The prognostic role of Ki-67/MIB-1 in meningioma: A systematic review with meta-analysis

Ki-67 index as a predictive marker of meningioma recurrence following surgical resection

BACKGROUND

Meningiomas are the most common primary intracranial tumors in adults. Although benign in a majority of cases, they have a variable clinical course and may recur even after a thorough surgical resection. Ki-67, a nuclear protein involved in cell cycle regulation, has been widely studied as a marker of cellular proliferation in various cancers. However, the prognostic significance of Ki-67 in meningiomas remains controversial. Here, we investigate the Ki-67 index, as a predictive marker of meningioma recurrence following surgical resection and compare it to established prognostic markers such as WHO grade and degree of resection.

METHODS

The medical records of 451 patients with previously untreated cranial meningiomas who underwent resections from January 2011 to January 2021 at North Shore University Hospital (NSUH) were reviewed. Collected data included WHO grade, Ki-67 proliferative index, degree of resection - gross (GTR) vs subtotal (STR) - as judged by the surgeon, tumor location, and meningioma recurrence. This study was approved by the NSUH Institutional Review Board IRB 21-1107.

RESULTS

There were 290 patients with grade I, 154 with grade II, and 7 with grade III meningiomas. The average post-resection follow-up period was 4 years, and 82 tumors (18 %) recurred. Higher WHO grades were associated with higher rates of recurrence, with rates of 11.4 %, 27.9 %, and 71.4 % for grades 1, 2, and 3, respectively, and subtotal resection corresponded to a higher rate of recurrence than total resection (34.3 % and 13.4 %, respectively). Higher WHO grades also correlated with higher Ki-67 scores (2.59, 10.01, and 20.71) for grades 1, 2, and 3, respectively. A multivariate logistic regression model identified Ki-67 and degree of resection as independent predictive variables for meningioma recurrence, with Ki-67 specifically predicting recurrence in the WHO grade II subset when analyzed separately for WHO grades I and II.

CONCLUSION

Our 10-year retrospective study suggests that the Ki-67 index is an important predictive marker for recurrence of intracranial meningiomas following surgical resection, particularly among patients with WHO grade II tumors. Our findings add to a growing body of data that support inclusion of Ki-67 index in the WHO grading criteria for patients with meningiomas.

Re-irradiation for recurrent intracranial meningiomas: Analysis of clinical outcomes and prognostic factors

PURPOSE

Re-irradiation (re-RT) for recurrent intracranial meningiomas is hindered by the limited radiation tolerance of surrounding tissue and the risk of side effects. This study aimed at assessing outcomes, toxicities and prognostic factors in a cohort of patients with recurrent meningiomas re-treated with different RT modalities.

MATERIALS AND METHODS

A multi-institutional database from 8 Italian centers including intracranial recurrent meningioma (RM) patients who underwent re-RT with different modalities (SRS, SRT, PT, EBRT) was collected. Biologically Equivalent Dose in 2 Gy-fractions (EQD2) and Biological Effective Dose (BED) for normal tissue and tumor were estimated for each RT course (α/β = 2 for brain tissue and α/β = 4 for meningioma). Primary outcome was second progression-free survival (s-PFS). Secondary outcomes were overall survival (OS) and treatment-related toxicity. Kaplan-Meier curves and Cox regression models were used for analysis.

RESULTS

Between 2003 and 2021 181 patients (pts) were included. Median age at re-irradiation was 62 (range 20-89) and median Karnofsky Performance Status (KPS) was 90 (range 60-100). 78 pts were identified with WHO grade 1 disease, 65 pts had grade 2 disease and 10 pts had grade 3 disease. 28 pts who had no histologic sampling were grouped with grade 1 patients for further analysis. Seventy-five (41.4 %) patients received SRS, 63 (34.8 %) patients SRT, 31 (17.1 %) PT and 12 (6.7 %) EBRT. With a median follow-up of 4.6 years (interquartile range 1.7-6.8), 3-year s-PFS was 51.6 % and 3-year OS 72.5 %. At univariate analysis, SRT (HR 0.32, 95 % CI 0.19-0.55, p < 0.001), longer interval between the two courses of irradiation (HR 0.37, 95 % CI 0.21-0.67, p = 0.001), and higher tumor BED (HR 0.45 95 % CI 0.27-0.76, p = 0.003) were associated with longer s-PFS; in contrast, Ki67 > 5 % (HR 2.81, 95 % CI 1.48-5.34, p = 0.002) and WHO grade > 2 (HR 3.08, 95 % CI 1.80-5.28, p < 0.001) were negatively correlated with s-PFS. At multivariate analysis, SRT, time to re-RT and tumor BED maintained their statistically significant prognostic impact on s-PFS (HR 0.36, 95 % CI 0.21-0.64, p < 0.001; HR 0.38, 95 % CI 0.20-0.72, p = 0.003 and HR 0.31 95 % CI 0.13-0.76, p = 0.01, respectively). Acute and late adverse events (AEs) were reported in 38 (20.9 %) and 29 (16 %) patients. Larger tumor GTV (≥10 cc) was significantly associated with acute and late toxicity (p < 0.001 and p = 0.009, respectively).

CONCLUSIONS

In patients with recurrent meningiomas, reirradiation is a feasible treatment option associated with acceptable toxicity profile. Prognostic factors in the decision-making process have been identified and should be incorporated in daily practice.

Primary extradural meningioma with a history of traumatic head injury during infancy: A case report

INTRODUCTION AND IMPORTANCE

Meningiomas are an extra-axial tumour arising from arachnoid cells and are typically benign and slow growing. Primary extradural meningiomas refer to meningiomas that arise outside the subdural compartment and are extremely rare (0.3 % of meningiomas).

CASE PRESENTATION

A 42-year-old female presented to her primary health care provider with a 2-year history of a painful mass on her left forehead with a past medical history of a traumatic brain injury and intracranial hematoma from a motor vehicle accident when she was 11 months old. An ultrasound reported as likely sebaceous cyst. The lesion was resected and sent for pathological examination. The diagnostic summary reported an ectopic subgaleal left frontal meningioma WHO Grade 1.

CLINICAL DISCUSSION

Extracranial meningiomas have been divided into two classifications; primary extracranial meningiomas and secondary extracranial meningiomas. In the female population group 88 % of extracranial meningiomas found on the scalp/skin are grade 1 meningiomas. Most extracranial meningiomas are diagnosed after histology examination, due to the rarity. They can arise via entrapment of arachnoid cells during embryologic development and from traumatic events displacing arachnoid cells.

CONCLUSION

The authors suggest that the patient's aetiology of her PEM is from the entrapment of arachnoid islet cells secondary to her traumatic brain injury during infancy. Interestingly, the patients' symptoms began 40 years post trauma. Other case studies of this rare tumour have correlated a shorter time period between the trauma and the diagnosis. We suggest that all patients should have radiographic and histologic investigations of scalp masses.

A comprehensive correlation of the KI-67 proliferation index to patient´s, imaging and tumor features and its value in predicting long-term course of patients with newly diagnosed intracranial meningiomas

To analyze the correlation of KI-67-Proliferation Index (KI-67-PI) with preoperative patients and MRI characteristics, WHO grading, histological subtype and long-term-course of patients with newly diagnosed intracranial meningiomas (IM). In this single-center retrospective study, all consecutive patients with IM were analyzed from January 2007 to August 2019. Patient´s demographics (age, sex), imaging parameters (location, volume, edema, necrosis), and tumor features (WHO grade, histology) were assessed and correlated with KI-67-PI. Long-term data were retrieved from patient's last follow-up visits. This study included 463 IM in 457 surgically treated patients. Males exhibited a higher KI-67-PI than females (7.31 ± 0.22 vs. 5.37 ± 0.53; p < 0.01, Mann-Whitney U Test). Age positively correlated with KI-67-PI in both sexes (p < 0.01, Spearman), with older patients having a higher KI-67-PI. KI-67-PI was significantly higher in convexity IM compared to frontobasal IM (7.15 ± 5.56 vs. 4.66 ± 2.94; p < 0.05, ANOVA, Tukey´s HSD), while no difference in KI-67-PI expression was found when other locations were compared to each other (Tukey´s HSD). Higher KI-67-PI was significantly correlated with larger tumor volume (p < 0.01, Spearman), larger tumor necrosis and larger peritumoral edema (p < 0.01, Kruskal-Wallis). Patients with recurrent IM had a significantly higher KI-67-PI than patients without recurrence (8.24 ± 5.88 vs. 5.14 ± 3.53; p < 0.01, ANOVA, Tukey´s HSD) during a mean follow-up period of 80.92 ± 38.1 months. Atypical and anaplastic IM exhibited significantly higher KI-67-PI compared to all other WHO grade 1 histological subtypes (12.09 ± 0.73 vs. 4.51 ± 0.13; p < 0.01, Kruskal-Wallis test) and KI-67-PI was significantly higher in anaplastic IM compared to atypical meningioma (19.67 ± 1.41 vs. 11.01 ± 0.38; p < 0.01, ANOVA). Higher KI-67-PI is not only associated with atypical and anaplastic subtypes of IM, but is also significantly higher in males, positively correlates with patients age, larger tumor volume, lager peritumoral edema and necrosis on preoperative MRI and predicts tumor recurrence. Therefore, KI-67-PI may serve as a decision indicator for adjuvant treatment in patients with IM.

