Fibroblastic Meningiomas Research Articles

Spatial distribution of histological subtypes of Meningioma: A 14-Year longitudinal study in a developing country

BackgroundMeningiomas are extra-axial tumors that arise from meningothelial cells, accounting for about one-third of primary central nervous system malignancies. While they are often classified by location and histology, the role of the molecular profile in their development and progression is significant. The topographic distribution of meningiomas has not been extensively studied, and it is unclear whether specific histological subtypes have predilection sites. Therefore, this study analyzes the preferred locations of meningiomas according to different biological characteristics and their association with different gradings. MethodsThis is a retrospective chart review of patients in tertiary institutes over 14 years. The data were retrieved from medical and pathological record archives. An association between the biological nature of tumors and the location of meningiomas was analyzed. SPSS version 25 was used to analyze the data. ResultsOut of 272 patients, the predominant location for meningioma distribution was convexity (33.5%), followed by parafalcine (12.5%). WHO Grade I meningiomas were the most common, accounting for 84.2% of all meningiomas. The transitional histological subtype is the common variant (34.6%). The distribution of the histological subtype of meningioma in relation to tentorium was statistically significant. However, that was not the case with the skull base. ConclusionThe spatial distribution of meningiomas within the brain is not uniform. The most frequent locations for meningiomas were found to be convexity and parafalcine. Transitional and fibroblastic meningiomas were the predominant subtypes.

Apparent diffusion coefficient histogram analysis for differentiating fibroblastic meningiomas from non-fibroblastic WHO grade 1 meningiomas

PurposeTo investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating fibroblastic meningiomas (FM) from non-fibroblastic WHO grade 1 meningiomas (nFM). MethodsThis retrospective study analyzed the histopathological and diagnostic imaging data of 220 patients with histopathologically confirmed FM and nFM. The whole tumors were delineated on axial ADC images, and histogram parameters (mean, variance, skewness, kurtosis, as well as the 1st, 10th, 50th, 90th, and 99th percentile ADC [ADCp1, ADCp10, ADCp50, ADCp90, and ADCp99, respectively]) were obtained. Multivariate logistic regression analysis was used to identify the most valuable variables for discriminating FM from nFM WHO grade 1 meningiomas, and their diagnostic efficacy in differentiating FM from nFM before surgery was assessed using receiver operating characteristic (ROC) curves. ResultsThe mean, variance, ADCp50, ADCp90, and ADCp99 of the FM group were all lower than those of the nFM group (P < 0.05), there was significant difference in location and sex (P < 0.05). Multivariate logistic regression showed ADCp99 (P < 0.001) and location (P = 0.007) were the most valuable parameters in the discrimination of FM and nFM WHO grade 1 meningiomas. The diagnostic efficacy was achieved an AUC of 0.817(95% CI, 0.759–0.866), the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 66.4%, 83.6%, 75.0%, 80.2%, and 71.3%, respectively. ConclusionADC histogram analysis is helpful in noninvasive differentiation of FM and nFM WHO grade 1 meningiomas, and combined ADCp99 and location have the best diagnostic efficacy.

Preoperative Prediction of Meningioma Subtype by Constructing a Clinical-Radiomics Model Nomogram Based on Magnetic Resonance Imaging

We sought to investigate the value of a clinical-radiomics model based on magnetic resonance imaging in differentiating fibroblastic meningiomas from non-fibroblastic meningiomas. Clinical, imaging, and postoperative pathologic data of 423 patients (128 fibroblastic meningiomas and 295 non-fibroblastic meningiomas) were randomly categorized into training (n= 296) and validation (n= 127) groups at a 7:3 ratio. The Selectpercentile and LASSO were used to selected the highly correlated features from 3376 radiomics features. Different classifiers were used to train and verify the model. The receiver operating characteristic curves, accuracy (ACC), sensitivity (SEN), and specificity (SPE) were drawn to evaluate the performance. The optimal radiomics model was selected. Calibration curves and decision curve analysis were used to verify the clinical utility and consistency of the nomogram constructed from the radiomics features and clinical factors. Thirteen radiomics features were selected from contrast-enhanced T1-weighted imaging and T2-weighted imaging after dimensionality reduction. The prediction performance of random forest radiomics model is slightly lower than that of the clinical-radiomics model. The area under the curve, SEN, SPE, and ACC of the clinical-radiomics model training set were 0.836 (95% confidence interval, 0.795-0.878), 0.922, 0.583, and 0.686, respectively. The area under the curve, SEN, SPE, and ACC of the validation set were 0.756 (95% confidence interval, 0.660-0.846), 0.816, 0.596, and 0.661, respectively. The diagnostic efficacy of the clinical-radiomics model of fibroblastic meningioma and non-fibroblastic meningioma was better than that of the radiomics prediction model alone and can be used as a potential tool for clinical surgical planning and evaluation of patient prognosis.

