Non-operative meningiomas: long-term follow-up of 136 patients

Evaluation of four tumour growth models to describe the natural history of meningiomas

BACKGROUND

The incidence of newly diagnosed meningiomas, particularly those diagnosed incidentally, is continually increasing. The indication for treatment is empirical because, despite numerous studies, the natural history of these tumours remains difficult to describe and predict.

METHODS

This retrospective single-centre study included 294 consecutive patients with 333 meningiomas who underwent three or more brain imaging scans. Linear, exponential, power, and Gompertz models were constructed to derive volume-time curves, by using a mixed-effect approach. The most accurate model was used to analyse tumour growth and predictors of rapid growth.

FINDINGS

The Gompertz model provided the best results. Hierarchical clustering at the time of diagnosis and at the end of follow-up revealed at least three distinct groups, which can be described as pseudoexponential, linear, and slowing growth with respect to their parameters. Younger patients and smaller tumours were more frequent in the pseudo-exponential clusters. We found that the more "aggressive" the cluster, the higher the proportion of patients with grade II meningiomas and who have had a cranial radiotherapy. Over a mean observation period of 56.5 months, 21% of the tumours moved to a cluster with a lower growth rate, consistent with the Gompertz's law.

INTERPRETATION

Meningiomas exhibit multiple growth phases, as described by the Gompertz model. The management of meningiomas should be discussed according to the growth phase, comorbidities, tumour location, size, and growth rate. Further research is needed to evaluate the associations between radiomics features and the growth phases of meningiomas.

FUNDING

No funding.

Incidental Meningiomas: Potential Predictors of Growth and Current State of Management

The rise in availability of neuroimaging has led to an increase in incidentally discovered meningiomas. These tumors are typically asymptomatic and tend to display slow growth. Treatment options include observation with serial monitoring, radiation, and surgery. Although optimal management is unclear, clinicians recommend a conservative approach, which preserves quality of life and limits unnecessary intervention. Several risk factors have been investigated for their potential utility in the development of prognostic models for risk assessment. Herein, the authors review the current literature on incidental meningiomas, focusing their discussion on potential predictive factors for tumor growth and appropriate management practices.

Stereotactic Radiosurgery for Intracranial Meningiomas

Meningiomas are thought to originate from the meningothelial cells of the arachnoid mater and are the most common primary brain tumor in adults. Histologically confirmed meningiomas occur with an incidence of 9.12/100,000 population and account for 39% of all primary brain tumors and 54.5% of all non-malignant brain tumors. Risk factors for meningioma include age 65 years and older, female gender, African-American race, history of exposure to head and neck ionizing radiation, and certain genetic disorders such as neurofibromatosis II. Intracranial meningiomas are the most commonly benign, WHO Grade I neoplasms. Atypical and anaplastic are considered malignant lesions.

Growth dynamics of incidental meningiomas: A prospective long-term follow-up study

Background

There is no consensus on the management of incidental meningiomas. The literature on long-term growth dynamics is sparse and the natural history of these tumors remains to be illuminated.

Methods

We prospectively assessed long-term tumor growth dynamics and survival rates during active monitoring of 62 patients (45 female, mean age 63.9 years) harboring 68 tumors. Clinical and radiological data were obtained every 6 months for 2 years, annually until 5 years, then every second year.

Results

The natural progression of incidental meningiomas during 12 years of monitoring was growth (P < .001). However, mean growth decelerated at 1.5 years and became insignificant after 8 years. Self-limiting growth patterns were seen in 43 (63.2%) tumors, non-decelerating in 20 (29.4%) and 5 (7.4%) were inconclusive due to  ≤ 2 measurements. Decelerating growth persisted once established. Within 5 years, 38 (97.4%) of 39 interventions were initiated. None developed symptoms prior to intervention. Large tumors (P < .001) involving venous sinuses (P = .039) grew most aggressively. Since inclusion 19 (30.6%) patients have died of unrelated causes and 2 (3%) from grade 2 meningiomas.

