Subtype Of Meningioma Research Articles

Recent Advances in Meningioma Immunogenetics.

Meningiomas are relatively common, and typically benign intracranial tumors, which in many cases can be cured by surgical resection. However, less prevalent, high grade meningiomas, grow quickly, and recur frequently despite treatment, leading to poor patient outcomes. Across tumor grades, subjective guidelines for histological analysis can preclude accurate diagnosis, and an insufficient understanding of recurrence risk can cloud the choice of optimal treatment. Improved diagnostic and prognostic markers capable of discerning between the 15 heterogeneous WHO recognized meningioma subtypes are necessary to improve disease management and identify new targeted drug treatments. In this review, we show the advances in molecular profiling and immunophenotyping of meningiomas, which may lead to the development of new personalized therapeutic strategies.

Diagnostic role of MUC4 immunohistochemical expression in various subtypes of meningioma

Background Meningiomas exhibit a wide range of histological appearances, and they may show overlapping morphology with other nonmeningothelial tumors, and so the differential diagnosis may be challenging.Aim To examine the diagnostic role of MUC4 expression in various histological subtypes and grades of meningioma and some other nonmeningothelial tumors relevant to the potential diagnosis.Materials and methods The expression of MUC4 and epithelial membrane antigen was analyzed by immunohistochemical staining in various subtypes of meningiomas and other nonmeningothelial tumors that enter in the differential diagnosis (schwannoma, solitary fibrous tumors/hemangiopericytoma, glioblastoma, and hemangioblastoma).Results A statistically significant difference was detected between MUC4 expression in meningioma and other nonmeningothelial tumors (P<0.001). MUC4 was expressed in 83.3% of meningioma cases and was entirely negative in nonmeningothelial tumors, with 83.3% sensitivity and 100% specificity.Conclusion MUC4 is a possible novel adjunct diagnostic marker that can distinguish between confusing cases of meningioma and the tested nonmeningothelial tumors.

Comparative Analysis of the MRI Characteristics of Meningiomas According to the 2016 WHO Pathological Classification.

Objects:To evaluate the performance of preoperative magnetic resonance imaging (MRI) in evaluating diagnoses, operation methods and recurrence of meningiomas according to the World health organization (WHO) pathological classification.Methods:MRI characteristics of 127 meningioma patients were retrospectively analysed according to pathological results (WHO grade) and their association with Simpson’s grades (resection) and recurrence.Results:The T1-weighted imaging (T1WI) signal intensity of WHO grade I meningiomas was slightly hypointense or isointense gray, while the T2-weighted imaging (T2WI) signal intensity was isointense or slightly hyperintense. The T1WI and T2WI signal intensity in WHO grade II and III meningiomas was isointense gray. The enhancement degree and patterns, lobulation, flowing voids, dural tail, maximum diameter, peritumoural oedema, ADC values and margin were significantly different between any 2 grades (P < 0.05). The ADC values were higher for WHO grade I tumors than for WHO grade II and III tumors (P < 0.001). Among all the analyzed characteriscs, ADC values, peritumoural oedema, and margin effectively predicted the diagnosis according to the WHO classification. The operation method and surgical resection were different between WHO grade Ⅰ and WHO grade Ⅱ/Ⅲ meningiomas (P < 0.05). The recurrence rate increased with tumor grade, but there was no statistical difference among the 3 types(P> 0.05).Conclusions:WHO grades and pathological subtypes of meningiomas can generally be determined based on their MRI characteristics. In addition, MRI provides significant guidance for the grading of surgical success and prognosis.

Estrogen and progesterone receptor in meningiomas: An immunohistochemical analysis.