Differentiation between various types and subtypes of intracranial meningiomas with advanced MRI.

Meningiomas are the most prevalent of all intracranial tumours. Although they are mostly benign, about 20% of meningiomas are atypical or malignant. Knowledge of their histologic grade can be clinically useful while planning surgery. To differentiate between various grades and subtypes of meningiomas with advanced MR parameters. We assessed the advanced MR imaging characteristics of 27 histopathologically confirmed meningiomas on a 3T MRI, of which 23 were grade I meningiomas (2 fibroblastic, 9 meningothelial, 9 transitional, 3 unspecified) and 4 were grade II/III meningiomas (2 atypical, 1 papillary, 1 anaplastic). Analysis of the ADC, FA, λ1, λ2, λ3 and mean diffusivity was performed using standard post-processing software. The mean size of atypical meningiomas (5.9 cm ± 0.7 cm) was significantly higher (p = 0.038, 95% confidence interval [CI]) than that of typical meningiomas (4.6 cm ± 1.6 cm) with a cut-off value of 6.05 cm (75% sensitivity and 87% specificity). The mean cerebral blood flow (CBF) (ASL) of atypical meningiomas (286.70 ± 8.06) was significantly higher (p = 0.0000141, 95% CI) than that of typical meningiomas (161.09 ± 87.04) with a cut-off value of 276.75 (66.7% sensitivity and 75% specificity). Among the typical meningiomas, transitional subtypes had the lowest ADC. High FA and planar coefficient (CP) values and low λ3 and spherical coefficient (CS) values were seen in fibroblastic meningiomas. Fibroblastic meningiomas also showed the lowest vascularity among typical meningiomas. Tumour size and ASL perfusion are two parameters that could differentiate between typical and atypical meningiomas while ADC, FA, λ3, CP, CS, rCBF and rCBV may be helpful in distinguishing different subtypes of typical meningiomas.

Inhibiting PP2A Upregulates B7-H3 Expression and Potentially Increases the Sensitivity of Malignant Meningiomas to Immunotherapy by Proteomics.

Malignant meningiomas have a high mortality rate and short survival time and currently have no effective treatment. In our study, proteomics analysis was performed to identify highly expressed proteins as therapeutic targets in malignant meningiomas. Cell Counting Kit-8 (CCK-8) assays were performed to verify the effect of LB-100 on the growth of malignant meningiomas. In addition, immunoblotting was used to verify the expression of B7-H3 and phosphorylation of STAT1 (Tyr701) in tissues and cells. Our results show that STAT1 and CD276 (B7-H3) regulated by PP2A were enriched in GO_IMMUNE_EFFECTOR_PROCESS and GO_REGULATION_OF_IMMUNE_SYSTEM_PROCESS. The immunotherapy target protein B7-H3 was confirmed to be upregulated in malignant meningiomas compared with meningothelial (p = 0.0001) and fibroblastic (p = 0.0046) meningiomas. In vitro, the PP2A inhibitor LB-100 suppressed the growth and invasion of malignant meningioma cells. Notably, the PP2A inhibitor LB-100 increased the phosphorylation of STAT1, thereby increasing the expression of the immune checkpoint protein B7-H3 in malignant meningioma cells in vitro. In conclusion, B7-H3 was found to be upregulated in malignant meningiomas. The PP2A inhibitor LB-100 increased the phosphorylation of STAT1 and B7-H3 expression, which could increase the sensitivity of malignant meningiomas to B7-H3 targeted immunotherapy.

