Primary central nervous system (CNS) neuroblastoma, FOXR2-activated (CNS-NB-FOXR2), is a rare embryonal tumor characterized by neuroblastic differentiation and structural rearrangement of the FOXR2 gene. Previously grouped under CNS primitive neuroectodermal tumors (PNET), this entity has been reclassified based on genome-wide DNA methylation profiling. In this study, we present the detailed clinicopathological and immunohistochemical features of two pediatric cases diagnosed at our center. The first case involved a six-year-old with a left frontal mass; the second was a one-year-old with a large bifrontal lesion. Radiologically, both cases mimicked other embryonal tumors or high-grade gliomas. Histologically, tumors displayed small round blue cell morphology with neuroblastic features, including Homer-Wright rosettes and ganglionic differentiation. Immunohistochemistry demonstrated diffuse positivity for OLIG2, synaptophysin, and L1CAM, with negative expression for GFAP, EMA, and IDH1 R132H. FOXR2 showed nuclear positivity in both cases, supporting the diagnosis. Both cases exhibited diffuse L1CAM positivity-a rare finding with limited evidence in the existing literature. Although DNA methylation profiling could not be performed, the diagnosis was supported by characteristic morphology and immunohistochemistry profile. This report highlights key diagnostic features and potential mimics of CNS neuroblastoma, FOXR2-activated, and underscores the utility of immunohistochemistry in low-resource settings. Recognizing this entity is essential for accurate classification and appropriate therapeutic planning. Further studies are warranted to explore targeted therapies, including MEK inhibitors, which may hold promise based on emerging molecular data.

Diffuse midline glioma (DMG) and midline glioblastoma (mGBM) are aggressive WHO grade 4 tumors with comparable median survival of 12–18 months but require fundamentally different therapeutic approaches. DMG is molecularly defined by H3 K27-alteration, whereas mGBM lacks this alteration, however, non-invasive differentiation remains challenging due to overlapping conventional MRI features and the difficulty of obtaining tissue diagnosis from eloquent midline locations. This retrospective study included 62 patients with histologically confirmed midline gliomas (30 mGBM, 32 DMG) evaluated with 3T MRI. Quantitative DCE-MRI perfusion parameters (rCBV, rCBF, Slope-2, Ktrans, Vp, Ve) were computed and compared between the midline tumor types. Statistical analyses included Shapiro-Wilk test, t-test, and ROC curve analysis using perfusion parameters. Machine learning-based classification was also performed using four classifiers and 5-fold cross-validation, evaluating all possible feature combinations among the best features from the perfusion parameters. Among the statistical features extracted from each parametric map, the 95th percentile values showed the highest discriminative performance for differentiating mGBM from DMG, outperforming the mean, standard deviation, and other percentile measures. DMG exhibited significantly lower 95th percentile perfusion parameter values compared to mGBM (p < 0.05). Individual perfusion parameters, particularly rCBF, rCBV, Ve showed discriminative performance achieving AUC values ranging from 70.62

Intracranial fungal lesions in immunocompetent hosts without any known primary focus are rare. We present an illustrative case series of intracranial fungal mass lesions in immunocompetent hosts who presented with non-specific symptoms and imaging features that were erroneously diagnosed as neoplasms. We evaluated the imaging features of these infiltrative fungal infections, compared them with neoplastic lesions with similar presentations, and tried to seek imaging features that could help in the differentiation of fungal lesions from neoplastic/ other non-neoplastic etiologies. We speculated that two important signs that may help in raising suspicion of fungal etiology are T2 hypointensity within the lesions and lack of diffusion restriction. T2 hypointensity, when combined with other imaging features such as absence of magnetization transfer hyperintensity and lack of diffusion restriction, may help in differentiating the fungal lesion from neoplastic/other non-neoplastic etiologies. Although relative cerebral blood volume (rCBV)/relative cerebral blood flow values are relatively lower in fungal cerebritis as compared to glioblastoma, fungal lesions can also demonstrate markedly elevated rCBV values that may mimic high-grade neoplasms.