Meningiomas are common slow-growing primary intracranial neoplasms attached to the dura mater and are composed of neoplastic meningothelial cells. Increased incidence of meningiomas in women with an increased tumor growth during pregnancy and a possible association with breast cancer suggested that female sex hormones have been involved in the growth of meningiomas. Antihormonal-targeted therapy would be beneficial in such patients. The aim of this study is to correlate the expression of estrogen receptor (ER) and progesterone receptor (PR) in meningiomas with gender, location, histological subtypes, and grade. This is a 3½-year prospective and retrospective study of intracranial and intraspinal meningiomas. Clinical details of all the patients were noted from the computerized hospital information system. Immunohistochemistry for ER and PR was performed. Statistical analysis was performed using Chi-square test. During the study period, there were 80 Grade I, 18 Grade II, and 2 Grade III meningiomas categorized as per the World Health Organization 2007 classification. The female-to-male ratio was 1.9:1 and the mean age was 47.8 years. ER was expressed in 2% of meningiomas. PR was expressed in 67.5% of Grade I and 66.6% of Grade II and none of Grade III meningiomas. Brain-invasive meningiomas showed 54.5% PR immunopositivity and negative for ER. ER and PR were expressed in 2% and 66% of meningiomas, respectively. Statistically significant relationship was not found between the positivity of PR in females and males of Grade I and Grade II/III meningiomas, intracranial and spinal tumors, Grade I and Grade II/III cases, and various histological subtypes of meningiomas.

En Plaque Meningiomas: A Narrative Review

Background En plaque meningiomas are a rare subtype of meningiomas that are frequently encountered in the spheno-orbital region. Characterized by a hyperostotic and dural invasive architecture, these tumors present unique diagnostic and treatment considerations. Objective The authors conduct a narrative literature review of clinical reports of en plaque meningiomas to summarize the epidemiology, clinical presentation, diagnostic criteria, and treatment considerations in treating en plaque meningiomas. Additionally, the authors present a case from their own experience to illustrate its complexity and unique features. Methods A literature search was conducted using the MEDLINE database using the following terminology in various combinations: meningioma , meningeal neoplasms, en plaque , skull base , spheno-orbital, and sphenoid wing . Only literature published in English between 1938 and 2018 was reviewed. All case series were specifically reviewed for sufficient data on treatment outcomes, and all literature was analyzed for reports of misdiagnosed cases. Conclusion En plaque meningiomas may present with a variety of symptoms according to their location and degree of bone invasion, requiring a careful diagnostic and treatment approach. While early and aggressive surgical resection is generally accepted as the optimal goal of treatment, these lesions require an individualized approach, with further investigation needed regarding the role of new therapies.

Grade III meningioma: 10 year single centre case series

Abstract Rationale WHO Grade 3 meningiomas are a rare, malignant subtype of meningioma. Few controlled case series detailing its treatment and follow-up are to be found in the literature. Methods Retrospective cohort study of patients treated in a single neuro-oncology centre in the period between September 2008 and March 2019 with an initial diagnosis of WHO Grade 3 meningioma. Demographic and clinical data has been collected from the available medical records. Results 9 patients were included in this series: 2 had convexity, 2 sphenoid wing, 2 parafalcine, 1 parasagittal with a further 3 multiple locations and 1 patient with parietal convexity meningioma. 3 tumours displayed rhabdoid features, whilst 4 displayed papillary features and a further 2 displayed epithelial structures. All patients underwent surgical intervention: 5 patients had a subtotal resection with 3 having total resection. 3/4 of reported Simpson Grading was grade 2, whilst the remaining 1/4 was grade 1. The extent of resection for 1 patient was uncertain. Post surgically, 6 received adjuvant radiotherapy, 2 had no further treatment and 1 received gamma knife therapy. No patient received chemotherapy. 5 patients saw no tumour recurrence at follow up appointments (mean 50 months). Within 2 years of their respective surgical interventions, 4 patients died due to tumour recurrence and associated complications (3 patients). Conclusion To establish a uniform approach to treatment of patients with WHO Grade 3 meningiomas is challenging. Management involves a patient-centred approach based on multidisciplinary meeting decisions. Multicentre registries may allow further conclusions.