Use of magnetic resonance elastography to gauge meningioma intratumoral consistency and histotype

ObjectiveTo determine whether tumor shear stiffness, as measured by magnetic resonance elastography, corresponds with intratumoral consistency and histotype. Materials and methodsA total of 88 patients with 89 meningiomas (grade 1, 74 typical [13 fibroblastic, 61 non-fibroblastic]; grade 2, 12 atypical; grade 3, 3 anaplastic) were prospectively studied, each undergoing preoperative MRE in conjunction with T1-, T2- and diffusion-weighted imaging. Contrast-enhanced T1-weighted sequences were also obtained. Tumor consistency was evaluated as heterogeneous or homogenous, and graded on a 5-point scale intraoperatively. MRE-determined shear stiffness was associated with tumor consistency by surgeon’s evaluation and whole-slide histologic analyses. ResultsMean tumor stiffness overall was 3.81+/-1.74 kPa (range, 1.57–12.60 kPa), correlating well with intraoperative scoring (r = 0.748; p = 0.001). MRE performed well as a gauge of tumor consistency (AUC = 0.879, 95 % CI: 0.792–0.938) and heterogeneity (AUC = 0.773, 95 % CI: 0.618–0.813), significantly surpassing conventional MR techniques (DeLong test, all p < 0.001 after Bonferroni adjustment). Shear stiffness was independently correlated with both fibrous content (partial correlation coefficient = 0.752; p < 0.001) and tumor cellularity (partial correlation coefficient = 0.547; p < 0.001). MRE outperformed other imaging techniques in distinguishing fibroblastic meningiomas from other histotypes (AUC = 0.835 vs 0.513 ∼ 0.634; all p < 0.05), but showed limited ability to differentiate atypical or anaplastic meningiomas from typical meningiomas (AUC = 0.723 vs 0.616 ∼ 0.775; all p > 0.05). Small (<2.5 cm, n = 6) and intraventricular (n = 2) tumors displayed inconsistencies between MRE and surgeon’s evaluation. ConclusionsThe results of this prospective study provide substantial evidence that preoperative evaluation of meningiomas with MRE can reliably characterize tumor stiffness and spatial heterogeneity to aid neurosurgical planning.

INNV-24. METASTATIC HEMANGIOPERICYTOMA TO THE LIVER: DEFINING THE IMPORTANCE OF NAB-STAT2 FUSION

Abstract BACKGROUND Meningeal hemangiopericytoma (HPC) is a rare and aggressive vascular tumor which typically occurs in younger adults and has a tendency for local recurrence with delayed metastases outside the CNS. HPC is considered a variant of solitary fibrous tumor (SFT), and is associated with the presence of the fusion oncoprotein NAB2-STAT6. This fusion results in over-expression of the EGR1 gene and results in tumorigenesis. CASE REPORT We present a case of a 49 y/o female with a remote history of left occipital lobe HPC, initially treated with resection and radiotherapy in 2007, who presented with symptoms of right upper quadrant abdominal pain. She was found to have a hypervascular 7 cm mass in the right upper lobe of the liver on magnetic resonance imaging (MRI) studies and subsequently underwent hepatectomy for removal of the mass. Histopathological findings revealed metastatic HPC with features consistent with her primary meningeal tumor that was removed over 13 years agoearlier. Presence of the NAB2-STAT6 fusion was confirmed by targeted genomic analysis. MRI revealed a small focus of nodular enhancement abutting the confluence of the superior sagittal sinus and transverse sinus. This was considered her source of disease and possible dissemination. She was treated with stereotactic radiosurgery to target the lesion. DISCUSSION Given the rarity and often remote medical history of the primary intracranial HPC, this report suggests that 1) long term follow up of HPC is essential and 2) detection of the NAB2-STAT6 fusion can identify and confirm recurrent HPC at metastatic sites. In regards to the latter, distinguishing HPCs from other more benign spindle cell tumors that may mimic SFT (such as fibroblastic meningiomas) is also of therapeutic significance as HPCs typically require adjuvant treatment, (i.e. radiotherapy) as opposed to surgical resection alone.

Atypical evolution of meningiomatosis after discontinuation of cyproterone acetate: clinical cases and histomolecular characterization.