Dedifferentiated chordoma (DDC) is a rare subtype of chordoma, having a biphasic appearance, and is characterized by conventional chordoma juxtaposed with a high-grade sarcoma. The high-grade component varies from pleomorphic to fibrosarcomatous type. Several studies have been published in the literature highlighting the genetic mutations associated with conventional and poorly differentiated chordoma, however only one study has been published in the literature that included four cases of DDCs and has shown genetic alterations in p53, PTEN, RB, CDKN2A, and TERT promoter genes. There is no further molecular data available regarding DDCs. Hence, we have tried sequencing in our case of DDC which included 109 sarcoma-related genes covering all SNVs, insertions-deletions, and fusions. In our case, it is found to have a G13D mutation in the KRAS gene and a novel RPSAP52-HMGA2 fusion. Though, the clinical significance of these alterations is yet to be proven, it may help to better understand this entity.

BACKGROUND:Isocitrate dehydrogenase (IDH) wild-type (IDHwt) glioblastomas (GB) are more aggressive and have a poorer prognosis than IDH mutant (IDHmt) tumors, emphasizing the need for accurate preoperative differentiation. However, a distinct imaging biomarker for differentiation mostly lacking. Intratumoral thrombosis has been reported as a histopathological biomarker for GB. PURPOSE:To evaluate the fragmented intratumoral thrombosed microvasculature (FTV) signs on susceptibility-weighted imaging (SWI) for distinguishing IDHwt and IDHmt tumors. STUDY TYPE:Retrospective. SUBJECTS:Ninety-seven treatment-naïve patients with histopathologically confirmed IDHwt GB (54 males, 26 females) and IDHmt grade 4 astrocytoma (13 males, 4 females). FIELD STRENGTH/SEQUENCE:3-T, SWI, fluid-attenuated-inversion-recovery (FLAIR), T1-weighted, T2-weighted, PD-weighted, post-contrast T1-weighted and dynamic-contrast-enhanced (DCE)-MRI. ASSESSMENT:SWI data were evaluated by three experienced neuroradiologists (S.S., 11 years; J.S., 15 years; R.K.G., 40 years of experience), who assessed FTV presence in necrotic and peri-necrotic regions. FTV was identified as intratumoral susceptibility signal having minimal or no interslice connections. Quantitative DCE-MRI parameters were derived using first-pass-analysis and extended Tofts model. FLAIR abnormal, contrast-enhancing, and necrotic regions were segmented using in-house developed U-Net architecture. STATISTICAL TESTS:Fleiss' Kappa, Cohen's Kappa, Shapiro-Wilk test, t tests or Mann-Whitney U test, receiver-operating characteristic (ROC) analysis, confusion matrix. A P-value <0.05 was considered statistically significant. RESULTS:Fleiss' kappa test provided 91% inter-rater agreement, and Cohen's kappa provided intrarater agreement ranged from 81% to 97%. The raters' accuracy in distinguishing IDHwt from IDHmt ranged from 92% to 94%. Some of the quantitative DCE-MRI parameters (CBV, Ve, and Ktrans) provided statistically significant differences in differentiating IDHwt and IDHmt. Ktrans demonstrated 80.3% sensitivity and 81.2% specificity, with ROC analysis showing an AUC of 0.77. DATA CONCLUSION:FTV signs in necrotic and peri-necrotic regions on SWI demonstrated a high accuracy in distinguishing IDHwt from IDHmt. Qualitative assessment of FTV signs showed almost perfect inter-rater and intrarater agreement. Quantitative DCE-MRI metrics also showed statistically significant differentiation of IDHwt and IDHmt. PLAIN LANGUAGE SUMMARY:This study demonstrates that preoperative imaging, particularly the visualization of the fragmented thrombosed vasculature (FTV) sign on susceptibility-weighted imaging (SWI), effectively differentiates isocitrate dehydrogenase (IDH) wild-type (IDHwt) glioblastoma (GB) from IDH mutant (IDHmt) grade 4 astrocytomas. Over 90% of IDHwt GB patients displayed the FTV sign, a specific imaging biomarker absent in IDHmt cases. Perfusion parameters such as cerebral blood volume, Ve, and Ktrans were elevated in IDHwt gliomas, reflecting distinct vascular profiles. SWI offers a noninvasive and accurate diagnostic method, overcoming limitations of histopathology. Despite limitations like unequal sample sizes and retrospective analysis, this study underscores the clinical potential of SWI in improving glioma characterization and aiding treatment planning. LEVEL OF EVIDENCE:4 TECHNICAL EFFICACY: Stage 2.

