Atypical Meningiomas: Histologic and Clinical Factors Associated With Recurrence

Progression/Recurrence of Meningioma: An Imaging Review Based on Magnetic Resonance Imaging

Meningiomas are the most common primary central nervous system tumors. The preferred treatment is maximum safe resection, and the heterogeneity of meningiomas results in a variable prognosis. Progression/recurrence (P/R) can occur at any grade of meningioma and is a common adverse outcome after surgical treatment and a major cause of postoperative rehospitalization, secondary surgery, and mortality. Early prediction of P/R plays an important role in postoperative management, further adjuvant therapy, and follow-up of patients. Therefore, it is essential to thoroughly analyze the heterogeneity of meningiomas and predict postoperative P/R with the aid of noninvasive preoperative imaging. In recent years, the development of advanced magnetic resonance imaging technology and machine learning has provided new insights into noninvasive preoperative prediction of meningioma P/R, which helps to achieve accurate prediction of meningioma P/R. This narrative review summarizes the current research on conventional magnetic resonance imaging, functional magnetic resonance imaging, and machine learning in predicting meningioma P/R. We further explore the significance of tumor microenvironment in meningioma P/R, linking imaging features with tumor microenvironment to comprehensively reveal tumor heterogeneity and provide new ideas for future research.

External auditory canal ectopic atypical meningioma: A case report and brief literature review

Meningiomas are tumours typically derived from the meningothelial cells of the arachnoid mater. They most often arise in intracranial, intraspinal, or orbital locations. Ectopic meningiomas, described as primary meningiomas with no intracranial involvement, are definitely unconventional. In fact, most of the extracranial meningiomas described in the literature, particularly in the outer ear, are effectively spreads of disease with primary intracranial localization. We describe a case of a primary external auditory canal meningioma with demonstrated absence of intracranial involvement, and we provide a full radiological, histological, immunohistochemical and molecular characterization of the lesion.

The Performance of Different Machine Learning Algorithm and Regression Models in Predicting High-Grade Intracranial Meningioma

Meningioma is the most common primary tumor of the central nervous system (CNS). Individualized treatment strategies should be formulated for the patients according to the WHO (World Health Organization) grade. Our aim was to investigate the effectiveness of various machine learning and traditional statistical models in predicting the WHO grade of preoperative patients with meningioma. Patients diagnosed with meningioma after surgery in West China Hospital and Shangjin Hospital of Sichuan University from 2009 to 2016 were included in the study cohort. As the training cohort (n = 1975), independent risk factors associated with high-grade meningioma were used to establish the Nomogram model. which was validated in a subsequent cohort (n = 1048) from 2017 to 2019 in our hospital. Logistic regression (LR), XGboost, Adaboost, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF) models were determined using F1 score, recall, accuracy, the area under the curve (ROC), calibration plot and decision curve analysis (DCA) were used to evaluate the different models. Logistic regression showed better predictive performance and interpretability than machine learning. Gender, recurrence history, T1 signal intensity, enhanced signal degree, peritumoral edema, tumor diameter, cystic, location, and NLR index were identified as independent risk factors and added to the nomogram. The AUC (Area Under Curve) value of RF was 0.812 in the training set, 0.807 in the internal validation set, and 0.842 in the external validation set. The calibration curve and DCA (Decision Curve Analysis) indicated that it had better prediction efficiency of LR than others. The Nomogram preoperative prediction model of meningioma of WHO II and III grades showed effective prediction ability. While machine learning exhibits strong fitting ability, it performs poorly in the validation set.

An interpretable radiomics model to select patients for radiotherapy after surgery for WHO grade 2 meningiomas

Objectives

This study investigated whether radiomic features can improve the prediction accuracy for tumor recurrence over clinicopathological features and if these features can be used to identify high-risk patients requiring adjuvant radiotherapy (ART) in WHO grade 2 meningiomas.

Methods

Preoperative magnetic resonance imaging (MRI) of 155 grade 2 meningioma patients with a median follow-up of 63.8 months were included and allocated to training (n = 92) and test sets (n = 63). After radiomic feature extraction (n = 200), least absolute shrinkage and selection operator feature selection with logistic regression classifier was performed to develop two models: (1) a clinicopathological model and (2) a combined clinicopathological and radiomic model. The probability of recurrence using the combined model was analyzed to identify candidates for ART.