The long-term use of cyproterone acetate (CPA) is associated with an increased risk of developing intracranial meningiomas. CPA discontinuation most often induces a stabilization or regression of the tumor. The underlying biological mechanisms as well as the reasons why some meningiomas still grow after CPA discontinuation remain unknown. We reported a series of patients presenting CPA-induced meningiomatosis with opposed tumor evolutions following CPA discontinuation, highlighting the underlying histological and genetic features. Patients presenting several meningiomas with opposite tumor evolution (coexistence of growing and shrinking tumors) following CPA discontinuation were identified. Clinical and radiological data were reviewed. A retrospective volumetric analysis of the meningiomas was performed. All the growing meningiomas were operated. Each operated tumor was characterized by histological and genetic analyses. Four women with multiple meningiomas and opposite tumor volume evolutions after CPA discontinuation were identified. Histopathological analysis characterized theconvexityand tentorial tumors which continued to grow after CPA discontinuation as fibroblastic meningiomas. The decreasing skull base tumor was characterized as a fibroblastic meningioma with increased fibrosis anda widespread collagen formation. The two growing skull base meningiomas were identified as meningothelial and transitional meningiomas. The molecular characterization found two NF2 mutations among the growing meningiomas and a PIK3CA mutation in the skull base tumor which decreased. To our knowledge, this is the first report describing an atypical tumor evolution of CPA-associated meningiomas after CPA discontinuation. The underlying biological mechanisms explaining this observation and especially the close relationship between mutational landscapes and embryologic origins of the meninges in CPA-related meningiomas as well as their clonal origin require further research.

Altered expression of E-Cadherin-related transcription factors indicates partial epithelial-mesenchymal transition in aggressive meningiomas

E-Cadherin has been suggested to be involved in meningioma progression but is also known as a key player of epithelial to mesenchymal transition (EMT). We wondered whether the adherens junction protein E-Cadherin, the tight junction protein Zo-1, and transcription factors suppressing E-Cadherin expression (Slug, Snail, Twist, Zeb-1) are differentially expressed between histopathological subtypes of meningioma, and if the expression of these factors is related to biological features of meningiomas. Analyzing 85 meningiomas of various histopathological subtypes and grades of malignancy by immunohistochemistry and 50 of them in addition by real-Time-PCR, we observed significantly reduced expression of Zeb-1, Twist and Slug, together with slightly increased expression levels for E-Cadherin and Zo- 1 in fibroblastic WHO-grade I tumors compared to meningothelial WHO grade I tumors, contradicting the hypothesis of EMT in the fibroblastic meningiomas characterized by mesenchymal appearance. However, comparing aggressive WHO grade II or III meningiomas with WHO-grade I tumors, we observed altered expression levels (loss of E-Cadherin and Zo-1, increased expression of Zeb-1 and Slug) indicating molecular features of EMT in aggressive meningiomas. This was supported by reduced E-Cadherin and increased Slug levels in recurrent compared to non-recurrent meningiomas. The expression levels of E-cadherin and Zo-1 were positively correlated with expression of NF2 mRNA. In primary meningioma cultures and IOMM-Lee meningioma cells, EMT induction by TGF-ß resulted in altered morphology and increased expression of EMT associated transcription factors. Meningioma cells with allelic losses of NF2 showed generally higher levels of various EMT relevant proteins, but were unresponsive to TGF-ß treatment. Our data indicate that aggressive meningiomas of WHO grade II/III are characterized by molecular alterations indicating partial EMT. This might contribute to the aggressive biology of these tumors.

Management of Intracranial Meningioma

Objective: The aim of this study is to evaluate different modalities of treatment of intracranial meningioma which admitted to neurosurgery department of Sohag University through two years. Methods: we operated upon 30 patients with the oldest was 70 years old and the youngest was 16 years old, with mean age of 49.23 years 21 females and 9 males, according to the complaint the most common was headache in 20 cases, followed by fits in 12 cases, then weakness in 6 cases, and mental and behavioral changes in 5 cases, and vision changes in 4cases. Results: The lesion was totally removed in 24 cases and subtotal in 6 cases. Among these 30 patients 22 patients improved, 7 patients remained the same, and one patient deteriorated. Among the 30 patients two patient complicated by CSF leak and 4 patients complicated by wound infection, and only two patients showed increased weakness, As for the pathology 7 cases with transitional meningiomas, 4 cases fibroblastic meningiomas, 2 cases with atypical meningiomas, 9 cases meningiothelial meningiomas, 5 cases psammomatus meningiomas, 3 cases mixed meningiomas. Conclusion: The use of both computerized tomography and magnetic resonance imaging was found to be mandatory and none of them can replace the other for proper and accurate diagnosis and visualization of these meningiomas preoperatively. The choice of surgical approach remains that of surgeon guided by tumor nature and many other factors. Although these approaches were found to be extremely satisfactory when properly selected, every effort should be done for applying the minimally invasive approaches as well as key-hole surgery whenever appropriately indicated and with the availability of their modern technical instrumentations and adjunctive image guidance.