Biomarkers for prognosis of meningioma patients: A systematic review and meta-analysis

Meningioma is the most common primary brain tumor and many studies have evaluated numerous biomarkers for their prognostic value, often with inconsistent results. Currently, no reliable biomarkers are available to predict the survival, recurrence, and progression of meningioma patients in clinical practice. This study aims to evaluate the prognostic value of immunohistochemistry-based (IHC) biomarkers of meningioma patients. A systematic literature search was conducted up to November 2023 on PubMed, CENTRAL, CINAHL Plus, and Scopus databases. Two authors independently reviewed the identified relevant studies, extracted data, and assessed the risk of bias of the studies included. Meta-analyses were performed with the hazard ratio (HR) and 95% confidence interval (CI) of overall survival (OS), recurrence-free survival (RFS), and progression-free survival (PFS). The risk of bias in the included studies was evaluated using the Quality in Prognosis Studies (QUIPS) tool. A total of 100 studies with 16,745 patients were included in this review. As the promising markers to predict OS of meningioma patients, Ki-67/MIB-1 (HR = 1.03, 95%CI 1.02 to 1.05) was identified to associate with poor prognosis of the patients. Overexpression of cyclin A (HR = 4.91, 95%CI 1.38 to 17.44), topoisomerase II α (TOP2A) (HR = 4.90, 95%CI 2.96 to 8.12), p53 (HR = 2.40, 95%CI 1.73 to 3.34), vascular endothelial growth factor (VEGF) (HR = 1.61, 95%CI 1.36 to 1.90), and Ki-67 (HR = 1.33, 95%CI 1.21 to 1.46), were identified also as unfavorable prognostic biomarkers for poor RFS of meningioma patients. Conversely, positive progesterone receptor (PR) and p21 staining were associated with longer RFS and are considered biomarkers of favorable prognosis of meningioma patients (HR = 0.60, 95% CI 0.41 to 0.88 and HR = 1.89, 95%CI 1.11 to 3.20). Additionally, high expression of Ki-67 was identified as a prognosis biomarker for poor PFS of meningioma patients (HR = 1.02, 95%CI 1.00 to 1.04). Although only in single studies, KPNA2, CDK6, Cox-2, MCM7 and PCNA are proposed as additional markers with high expression that are related with poor prognosis of meningioma patients. In conclusion, the results of the meta-analysis demonstrated that PR, cyclin A, TOP2A, p21, p53, VEGF and Ki-67 are either positively or negatively associated with survival of meningioma patients and might be useful biomarkers to assess the prognosis.

Meningioma recurrence: Time for an online prediction tool?

Background

Meningioma, the most common brain tumor, traditionally considered benign, has a relatively high risk of recurrence over a patient's lifespan. In addition, with the emergence of several clinical, radiological, and molecular variables, it is becoming evident that existing grading criteria, including Simpson's and World Health Organization classification, may not be sufficient or accurate. As web-based tools for widespread accessibility and usage become commonplace, such as those for gene identification or other cancers, it is timely for meningioma care to take advantage of evolving new markers to help advance patient care.

Methods

A scoping review of the meningioma literature was undertaken using the MEDLINE and Embase databases. We reviewed original studies and review articles from September 2022 to December 2023 that provided the most updated information on the demographic, clinical, radiographic, histopathological, molecular genetics, and management of meningiomas in the adult population.

Results

Our scoping review reveals a large body of meningioma literature that has evaluated the determinants for recurrence and aggressive tumor biology, including older age, female sex, genetic abnormalities such as telomerase reverse transcriptase promoter mutation, CDKN2A deletion, subtotal resection, and higher grade. Despite a large body of evidence on meningiomas, however, we noted a lack of tools to aid the clinician in decision-making. We identified the need for an online, self-updating, and machine-learning-based dynamic model that can incorporate demographic, clinical, radiographic, histopathological, and genetic variables to predict the recurrence risk of meningiomas.

Conclusion

Although a challenging endeavor, a recurrence prediction tool for meningioma would provide critical information for the meningioma patient and the clinician making decisions on long-term surveillance and management of meningiomas.

Single versus multiple reoperations for recurrent intracranial meningiomas

PURPOSE

To identify the risk factors and management of the multiple recurrences and reoperations for intracranial meningiomas.

METHODS

Data of a neurosurgical series of 35 patients reoperated on for recurrent intracranial meningiomas were reviewed. Analyzed factors include patient age and sex, tumor location, extent of resection, WHO grade, Ki67-MIB1 and PR expression at initial diagnosis, time to recurrence; pattern of regrowth, extent of resection, WHO grade and Ki67-MIB1 at first recurrence were also analyzed. All these factors were stratified into two groups based on single (Group A) and multiple reoperations (Group B).

RESULTS

Twenty-four patients (69%) belonged to group A and 11 (31%) to group B. The age < 65 years, male sex, incomplete resection at both initial surgery and first reoperation, and multicentric-diffuse pattern of regrowth at first recurrence are risk factors for multiple recurrences and reoperations. In group B, the WHO grade and Ki67-MIB1 increased in further recurrences in 54% and 64%, respectively. The time to recurrence was short in 7 cases (64%), whereas 4 patients (36%) further recurred after many years. Eight patients (73%) are still alive after 7 to 22 years and 2 to 4 reoperations.

CONCLUSION

The extent of resection and the multicentric-diffuse pattern of regrowth at first recurrence are the main risk factors for multiple recurrences and reoperations. Repeated reoperations might be considered even in patients with extensive recurrent tumors before the anaplastic transformation occurs. In such cases, even partial tumor resections followed by radiation therapy may allow long survival in good clinical conditions.

An MRI-Based Deep Transfer Learning Radiomics Nomogram to Predict Ki-67 Proliferation Index of Meningioma

The objective of this study was to predict Ki-67 proliferation index of meningioma by using a nomogram based on clinical, radiomics, and deep transfer learning (DTL) features. A total of 318 cases were enrolled in the study. The clinical, radiomics, and DTL features were selected to construct models. The calculation of radiomics and DTL score was completed by using selected features and correlation coefficient. The deep transfer learning radiomics (DTLR) nomogram was constructed by selected clinical features, radiomics score, and DTL score. The area under the receiver operator characteristic curve (AUC) was calculated. The models were compared by Delong test of AUCs and decision curve analysis (DCA). The features of sex, size, and peritumoral edema were selected to construct clinical model. Seven radiomics features and 15 DTL features were selected. The AUCs of clinical, radiomics, DTL model, and DTLR nomogram were 0.746, 0.75, 0.717, and 0.779 respectively. DTLR nomogram had the highest AUC of 0.779 (95% CI 0.6643-0.8943) with an accuracy rate of 0.734, a sensitivity value of 0.719, and a specificity value of 0.75 in test set. There was no significant difference in AUCs among four models in Delong test. The DTLR nomogram had a larger net benefit than other models across all the threshold probability. The DTLR nomogram had a satisfactory performance in Ki-67 prediction and could be a new evaluation method of meningioma which would be useful in the clinical decision-making.

Enhancing mitosis quantification and detection in meningiomas with computational digital pathology

Mitosis is a critical criterion for meningioma grading. However, pathologists' assessment of mitoses is subject to significant inter-observer variation due to challenges in locating mitosis hotspots and accurately detecting mitotic figures. To address this issue, we leverage digital pathology and propose a computational strategy to enhance pathologists' mitosis assessment. The strategy has two components: (1) A depth-first search algorithm that quantifies the mathematically maximum mitotic count in 10 consecutive high-power fields, which can enhance the preciseness, especially in cases with borderline mitotic count. (2) Implementing a collaborative sphere to group a set of pathologists to detect mitoses under each high-power field, which can mitigate subjective random errors in mitosis detection originating from individual detection errors. By depth-first search algorithm (1) , we analyzed 19 meningioma slides and discovered that the proposed algorithm upgraded two borderline cases verified at consensus conferences. This improvement is attributed to the algorithm's ability to quantify the mitotic count more comprehensively compared to other conventional methods of counting mitoses. In implementing a collaborative sphere (2) , we evaluated the correctness of mitosis detection from grouped pathologists and/or pathology residents, where each member of the group annotated a set of 48 high-power field images for mitotic figures independently. We report that groups with sizes of three can achieve an average precision of 0.897 and sensitivity of 0.699 in mitosis detection, which is higher than an average pathologist in this study (precision: 0.750, sensitivity: 0.667). The proposed computational strategy can be integrated with artificial intelligence workflow, which envisions the future of achieving a rapid and robust mitosis assessment by interactive assisting algorithms that can ultimately benefit patient management.

Drug target therapy and emerging clinical relevance of exosomes in meningeal tumors

Meningioma is the most common central nervous system (CNS) tumor. In recent decades, several efforts have been made to eradicate this disease. Surgery and radiotherapy remain the standard treatment options for these tumors. Drug therapy comes to play its role when both surgery and radiotherapy fail to treat the tumor. This mostly happens when the tumors are close to vital brain structures and are nonbenign. Although a wide variety of chemotherapeutic drugs and molecular targeted drugs such as tyrosine kinase inhibitors, alkylating agents, endocrine drugs, interferon, and targeted molecular pathway inhibitors have been studied, the roles of numerous drugs remain unexplored. Recent interest is growing toward studying and engineering exosomes for the treatment of different types of cancer including meningioma. The latest studies have shown the involvement of exosomes in the theragnostic of various cancers such as the lung and pancreas in the form of biomarkers, drug delivery vehicles, and vaccines. Proper attention to this new emerging technology can be a boon in finding the consistent treatment of meningioma.

Domestic Animal Models of Central Nervous System Tumors: Focus on Meningiomas

Intracranial primary tumors (IPTs) are aggressive forms of malignancies that cause high mortality in both humans and domestic animals. Meningiomas are frequent adult IPTs in humans, dogs, and cats, and both benign and malignant forms cause a decrease in life quality and survival. Surgery is the primary therapeutic approach to treat meningiomas, but, in many cases, it is not resolutive. The chemotherapy and targeted therapy used to treat meningiomas also display low efficacy and many side effects. Therefore, it is essential to find novel pharmacological approaches to increase the spectrum of therapeutic options for meningiomas. This review analyzes the similarities between human and domestic animal (dogs and cats) meningiomas by evaluating the molecular and histological characteristics, diagnosis criteria, and treatment options and highlighting possible research areas to identify novel targets and pharmacological approaches, which are useful for the diagnosis and therapy of this neoplasia to be used in human and veterinary medicine.