1927P - Identification of meningioma patients in high risk of tumor recurrence using microRNA profiling

BackgroundMeningioma growth rates are highly variable, even within benign subgroups, causing some cases to remain stable while others grow rapidly despite radiotherapy. Biomarkers that differentiate meningiomas by aggression and enable prediction of their biological behavior would therefore be clinically beneficial. MethodsMicroarrays were used to identify microRNA (miRNA) expression in primary recurrent, non-recurrent and secondary meningiomas of all grades. miRNAs found to be deregulated in the microarray experiments were validated by quantitative real-time PCR using samples from a cohort of 191 patients (median age 56). Statistical analysis of the resulting dataset revealed miRNA predictors of meningioma recurrence. ResultsmiRNAs exhibiting differential expression (independently of histological grade) in primary recurrent, non-recurrent and secondary meningiomas were identified. The most effective predictive model included miR-331-3p, extent of tumor resection and its localization as predictive markers. The model with a recurrence probability cut-off of 28% and small number of the input data (7) had a high area under the curve (AUC) (0.829), sensitivity (75%), specificity (75%), and acceptable leave-one-out cross-validation (LOOCV) test error (23.2%). miR-18a-5p, miR-130b-3p, miR-146a-5p, miR-1271-5p, age at diagnosis, gender and histological grade showed to be supportive but not predictive factors in the tested models. ConclusionsThis model is a novel predictor of meningioma recurrence that could facilitate optimal postoperative management. Moreover, combining this model with information on the molecular processes underpinning recurrence could enable the identification of distinct meningioma subtypes and targeted therapies. Legal entity responsible for the studyThe authors. FundingMinistry of Health of the Czech Republic (15-29021A); Palacky University Olomouc (LF 2019_003); Ministry of Education, Youth and Sports of the Czech Republic (LO1304, LM2015091); European Regional Development Fund (ENOCH CZ.02.1.01/0.0/0.0/16_019/0000868). DisclosureAll authors have declared no conflicts of interest.

OS8.8 Modified chromatin histone marks at noncoding elements are associated with aggressive meningioma subtype

Abstract Background: Although most meningiomas are non-malignant, there is a high recurrence rate among atypical and anaplastic (malignant) meningiomas (grades II/III). In addition, malignant meningioma usually progresses after treatment. Recently, based on DNA methylation, two subgroups of meningioma were described with recurrence-free survival differences (favorable and unfavorable). Epigenetic deregulation at distinct genomic elements such as enhancers can drive changes in gene expression and alter the transcriptional profile of the cancer cells. We seek to understand the mechanisms of meningioma recurrence and progression after initial treatment. Material and Methods: Two favorable and two unfavorable meningioma high grade tumor tissue were selected for this pilot study. Immunoprecipitation (Antibodies) for two different histone modifications (H3K4me3 and H3K27ac) were used to generate genome-wide chromatin-IP sequencing. Genome-wide DNA methylation profile was assessed for 90 meningioma cases including the four samples used in this pilot study. Results: Using a FDR cutoff of 5%, we identified 10,049 H3K27ac and 5,752 H3K4me3 chromatin marks that distinguish favorable from unfavorable meningioma. We dichotomized the results into genomic regions overlapping known gene promoters and non-promoters. Promoter associated chromatin changes (H3K27ac and H3K4me3) coincide with DNA methylation changes in aggressive meningioma. The top 1,000 H3K27ac (sorted by fold difference) without H3K4me3 coincide with highly conserved DNA elements known to be associated with enhancers. These enhancers can drive expression of multiple genes simultaneously. Using DNA methylation differences between favorable and unfavorable meningioma, we will overlap with our unfavorable associated enhancers in order to refine our candidate enhancers for follow up mechanistic studies using aggressive meningioma cell lines. Conclusion: Our preliminary results are the first to unravel the genome-wide chromatin changes associated with unfavorable or clinically aggressive meningioma. Identification of these candidate enhancers will provide knowledge of the role of epigenomics in the development of malignant meningioma and of opportunities for targeted therapy. This project is supported by the Henry Ford Health System, Department of Neurosurgery and the Hermelin Brain Tumor Center Foundation (A30935), United States National Institutes of Health (R01CA222146), and United States Department of Defense (CA170278)

Comparative genomic analysis of driver mutations in matched primary and recurrent meningiomas.