This review aimed to formulate the most current, evidence-based recommendations for the prediction of outcome, life expectancy, and quality of life in patients with metastatic vertebral tumors. A systematic literature search on PubMed and Google Scholar from 2012–2022 was done, using the keywords “metastatic vertebral tumors + outcome prediction + prognoses,” “quality of life + spine metastases,” and “spine metastases + life expectancy.” Our PubMed search yielded 402 articles for outcome prediction, whereas 40 articles were identified for life expectancy in spine metastases. These were carefully screened by the co-authors, resulting in 61 and 11 final articles analyzed for this study. Our PubMed search for quality of life yielded 137 articles, of which 63 were carefully analyzed for this study. This up-to-date information was reviewed at two separate Spine Committee meetings of the World Federation of Neurosurgical Societies (WFNS). Two rounds of the Delphi method were used to vote and arrive at a positive or negative consensus. The WFNS Spine Committee finalized seven recommendation guidelines on the prediction of outcome, life expectancy, and quality of life in metastatic vertebral tumors. Irrespective of the primary tumor, surgical decompression in appropriately selected patients potentially improves the quality of life. Pre-operative ambulatory status, overall performance, and age are independent predictors of outcome and overall survival. Prognostic scoring systems have evolved to principle-based algorithms, amongst which NOMS is the most widely used.The best tools to measure the quality of life are EUQOL5-D and SOSGOQ in patients with metastatic spine disease.

Objective: This review aims to formulate the most current, evidence-based recommendations regarding complication avoidance, rehabilitation, pain therapy and palliative care for patients with metastatic spine tumors. Methods: A systematic literature search in PubMed and MEDLINE, and was performed from 2013 to 2023 using the search terms “complications” + “spine metastases”, “spine metastases” + + “rehabilitation”, “spine metastases” + “pain therapy” + “palliative care”. Screening criteria resulted in 35, 15 and 56 studies respectively that were analyzed. Using the Delphi method and two rounds of voting at two separate international meetings, nine members of the WFNS (World Federation of Neurosurgical Societies) Spine Committee generated nine final consensus statements. Results: Preoperative assessment for complications following surgery in patients with metastatic spine tumors should include estimation of Karnofsky score, site of primary tumor, number of spinal and visceral metastasis, ASA score and preoperative Hb (Hemoglobin) value. Complication risk factors are age > 65 years, preoperative ASA score of 3 and 4 and greater operative blood loss. Pain management using WHO analgesic concept and early mobilization are needed, starting with non-opioids, weak opioids followed by strong opioids. Morphine is the first choice for moderate to severe pain whereas IV-PCA may be used for severe breakthrough pain with monitoring. Use of bisphosphonates is considered in cases of non-localized pain and not accessible radiation therapy. Conclusions: These nine final consensus statements provide current, evidence-based guidelines on complication avoidance, rehabilitation, pain therapy and palliative care for patients with spinal metastases.

Astroblastoma is an uncommon circumscribed glial tumor mostly involving the cerebral hemisphere. The characteristic molecular alteration is meningioma (disrupted in balanced translocation) 1 (MN1) rearrangement. No definite World Health Organization grade has been assigned as both low- and high-grade tumors are known to occur. Tumors in the spine are extremely rare; to date only three cases have been reported in the literature. A vigilant microscopy and ancillary testing aid in diagnosis when the tumors present in unusual locations, as in our case. The prompt differentiation of this tumor from its mimickers is a mandate as modalities of management are different and not clearly established.