A prognostic model for tumor recurrence and progression after meningioma surgery: preselection for further molecular work-up

Purpose

The selection of patients for further therapy after meningioma surgery remains a challenge. Progress has been made in this setting in selecting patients that are more likely to have an aggressive disease course by using molecular tests such as gene panel sequencing and DNA methylation profiling. The aim of this study was to create a preselection tool warranting further molecular work-up.

Methods

All patients undergoing surgery for resection or biopsy of a cranial meningioma from January 2013 until December 2018 at the University Hospital Zurich with available tumor histology were included. Various prospectively collected clinical, radiological, histological and immunohistochemical variables were analyzed and used to train a logistic regression model to predict tumor recurrence or progression. Regression coefficients were used to generate a scoring system grading every patient into low, intermediate, and high-risk group for tumor progression or recurrence.

Results

Out of a total of 13 variables preselected for this study, previous meningioma surgery, Simpson grade, progesterone receptor staining as well as presence of necrosis and patternless growth on histopathological analysis of 378 patients were included into the final model. Discrimination showed an AUC of 0.81 (95% CI 0.73 - 0.88), the model was well-calibrated. Recurrence-free survival was significantly decreased in patients in intermediate and high-risk score groups (p-value < 0.001).

Conclusion

The proposed prediction model showed good discrimination and calibration. This prediction model is based on easily obtainable information and can be used as an adjunct for patient selection for further molecular work-up in a tertiary hospital setting.

Disease-Based Prognostication: Neuro-Oncology

Primary malignant and non-malignant brain and other central nervous system (CNS) tumors, while relatively rare, are a disproportionate source of morbidity and mortality. Here we provide a brief overview of approaches to modeling important clinical outcomes, such as overall survival, that are critical for clinical care. Because there are a large number of histologically distinct types of primary malignant and non-malignant brain and other CNS tumors, this chapter will provide an overview of prognostication considerations on the most common primary non-malignant brain tumor, meningioma, and the most common primary malignant brain tumor, glioblastoma. In addition, information on nomograms and how they can be used as individualized prognostication tools by clinicians to counsel patients and their families regarding treatment, follow-up, and prognosis is described. The current state of nomograms for meningiomas and glioblastomas are also provided.

MRI-based machine learning models predict the malignant biological behavior of meningioma

BACKGROUND

The WHO grade and Ki-67 index are independent indices used to evaluate the malignant biological behavior of meningioma. This study aims to develop MRI-based machine learning models to predict the malignant biological behavior of meningioma from the perspective of the WHO grade, Ki-67 index, and their combination.

METHODS

This multicenter, retrospective study included 313 meningioma patients, of which 70 were classified as high-grade (WHO II/III) and 243 as low-grade (WHO I). The Ki-67 expression was classified into low-expression (n = 216) and high-expression (n = 97) groups with a threshold of 5%. Among them, there were 128 patients with malignant biological behavior whose WHO grade or Ki-67 index increased either or both. Data from Center A and B are were utilized for model development, while data from Center C and D were used for external validation. Radiomic features were extracted from the maximum cross-sectional area (2D) region of Interest (ROI) and the whole tumor volume (3D) ROI using different paraments from the T1, T2-weighted, and T1 contrast-enhanced sequences (T1CE), followed by five independent feature selections and eight classifiers. 240 prediction models were constructed to predict the WHO grade, Ki-67 index and their combination respectively. Models were evaluated by cross-validation in training set (n = 224). Suitable models were chosen by comparing the cross-validation (CV) area under the curves (AUC) and their relative standard deviations (RSD). Clinical and radiological features were collected and analyzed; meaningful features were combined with radiomic features to establish the clinical-radiological-radiomic (CRR) models. The receiver operating characteristic (ROC) analysis was used to evaluate those models in validation set. Radiomic models and CRR models were compared by Delong test.

RESULTS

1218 and 1781 radiomic features were extracted from 2D ROI and 3D ROI of each sequence. The selected grade, Ki-67 index and their combination radiomic models were T1CE-2D-LASSO-LR, T1CE-3D-LASSO-NB, and T1CE-2D-LASSO-LR, with cross-validated AUCs on the training set were 0.857, 0.798, and 0.888, the RSDs were 0.06, 0.09, and 0.05, the validation set AUCs were 0.829, 0.752, and 0.904, respectively. Heterogeneous enhancement was found to be associated with high grade and Ki-67 status, while surrounding invasion was associated with the high grade status, peritumoral edema and cerebrospinal fluid space surrounding tumor were correlated with the high Ki-67 status. The Delong test showed that these significant radiological features did not significantly improve the predictive performance. The AUCs for CRR models predicting grade, Ki-67 index, and their combination in the validation set were 0.821, 0.753, and 0.906, respectively.

CONCLUSIONS

This study demonstrated that MRI-based machine learning models could effectively predict the grade, Ki-67 index of meningioma. Models considering these two indices might be valuable for improving the predictive sensitivity and comprehensiveness of prediction of malignant biological behavior of meningioma.

Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas

Recurrence of meningiomas is unpredictable by current invasive methods based on surgically removed specimens. Identification of patients likely to recur using noninvasive approaches could inform treatment strategy, whether intervention or monitoring. In this study, we analyze the DNA methylation levels in blood (serum and plasma) and tissue samples from 155 meningioma patients, compared to other central nervous system tumor and non-tumor entities. We discover DNA methylation markers unique to meningiomas and use artificial intelligence to create accurate and universal models for identifying and predicting meningioma recurrence, using either blood or tissue samples. Here we show that liquid biopsy is a potential noninvasive and reliable tool for diagnosing and predicting outcomes in meningioma patients. This approach can improve personalized management strategies for these patients.

Intracranial meningiomas: an update of the 2021 World Health Organization classifications and review of management with a focus on radiation therapy

Meningiomas account for approximately one third of all primary intracranial tumors. Arising from the cells of the arachnoid mater, these neoplasms are found along meningeal surfaces within the calvarium and spinal canal. Many are discovered incidentally, and most are idiopathic, although risk factors associated with meningioma development include age, sex, prior radiation exposure, and familial genetic diseases. The World Health Organization grading system is based on histologic criteria, and are as follows: grade 1 meningiomas, a benign subtype; grade 2 meningiomas, which are of intermediately aggressive behavior and usually manifest histologic atypia; and grade 3, which demonstrate aggressive malignant behavior. Management is heavily dependent on tumor location, grade, and symptomatology. While many imaging-defined low grade appearing meningiomas are suitable for observation with serial imaging, others require aggressive management with surgery and adjuvant radiotherapy. For patients needing intervention, surgery is the optimal definitive approach with adjuvant radiation therapy guided by extent of resection, tumor grade, and location in addition to patient specific factors such as life expectancy. For grade 1 lesions, radiation can also be used as a monotherapy in the form of stereotactic radiosurgery or standard fractionated radiation therapy depending on tumor size, anatomic location, and proximity to dose-limiting organs at risk. Optimal management is paramount because of the generally long life-expectancy of patients with meningioma and the morbidity that can arise from tumor growth and recurrence as well as therapy itself.

Conditional Recurrence-Free Survival After Surgical Resection of Meningioma

BACKGROUND

Recurrence after meningioma resection warrants serial surveillance imaging, but little evidence guides the optimal time interval between imaging studies/surveillance duration.

OBJECTIVE

To describe recurrence-free survival (RFS) after meningioma resection, conditioned to short-term RFS.

METHODS

A retrospective cohort study for adults presenting for meningioma resection from 2000 to 2018 was conducted. The primary outcome was postoperative follow-up RFS. Conditional RFS Kaplan-Meier analysis was performed at 1, 2, 3, 5, and 10 years, conditioned to 6-month and 12-month RFS. RFS probabilities conditioned to 6-month RFS were estimated in subgroups, stratified by World Health Organization grade, extent of resection, and need for postoperative radiation.

RESULTS

In total, 723 patients were included. Median age at surgery was 57.4 years (IQR = 47.2-67.2). Median follow-up was 23.5 months (IQR = 12.3-47.8). Recurrence was observed in 90 patients (12%), with median time to recurrence of 14.4 months (IQR = 10.3-37.1). Conditioned to 6-month postoperative RFS, patients had 90.3% probability of remaining recurrence-free at 2 years and 69.4% at 10 years. Subgroup analysis conditioned to 6-month RFS demonstrated grade 1 meningiomas undergoing gross total resection (GTR) had 96.0% probability of RFS at 1 year and 82.8% at 5 years, whereas those undergoing non-GTR had 94.5% and 79.9% probability, respectively. RFS probability was 78.8% at 5 years for non-grade 1 meningiomas undergoing GTR, compared with 69.7% for non-grade 1 meningiomas undergoing non-GTR. Patients with non-grade 1 meningiomas undergoing upfront radiation had a 1-year RFS of 90.1% and 5-year RFS of 51.7%.

CONCLUSION

Recurrence risk after meningioma resection after an initial recurrence-free period is reported, with high-risk subgroups identified. These results can inform objective shared decision-making for optimal follow-up.

Target volume delineation for radiotherapy of meningiomas: an ANOCEF consensus guideline

PURPOSE

Radiotherapy is, with surgery, one of the main therapeutic treatment strategies for meningiomas. No prospective study has defined a consensus for the delineation of target volumes for meningioma radiotherapy. Therefore, target volume definition is mainly based on information from retrospective studies that include heterogeneous patient populations. The aim is to describe delineation guidelines for meningioma radiotherapy as an adjuvant or definitive treatment with intensity-modulated radiation therapy and stereotactic radiation therapy techniques. This guideline is based on a consensus endorsed by a multidisciplinary group of brain tumor experts, members of the Association of French-speaking Neuro-oncologists (ANOCEF).