Ultrastructural charachteristic of benign and anaplastic meningiomas

Taking into account high prevalence of meningiomas (35 %) among other intracranial tumors and variety of their histological structure, electron microscopy (EM) can provide important diagnostic information and be substantially complementary to light microscopy data and immunohistochemical studies.Objective: to study ultrastructural changes in benign and anaplastic meningiomas and to establish the main differential diagnostic ultrastructural features of meningiomas of different grades.Material and Methods: light microscopy and EM studies were conducted using 35 cases of meningioma.Results: Our EM data allow highlighting the characteristic ultrastructural changes in different subtypes of benign meningiomas. In particular, meningothelial subtype comprised of cells with homogeneous structure with light oval nuclei, with evenly arranged finely granular chromatin, well differentiated cell-cell contacts such as desmosomes. Cytoplasmic membranes of adjacent cells adhered to one another, forming small intussusceptions sometimes, which penetrated into the neighboring cells, which significantly increased the contact area of adjacent cells. Fibroblastic meningiomas were rich in modified fibroblasts, which contained bizarre nuclei of irregular shape with compact chromatin arrangement near the nuclear membrane. Also there were plenty bundles of collagen fibrils with the orderly assembled collagen fibers as well as with a chaotic arrangement. Transitional meningiomas were characterized by the combination of meningothelial like areas and areas of typical fibroblastic differentiation. EM changes were similar to meningothelial and fibrous meningiomas.Anaplastic meningiomas were characterized by increased in size or pyknotic nuclei, presence of nuclei with deep intussusceptions, a significant dilution of chromatin structure, focal disturbances of karyolemma integrity, vacuolization of intracellular membrane structures and extracellular edema, a significant reduction of cell-cell contacts.Conclusions: The ultrastructural features of benign meningiomas are reflected in the presence of desmosomes in meningothelial subtypes, a significant number of collagen fibrils in the fibroblastic subtypes, which confirms the double epithelial-mesenchymal histogenesis of these tumors. The cells of anaplastic meningiomas were characterized by marked signs of nuclear polymorphism, processes of alteration such as karyopyknosis and apoptosis, as well as a significant reduction of cell-cell contacts, which can promote recurrence and possible metastasizing.

Prediction of Tumor Consistency of Meningiomas using Diffusion Tensor Imaging

Introduction: Skull base meningiomas tend to be intimately attached to cranial nerves, major feeding vessel arteries as well as eloquent brain, thus making their resection quite challenging. In addition, endoscopic skull base approaches limit the natural dexterity available to traditional open surgeons. When deciding between a fully endoscopic approach versus an open approach, surgeons may benefit from knowledge of meningioma consistency (hard vs. soft) to facilitate decision making. Diffusion tensor imaging (DTI) relies on the principles of water diffusion, and we hypothesize that “soft” tumors have greater water diffusion in random directions whereas “hard” tumors have less water diffusion in random directions. In addition, we hypothesize that high content of intercellular collagen is responsible for the hard consistency. The goal of this study is to determine whether DTI can predict tumor consistency as determined by percent collagen contents. Materials and Methods: A total of 42 meningiomas with histopathologic diagnosis of atypical (n = 7; grade II, 7M; age, 47–80 years), anaplastic (n = 2; grade III, 2F; age, 44–56 years), and typical (n = 33;grade I; 8M/25F; age, 27–86 years) meningiomas were included in this study. Subtypes of typical meningiomas include 10 fibroblastic, 7 transitional, 15 meningothelial, and 1 angiomatous. All patients underwent MR studies before surgery on a 3T Siemens scanner. DTI data were acquired using a single shot spin echo EPI sequence with parallel imaging using GRAPPA (acceleration factor = 2). Contrast-enhanced T1-weighted images, FLAIR, and DTI metrics including fractional anisotropy (FA), mean diffusity (MD), linear anisotropy (CL), planar anisotropy (CP), and spherical anisotropy (CS) maps were coregistered and the median values were measured from the enhancing region. After the surgery, the histologic slides from the patients were evaluated for collagen content using sirius red stain. The percentage of collagen content was calculated using the following equation: Collagen content (%) = (collagen area/total tumor area) × 100. DTI metrics and collagen contents were compared between different subtypes. Results: Fibroblastic meningiomas demonstrated significantly higher collagen contents compared with other subtypes. The median FA and CP values were significantly higher in fibroblastic meningiomas compared with other subtypes and atypical meningiomas. The correlation coefficient between FA and collagen contents was 0.43 and between CP and collagen contents was 0.35. Conclusion: DTI may be helpful to predict tumor consistency as determined by collagen contents. This information may influence decision making in skull base surgery for meningiomas.