Results

The combined clinicopathological and radiomics model exhibited superior performance for the prediction of recurrence compared with the clinicopathological model in the training set (area under the curve [AUC] 0.78 vs. 0.67, P = 0.042), which was also validated in the test set (AUC 0.77 vs. 0.61, P = 0.192). In patients with a high probability of recurrence by the combined model, the 5-year progression-free survival was significantly improved with ART (92% vs. 57%, P = 0.024), and the median time to recurrence was longer (54 vs. 17 months after surgery).

Conclusions

Radiomics significantly contributes added value in predicting recurrence when integrated with the clinicopathological features in patients with grade 2 meningiomas. Furthermore, the combined model can be applied to identify high-risk patients who require ART.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02090-7.

Somatostatin Receptor Theranostics for Refractory Meningiomas

Somatostatin receptor (SSTR)-targeted peptide receptor radionuclide therapy (PRRT) represents a promising approach for treatment-refractory meningiomas progressing after surgery and radiotherapy. The aim of this study was to provide outcomes of patients harboring refractory meningiomas treated by 177Lu-DOTATATE and an overall analysis of progression-free survival at 6 months (PFS-6) of the same relevant studies in the literature. Eight patients with recurrent and progressive WHO grade II meningiomas were treated after multimodal pretreatment with 177Lu-DOTATATE between 2019 and 2022. Primary and secondarily endpoints were progression-free survival at 6-months (PFS-6) and toxicity, respectively. PFS-6 analysis of our case series was compared with other similar relevant studies that included 86 patients treated with either 177Lu-DOTATATE or 90Y-DOTATOC. Our retrospective study showed a PFS-6 of 85.7% for WHO grade II progressive refractory meningiomas. Treatment was clinically and biologically well tolerated. The overall analysis of the previous relevant studies showed a PFS-6 of 89.7% for WHO grade I meningiomas (n = 29); 57.1% for WHO grade II (n = 21); and 0 % for WHO grade III (n = 12). For all grades (n = 86), including unknown grades, PFS-6 was 58.1%. SSTR-targeted PRRT allowed us to achieve prolonged PFS-6 in patients with WHO grade I and II progressive refractory meningiomas, except the most aggressive WHO grade II tumors. Large scale randomized trials are warranted for the better integration of PRRT in the treatment of refractory meningioma into clinical practice guidelines.

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.

Diagnostic nomogram model for predicting preoperative pathological grade of meningioma

Background

Meningioma is the most common primary tumor of the central nervous system. Preoperative diagnosis of high-grade meningioma is helpful for the selection of treatment options. The aim of our study is to establish a diagnostic nomogram model for preoperative prediction of the pathological grade of meningioma.

Methods

The predictive model was established from a cohort of 215 clinicopathologically confirmed meningioma between January 2012 and December 2017. Radiomic features were collected from preoperative magnetic resonance imaging (MRI) and computed tomography of patients with meningioma. The least absolute shrinkage and selection operator (LASSO) regression model was used for data dimension reduction and feature selection. Multivariate logistic regression was used to build a predictive model and presented as a nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Internal validation was evaluated using bootstrapping validation.

Results

High-grade meningioma was observed in 47 patients (22%). The predictors included in the nomogram were tumor-brain interface, bone invasion, and tumor location. The final diagnostic model exhibited good calibration and discrimination with a C-index of 0.874 (95% confidence interval: 0.818–0.929) and a higher C-index of 0.868 in internal validation. Decision curve analysis (DCA) indicated that the nomogram is very useful in clinical practice.

Conclusions

This study provides a nomogram model with tumor-brain interface, bone invasion, and tumor location that can effectively predict the preoperative pathological grading of patients with meningioma and thus help clinicians provide more reasonable treatment strategies for meningioma patients.

Lateral Ventricular Meningiomas: Clinical Features, Radiological Findings and Long-Term Outcomes

Purpose

Lateral ventricle meningioma (LVM) is a rare type of intracranial meningioma, which has been rarely studied. It has different clinical features, imaging features, and long-term results from other locations. This study investigated the epidemiology, clinical characteristics and prognosis of LVM and comprehensively describes its characteristics.

Methods

This article analyzes the LVMs that were diagnosed pathologically in West China hospital between January 1, 2009 and July 1 2020. Demographic information, imaging characteristics and prognostic factors are discussed. Data analysis was performed using SPSS 23.0 and R version 3.5.3.