MATERIALS AND METHODS

A 3-step procedure was used. First, the steering group carried out a comprehensive review to identify divergent issues on meningiomas target volume delineation. Second, an 84-item web-questionnaire has been developed to precisely define meningioma target volume delineation in the most common clinical situations. Third, experts members of the ANOCEF were requested to answer. The first two rounds were completed online. A third round was carried out by videoconference to allow experts to debate and discuss the remaining uncertain questions. All questions remained in a consensus.

RESULTS

Limits of the target volume were defined using visible landmarks on computed tomography and magnetic resonance imaging, considering the pathways of tumor extension. The purpose was to develop clear and precise recommendations on meningiomas target volumes.

CONCLUSION

New recommendations for meningiomas delineation based on simple anatomic boundaries are proposed by the ANOCEF. Improvement in uniformity in target volume definition is expected.

Impact of Shape Irregularity in Medial Sphenoid Wing Meningiomas on Postoperative Cranial Nerve Functioning, Proliferation, and Progression-Free Survival

Medial sphenoid wing meningiomas (MSWM) are surgically challenging skull base tumors. Irregular tumor shapes are thought to be linked to histopathology. The present study aims to investigate the impact of tumor shape on postoperative functioning, progression-free survival, and neuropathology. This monocentric study included 74 patients who underwent surgery for primary sporadic MSWM (WHO grades 1 and 2) between 2010 and 2021. Furthermore, a systematic review of the literature regarding meningioma shape and the MIB-1 index was performed. Irregular MSWM shapes were identified in 31 patients (41.9%). Multivariable analysis revealed that irregular shape was associated with postoperative cranial nerve deficits (OR: 5.75, 95% CI: 1.15-28.63, p = 0.033). In multivariable Cox regression analysis, irregular MSWM shape was independently associated with tumor progression (HR:8.0, 95% CI: 1.04-62.10, p = 0.046). Multivariable regression analysis showed that irregular shape is independently associated with an increased MIB-1 index (OR: 7.59, 95% CI: 2.04-28.25, p = 0.003). A systematic review of the literature and pooled data analysis, including the present study, showed that irregularly shaped meningiomas had an increase of 1.98 (95% CI: 1.38-2.59, p < 0.001) in the MIB-1 index. Irregular MSWM shape is independently associated with an increased risk of postoperative cranial nerve deficits and a shortened time to tumor progression. Irregular MSWM shapes might be caused by highly proliferative tumors.

Predictive Value of K i -67 Index in Evaluating Sporadic Vestibular Schwannoma Recurrence: Systematic Review and Meta-analysis

Introduction  K _i -67 is often used as a proliferation index to evaluate how aggressive a tumor is and its likelihood of recurrence. Vestibular schwannomas (VS) are a unique benign pathology that lends itself well to evaluation with K _i -67 as a potential marker for disease recurrence or progression following surgical resection. Methods  All English language studies of VSs and K _i -67 indices were screened. Studies were considered eligible for inclusion if they reported series of VSs undergoing primary resection without prior irradiation, with outcomes including both recurrence/progression and K _i -67 for individual patients. For published studies reporting pooled K _i -67 index data without detailed by-patient values, we contacted the authors to request data sharing for the current meta-analysis. Studies reporting a relationship between K _i -67 index and clinical outcomes in VS for which detailed patients' outcomes or K _i -67 indices could not be obtained were incorporated into the descriptive analysis, but excluded from the formal (i.e., quantitative) meta-analysis. Results  A systematic review identified 104 candidate citations of which 12 met inclusion criteria. Six of these studies had accessible patient-specific data. Individual patient data were collected from these studies for calculation of discrete study effect sizes, pooling via random-effects modeling with restricted maximum likelihood, and meta-analysis. The standardized mean difference in K _i -67 indices between those with and without recurrence was calculated as 0.79% (95% confidence interval [CI]: 0.28-1.30; p  = 0.0026). Conclusion  K _i -67 index may be higher in VSs that demonstrate recurrence/progression following surgical resection. This may represent a promising means of evaluating tumor recurrence and potential need for early adjuvant therapy for VSs.

Association between preoperative hematologic markers and aggressive behavior in meningiomas

INTRODUCTION

Meningiomas have varying degrees of aggressive behavior. Some systemic hematologic makers are associated with malignancy, but their value in predicting aggressive meningioma behavior is not fully understood.

OBJECTIVE

To evaluate the association between preoperative markers such as neutrophil-lymphocyte ratio (NLR), neutrophil-monocyte ratio (NMR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), and prognostic nutritional index (PNI), and diagnostic and prognostic factors including WHO grade, proliferation index, presence of edema on preoperative MRI, and tumor recurrence.

METHODS

A retrospective review of patients treated between 2000 and 2019 with a preoperative complete blood count (CBC) differential lab draw before intracranial meningioma resection was conducted. All preoperative steroid dosages were converted to dexamethasone equivalents. Primary outcomes included presence/absence of perilesional edema, WHO grade, Ki-67/MIB-index, and recurrence. Univariate and multivariable regression analyses were conducted.

RESULTS

A total of 209 meningioma patients were included. Of these, 143 (68 %) were WHO grade I, 61 (29 %) grade II and 5 (2 %) were grade III. Recurrence was reported in 19 (9.1 %) tumors. No hematologic markers were associated with recurrence. In separate multivariable logistic analyses, no biomarkers were associated with perilesional edema or WHO grade. MLR was associated with higher MIB-index (p = 0.018, OR 6.57, 95 % CI 1.37-30.91).

CONCLUSION

Most hematologic markers were not associated with meningioma invasiveness, grade, proliferative index, or aggressiveness. Preoperative MLR was associated with high proliferation index in patients undergoing surgery for intracranial meningioma. Higher MLR could be a surrogate for meningioma proliferation and has potential to be used as an adjunct for risk-stratifying meningiomas.

Contrast enhanced magnetic resonance imaging-based radiomics nomogram for preoperatively predicting expression status of Ki-67 in meningioma: a two-center study

Background

The aim of this study was to develop and validate a radiomics nomogram for preoperative prediction of Ki-67 proliferative index (Ki-67 PI) expression in patients with meningioma.

Methods

A total of 280 patients from 2 independent hospital centers were enrolled. Patients from center I were randomly divided into a training cohort of 168 patients and a test cohort of 72 patients, and 40 patients from center II served as an external validation cohort. Interoperator reproducibility test, Z-score standardization, analysis of variance (ANOVA), and least absolute shrinkage and selection operator (LASSO) binary logistic regression were used to select radiomics features, which were extracted from contrast-enhanced T1-weighted imaging (CE-T1WI) imaging. The radiomics signature for predicting Ki-67 PI expression was developed and validated using 4 classifiers including logistic regression (LR), decision tree (DT), support vector machine (SVM), and adaptive boost (AdaBoost). Finally, combined radiological characteristics with radiomics signature were used to establish the nomogram to predict the risk of high Ki-67 PI expression in patients with meningioma.

Results

Fourteen radiomics features were used to construct the radiomics signature. The radiomics nomogram that incorporated the radiomics signature and radiological characteristics showed excellent discrimination in the training, test, and validation cohorts with areas under the curve of 0.817 (95% CI: 0.753-0.881), 0.822 (95% CI: 0.727-0.916), and 0.845 (95% CI: 0.708-0.982), respectively. In addition, the calibration curve for the nomogram demonstrated good agreement between prediction and actual observation.

Conclusions

The proposed contrast enhanced magnetic resonance imaging (MRI)-based radiomics nomogram could be an effective tool to predict the risk of Ki-67 high expression in patients with meningioma.

Spinal meningiomas, from biology to management - A literature review

Meningiomas arise from arachnoidal cap cells of the meninges, constituting the most common type of central nervous system tumors, and are considered benign tumors in most cases. Their incidence increases with age, and they mainly affect females, constituting 25-46% of primary spinal tumors. Spinal meningiomas could be detected incidentally or be unraveled by various neurological symptoms (e.g., back pain, sphincter dysfunction, sensorimotor deficits). The gold standard diagnostic modality for spinal meningiomas is Magnetic resonance imaging (MRI) which permits their classification into four categories based on their radiological appearance. According to the World Health Organization (WHO) classification, the majority of spinal meningiomas are grade 1. Nevertheless, they can be of higher grade (grades 2 and 3) with atypical or malignant histology and a more aggressive course. To date, surgery is the best treatment where the big majority of meningiomas can be cured. Advances in surgical techniques (ultrasonic dissection, microsurgery, intraoperative monitoring) increase the complete resection rate. Operated patients have a satisfactory prognosis, even in those with poor preoperative neurological status. Adjuvant therapy has a growing role in treating spinal meningiomas, mainly in the case of subtotal resection and tumor recurrence. The current paper reviews the fundamental epidemiological and clinical aspects of spinal meningiomas, their histological and genetic characteristics, and their management, including the various surgical novelties and techniques.

Primary ectopic meningioma in the thoracic cavity: A rare case report and review of the literature

Background

Meningioma is a common type of intracranial tumor in adults. It rarely arises in the chest, with only a few case reports in the English literature. Here, we report the case of a patient with a primary ectopic meningioma (PEM) located in the thoracic cavity.

Case presentation

A 55-year-old woman presented with exercise-induced asthma, chest tightness, intermittent dry cough and fatigue for several months. Computed tomography revealed the presence of a huge mass in the thoracic cavity, with no connection to the spinal canal. Lung cancer and mesothelioma were suspected, and surgery was performed. Grossly, the mass was a grayish-white solid 9.5 cm × 8.4 cm × 5.3 cm in size. The microscopic morphology of the lesion was consistent with that of typical central nervous system meningioma. The pathological subtype was transitional meningioma. The tumor cells were arranged in a fascicular, whorled, storiform and meningithelial pattern, with occasional intranuclear pseudo-inclusions and psammoma bodies. In focal areas tumor cells were considerably dense, and the cells were round or irregular in shape, with less cytoplasm, uniform nuclear chromatin, and visible nucleoli and mitoses (2/10 HPF). By immunohistochemistry, the neoplastic cells showed strong and diffuse staining with vimentin, epithelial membrane antigen and SSTR2 with variable expression of PR, ALK and S100 protein. However, the cells were negative for GFAP, SOX-10, inhibin, CD34, STAT6, smooth muscle actin, desmin, CKpan, D2-40, WT-1, CK5/6 and CD45. The highest proliferation index by Ki-67 was 15%. The abnormal expression of ALK led to the initial misdiagnosis of an inflammatory myofibroblastic tumor. After 12 months of follow-up, no disease progression was observed.