Determination of Grade and Subtype of Meningiomas by Using Histogram Analysis of Diffusion-Tensor Imaging Metrics

To determine whether histogram analysis of diffusion-tensor (DT) magnetic resonance (MR) imaging metrics, including tensor shape measurements, can help determine the grades and subtypes of meningiomas. The institutional review board approved this HIPAA-compliant study. Nine atypical, three anaplastic, and 39 typical meningiomas were retrospectively studied. The 39 typical meningiomas included one secretory meningioma and 11 fibroblastic, 11 transitional, 14 meningothelial, and two angiomatous meningiomas. DT imaging metrics, including fractional anisotropy, mean diffusivity, linear anisotropy coefficient, planar anisotropy coefficient (CP), spherical anisotropy coefficient (CS), and eigenvalue skewness (SK), as well as normalized signal intensity from contrast-enhanced T1- and T2-weighted images, were measured from the enhancing region of the tumor. Mean, variance, skewness, and kurtosis were extracted from the histograms. A two-level decision tree was designed, and a multivariate logistic regression analysis was used at each level to determine the best model for classification. Histogram skewness of SK and kurtosis of SK were significantly higher in atypical and anaplastic meningiomas than in typical meningiomas (P<.01). Among typical meningiomas, significant differences in histogram measures of CP and CS between fibroblastic meningiomas and other subtypes were observed (P<.01). The best model for differentiating atypical and anaplastic meningiomas from typical meningiomas consisted of mean and skewness of SK and kurtosis of T1 signal intensity, with an area under the receiver operating characteristic curve (AUC) of 0.946. The best model for differentiating fibroblastic meningiomas from other subtypes consisted of skewness of T2 signal intensity and kurtosis of CP (AUC, 0.970). Histogram analysis of DT imaging metrics can help determine the grades and subtypes of meningiomas, which can better assist in surgical planning.

Role of diffusion tensor imaging in differentiating subtypes of meningiomas

Meningiomas are the most common extraaxial intracranial type of tumor, and their management and prognosis depend on their grade and histology. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are two new imaging techniques that have proved helpful in elucidating the microarchitecture of brain tumors. The aim of the present study was to assess the role of diffusion and diffusion tensor metrics in the identification and classification of meningioma grades and subtypes. A total of 21 consecutive patients with meningioma were included in this retrospective study, of whom 16 had benign meningiomas (three fibroblastic, 11 transitional/mixed, two meningothelial) and five had atypical meningiomas. Tumor mean diffusivity (Dav), fractional anisotropy (FA), linear anisotropy (CL), planar anisotropy (CP), spherical anisotropy (CS) and eigenvalues (e1, e2, e3) were measured in all cases, and differences in diffusion tensor metrics between atypical, fibroblastic and other benign (transitional, meningothelial) meningiomas were statistically analyzed using the Mann-Whitney test. No statistically significant differences were found among the mean Dav values for atypical, fibroblastic and other benign meningiomas. Both atypical and fibroblastic meningiomas showed significantly higher mean FA values and lower mean CS values compared with other meningiomas (P<0.01), but no statistically significant difference in these values between each other. Atypical meningiomas showed higher CL values compared with fibroblastic and other benign meningiomas but, again, the difference was not statistically significant. Both atypical and fibroblastic meningiomas showed statistically significantly higher CP values and lower e3 values compared with transitional meningiomas (P<0.01). These results suggest that diffusion tensor metrics may be helpful in the differentiation of atypical, fibroblastic and other benign meningiomas.