Spinal metastasis (SMs) are the most encountered tumors of the spine. Their occurrence is expected roughly around one to two years after primary tumor diagnosis. Since the advent of Magnetic Resonance Imaging (MRI), this technology has been considered the gold standard for SMs diagnosis and characterization due to its precise ability to comprehend the rate of soft tissue compression/invasion (dural sac/nervous tissue), which is one of the main drivers of management strategies. Computed Tomography (CT) remains unbeatable when a detailed bony anatomy and instability assessment is searched. Nuclear medicine technologies may have a role in diagnosis when standard MR or CT study findings are inconclusive or when the extent of the systemic metastatic disease is studied. The main objective of this study is to offer an update on the epidemiology and radiology of spinal metastasis (SMs), endorsed by the WFNS Spine Committee. A systematic review of the literature of the last ten years gave 1531 results with “spine/spinal metastatic tumors/metastasis AND radiology OR imaging OR classification” as search strings in all fields, of which 56 papers were fully analyzed. The results were discussed and voted on in two consensus meetings of the WFNS (World Federation of Neurosurgical Societies) Spine Committee, reaching a positive or negative consensus using the Delphi method. The committee stated nine recommendations on two main topics: (1) Incidence and epidemiology of SMs; (2) Radiology and classifications of SMs.

Introduction: Cauda equina syndrome (CES), conus medullaris syndrome (CMS), and sciatica-like syndromes or “sciatica mimics” (SM) may present as diagnostic and/or therapeutic dilemmas for the practicing spine surgeon. There is considerable controversy regarding the appropriate definition and diagnosis of these entities, as well as indications for and timing of surgery. Our goal is to formulate the most current, evidence-based recommendations for the definition, diagnosis, and management of CES, CMS, and SM syndromes. Methods: We performed a systematic literature search in PubMed from 2012 to 2022 using the keywords “cauda equina syndrome”, “conus medullaris syndrome”, “sciatica”, and “sciatica mimics”. Standardized screening criteria yielded a total of 43 manuscripts, whose data was summarized and presented at two international consensus meetings of the World Federation of Neurosurgical Societies (WFNS) Spine Committee. Utilizing the Delphi method, we generated seven final consensus statements. Results and conclusion: s: We provide standardized definitions of cauda equina, cauda equina syndrome, conus medullaris, and conus medullaris syndrome. We advocate for the use of the Lavy et al classification system to categorize different types of CES, and recommend urgent MRI in all patients with suspected CES (CESS), considering the low sensitivity of clinical examination in excluding CES. Surgical decompression for CES and CMS is recommended within 48 h, preferably within less than 24 h. There is no data regarding the role of steroids in acute CES or CMS. The treating physician should be cognizant of a variety of other pathologies that may mimic sciatica, including piriformis syndrome, and how to manage these.

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Spinal metastases are a significant concern for patients with advanced cancer, leading to pain, neurological deficits, and reduced quality of life. They occur in up to 70

Objective: To formulate the most current, evidence-based recommendations for the conservative management of lumbar disc herniations (LDH). Methods: A systematic literatüre search was performed 2012–2022 in PubMed/Medline and Cochrane using the keywords ‘’lumbar disc herniation’’ and ‘’conservative treatment,’’ yielding 342 total manuscripts. Screening criteria resulted in 12 final manuscripts which were summarized and presented at two international consensus meetings of the World Federation of Neurosurgical Societies (WFNS) Spine Committee. The Delphi method was utilized to arrive at three final consensus statements. Results and conclusion: s: In the absence of cauda equina syndrome, motor, or other serious neurologic deficits, conservative treatment should be the first line of treatment for LDH. NSAIDs may significantly improve acute low back and sciatic pain caused by LDH. A combination of activity modification, pharmacotherapy, and physical therapy provides good outcomes in most LDH patients.