Conclusion

The presence of primary ectopic meningiomas in the thoracic cavity is extremely rare, and this tumor is easily misdiagnosed clinically. Imaging is suggested to determine the location and possible differential diagnosis, while the final diagnosis should be via pathological examination. Immunohistochemistry is crucial for disease diagnosis. Owing to our limited knowledge of PEM, its pathogenesis and tissue of origin remain unclear. Clinicians should pay close attention to such potential patients. The present case report may provide insights into the diagnosis and therapy of patients with this tumor.

Supervised machine learning algorithms demonstrate proliferation index correlates with long-term recurrence after complete resection of WHO grade I meningioma

OBJECTIVE

Meningiomas are the most common primary intracranial tumor, and resection is a mainstay of treatment. It is unclear what duration of imaging follow-up is reasonable for WHO grade I meningiomas undergoing complete resection. This study examined recurrence rates, timing of recurrence, and risk factors for recurrence in patients undergoing a complete resection (as defined by both postoperative MRI and intraoperative impression) of WHO grade I meningiomas.

METHODS

The authors conducted a retrospective, single-center study examining recurrence risk for adult patients with a single intracranial meningioma that underwent complete resection. Uni- and multivariate nominal logistic regression and Cox proportional hazards analyses were performed to identify variables associated with recurrence and time to recurrence. Two supervised machine learning algorithms were then implemented to confirm factors within the cohort that were associated with recurrence.

RESULTS

The cohort consisted of 823 patients who met inclusion criteria, and 56 patients (6.8%) had recurrence on imaging follow-up. The median age of the cohort was 56 years, and 77.4% of patients were female. The median duration of head imaging follow-up for the entire cohort was 2.7 years, but for the subgroup of patients who had a recurrence, the median follow-up was 10.1 years. Estimated 1-, 5-, 10-, and 15-year recurrence-free survival rates were 99.8% (95% confidence interval [CI] 98.8%-99.9%), 91.0% (95% CI 87.7%-93.6%), 83.6% (95% CI 78.6%-87.6%), and 77.3% (95% CI 69.7%-83.4%), respectively, for the entire cohort. On multivariate analysis, MIB-1 index (odds ratio [OR] per 1% increase: 1.34, 95% CI 1.13-1.58, p = 0.0003) and follow-up duration (OR per year: 1.12, 95% CI 1.03-1.21, p = 0.012) were both associated with recurrence. Gradient-boosted decision tree and random forest analyses both identified MIB-1 index as the main factor associated with recurrence, aside from length of imaging follow-up. For tumors with an MIB-1 index < 8, recurrences were documented up to 8 years after surgery. For tumors with an MIB-1 index ≥ 8, recurrences were documented up to 12 years following surgery.

CONCLUSIONS

Long-term imaging follow-up is important even after a complete resection of a meningioma. Higher MIB-1 labeling index is associated with greater risk of recurrence. Imaging screening for at least 8 years in patients with an MIB-1 index < 8 and at least 12 years for those with an MIB-1 index ≥ 8 may be needed to detect long-term recurrences.

Novel evaluation of the expression patterns CD44 and MMP9 proteins in intracranial meningiomas and their relationship to the overall survival

Background

Meningiomas are common primary brain neoplasms. CD44 is a cell surface glycoprotein receptor that is involved in matrix-mediated cell signaling and cell–matrix adhesion. Matrix metalloproteinase-9 (MMP-9) plays important role in angiogenesis and tumor invasion. The expression of CD44 protein membranous and cytoplasmic (CD44M and CD44C) has been reported in several tumors (such as lobular carcinoma, renal cell carcinoma, sinonasal melanoma, and lymphoma) except CNS tumors.

Methods

This study addressed the expression of CD44M and CD44C and MMP9 proteins in intracranial meningiomas and their relationship to overall survival. The expression patterns of CD44M&C and MMP-9 proteins were examined in 32 cases of benign meningiomas, 12 cases of atypical meningiomas, and 6 cases of anaplastic meningiomas using immunohistochemical staining methods.

Results

There was more evidence of CD44M expression in atypical and anaplastic meningioma (p =  < 0.001). Interestingly, Spearman correlation analyses revealed significant positive correlation between CD44M and MMP9 protein (r = 0.572, p =  < 0.001) in spite of the negative correlation between MMP9 and CD44 score (r = − 0.035 p = 0.405). There was a significant association between Ki67 protein expression and the grade of meningiomas (p < 0.001) and gender (p = 0.026). There was a significant correlation between overall survival (OS) and age, gender, tumor grade, and Ki-67.

Conclusions

Extensive CD44M expression in high-grade meningioma may reflect a tendency toward more invasive power of meningioma cells into surrounding structures (dura, bone, and brain).CD44M/MMP-9 axis presented by this study is open for future investigations.

Prostate-Specific Membrane Antigen Expression in Meningioma: A Promising Theranostic Target

Meningioma is the most common intracranial neoplasm, yet there is no effective therapy for recurrent/refractory meningiomas after surgery and radiation. Prostate-specific membrane antigen (PSMA) is an enzyme upregulated on endothelial cells of multiple neoplasms and is being investigated as a theranostic target. Until now, PSMA has not been studied in meningiomas. We aimed to verify PSMA endothelial expression in meningiomas, detect tumor grade variability, and investigate the relationship of PSMA signal with tumor recurrence. We analyzed 96 archival meningiomas including 58 de novo and 38 recurrent specimens. All specimens were stained routinely and immunostained for CD31 and PSMA. Slides were scanned and analyzed producing raw data for images of PSMA, CD31, PSMA/CD31, and PSMA/vasculature. PSMA expression was seen within 98.9% of meningioma samples. In the total cohort, higher-grade tumors had increased expression of raw PSMA and PSMA/CD31, and PSMA/vasculature ratios compared to grade 1 tumors. PSMA expression and PSMA/vasculature ratios (p = 0.0015) were higher in recurrent versus de novo tumors among paired samples. ROC curves demonstrated PSMA/CD31, PSMA/vasculature, and raw CD31 as indicators of tumor recurrence. Thus, PSMA is expressed within endothelial cells of meningiomas, is increased with tumor grade and recurrence, and persists with prior irradiation.

Predictive Power of MIB-1 vs. Mitotic Count on Progression-Free Survival in Skull-Base Meningioma

Simple Summary

Meningiomas are mainly benign intracranial tumors. Nevertheless, risk of recurrence exists in long-term follow-up, so new prognostic markers are still need to be identified. MIB-1 is no diagnostic criterion in WHO classification of meningiomas by now. This retrospective study shows that MIB-1 as well as mitotic count are good predictors for progression-free survival in skull-base meningiomas. The implantation of MIB-1 may enable an improved classification of meningiomas regarding progression-free survival. Moreover, this analysis of skull-base meningiomas shows that current cut-offs may have to be adjusted for meningioma location.

Abstract

Although meningiomas are mainly non-aggressive and slow-growing tumors, there is a remarkable recurrence rate in a long-term follow-up. Proliferative activity and progression-free survival (PFS) differs significantly among the anatomic location of meningiomas. The aim of the present study was to investigate the predictive power of MIB-1 labeling index and mitotic count (MC) regarding the probability of PFS in the subgroup of skull-base meningiomas. A total of 145 patients were included in this retrospective study. Histopathological examinations and follow-up data were collected. Ideal cut-off values for MIB-1 and MC were ≥4.75 and ≥6.5, respectively. MIB-1 as well as MC were good predictors for PFS in skull-base meningiomas. Time-dependent analysis of MIB-1 and MC in prediction of recurrence of skull-base meningioma showed that their prognostic values were comparable, but different cut-offs for MC should be considered regarding the meningioma’s location. As the achievement of a gross total resection can be more challenging in skull-base meningiomas and second surgery implies a higher risk profile, the recurrence risk could be stratified according to these findings and guide decision-making for follow-ups vs. adjuvant therapies.

Should adjuvant radiotherapy be used in atypical meningioma (WHO grade 2) following gross total resection? A systematic review and Meta-analysis

BACKGROUND

The role of adjuvant radiotherapy (RT) following gross total resection (GTR) in atypical meningioma (AM) is not well established and its benefit remains unclear. We aim to evaluate the survival benefit of adjuvant RT in AM following GTR.

METHODS

We searched biomedical databases for studies published between January 1964-February 2021 and included studies reporting primary outcomes of 5-year PFS, 5-year OS and had survival curves for restricted mean survival time (RMST) calculations. Data extracted from survival curves were pooled and analyzed using a random-effects model. Hazard ratio (HR) was calculated for sensitivity analysis.

RESULTS

We included 12 non-randomized studies comprising 1,078 patients. 803 (74.5%) patients were treated with GTR alone and 275 (25.5%) patients received adjuvant RT. In 9 studies, RT included 3 D conformal RT, intensity modulated RT, or fractionated stereotactic radiotherapy); in 3 studies, stereotactic radiosurgery was also used. Median dose of RT was 59.4 Gy. Adjuvant RT resulted in an increase of 3.9 months for restricted mean PFS truncated at 5 years (95% CI 0.23-7.72; p = 0.037) and a 22% reduction in the hazard of disease progression or death (hazards ratio 0.78; 95% CI 0.46-1.33; p = 0.370). Restricted mean OS, truncated at 5 years, was improved with adjuvant RT by 1.1 months (95% CI 0.37-1.81; p = 0.003) and a 21% reduction in the hazard of death from any cause (HR 0.79; 95% CI 0.51-1.24; p = 0.310). Meta-regression analysis of the RMST of EBRT dose did not reveal any significant difference in PFS or OS between studies reporting median dose of <59.4 Gy vs. ≥ 59.4 Gy.