A significant proportion of low-grade WHO grade I and higher-grade WHO grade II or III meningiomas are at risk to develop post-resection recurrence. Though recent studies investigated genomic alterations within histological subtypes of meningiomas, few have compared genomic profiles of primary meningiomas matched to their recurrences. The present study aimed to identify oncogenic driver mutations that may indicate risk of meningioma recurrence and aggressive clinical course. Seventeen patients treated for low-grade (n = 8) or high-grade (n = 9) meningioma and underwent both primary and recurrent resection between 2007–2017 were reviewed. Tumor specimens (n = 38) underwent genomic sequencing of known oncogenic driver mutations. Primary and recurrent tumors were compared using matched-pair analyses for mutational associations with clinical outcomes including functional status, progression-free survival (PFS) and overall survival (OS). Most common driver mutations included POLE and NF2. There was no enrichment for any driver mutation from primary to recurrent tumor specimen. NF2 mutant meningiomas were associated with larger tumor size (8-fold increase), presence of vasogenic edema, and higher mitotic proliferation on univariate and independently on multivariate regression (p’s < 0.05) after controlling for preoperative and tumor features. Tumors with POLE driver mutations were associated with decreased functional status at last postoperative follow-up (p = 0.022) relative to presentation. Mutation status was not associated with PFS or OS on multivariate Cox regression, but rather with grade of resection (p = 0.046) for PFS. While primary and recurrent tumors exhibited similar driver mutations within patients, the identification of driver mutations associated with clinical outcomes is crucial for guiding potential targeted treatments in recurrent meningiomas.

Fourth Ventricular Meningiomas

Fourth ventricular meningiomas (FVMs) are extremely rare. Here, we report a series of 11 patients at a single institution. A comprehensive literature analysis is conducted. Information about 11 patient was extracted from the patient data. Reports of cases in English were obtained from the literature. Including our 11 patients, 71 patients were analyzed in this study. The most common age of onset was from the third decade to sixth decade of life. The female/male ratio was about 1.16:1. The most frequent subtype of meningioma was fibrous meningioma. FVMs had specific imaging features, such as calcification (20%), peritumoral edema (30.3%), heterogeneous enhancement (22.5%), cystic formation (4.3%), and hydrocephalus (52.8%). The proportion of total tumor resection was about 94.9%, with 15.3% of postoperative complications. During follow-up, the recurrent rate of FVMs was about 6.8%. There was no significant difference in the analysis of correlation between hydrocephalus and the maximum diameter of tumors, correlation between hydrocephalus and the volume of tumor, or correlation between peritumoral edema and the volume of tumor, as well as correlation between heterogeneous enhancement and the grade of meningiomas. FVMs have their own characteristics in age of onset, gender ratio, histologic types, and imaging features. The recommended treatment is surgical treatment via the telovelar approach with suboccipital craniotomy/craniectomy. Adjuvant therapy is needed in some high-grade meningiomas and in patients undergoing partial resection. The prognosis is relatively good, with fewer postoperative complications and a higher rate of total resection.

Differentiation Researches on the Meningioma Subtypes by Radiomics from Contrast-Enhanced Magnetic Resonance Imaging: A Preliminary Study

Meningioma subtypes are one of the most common key points to the treatment and prognosis of patients. The purpose of this study was to investigate the differential diagnostic value of radiomics features on meningioma. A total of 241 patients with meningioma who had undergone tumor resection were randomly selected including 80 with meningothelial meningioma, 80 with fibrous meningioma, and 81 with transitional meningioma. These meningiomas were divided into 4 groups including: meningothelial versus fibrous (group 1), fibrous versus transitional (group 2), meningothelial versus transitional (group 3), and meningothelial versus fibrous versus transitional (group 4). All patients were examined using the same magnetic resonance scanner (GE 3.0 T) and the preoperative contrast-enhanced T1-weighted images were available. Radiomics features from the contrast-enhanced T1-weighted images of 241 patients were evaluated by 2 experienced radiology specialists. A total of 385 radiomics features were extracted from the images of each patient. Several preprocessing methods were applied on the radiomics dataset to reduce the redundancy and highlight differences between different meningioma before the Fisher discrimination analysis was adopted and leave one out cross validation methods were used for the model validation. The differentiation accuracies of the Fisher discriminant analysis model for groups 1, 2, 3, and 4 were 99.4%, 98.8%, 100% and 100%, respectively; leave one out cross validation method was achieved for group 1, 2, 3, and 4 with the accuracies of 91.3%, 95.0%, 100%, and 94.2%, respectively. Radiomics features and the combined Fisher discriminant analysis could provide satisfactory performance in the preoperative differential diagnosis of meningioma subtypes and enable the potential ability for clinical application.