Conclusion

Active monitoring seems a safe and appropriate first-line management of incidental meningiomas. Intervention was avoided in  > 40% with indolent tumors in this cohort. Treatment was not compromised by tumor growth. Clinical follow-up seems sufficient beyond 5 years if self-limiting growth is established. Steady or accelerating growth warrant monitoring until they reach a stable state or intervention is initiated.

Treatment Strategies and Current Results of Petroclival Meningiomas

Petroclival meningiomas (PCMs) are complex skull-base tumors that continue to pose a formidable surgical challenge to neurosurgeons because of their deep-seated location/intimate relationship with the brainstem and neurovascular structures. The advent of stereotactic radiosurgery (SRS), along with the shifting of management goals from complete radiological cure to maximal preservation of the patient's quality of life (QOL), has further cluttered the topic of "optimal management" in PCMs. Not all patients with PCM need treatment ("watchful waiting"). However, many who reach the neurosurgeons with a symptomatic disease need surgery. The goal of the surgery in PCMs is a GTR, yet this can be achieved in only less than half of the patients with acceptable morbidity. The remainder of the patients are better treated by STR followed by SRS for residual tumor control or close follow-up. A small subset of patients with PCM may be best treated by primary SRS. In this chapter, we have tried to summarize the scientific evidence pertaining to the management of PCMs (including the senior author's series), particularly those regarding the available treatment strategies and current outcomes, and discuss the decision-making process to formulate an "optimal management" plan for individual PCMs.

Growth risk classification and typical growth speed of convexity, parasagittal, and falx meningiomas: a retrospective cohort study

OBJECTIVE

Meningiomas are the most common primary intracranial tumors, and their clinical and biological characteristics vary by location. Convexity, parasagittal, and falx meningiomas account for approximately 50%-65% of intracranial meningiomas. Focusing only on these locations, the aim of this study was to determine the typical speed of tumor growth, to assess the growth risk, and to show the possible tumor volume that many lesions can reach after 5 years.

METHODS

Patients with radiologically suspected convexity, parasagittal, or falx meningiomas at the authors' institution were studied retrospectively. The relative growth rate (RGR) and annual volume change (AVC) were calculated from MRI at more than 3-month intervals. Based on sex, age, and signal intensity on T2-weighted MRI, the cases were classified into three groups: extremely high-growth, high-growth, and low-growth groups.

RESULTS

The data of 313 cases were analyzed. The median RGR and AVC for this entire cohort were 6.1% (interquartile range [IQR] 2.4%-16.0%) and 0.20 (IQR 0.04-1.18) cm3/year, respectively. There were significant differences in sex (p = 0.018) and T2-weighted MRI signal intensity (p < 0.001) for RGR, and T2-weighted MRI signal intensity (p < 0.001), tumor location (p = 0.025), and initial tumor volume (p < 0.001) for AVC. The median RGR and AVC were 17.5% (IQR 8.3%-44.1%) and 1.05 (IQR 0.18-3.53) cm3/year, 8.2% (IQR 2.9%-18.6%) and 0.33 (IQR 0.06-1.66) cm3/year, and 3.4% (IQR 1.2%-5.8%) and 0.04 (IQR 0.02-0.21) cm3/year for the extremely high-growth, high-growth, and low-growth groups, respectively, with a significant difference among the groups (p < 0.001). A 2.24-times, or 5.24 cm3, increase in tumor volume over 5 years was typical in the extremely high-growth group, whereas the low-growth group showed little change in tumor volume even over a 5-year follow-up period.

CONCLUSIONS

For the first time, the typical speed of tumor growth was calculated, focusing only on patients with convexity, parasagittal, and falx meningiomas. In addition, the possible tumor volume that many lesions in these locations can reach after 5 years was shown based on objective indicators. These results may allow clinicians to easily detect lesions that require frequent follow-up or early treatment by determining whether they deviate from the typical range of the growth rate, similar to a growth chart for children.