CONCLUSION

Adjuvant RT following GTR in patients with AM improved restricted mean PFS and OS. While we await the results from ongoing randomized controlled trials, adjuvant RT should be recommended.

Low-Dose Acetylsalicylic Acid Treatment in Non-Skull-Base Meningiomas: Impact on Tumor Proliferation and Seizure Burden

MIB-1 index is an important predictor of meningioma progression and was found to be correlated with COX-2 expression. However, the impact of low-dose acetylsalicylic acid (ASA) on MIB-1 index and clinical symptoms is unclear. Between 2009 and 2022, 710 patients with clinical data, tumor-imaging data, inflammatory laboratory (plasma fibrinogen, serum C-reactive protein) data, and neuropathological reports underwent surgery for primary cranial WHO grade 1 and 2 meningioma. ASA intake was found to be significantly associated with a low MIB-1 labeling index in female patients ≥ 60 years. Multivariable analysis demonstrated that female patients ≥ 60 years with a non-skull-base meningioma taking ASA had a significantly lower MIB-1 index (OR: 2.6, 95%: 1.0–6.6, p = 0.04). Furthermore, the intake of ASA was independently associated with a reduced burden of symptomatic epilepsy at presentation in non-skull-base meningiomas in both genders (OR: 3.8, 95%CI: 1.3–10.6, p = 0.03). ASA intake might have an anti-proliferative effect in the subgroup of elderly female patients with non-skull-base meningiomas. Furthermore, anti-inflammatory therapy seems to reduce the burden of symptomatic epilepsy in non-skull-base meningiomas. Further research is needed to investigate the role of anti-inflammatory therapy in non-skull-base meningiomas.

MAC-spinal meningioma score: A proposal for a quick-to-use scoring sheet of the MIB-1 index in sporadic spinal meningiomas

Objective

MIB-1 index is an important predictor of meningioma progression. However, MIB-1 index is not available in the preoperative tailored medical decision-making process. A preoperative scoring sheet independently estimating MIB-1 indices in spinal meningioma (SM) patients has not been investigated so far.

Methods

Between 2000 and 2020, 128 patients with clinical data, tumor imaging data, inflammatory laboratory (plasma fibrinogen, serum C-reactive protein) data, and neuropathological reports (MIB-1, mitotic count, CD68 staining) underwent surgery for spinal WHO grade 1 and 2 meningioma.

Results

An optimal MIB-1 index cut-off value (≥5/<5) predicting recurrence was calculated by ROC curve analysis (AUC: 0.83; 95%CI: 0.71-0.96). An increased MIB-1 index (≥5%) was observed in 55 patients (43.0%) and multivariable analysis revealed significant associations with baseline Modified McCormick Scale ≥2, age ≥65, and absence of calcification. A four-point scoring sheet (MAC-Spinal Meningioma) based on Modified McCormick, Age, and Calcification facilitates prediction of the MIB-1 index (sensitivity 71.1%, specificity 60.0%). Among those patients with a preoperative MAC-Meningioma Score ≥3, the probability of a MIB-1 index ≥5% was 81.3%.

Conclusion

This novel score (MAC-Spinal Meningioma) supports the preoperative estimation of an increased MIB-1 index, which might support preoperative patient-surgeon consultation, surgical decision making and enable a tailored follow-up schedule or an individual watch-and-wait strategy.

Efficient Prediction of Ki-67 Proliferation Index in Meningiomas on MRI: From Traditional Radiological Findings to a Machine Learning Approach

Background/aim This study aimed to explore the value of radiological and radiomic features retrieved from magnetic resonance imaging in the prediction of a Ki-67 proliferative index in meningioma patients using a machine learning model. Methods This multicenter, retrospective study included 371 patients collected from two centers. The Ki-67 expression was classified into low-expressed and high-expressed groups with a threshold of 5%. Clinical features and radiological features were collected and analyzed by using univariate and multivariate statistical analyses. Radiomic features were extracted from contrast-enhanced images, followed by three independent feature selections. Six predictive models were constructed with different combinations of features by using linear discriminant analysis (LDA) classifier. Results The multivariate analysis suggested that the presence of intratumoral necrosis (p = 0.032) and maximum diameter (p < 0.001) were independently correlated with a high Ki-67 status. The predictive models showed good performance with AUC of 0.837, accuracy of 0.810, sensitivity of 0.857, and specificity of 0.771 in the internal test and with AUC of 0.700, accuracy of 0.557, sensitivity of 0.314, and specificity of 0.885 in the external test. Conclusion The results of this study suggest that the predictive model can efficiently predict the Ki-67 index of meningioma patients to facilitate the therapeutic management.

Increased MIB-1 Labeling Index Is Associated with Abducens Nerve Morbidity in Primary Sporadic Petroclival Meningioma Surgery: Beyond Location and Approach

Abducens nerve palsy is a severe dysfunction after petroclival meningioma (PC MNG) surgery. The objective of this investigation was to analyze abducens nerve outcomes in patients who underwent the retrosigmoid approach in relation to the MIB-1 index. Thirty-two patients with primary sporadic PC MNG were retrospectively analyzed. Mean follow-up was 28.0 months. Analysis of the MIB-1 index was performed to evaluate the abducens nerve outcome. An optimal MIB-1 index cut-off value (<4/≥4) in the association with postoperative CN VI palsy was determined by ROC analysis (AUC: 0.74, 95% CI: 0.57−0.92). A new-onset CN VI palsy was present in 7 cases (21.88%) and was significantly associated with an increased MIB-1 index (≥4%, p = 0.025) and a peritumoral edema in the brachium pontis (p = 0.047) which might be caused by the increased growth rate. Tumor volume, cavernous sinus infiltration, auditory canal invasion, and Simpson grading were not associated with new CN VI deficits. Six (85.7%) of the 7 patients with both an increased MIB-1 index (≥4%) and new abducens nerve palsy still had a CN VI deficit at the 12-month follow-up. A peritumoral edema caused by a highly proliferative PC MNG with an elevated MIB-1 index (≥4%) is associated with postoperative abducens nerve deficits.

Meningioma Cell Invasion into DuraGen-Derived Dura Mater: A Case Report

Background: Dura mater infiltration is the main growth pattern of meningiomas. Local recurrence may occur in any type of meningioma, but it is more likely so in atypical meningiomas. Therefore, a wide resection of tumor cell-invaded dura mater is necessary to avoid recurrence. DuraGen^® (an artificial dural substitute) can be used for dural reconstruction in meningiomas. Here, we report a rare case of a patient with atypical meningioma that invaded into the DuraGen^®-derived mature dura mater. Case presentation: A 66-year-old female showed a three-time recurrence of atypical meningioma. Simpson grade I resection (en bloc tumor with autologous dura mater and DuraGen^®-derived dura mater resection) was achieved at the 3rd recurrence. Collagen fibers running regularly and transversely were observed in the DuraGen^®-derived dura mater resembling the autologous meningeal layer. Meningioma cell invasion, displayed by occasional EMA immunostaining, was observed in the DuraGen^®-derived dura mater. Conclusions: This case indicates that meningioma cells may invade and survive in the DuraGen^®-derived dura mater. Whether or not DuraGen^® is not appropriate as a dural substitute remains unanswered. Further experiences are needed to validate these findings in large sample sizes.

MRI multiparametric scoring system for pial blood supply of intracranial meningiomas

Background

Meningiomas are occasionally fed by pial blood supply (PBS). It is postulated that peritumoral flow void (PTFV), peritumoral brain edema (PTBE), and absence of an arachnoid plane (AP) are useful parameters for evaluating PBS.

Purpose

To determine whether conventional magnetic resonance imaging (MRI) using a multiparametric scoring system (MSS) is a useful way to predict PBS.

Material and Methods

Forty-six patients were included and divided: PBS and non-PBS groups. Differences between the groups in six parameters of MR imaging were analyzed: tumor size, tumor location, PTBE grade, AP grade, PTFV, and MIB1 labeling index (MIB1-LI) grade. Cutoff values were determined using receiver operating characteristic (ROC) curve analysis for the differentiation of both groups based on statistically significant parameters. All cases were scored as 1 (PBS) or 0 (non-PBS) for each parameter according to set thresholds. Individual scores were totaled for each case, yielding a combined score for each case to obtain a cutoff value using ROC curve analysis for the MSS.

Results

Peritumoral brain edema grade, AP grade, PTFV, and MIB-LI grade were statistically associated with PBS. Receiver operating characteristic curve analyses showed that PTBE grade 3 or 4, AP grade 3 or 4, and PTFV positivity had the highest accuracy of 69%, 64%, and 68%, respectively. Regarding the MSS, a cutoff value of 2 had the highest accuracy of 71%; PBS diagnosis was indicated by at least two of the three parameters, namely, PTBE grade, AP grade, and PTFV.

Conclusion

The MSS is a useful way to predict PBS in intracranial meningiomas on MRI.

DNA Methylation Associates With Clinical Courses of Atypical Meningiomas: A Matched Case-Control Study

Background

Accounting for 15–20% of all meningiomas, WHO grade II meningiomas represent an intermediate group regarding risk of tumor recurrence. However, even within this subgroup varying clinical courses are observed with potential occurrence of multiple recurrences. Recently, DNA methylation profiles showed their value for distinguishing biological behaviors in meningiomas. Therefore, aim of this study was to investigate DNA methylation profiles in WHO grade II meningiomas.

Methods

All patients that underwent resection of WHO grade II meningiomas between 1993 and 2015 were screened for a dismal course clinical course with ≥2 recurrences. These were matched to control cases with benign clinical courses without tumor recurrence. DNA methylation was assessed using the Infinium Methylation EPIC BeadChip microarray. Unsupervised hierarchical clustering was performed for identification of DNA methylation profiles associated with such a dismal clinical course.