Microarray gene expression profiling in meningiomas: Differential expression according to grade or histopathological subtype

Meningiomas, one of the largest subgroup of intracranial tumours are generally benign, but can progress to malignancy. They are classified into the three World Health Organization grades: benign, atypical and anaplastic meningiomas. Various histopathological features have been associated with aggressiveness or recurrence. Several genes have been suggested as prognostic factors, but molecular signatures have not permitted the classification of the tumours into the three grades. We have performed a microarray transcriptomic study on 17 meningiomas of different malignancy using CodeLink Uniset Human Whole Genome Bioarrays to try to distinguish the different grades and histopathological subtypes. Unsupervised hierarchical clustering classified the meningiomas into groups A, B and C, which corresponded to the three grades except for 3 benign meningiomas with higher proliferation indexes and/or recurrence, included in the atypical group. Several genes involved in cell adhesion (CD44, LOX), cell division (CKS2, BIRC5 and UBE2C), cell differentiation (Notch1) or signal transduction (ARHGAP28) were upregulated, whereas tumour suppressor genes (LR1B, DRR1, PLZF, GPX3, SYNPO, TIMP3 and HOPS) and genes involved in cell adhesion (PROS1), proliferation (SERPINF1 and PDGFD) and differentiation (AOX1) were downregulated in groups B and C compared to group A. In the benign tumours, we identified genes with signatures specific for fibroblastic meningiomas (FBLN1, Tenascin C and MMP2 encoding extracellular matrix proteins) and for meningothelial meningiomas (MLPH, DEFB1 and FAT3), suggesting different mechanisms involved in the tumorigenesis of these subtypes. This microarray-based expression profiling study revealed candidate genes and pathways that may contribute to a better understanding of the recurrence of a benign meningioma. Our results might make it possible to determine which benign meningiomas might recur despite complete resection, and will provide helpful information for neurosurgeons in the follow-up of the patients.

Childhood and juvenile meningiomas

The purpose of this paper was to study the clinical characteristic, treatment, and prognosis of childhood meningioma. Fifty-four meningioma cases below the age of 18 have been treated in Huashan Hospital in the last 15 years (from 1993 to 2008), their sex and age distribution, clinical manifestation, radiological finding, pathological subtype, treatment, and prognosis are retrospectively analyzed, and the results are compared with those reported in the literature. The ratio of male to female was 1.16:1 (29:25) and mean age was 13.14 years (ranging from 2.75 to 18 years). Five patients in this series were associated with neurofibromatosis-2. The most common symptoms and signs were the signs of increased intracranial pressure including headache, papilledema, and vomiting. The most common radiological finding was homogeneous enhancement with contrast. The most common locations of meningiomas in this series were intraventricular and anterior/middle fossa. All of these patients were surgically treated; resection both in Simpson grades I and II could be achieved in 39 out of 54 patients. Perioperative mortality was 3.7% (2 out of 54); the most common postoperative complications were intracranial infection and injury of cranial nerve. Fibroblastic meningiomas were the most common pathological subtype, and malignant and atypical meningiomas (both of grades II and III according to WHO classification) accounted for 18.5% of the whole series. Childhood meningiomas are scarce in clinical practice, which are characterized with its male predominance, large size, distinctive radiological features, and high rate of atypical/malignant histological subtypes; favorable outcome is accessible with total removal.

Prediction of meningioma consistency using fractional anisotropy value measured by magnetic resonance imaging

Preoperative planning for meningiomas requires information about tumor consistency as well as location and size. In the present study the authors aimed to determine whether the fractional anisotropy (FA) value calculated on the basis of preoperative magnetic resonance (MR) diffusion tensor (DT) imaging could predict meningioma consistency. In 29 patients with intracranial meningiomas, MR DT imaging was performed preoperatively, and the FA values of the tumors were calculated. Tumor consistency was intraoperatively determined as hard or soft, and the histological diagnosis of the tumor was established. Of the 29 tumors, 11 were classified as hard and 18 as soft. The FA values of fibroblastic meningiomas were significantly higher than those of meningothelial meningiomas (p = 0.002). The FA values of hard tumors were significantly higher than those of soft tumors (p = 0.0003). Logistic regression analysis demonstrated that the FA value was a significant independent predictor of tumor consistency (p = 0.007). The FA value calculated from preoperative MR DT imaging predicts meningioma consistency.