Results

We collected 7202 meningiomas and 195 LVMs (136 females; median age, 46 years; range, 5–81 years) were included in this study. Gross total resection was completed in 189 patients. The OS rate was 93.8%, and the recurrence rate was 5.2%. Multivariate regression analysis showed that sex (P = 0.01) and tumor size (P = 0.018) were related to WHO grade. Postoperative KPS (P = 0.003) was associated with OS. WHO grade (P = 0.025), extent of tumor resection (P < 0.001), and hospital day (P=0.028) were associated with recurrence.

Conclusion

LVMs require long-term follow-up, individualized treatment, and follow-up strategies to be formulated according to the relevant risk factors.

The 2016 Edition of the WHO Classification of Primary Brain Tumors: Applicable to Assess Individual Risk of Recurrence in Atypical Meningioma? A Single-Center Experience

BACKGROUND AND STUDY AIMS/OBJECT

 Despite the relevance of molecular criteria for brain tumor diagnosis and prognosis, meningioma grading is still solely based on histologic features. Atypical meningiomas (AMs; WHO grade II) display a great histologic heterogeneity and individual courses of disease can differ significantly. This study aimed to identify clinically aggressive AMs that are prone to early recurrence after gross total resection (GTR) by assessing a specific histologic score.

PATIENTS AND METHODS

 A retrospective analysis of 28 consecutive patients (17 females and 11 males; mean age of 62 years [range: 35-88 years]) treated in our institution between January 2006 and December 2015 was performed. Basic demographic and clinical characteristics were assessed. A scoring scale was designed to address the histologic diversity by summing up the individual histologic features in every tumor sample. According to that, points were awarded as follows: major AM defining criterion (3 points) and minor criterion (1 point).

RESULTS

 The subclassification based on our specific histologic score revealed no significant difference in frequency of one (46.4%) or two (42.9%) AM defining features; three criteria were less frequently seen (10.7%). Mean follow-up was 61.89 ± 9.03 months. Local recurrence occurred in 35.7% after a mean time of 37.4 ± 22.6 months after primary surgery. Age > 60 years was significantly associated with a shorter progression-free survival (PFS). There was a trend toward shorter PFS with increasing scores, tantamount with the presence of several AM defining histologic criteria in one sample. No tumor relapse was seen when diagnosis was based only on minor criteria.

CONCLUSION

 AMs display a histologic diversity. There is a trend toward shorter PFS with increasing numbers of AM defining histologic features. The inclusion of this score in the decision algorithm regarding further treatment for patients >60 years after GTR might be helpful and should be evaluated in further studies.

Adjuvant radiotherapy versus observation following gross total resection for atypical meningioma: a systematic review and meta-analysis

Background

The impact of adjuvant radiotherapy (RT) on atypical meningioma (AM) underwent a gross total resection (GTR) remains unclear, showing conflicting results from various studies. The objective of this study was to perform an updated meta-analysis for observational studies to determine the effect of adjuvant RT after GTR on local recurrence and survival outcomes compared to observation after GTR.

Methods

PubMed, Embase, and Web of Science were searched to identify comparative studies that reported outcomes of adjuvant RT versus observation for AM patients after GTR. Local recurrence rate, progression-free survival (PFS), overall survival (OS), and toxicities related to RT were considered as outcomes of interest. Differences between two cohorts were estimated by calculating odds ratios (OR) for LR rate and hazard ratios (HR) for survival outcomes with 95% confidence intervals (CIs) for meta-analysis, using R version 4.0.3 software. Included studies were appraised with the Risk of Bias Assessment tool for Non-Randomized Studies. Outcome ratios were combined with the Mantel–Haenszel method and the inverse variance-weighted method, appropriately.

Results

Data from 30 studies involving 2904 patients (adjuvant RT: n = 737; observation: n = 2167) were eventually included. Significant reduction of local recurrence rate was seen in the adjuvant RT cohort compare to that in the observation cohort (OR 0.50; 95% CI 0.36–0.68; p < 0.0001). Pooled HRs of PFS at 1-year, 3-year, 5-year, and > 5-year revealed that adjuvant RT was superior to observation. There was no significant difference in OS between the two cohorts during any period. Most toxicities were tolerable with grade 1 or 2. There was no documented grade 5 toxicity.

Conclusions

For AM patients who underwent GTR, evidence suggested that adjuvant RT could potentially decrease local recurrence and improve PFS better than observation.

Extent of resection and survival outcomes in World Health Organization grade II meningiomas

PURPOSE

WHO grade II meningiomas behave aggressively, with recurrence rates as high as 60%. Although complete resection in low-grade meningiomas is associated with a relatively low recurrence rate, the impact of complete resection for WHO grade II meningiomas is less clear. We studied the association of extent of resection with overall and progression-free survivals in patients with WHO grade II meningiomas.