Pediatric high grade gliomas have undergone remarkable changes in recent time with discovery of new molecular pathways. They have been added separately in current WHO 2021 blue book. All the entities show characteristic morphology and immunohistochemistry. Methylation data correctly identifies these entities into particular group of clusters. The pediatric group high grade glioma comprises- Diffuse midline glioma, H3K27-altered; Diffuse hemispheric glioma, H3G34-mutant; Diffuse pediatric-type high-grade glioma, H3-wild type & IDH-wild type; Infant hemispheric glioma and Epithelioid glioblastoma/Grade 3 pleomorphic xanthoastrocytoma and very rare IDH-mutant astrocytoma. However it is not always feasible to perform these molecular tests where cost-effective diagnosis is a major concern. Here we discuss the major entities with their characteristic histopathology, immunohistochemistry and molecular findings that may help to reach to suggest the diagnosis and help the clinician for appropriate treatment strategies. We have also made a simple algorithmic flow chart integrated with histopathology, immunohistochemistry and molecular characteristics for better understanding.

Surgical treatments for metastatic spine tumors have evolved tremendously over the last decade. Improvements in immunotherapies and other medical treatments have led to longer life expectancy in cancer patients. This, in turn, has led to an increase in the incidence of metastatic spine tumors. Spine metastases remain the most common type of spine tumor. In this study, we systematically reviewed all available literature on metastatic spine tumors and spinal instability within the last decade. We also performed further systematic reviews on cervical metastatic tumors, thoracolumbar metastatic tumors, and minimally invasive surgery in metastatic spine tumors. Lastly, the results from the systematic reviews were presented to an expert panel at the World Federation of Neurosurgical Societies (WFNS) meeting, and their consensus was also presented.

Thyroid transcription factor-1 (TTF-1) is a nuclear protein primarily recognized for its role in the development and differentiation of thyroid, lung, and certain diencephalic tissues. Although well-established as an immunohistochemical marker in thyroid and lung cancers, recent studies have explored its expression and diagnostic value in primary central nervous system (CNS) tumors. This systematic review aims to consolidate current knowledge on TTF-1 immunohistochemistry in primary CNS tumors, assessing its prevalence, diagnostic utility, and clinical implications. The review encompasses various CNS tumor types, including subependymal giant cell astrocytoma, chordoid glioma, pituicytoma, ependymomas, astrocytomas, glioblastomas, medulloblastomas, and choroid plexus tumors, highlighting the potential role of TTF-1 in differentiating these neoplasms from other CNS and metastatic tumors. By synthesizing findings from multiple studies, this review underscores the diagnostic value of TTF-1 in the neuropathological evaluation of CNS tumors and suggests directions for future research to refine its clinical application.

BACKGROUND: Conclusive evidence describing the outcomes following different treatment strategies for tension pneumocranium (TP) is lacking. Impact of predisposing conditions like multiple transnasal transsphenoidal (TNTS) procedures, intraoperative cerebrospinal fluid leak, obstructive sleep apnea, continuous positive airway pressure, violent coughing, nose blowing, positive pressure ventilation on TP outcomes is also unknown. METHODS: PubMed, Embase, Cochrane, and Google Scholar were searched for articles using Preferred Reporting Items for Systematic Review and Meta -Analysis guidelines. Multivariate logistic regression analysis was done using STATA/ BE ver 17.0. RESULTS: Thirty-five studies with 49 cases of endoscopic TNTS surgeries were included. Tension pneumocephalus was seen in 77.5% (n [ 38), tension pneumosella in 7 (14.28%), and tension pneumoventricle in 4 (8.16%). Nonfunctional pituitary adenomas (40.81%) were most common lesions associated with TP. The need of mechanical ventilation was significantly higher in patients who received conservative management (odds ratio, 1.34; confidence interval, 0.65e 2.74) (P < 0.01). However, incidence of meningitis or mortality were not influenced by factors like age, gender, pathological diagnosis, initial conservative management or early skull base repair, use of adjuvant radiation, intraoperative cerebrospinal fluid leak, multiple TNTS explorations, or presence of precipitating factors. CONCLUSIONS: Nonfunctional pituitary adenomas were the most common lesions associated with TP. Multiple TNTS procedures did not increase incidence of meningitis or mortality. Conservative management increased the need for mechanical ventilation but did not worsen the mortality outcomes.