Prediction of meningioma consistency using fractional anisotropy value measured by magnetic resonance imaging

Object Preoperative planning for meningiomas requires information about tumor consistency as well as location and size. In the present study the authors aimed to determine whether the fractional anisotropy (FA) value calculated on the basis of preoperative magnetic resonance (MR) diffusion tensor (DT) imaging could predict meningioma consistency. Methods In 29 patients with intracranial meningiomas, MR DT imaging was performed preoperatively, and the FA values of the tumors were calculated. Tumor consistency was intraoperatively determined as hard or soft, and the histological diagnosis of the tumor was established. Results Of the 29 tumors, 11 were classified as hard and 18 as soft. The FA values of fibroblastic meningiomas were significantly higher than those of meningothelial meningiomas (p = 0.002). The FA values of hard tumors were significantly higher than those of soft tumors (p = 0.0003). Logistic regression analysis demonstrated that the FA value was a significant independent predictor of tumor consistency (p = 0.007). Conclusions The FA value calculated from preoperative MR DT imaging predicts meningioma consistency.

Merlin Expression in Secretory Meningiomas: Evidence of an NF2-independent Pathogenesis?

One of the most common chromosomal regions implicated in the meningiomas tumorigenesis is 22q12 where the neurofibromatosis 2 (NF2) gene resides. The NF2 tumor-suppressor gene encodes for the merlin/schwannomin protein, which is responsible for the inherited disease neurofibromatosis 2. NF2 gene mutations predominantly occur in transitional and fibroblastic meningiomas, whereas the meningothelial variant is less affected. Secretory meningioma is an infrequent meningioma subtype. Its most typical morphologic feature is the presence of intracytoplasmic or extracytoplasmic round hyaline, eosinophilic, and periodic acid Shiff-positive bodies in a lesion frequently otherwise classifiable as meningothelial meningioma. This study reviews the immunohistochemical merlin expression in 14 consecutive secretory meningiomas. Our purpose was to investigate if secretory meningiomas, analogous to meningothelial meningiomas, follow a molecular route of pathogenesis independent of the neurorofibromatosis 2 gene-associated pathway. All meningiomas showed positive immunocoloration involving the majority of the hyaline inclusions and secretory cells; in 12 (86%) meningiomas, a positive immunoreaction was also documented in nonsecretory tumoral cells. Our results may indicate a molecular, besides morphologic, similarity between secretory and meningothelial meningiomas: the almost constant merlin immunohistochemical expression in our series gives evidence for a possible NF2 gene-independent pathogenesis in secretory meningiomas.

Differentiation of fibroblastic meningiomas from other benign subtypes using diffusion tensor imaging

To differentiate fibroblastic meningiomas, usually considered to be of a hard consistency, from other benign subtypes using diffusion tensor imaging (DTI). From DTI data sets of 30 patients with benign meningiomas, we calculated diffusion tensors and mean diffusivity (MD) and fractional anisotropy (FA) maps as well as barycentric maps representing the geometrical shape of the tensors. The findings were compared to postoperative histology. The study was approved by the local ethics committee, and informed consent was given by the patients. According to one-way analysis of variance (ANOVA), FA was the best parameter to differentiate between the subtypes (F=32.2; p<0.0001). Regarding tensor shape, endothelial meningiomas were represented by spherical tensors (80%) corresponding to isotropic diffusion, whereas the fibroblastic meningiomas showed a high percentage (43%) of nonspherical tensors, indicating planar or longitudinal diffusion. The difference was highly significant (F=28.4; p<0.0001) and may be due to the fascicular arrangement of long spindle-shaped tumor cells and the high content of intra- and interfascicular fibers as shown in the histology. In addition, a capsule-like rim of the in-plane diffusion surrounded most meningiomas irrespective of their histological type. If these results correlate to the intraoperative findings of meningioma consistency, DTI-based measurement of FA and analysis of the shape of the diffusion tensor is a promising method to differentiate between fibroblastic and other subtypes of benign meningiomas in order to get information about their "hard" or "soft" consistency prior to removal.