METHODS

A retrospective database review was performed to identify all patients who underwent surgical resection for intracranial WHO grade II meningiomas at our institution between 1995 and 2019. Kaplan-Meier analysis was used to compare overall and progression-free survivals between patients who underwent gross total resection (GTR) and those who underwent subtotal resection (STR). Multivariable Cox proportional-hazards analysis was used to identify independent predictors of tumor recurrence and mortality.

RESULTS

Of 214 patients who underwent surgical resection for WHO grade II meningiomas (median follow-up 53.4 months), 158 had GTR and 56 had STR. In Kaplan-Meier analysis, patients who underwent GTR had significantly longer progression-free (p = 0.002) and overall (p = 0.006) survivals than those who underwent STR. In multivariable Cox proportional-hazards analysis, GTR independently predicted prolonged progression-free (HR 0.57, p = 0.038) and overall (HR 0.44, p = 0.017) survivals when controlling for age, tumor location, and adjuvant radiation.

CONCLUSIONS

Extent of resection independently predicts progression-free and overall survivals in patients with WHO grade II meningiomas. In an era of increasing support for adjuvant treatment modalities in the management of meningiomas, our data support maximal safe resection as the primary goal in treatment of these patients.

Surgical Treatment and Predictive Factors for Atypical Meningiomas: A Multicentric Experience

BACKGROUND

Atypical meningiomas are characterized by a high rate of recurrence and shorter overall survival (OS) compared with grade I meningioma. Predictive parameters for OS and recurrence-free survival (RFS) are controversial.

METHODS

Patient age, sex, preoperative symptoms, tumor localization, size, Simpson grade, postoperative complications, extent of resection, number of mitoses, MIB1 proliferation index, brain invasion, postoperative radiotherapy, and clinical outcome (Karnofsky performance scale [KPS] postoperatively and at long-term follow-up) were evaluated. Data regarding recurrence rate, mortality, OS, and RFS at 1-, 3-, and 5-year follow-up were also collected. Median follow-up was 76 months; all patients had at least 3 years of follow-up.

RESULTS

Between 2007 and 2017, 73 patients underwent surgery for atypical meningiomas (World Health Organization grade II) at 2 centers. Preoperative KPS score >80 as well as 1-month, 6-month, and 1-year follow-up KPS scores were related to better OS. Postoperative complications did not modify OS and RFS. Gross total removal (Simpson grade I, II) was achieved in 80.8% of patients. RFS was statistically influenced by extent of resection (P = 0.002). MIB1 proliferation index >8 was a negative predictive factor for recurrence at univariate and multivariate analysis (P = 0.001 and P = 0.021). Radiotherapy was statistically related to a worse outcome. The incidence of recurrence was 38%. RFS was 98.6% at 1-year follow-up, 81.1% at 3 years, and 57.5% at 5 years. All patients were alive at 1-year follow-up. OS was 90.5% at 3-year follow-up and 78.8% at 5-year follow-up.

CONCLUSIONS

Despite some limitations, our study demonstrates that aggressive surgical treatment achieving a gross total removal is a positive predictive parameter for RFS as well as a good clinical outcome (KPS score >80) and is related to a longer OS.

Factors Related to the Post-operative Recurrence of Atypical Meningiomas

Aim: This study aimed to investigate the relationship between clinicopathological characteristics of atypical meningiomas (AM) and its post-operative recurrence.

Materials and Methods: The clinicopathological characteristics and findings from follow up were retrospectively reviewed and compared between AM and benign meningioma (BM) patients. Univariate and multivariate analyses were employed to identify the factors related to the post-operative recurrence of AM.

Results: More BM patients were females and received complete resection; the recurrence rate was significantly lower in BM patients as compared to AM patients. The progesterone receptor (PR), E-cadherin protein (E-Ca) and β-catenin positive rates and Ki67 labeling index were significantly different between two groups. Univariate analysis showed the age, tumor size, tumor invasiveness, E-Ca expression, and extent of resection were related to the post-operative recurrence of AM. However, multivariate analysis showed only the extent of resection and tumor invasiveness were the independent factors associated with the post-operative recurrence of AM.

Conclusions: The extent of resection and tumor invasiveness are related to the post-operative recurrence of AM. To improve the surgical procedures to maximize the tumor resection is important to improve the prognosis of AM patients.