognosis, patient counseling, and follow-up planning in clinical practice. While it offers individualized prognostic insights, its clinical use requires further external validation.

Better understanding of ependymoma (EPN) biology at relapse is needed to improve therapy at this critical event. Convincing data exist defining transcriptionally distinct posterior fossa (PF) sub-groups A and B at diagnosis. The clinical and biological consequence of these sub-groups at recurrence has not yet been defined. Genome and transcriptome microarray profiles and clinical variables of matched primary and first recurrent PF EPN pairs were used to identify biologically distinct patterns of progression between EPN sub-groups at recurrence. Key findings were validated by histology and immune function assays. Transcriptomic profiles were partially conserved at recurrence. However, 4 of 14 paired samples changed sub-groups at recurrence, and significant sub-group-specific transcriptomic changes between primary and recurrent tumors were identified, which were predominantly immune-related. Further examination revealed that Group A primary tumors harbor an immune gene signature and cellular functionality consistent with an immunosuppressive phenotype associated with tissue remodeling and wound healing. Conversely, Group B tumors develop an adaptive, antigen-specific immune response signature and increased T-cell infiltration at recurrence. Clinical distinctions between sub-groups become more apparent after first recurrence. Group A tumors were more often sub-totally resected and had a significantly shorter time to subsequent progression and worse overall survival. Minimal tumor-specific genomic changes were observed for either PF Groups A or B at recurrence. Molecular sub-groups of PF EPN convey distinct immunobiologic signatures at diagnosis and recurrence, providing potential biologic rationale to their disparate clinical outcomes. Immunotherapeutic approaches may be warranted, particularly in Group A PF EPN.

Background This particular case is a world-first with no previous literature reports on patients presenting with both benign acoustic schwannoma and malignant ependymoma. Case presentation: A 60-year-old woman with unexplained right-sided hearing loss that had worsened progressively over 4 years, along with intermittent dizziness that had begun 3 years prior. Our preliminary diagnosis included: (1) Right acoustic neuroma; (2) Ependymoma of the fourth ventricle; and (3) Hydrocephalus. We employed the right sigmoid sinus posterior approach combined with the posterior median approach, beginning with removal of the fourth ventricle tumor and then proceeding to acoustic schwannomas resection through rotating operation positions. Conclusions: The case presented significant challenges owing to: The difficulty encountered in arriving at a diagnosis; The difficulty in choosing a suitable surgical approach; The complexity of the surgical sequence; The intricacy of the surgical process. It’s rare, complex, and had excellent surgical results.

Although ependymoma (EPN) molecular subgroups have been well established by integrated high-throughput platforms, low- and middle-income countries still need low-cost techniques to promptly classify these molecular subtypes. Here, we applied low-cost methods to classify EPNs from a Brazilian cohort with 60 pediatric EPN patients. Fusion transcripts (C11orf95-RELA, YAP1-MAMLD1, and YAP1-FAM118B) were investigated in supratentorial EPN (ST-EPNs) samples through RT-PCR/Sanger sequencing and immunohistochemistry (IHC) for p65/L1CAM. qRT-PCR and IHC were used to evaluate expression profiling of CXorf67, LAMA2, NELL2, and H3K27me3 in posterior fossa EPN (PF-EPNs) samples. In silico analysis was performed using public microarray data to validate the molecular assignment PF-EPNs with LAMA2/NELL2 markers. RELA cases and YAP1-MAMLD1 fusions were identified in nine and four ST-EPNs, respectively. An additional RELA case was identified by IHC. Of note, LAMA2 and NELL2 gene expression and immunoprofiling were less accurate for classifying PF-EPNs, which were confirmed by in silico analysis. Yet, H3K27me3 staining was sufficient to classify PF-EPN subgroups. Our results emphasize the feasibility of a simplified strategy to molecularly classify EPNs in the vast majority of cases (49/60; 81.7%). A coordinated combination of simple methods can be effective to screen pediatric EPN with the available laboratory resources at most low-/mid-income countries, giving support for clinical practice in pediatric EPN.Key messagesLow- and middle-income countries need effective low-cost approaches to promptly distinguish between EPN molecular subgroups.RT-PCR plus Sanger sequencing is able to recognize the most common types of RELA and YAP1 fusion transcripts in ST-EPNs.Genetic and protein expressions of LAMA2 and NELL2 are of limited value to accurately stratify PF-EPNs.Immunohistochemical staining for H3K27me3 may be used as a robust method to accurately diagnose PF-EPNs subgroups.A coordinated flow diagram based on these validated low-cost methods is proposed to help clinical-decision making and to reduce costs with NGS assessment outside research protocols.