Background and purpose: Differentiation of pilocytic astrocytoma (PA) from glioblastoma is difficult using con-ventional MRI parameters. The purpose of this study was to differentiate these two similar in appearance tumors using quantitative T1 perfusion MRI parameters combined under a machine learning framework.Materials and methods: This retrospective study included age/sex and location matched 26 PA and 33 glioblas-toma patients with tumor histopathological characterization performed using WHO 2016 classification. Multi -parametric MRI data were acquired at 3 T scanner and included T1 perfusion and DWI data along with con-ventional MRI images. Analysis of T1 perfusion data using a leaky-tracer-kinetic-model, first-pass-model and piecewise-linear-model resulted in multiple quantitative parameters. ADC maps were also computed from DWI data. Tumors were segmented into sub-components such as enhancing and non-enhancing regions, edema and necrotic/cystic regions using T1 perfusion parameters. Enhancing and non-enhancing regions were combined and used as an ROI. A support-vector-machine classifier was developed for the classification of PA versus glioblas-toma using T1 perfusion MRI parameters/features. The feature set was optimized using a random-forest based algorithm. Classification was also performed between the two tumor types using the ADC parameter.Results: T1 perfusion parameter values were significantly different between the two groups. The combination of T1 perfusion parameters classified tumors more accurately with a cross validated error of 9.80% against that of ADC's 17.65% error.Conclusion: The approach of using quantitative T1 perfusion parameters based upon a support-vector-machine classifier reliably differentiated PA from glioblastoma and performed better classification than ADC.

Background: Glioblastoma (GB) is among the most devastative brain tumors, which usually comprises sub-regions like enhancing tumor (ET), non-enhancing tumor (NET), edema (ED), and necrosis (NEC) as described on MRI. Semi-automated algorithms to extract these tumor subpart volumes and boundaries have been demonstrated using dynamic contrast-enhanced (DCE) perfusion imaging. We aim to characterize these sub-regions derived from DCE perfusion MRI using routine 3D post-contrast-T1 (T1GD) and FLAIR images with the aid of Radiomics analysis. We also explored the possibility of separating edema from tumor sub-regions by extracting the most influential radiomics features.Methods: A total of 89 patients with histopathological confirmed IDH wild type GB were considered, who underwent the MR imaging with DCE perfusion-MRI. Perfusion and kinetic indices were computed and further used to segment tumor sub-regions. Radiomics features were extracted from FLAIR and T1GD images with PyRadiomics tool. Statistical analysis of the features was carried out using two approaches as well as machine learning (ML) models were constructed separately, i) within different tumor sub-regions and ii) ED as one category and the remaining sub-regions combined as another category. ML based predictive feature maps was also constructed.Results: Seven features found to be statistically significant to differentiate tumor sub-regions in FLAIR and T1GD images, with p-value < 0.05 and AUC values in the range of 0.72 to 0.93. However, the edema features stood out in the analysis. In the second approach, the ML model was able to categorize the ED from the rest of the tumor sub-regions in FLAIR and T1GD images with AUC of 0.95 and 0.89 respectively.Conclusion: Radiomics-based specific feature values and maps help to characterize different tumor sub-regions. However, the GLDM_DependenceNonUniformity feature appears to be most specific for separating edema from the remaining tumor sub-regions using conventional FLAIR images. This may be of value in the segmentation of edema from tumors using conventional MRI in the future.