Results

Overall, 11 patients with WHO grade II meningiomas with ≥2 recurrences (Group dismal) and matched 11 patients without tumor recurrence (Group benign) were identified. DNA methylation profiles revealed 3 clusters—one comprising only patients of group dismal, a second cluster comprising mainly patients from group benign and a third cluster comprising one group dismal and one group benign patient. Based on differential methylation pattern associations with the Wnt and the related cadherin signaling pathway was observed.

Conclusion

DNA methylation clustering showed remarkable differences between two matched subgroups of WHO grade II meningiomas. Thus, DNA methylation profiles may have the potential to support prognostic considerations regarding meningioma recurrence and radiotherapeutic treatment allocation after surgical resection.

Inflammatory Tumor Microenvironment in Cranial Meningiomas: Clinical Implications and Intraindividual Reproducibility

The MIB-1 index was demonstrated to be significantly correlated to meningioma recurrence. However, to date, the relationship of the intraindividual course of the MIB-1 index and the growth fraction, respectively, to clinical tumor recurrence has not been demonstrated in cranial WHO grade 1 and 2 meningiomas. In the present paper, we compare the MIB-1 indices of 16 solely surgically treated primary meningiomas and their recurrent tumors regarding the course of the MIB-1 indices, time to recurrence, reproducibility and factors influencing the intraindividual MIB-1 indices. Regression analyses revealed (1) a strong intra-lab reproducibility (r = 0.88) of the MIB-1 index at the second versus the first operation, corresponding to a constant intrinsic growth activity of an individual meningioma, (2) a significant inverse correlation of both primary (r = −0.51) and secondary (r = −0.70) MIB-1 indices to time to recurrence, and (3) male sex, low plasma fibrinogen and diffuse CD68⁺ macrophage infiltrates contribute to an increase in the MIB-1 index. A strong intraindividual reproducibility of the MIB-1 index and a direct relationship of the MIB-1 index to the time to recurrence were observed. Individual MIB-1 indices might be used for tailored follow-up imaging intervals. Further research on the role of macrophages and inflammatory burden in the regrowth potential of meningiomas are needed.

Proliferative Potential, and Inflammatory Tumor Microenvironment in Meningioma Correlate with Neurological Function at Presentation and Anatomical Location-From Convexity to Skull Base and Spine

Simple Summary

The World Health Organization (WHO) classification grades meningiomas exclusively due to their histopathological features. Meningiomas are predominantly benign intracranial entities, and surgical resection represents the therapy of choice. However, risk of progression and tailored scheduling of follow-up appointments are significantly influenced by various items, such as immunohistochemistry (e.g., MIB-1 index). Emerging evidence focuses attention on the anatomic location of meningiomas, especially regarding the differentiation between skull base and non-skull base meningiomas. In the present study, we therefore investigated demographic, histopathological, and laboratory variables regarding their association with the anatomic location. We found that spinal meningiomas have a significantly lower proliferative activity, less density of macrophage infiltrates, and a longer time to tumor progression. Moreover, increased MIB-1 indices are significantly associated with location-specific baseline symptoms (e.g., convexity: seizure burden, medial skull base: decreased vision, spinal: ambulatory ability). Therefore, anatomic location might be considered as a future subclassification in the grading of the prognosis of meningiomas.

Abstract

Emerging evidence emphasizes the prognostic importance of meningioma location. The present investigation evaluates whether progression-free survival (PFS), proliferative potential, World Health Organization (WHO) grades, and inflammatory burden differ between anatomical locations (skull base, non-skull base, and spinal) meningiomas. Five-hundred-forty-one patients underwent Simpson grade I or II resection for WHO grade 1 or 2 meningiomas. Univariable analysis revealed that spinal meningioma patients are significantly older, had a worse baseline Karnofsky Performance Status (KPS), higher acute-phase protein levels, lower incidence of WHO grade 2, lower mitotic counts, lower MIB-1 index, and less CD68⁺ macrophage infiltrates. Multivariable analysis identified WHO grade 2 (OR: 2.1, 95% CI: 1.1–3.7, p = 0.02) and cranial location (OR: 3.0, 95% CI: 1.8–4.9, p = 0.001) as independent predictors of diffuse CD68⁺ macrophage infiltrates. The mean PFS in cranial meningiomas was 115.9 months (95% CI: 107.5–124.3), compared to 162.2 months (95% CI: 150.5–174.0; log-rank test: p = 0.02) in spinal meningiomas. Multivariable Cox regression analysis revealed cranial location as an independent predictor (HR: 4.7, 95% CI: 1.0–21.3, p = 0.04) of shortened PFS. Increased MIB-1 indices ≥5% were significantly associated with location-specific deficits at presentation, such as decreased vision and seizure burden. Spinal meningiomas have a significantly longer PFS time and differ from the cranial meningiomas regarding MIB-1 index and density of tumor-associated macrophages.

Utilization of Cerebrospinal Fluid Proteome Analysis in the Diagnosis of Meningioma: A Systematic Review

Meningiomas have been classified as the most commonly occurring primary brain tumors. Although the majority of meningiomas are benign and slow-progressing, the tumors that grow to a larger size are associated with various risks during surgical procedures. Early detection of meningiomas is crucial to the treatment as those detected early can be treated through non-invasive methods. Due to their benign nature, meningiomas contain homogeneous protein biomarkers that can be easily identified. Cerebrospinal fluid (CSF) has a high protein composition which can be used to diagnose various brain tumors. Because CSF comes into direct contact with the brain during its functioning, it is one of the factors that makes it an important source of different biomarkers. An analysis of biochemical changes occurring in the CSF can be useful in assessing the condition of the periventricular white matter and the parenchyma.

In this review, PubMed, Medline, PubMed Central, and Google Scholar were used to identify studies discussing meningiomas regarding their assessment, types, diagnosis, and treatment, with more attention directed towards the application of CSF proteome analysis in diagnosis. Priority was given to studies published within the last 15 years. The following keywords were used in the literature search: “cerebrospinal fluid,” “meningiomas,” “brain tumors,” “primary brain tumors,” “protein biomarkers,” “proteome analysis,” and “diagnosis.” Subsequently, the 15 most relevant studies were selected for inclusion in the review. We excluded studies discussing different types of non-brain tumors as well as older articles. The selected studies also underwent a quality appraisal process using corresponding assessment tools. The selected articles were highly informative about meningiomas and the processes of diagnosis and treatment that are currently in use as well as those that are being developed or implemented. The use of CSF proteins in the diagnostic process is also discussed in this review. The studies also describe proteomics as a less invasive procedure that allows for the analysis of entire proteins and the projection of diagnostic images with higher resolutions that aid in the diagnosis.

Combining FORGE Score and Histopathological Diagnostic Criteria of Atypical Meningioma Enables Risk Stratification of Tumor Progression

More than 50% of atypical meningiomas regrow within 5 years after surgery. FORGE score is a newly created tool to estimate the MIB-1 index in cranial meningiomas. In this investigation, we aimed to assess the predictive value of the FORGE score in combination with major diagnostic criteria of atypical meningioma (brain invasion, mitotic count ≥ 4) regarding recurrence in atypical meningiomas. We included patients operated on primary atypical meningiomas in our center from 2011 to 2019. The study included 71 patients (58% women, median age 63 years). ROC curves revealed a superiority of FORGE score combined with histopathological diagnostic criteria of atypical meningioma (AT-FORGE) in the prediction of tumor progression compared to FORGE score only (AUC: 0.72; 95% CI: 0.54–0.91, cut-off: ≥5/<5, sensitivity: 75%, specificity: 78%). Patients with an AT-FORGE score ≥ 5 had a shorter time to tumor progression (32.8 vs. 71.4 months, p < 0.001) in the univariable analysis. Multivariable cox regression analysis revealed significant predictive value of Simpson grade > II, presence of multiple meningiomas and AT-FORGE score ≥ 5 for tumor progression. The combination of histopathological diagnostic criteria for atypical meningioma with FORGE score might facilitate an effective identification of patients with an atypical meningioma who have an increased risk of tumor progression.

A Clinical Prognostic Model Based on Preoperative Hematological and Clinical Parameters Predicts the Progression of Primary WHO Grade II Meningioma

Purpose

The purpose was to explore the correlation between hematological parameters and the progression of WHO grade II meningioma, and establish a clinical prognostic model based on hematological parameters and clinical prognostic factors to predict the progression-free survival (PFS) of patients.

Methods

A total of 274 patients with WHO grade II meningiomas were included. Patients were randomly divided into a training cohort (192, 70%) and a test cohort (82, 30%). In the training cohort, the least absolute shrinkage and selection operator Cox regression analysis were used to screen for hematological parameters with prognostic value, and the hematological risk model (HRM) was constructed based on these parameters; univariate and multivariate Cox regression analyses were utilized to screen for clinical prognostic factors, and a clinical prognostic model was constructed based on clinical prognostic factors and HRM. The prognostic stability and accuracy of the HRM and clinical prognostic model were verified in the test cohort. Subgroup analysis was performed according to the patients' different clinical characteristics.

Results

Preoperative neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, albumin-to-globulin ratio, D-dimer, fibrinogen, and lactate dehydrogenase were associated with the PFS of patients. The areas under curve of the HRM were 0.773 (95% confidence interval [CI] 0.707-0.839) and 0.745 (95% CI 0.637-0.852) in the training cohort and test cohort, respectively. The progression risk was higher in the high-risk group than that in the low-risk group categorized by the optimal cutoff value (2.05) of hematological risk scores. The HRM, age, tumor location, tumor size, peritumoral edema, extent of resection, Ki-67 index, and postoperative radiotherapy were the prognostic factors for the progression of meningiomas. The corrected C-index of the clinical prognosis model was 0.79 in the training cohort. Clinical decision analysis showed that the clinical prognostic model could be used to obtain favorable clinical benefits. In the subgroup analysis, the HRM displayed excellent prognostic stability and general applicability in different subgroups.