Role of MR Morphology and Diffusion-Weighted Imaging in the Evaluation of Meningiomas: Radio-Pathologic Correlation

Preoperative differentiation of benign, atypical and malignant meningiomas would significantly help in surgical planning and treatment. The aim of this study is to look at radio-morphologic behavior of various histopathological types and grades of meningiomas and their diffusion characteristics. We performed an analytical cross-sectional study including all patients operated on for meningiomas at our hospital during January 2016 to July 2018. We studied 38 meningiomas in 38 patients aged 14 to 73 years old. All patients underwent MRI prior to surgery, including diffusion-weighted sequences, in a 1.5T scanner. Signal intensity in T2-weighted images, diffusion-weighted images (b=0, 90 and 1,000), and Apparent Diffusion Coefficient maps within the tumors and in the normal parietal white matter as a reference were evaluated. In the histological study, cellularity, proliferation index, histological grade, and cerebral invasion were evaluated. There was female predilection with male:female ratio of 1:2.4. Most meningiomas were supratentorial with most common origin being parafalcine and convexity. Of the 38 meningiomas, 31 were WHO grade I, 6 were WHO grade II (atypical) and one was WHO grade III (anaplastic). Among various tumors' behaviors, incomplete CSF cleft, pial invasion and parenchymal invasion were significantly high in high-grade tumors. Similarly, tumors showing pial invasion, breached tumor-brain interface, no capsular enhancement and parenchyma invasion showed significantly low NADC. Mean ADC value was 0.722±7.7x10-3 mm2/s (normalized ADC 0.9±0.1) in the atypical group and 0.876±24.56x10-3 mm2/s (normalized ADC 1.11±0.31) in the typical group. No statistically significant differences of ADC/NADC were found between histologic subtypes. Two subtypes of typical meningiomas, metaplastic and angiomatous meningioma had the highest values in the ADC maps. MR morphology like pial invasion, breached tumors brain interface, parenchymal invasion can predict aggressiveness and atypical nature of meningiomas. Meningioma shows moderately restricted diffusion. The signal on the ADC map is associated with tumors cellularity and aggressiveness suggesting its usefulness for predicting the histological grade.

The correlation between phosphorylated Histone H3 (PHH3) and p-STAT3 in Meningiomas

ObjectiveTo assess the correlation between PHH-3 and STAT-3 in grade I and grade II meningiomas. Patients and methodsMedical records were retrospectively reviewed for all cranial cases which diagnosed and underwent surgery at Bezmialem Vakif University Hospital between 2012 and 2017. All cranial grade I and grade II meningioma patients constituted the core sample for this study. ResultsThis series included 104 (69 female, 35 male) patients, with a median age of 57.3 years. The mean preoperative course was 23.0 ± 40.5 months. The most common symptom was headache (76%) and followed by seizure (24%), weakness (18%) and visual disturbances (14%). Seventy one (68.2%) patients were diagnosed as WHO grade I meningioma and 33 (31.8%) were WHO grade II, grade III meningiomas were excluded from study due to small number of patients. Subtypes of meningioma includes 5 angiomatous (4,8%), 6 fibroblastic (5.7%), 1 meningothelial (0,9%), 11 psammomatous (10,5%), 3 secretory (2,8%), 43 transitional (41,3%) and 33 atypical (31,7%) meningiomas. There is a strong correlation with PHH-3 and Ki-67 (p:0,001>) and mitosis index (p:0,001 > ) although there is no correlation with STAT-3 (p:0,260). There is a strong correlation with STAT-3 and Ki-67 (p:0,013), although there is no correlation with mitosis index (p:0,085) and PHH-3 (p:0,260). ConclusionsIn our study we also obtain same results with Ki-67 and mitotic index, although correlation with PHH-3 and STAT-3 is firstly determined and there was no statistically significant relation were observed. Depends on the STAT-3 cell proliferation feature, inactivation of these pathways may predict new chemotherapies for grade II meningiomas.