Conclusions

Preoperative hematological parameters are associated with the postoperative progression of WHO grade II meningiomas. The clinical prognosis model constructed based on hematological parameters and clinical prognostic factors has favorable predictive accuracy and clinical benefits.

Machine Learning Using Multiparametric Magnetic Resonance Imaging Radiomic Feature Analysis to Predict Ki-67 in World Health Organization Grade I Meningiomas

BACKGROUND

Although World Health Organization (WHO) grade I meningiomas are considered "benign" tumors, an elevated Ki-67 is one crucial factor that has been shown to influence tumor behavior and clinical outcomes. The ability to preoperatively discern Ki-67 would confer the ability to guide surgical strategy.

OBJECTIVE

In this study, we develop a machine learning (ML) algorithm using radiomic feature analysis to predict Ki-67 in WHO grade I meningiomas.

METHODS

A retrospective analysis was performed for a cohort of 306 patients who underwent surgical resection of WHO grade I meningiomas. Preoperative magnetic resonance imaging was used to perform radiomic feature extraction followed by ML modeling using least absolute shrinkage and selection operator wrapped with support vector machine through nested cross-validation on a discovery cohort (n = 230), to stratify tumors based on Ki-67 <5% and ≥5%. The final model was independently tested on a replication cohort (n = 76).

RESULTS

An area under the receiver operating curve (AUC) of 0.84 (95% CI: 0.78-0.90) with a sensitivity of 84.1% and specificity of 73.3% was achieved in the discovery cohort. When this model was applied to the replication cohort, a similar high performance was achieved, with an AUC of 0.83 (95% CI: 0.73-0.94), sensitivity and specificity of 82.6% and 85.5%, respectively. The model demonstrated similar efficacy when applied to skull base and nonskull base tumors.

CONCLUSION

Our proposed radiomic feature analysis can be used to stratify WHO grade I meningiomas based on Ki-67 with excellent accuracy and can be applied to skull base and nonskull base tumors with similar performance achieved.

Pathologic Characteristics of Pregnancy-Related Meningiomas

Simple Summary

Meningiomas are the most common primary intracranial tumor in adults. Meningiomas are usually benign and slow growing. Treatment is surgical resection in the case of symptomatic growth. Dramatic growth can occur during pregnancy, complicating clinical management and entailing a risk to the well-being of the mother and fetus. Authors of a previous review paper raised the hypothesis that prolactin may be a key contributor to the sudden growth seen in pregnancy-related meningiomas. We set out to investigate the presence of prolactin receptors/prolactin, as well as other female hormones and histopathological characteristics of pregnancy-related meningiomas in Denmark, compared to meningiomas from female controls within the same age group. No differences in hormone receptor distribution were found between the groups and very few meningiomas expressed prolactin receptors, which contradicts the above-mentioned hypothesis. Interestingly, we observed above cut-point proliferative indices of the meningiomas for the entire study population of females in the reproductive age.

Abstract

Meningiomas are the most common intracranial tumor. During pregnancy, explosive growth of a known meningioma occasionally occurs, but the underlying reasons remain unknown. Prolactin has been suggested as a possible key contributor to pregnancy-related meningioma growth. This study sets out to investigate prolactin and prolactin receptor status in 29 patients with pregnancy-related meningiomas in Denmark, from January 1972 to December 2016, as compared to 68 controls aged 20–45 years, also undergoing resection of a meningioma. Furthermore, we investigated potential differences in the progesterone and estrogen receptor statuses, WHO grade, Ki-67 labeling indices, and locations of the resected meningiomas between the cases and controls. Immunohistochemical analyses were performed, and histopathology and intracranial location were assessed with the investigator blinded for the case–control status. None of the samples stained positive for prolactin and very few samples stained positive for prolactin receptors, equally distributed among cases and controls. Estrogen and progesterone receptors generally followed the same distributional pattern between groups, whereas above cut-point Ki-67 labeling indices for both groups were observed. In conclusion, our results did not support the notion of prolactin as a key contributor to pregnancy-related meningioma growth. Rather, the similarities between the cases and controls suggest that meningiomas early in life may comprise a distinct biological entity.

FORGE: A Novel Scoring System to Predict the MIB-1 Labeling Index in Intracranial Meningiomas

Simple Summary

Meningiomas are predominantly benign intracranial tumors, and surgical therapy represents the treatment of choice. However, the risk of recurrence and scheduling of follow-up intervals are significantly influenced by immunohistochemical items such as the MIB-1 labeling index. To date, it is not possible to integrate this essential information into the pre- or intraoperative surgical decision making. In the present study, we therefore analyzed baseline variables associated with the MIB-1 labeling index. We found four easily identifiable and routinely recorded risk factors for an increased MIB-1 index and developed a simple and quick-to-use score that allows us to estimate the risk of an elevated MIB-1 index prior to the surgical resection. Furthermore, this score seems to predict the progression-free survival in intracranial meningiomas. We believe that this score might us to more reliably guide patients in preoperative surgical strategy planning and postoperative follow-up scheduling.

Abstract

The MIB-1 index is an essential predictor of progression-free-survival (PFS) in meningioma. To date, the MIB-1 index is not available in preoperative treatment planning. A preoperative score estimating the MIB-1 index in patients with intracranial meningiomas has not been investigated so far. Between 2013 and 2019, 208 patients with tumor morphology data, MIB-1 index data, and plasma fibrinogen and serum C-reactive protein (CRP) data underwent surgery for intracranial WHO grade I and II meningioma. An optimal MIB-1 index cut-off value (≥6/<6) in the prediction of recurrence was determined by ROC curve analysis (AUC: 0.71; 95% CI: 0.55–0.87). A high MIB-1 index (≥6%) was present in 50 cases (24.0%) and was significantly associated with male sex, peritumoral edema, low baseline CRP, and low fibrinogen level in the multivariate analysis. A scoring system (“FORGE”) based on sex, peritumoral edema, preoperative CRP value, and plasma fibrinogen level supports prediction of the MIB-1 index (sensitivity 62%, specificity 79%). The MIB-1 labeling index and the FORGE score are significantly associated with an increased risk of poor PFS time. We suggest a novel score (“FORGE”) to preoperatively estimate the risk of an increased MIB-1 index (≥6%), which might help in surgical decision making and follow-up interval determination and inform future trials investigating inflammatory burden and proliferative activity.

Biomarkers for differentiating grade II meningiomas from grade I: a systematic review

INTRODUCTION

There are a number of prognostic markers (methylation, CDKN2A/B) described to be useful for the stratification of meningiomas. However, there are currently no clinically validated biomarkers for the preoperative prediction of meningioma grade, which is determined by the histological analysis of tissue obtained from surgery. Accurate preoperative biomarkers would inform the pre-surgical assessment of these tumours, their grade and prognosis and refine the decision-making process for treatment. This review is focused on the more controversial grade II tumours, where debate still surrounds the need for adjuvant therapy, repeat surgery and frequency of follow up.

METHODS

We evaluated current literature for potential grade II meningioma clinical biomarkers, focusing on radiological, biochemical (blood assays) and immunohistochemical markers for diagnosis and prognosis, and how they can be used to differentiate them from grade I meningiomas using the post-2016 WHO classification. To do this, we conducted a PUBMED, SCOPUS, OVID SP, SciELO, and INFORMA search using the keywords; 'biomarker', 'diagnosis', 'atypical', 'meningioma', 'prognosis', 'grade I', 'grade 1', 'grade II' and 'grade 2'.

RESULTS

We identified 1779 papers, 20 of which were eligible for systematic review according to the defined inclusion and exclusion criteria. From the review, we identified radiological characteristics (irregular tumour shape, tumour growth rate faster than 3cm³/year, high peri-tumoural blood flow), blood markers (low serum TIMP1/2, high serum HER2, high plasma Fibulin-2) and histological markers (low H3K27me3, low SMARCE1, low AKAP12, high ARIDB4) that may aid in differentiating grade II from grade I meningiomas.

CONCLUSION

Being able to predict meningioma grade at presentation using the radiological and blood markers described may influence management as the likely grade II tumours will be followed up or treated more aggressively, while the histological markers may prognosticate progression or post-treatment recurrence. This to an extent offers a more personalised treatment approach for patients.

Single-Session Stereotactic Radiosurgery for Large Benign Meningiomas: Medium-to Long-Term Results

BACKGROUND

The use of stereotactic radiosurgery for the treatment of intracranial meningiomas has been established as an effective and safe treatment modality. Larger meningiomas typically are managed by surgery followed by radiosurgery. Treatment of large meningiomas (usually defined as >10 cc) by stereotactic radiosurgery has been investigated in some recent reports, either by single-session, volume-staged, or the hypofractionation technique. We sought to assess the long-term efficacy and safety of single-session stereotactic radiosurgery for large (10 cc or more) intracranial benign meningiomas.

PATIENTS AND METHODS

In this retrospective study, we included 273 patients with large benign meningiomas (≥10 cc) who were treated by single-session SRS and followed up for more than 2 years. Tumors were in a basal location in 228 patients (84%). There were 161 tumors (59%) in the perioptic location. The median tumor volume was 15.5 (10-57.3 cc [interquartile range {IQR} 12.3 cc]). The median prescription dose was 12 Gy (9-15 Gy [IQR 1 Gy]).

RESULTS

The median follow-up period was 6.1 years (2-18 years [IQR 5.5 years]). The tumor control rate was 90%. The progression-free survival at 5 and 10 years was 96% and 81%, respectively, for the whole cohort. Among 161 patients with perioptic meningiomas, favorable (better/stable) visual outcome was reported in 155 patients (96%) and unfavorable (worse) outcome in 6 patients (4%). Temporary adverse radiation effects were observed in 41 patients (15%) but only 16 (6%) were symptomatic.

CONCLUSIONS

Stereotactic radiosurgery provides an effective and safe treatment option for large meningiomas.