Loss of SMARCB1/INI1 Immunoexpression in Chordoid Meningiomas.

Chordoid meningiomas have an aggressive clinical course characterized by frequent recurrences. Recent whole-genome sequencing studies demonstrated Chr22 loss in chordoid meningiomas not accounted for by NF2 mutations. SMARCB1/INI1 is a candidate gene on Chr22, which has not been analyzed extensively in meningiomas. AKT1 mutation has been recently identified to be a driver of meningiomagenesis. Cases of chordoid meningioma were retrieved along with meningiomas of other subtypes for comparison. INI1 immunohistochemistry was performed. SMARCB1 and AKT1 were analyzed by sequencing. Sixteen chordoid meningiomas were identified (1.1% of all meningiomas). Six cases (37.5%) showed loss of INI1 immunoexpression. All other meningioma subtypes (n = 16) retained INI1 immunoexpression. AKT1 E17K mutation was identified in one case (16.7%). Notably, SMARCB1 mutations were not identified in any of the chordoid meningiomas analyzed, including those showing INI1 loss immunohistochemically. This is the first study to demonstrate loss of SMARCB1/INI1 immunoexpression in chordoid meningiomas, adding to the tumors with INI1 loss. However, in absence of INI1 mutation, mechanisms for INI1 loss require further evaluation. Identification of AKT1 mutation opens up new avenues for targeted therapy in patients with such aggressive tumors.

Histopathological Patterns of Intracranial Tumours at a Tertiary Health Facility in Sokoto, North-West Nigeria

Brain tumours are diverse group of primary CNS tumours and secondary neoplasm arising either from the scalp or from haematogenous spread from distant sites with few biologically aggressive tumours in both adult and paediatric age groups. Brain tumours have been classified based on their presumed cell of origin and degree of differentiation as determined by light microscopy and immunohistochemical studies with tumours distinctive tumour biology, treatment and prognosis. A retrospective study of all cases of intracranial tumours seen over a period of 10 years from January 2008 to December 2017 at Department of Pathology, Usmanu Danfodiyo University Teaching Hospital. This is a regional neurosurgical centre situated at Sokoto North-West Nigeria receiving surgical specimens from Birnin Kebbi, Zamfara, Sokoto, and Katsina state. The age, sex, histologic diagnosis, and histologic grading system using the 2007 WHO grading system were retrieved and recorded. This study reviewed 151 patients managed with histology confirmed intracranial tumour (ICTs). Mean age was 28.17 ±17.26 years. The male-to-female ratio was 1.6:1.0. Peak age range was the third decade (21-30years) and accounted for (20.5%). Primary ICTs accounted for 95.4% of the cases and metastatic adenocarcinomas accounted for 4.6% of the diagnoses and all the cases were seen in adults. Meningioma was the most commonly diagnosed intracranial tumours (39.7%), followed by astrocytoma (23.2%), pituitary adenomas (7.3%), craniopharyngioma (11.9%) and nodular medulloblastoma accounted for 4.0%. The most common histologic subtype of meningioma was psammomatous accounted for 75.5%, followed by meningotheliomatous 18.5% and the least was transitional 1.3%. The mean age of meningioma was 32±11.9 years with age range from 3 – 58years and male to female ratio of 1.4:1 and WHO classification of meningioma are stratified into 3; 95% are in grade 1 and 5% are in grade 11. Meningioma was the most commonly diagnosed intracranial tumours (39.7%), followed by astrocytoma (23.2%), pituitary adenomas (7.3%), craniopharyngioma (11.9%) and nodular medulloblastoma accounted for 4.0%. The most common histologic subtype of meningioma was psammomatous accounted for 75.5%, followed by meningotheliomatous 18.5% and the least was transitional 1.3% with WHO classification of meningioma are stratified into 3; 95% are in grade 1 and 5% are in grade 11.

Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.

Preoperative, noninvasive prediction of the meningioma grade is important because it influences the treatment strategy. The purpose of this study was to evaluate the role of radiomics features of postcontrast T1-weighted images (T1C), apparent diffusion coefficient (ADC), and fractional anisotropy (FA) maps, based on the entire tumor volume, in the differentiation of grades and histological subtypes of meningiomas. One hundred thirty-six patients with pathologically diagnosed meningiomas (108 low-grade [benign], 28 high-grade [atypical and anaplastic]), who underwent T1C and diffusion tensor imaging, were included in the discovery set. The T1C image, ADC, and FA maps were analyzed to derive volume-based data of the entire tumor. Radiomics features were correlated with meningioma grades and histological subtypes. Various machine learning classifiers were trained to build classification models to predict meningioma grades. We tested the model in a validation set (58 patients; 46 low-grade; 12 high-grade). The machine learning classifiers showed variable performances depending on the machine learning algorithms. The best classification system for the prediction of meningioma grades had an area under the curve of 0.86 (95% confidence interval [CI], 0.74-0.98) in the validation set. The accuracy, sensitivity, and specificity of the best classifier were 89.7, 75.0, and 93.5% in the validation set, respectively. Various texture parameters differed significantly between fibroblastic and non-fibroblastic subtypes. Radiomics feature-based machine learning classifiers of T1C images, ADC, and FA maps are useful for differentiating meningioma grades. • Preoperative, noninvasive differentiation of the meningioma grade is important because it influences the treatment strategy. • Radiomics feature-based machine learning classifiers of T1C images, ADC, and FA maps are useful for differentiating meningioma grades. • In benign meningiomas, there were significant differences in the various texture parameters between fibroblastic and non-fibroblastic meningioma subtypes.

Hereditary clear cell meningiomas in a single family: three-cases report

Clear cell meningiomas (CCMs) are rare subtypes of meningiomas and usually treated by maximum safely achievable tumor resection. We here present three hereditary cases with CCMs which were confirmed by Sanger sequencing of lymphocyte DNA. Gross total resection was achieved in a 5-year-old son with a spinal CCM and a 34-year-old father with a CCM in the cerebellopontine angle (CPA). For a 14-year-old daughter with CCM in the CPA, total resection was not achieved due to its large size. Early detection by screening high-risk family with CCM is strongly recommended.

MNGI-11. LONGITUDINAL GENOMIC ANALYSIS OF SPORADIC MENINGIOMAS WITH MULTIPLE RECURRENCES

Recently, genomic patterns and methylation profiles of meningiomas were described as prognostic factors for aggressiveness and recurrence (e.g. TERT, SMO and AKT1 mutations). However, the particular molecular profiles of recurrence and malignant progression of specific meningioma subtypes remain undefined. In this regard, longitudinal molecular studies are very interesting. In this study, we characterized somatic mutations in a cohort of sporadic meningioma patients. We included 9 patients with multiple recurrences and up to 11 subsequent resections of sporadic meningiomas. We performed a comparative whole-exome sequencing (WES). Moreover, we used the whole-exome data to predict the HLA MHC class I peptides of the subsequent tumor samples in silico. Our study included patients with follow-up times accounted for up to 26 years (average: 12.6 years, range 3–26). We detected a TRAF7 mutation (c.1189G>C) in only 2 of 6 recurrent tumor samples of a female patient with a malignant progression from a WHO I to a WHO grade II meningioma. In a male patient with 9 analyzed meningioma tumor samples, recurrent somatic PLEKHG5, AGBL1, ALK, RICTOR, DEPDC5 mutations were detected. This individual pattern remained constantly evident under different treatments, even after systemic treatment with the mTOR inhibitor everolimus. Moreover, unique mutations in HLA-DQA1, OR14J1, PRH1 genes occurred after mTOR inhibition in this male patient. Furthermore, we identified somatic mutations in the tumor suppressor candidate NBPF1 in 7 of 9 patients. HLA allele types were predicted in silico, with A*02:01, B*57:01, C*03:03, C07:01 and B51:01 being most frequent. Neither ubiquitously shared somatic mutations nor shared MHC class I peptides were identified among this cohort. Taken together, our study outlines a heterogeneous molecular profile in this analysis. Since longitudinal samples in sporadic meningioma are rather rare, the ICOM consortium would be an ideal frame for studying the molecular profile of recurrence in meningioma in larger cohorts.

Pretreatment Texture Analysis of Routine Magnetic Resonance Images and Shape Analysis of the Diffusion Tensor Predict Volumetric Response after Radiosurgery for Meningiomas

Tumor progression after stereotactic radiosurgery remains a major complication in WHO grade I meningiomas, with figures reported between 5-10%. According to our previous study, Diffusion Tensor Imaging (DTI) parameters can differentiate between meningioma subtypes and predict the reduction in volume of meningiomas after SRS. However DTI is still not frequently performed for SRS. The objective of this study was to identify those parameters from routine T1- and T2-weigted Magnetic Resonance (MR) sequences, and as well as from DTI, which predict best volume changes of meningiomas after Gamma Knife Radio-Surgery (GKRS) treatment. In 32 patients (mean age 58y) with meningiomas (mean volume 8.80cm3, mean dose 14.2Gy), routine 3 Tesla MR images as well as 11 different DTI parameter maps, including skewness of tensor shape, were measured before SRS. A total of 104 parameters derived from first level texture analysis of the pre-treatment MR images, including calculation of mean, standard deviation, 2.5 and 97.5 percentiles, kurtosis and skewness of data histograms on a voxel-wise basis, were correlated with lesion volume change after a mean follow up period of 3 years (19.5 – 63.3 months). Mean volume change rate per month after SRS was 0.92%. 1 (3%) meningioma progressed, 5 (16%) meningiomas stayed stable and 26 (81%) regressed. Several DTI-derived parameters correlated significantly with meningioma volume change. The parameter to predict best response of SRS was the 2.5 percentile value of the planar spherical index of the diffusion tensor (correlation coefficient -0.682, p≤0.001), whereas from the non-DTI parameters, only standard deviation of T2-weighted data correlated significantly with tumor volume change (correlation coefficient 0.505, p≤0.05). Other factors, like original tumor size, prescription dose and patient’s age, did not present significant correlation. WHO grade I Meningiomas differ in tissue homogeneity and in radiosensitivity. DTI-derived parameters show a higher correlation to shrinkage of meningioma volume after SRS than data from T1- and T2-weigted sequences. Combinations of standard deviation of T2 and DTI parameters can further improve correlation. If only routine MR images are available, standard deviation of T2-weighted images may be considered to predict volumetric response of meningiomas after SRS.

Spinal Clear Cell Meningioma: Clinical Study with Long-Term Follow-Up in 12 Patients

Clear cell meningioma (CCM) is a rare histologic subtype of meningioma. The features of CCMs have commonly been based on intracranial cases. However, CCMs in the spinal cord are even rarer, and their natural history, management, and prognosis remain ill-defined. From January 2006 to January 2018, 12 patients with spinal CCM were treated in our hospital. The clinical features, radiologic findings, diagnosis, treatment, and outcome of these patients were analyzed retrospectively. Additionally, we performed a review of the reported data on spinal CCMs. CCMs accounted for 2.8% of all the spinal meningiomas treated in our hospital. The most common localization of this disease was the lumbar region (7 of 12). The mean age at diagnosis was significantly younger than that of patients with spinal meningiomas (28.8 ± 13.4 years vs. 54.0 ± 14.4 years). During the follow-up period, 5 patients (41.7%) experienced tumor recurrence. Kaplan-Meier analysis showed that younger patients had a significantly shorter progression-free survival time than older patients. The review of the reported data showed that 55 cases of spinal CCMs had been reported. Nineteen patients (38.0%) had developed local recurrence, with a 5-year progression-free survival rate of 33.3%. Spinal CCMs are extremely rare tumors with a predilection to affect younger patients and have a high recurrence rate. Although gross total resection is considered to be the optimal treatment, radiotherapy could be considered for patients who had undergone subtotal resection or for younger patients, regardless of the extent of removal. Close follow-up of the entire neuraxis for years is crucial.