Deep neural networks allow expert-level brain meningioma segmentation and present potential for improvement of clinical practice

Accurate brain meningioma segmentation and volumetric assessment are critical for serial patient follow-up, surgical planning and monitoring response to treatment. Current gold standard of manual labeling is a time-consuming process, subject to inter-user variability. Fully-automated algorithms for meningioma segmentation have the potential to bring volumetric analysis into clinical and research workflows by increasing accuracy and efficiency, reducing inter-user variability and saving time. Previous research has focused solely on segmentation tasks without assessment of impact and usability of deep learning solutions in clinical practice. Herein, we demonstrate a three-dimensional convolutional neural network (3D-CNN) that performs expert-level, automated meningioma segmentation and volume estimation on MRI scans. A 3D-CNN was initially trained by segmenting entire brain volumes using a dataset of 10,099 healthy brain MRIs. Using transfer learning, the network was then specifically trained on meningioma segmentation using 806 expert-labeled MRIs. The final model achieved a median performance of 88.2% reaching the spectrum of current inter-expert variability (82.6–91.6%). We demonstrate in a simulated clinical scenario that a deep learning approach to meningioma segmentation is feasible, highly accurate and has the potential to improve current clinical practice.

Natural history of meningiomas: a serial volumetric analysis of 240 tumors

OBJECTIVE

The management of asymptomatic intracranial meningiomas is controversial. Through the assessment of growth predictors, the authors aimed to create the basis for practicable clinical pathways for the management of these tumors.

METHODS

The authors volumetrically analyzed meningiomas radiologically diagnosed at their institution between 2003 and 2015. The primary endpoint was growth of tumor volume. The authors used significant variables from the multivariable regression model to construct a decision tree based on the exhaustive Chi-Square Automatic Interaction Detection (CHAID) algorithm.

RESULTS

Of 240 meningiomas, 159 (66.3%) demonstrated growth during a mean observation period of 46.9 months. On multivariable logistic regression analysis, older age (OR 0.979 [95% CI 0.958-1.000], p = 0.048) and presence of calcification (OR 0.442 [95% CI 0.224-0.872], p = 0.019) had a negative predictive value for tumor growth, while T2-signal iso-/hyperintensity (OR 4.415 [95% CI 2.056-9.479], p < 0.001) had a positive predictive value. A decision tree model yielded three growth risk groups based on T2 signal intensity and presence of calcifications. The median tumor volume doubling time (Td) was 185.7 months in the low-risk, 100.1 months in the intermediate-risk, and 51.7 months in the high-risk group (p < 0.001). Whereas 0% of meningiomas in the low- and intermediate-risk groups had a Td of ≤ 12 months, the percentage was 8.9% in the high-risk group (p = 0.021).

CONCLUSIONS

Most meningiomas demonstrated growth during follow-up. The absence of calcifications and iso-/hyperintensity on T2-weighted imaging offer a practical way of stratifying meningiomas as low, intermediate, or high risk. Small tumors in the low- or intermediate-risk categories can be monitored with longer follow-up intervals.

External validation and recalibration of an incidental meningioma prognostic model - IMPACT: protocol for an international multicentre retrospective cohort study

INTRODUCTION

Due to the increased use of CT and MRI, the prevalence of incidental findings on brain scans is increasing. Meningioma, the most common primary brain tumour, is a frequently encountered incidental finding, with an estimated prevalence of 3/1000. The management of incidental meningioma varies widely with active clinical-radiological monitoring being the most accepted method by clinicians. Duration of monitoring and time intervals for assessment, however, are not well defined. To this end, we have recently developed a statistical model of progression risk based on single-centre retrospective data. The model Incidental Meningioma: Prognostic Analysis Using Patient Comorbidity and MRI Tests (IMPACT) employs baseline clinical and imaging features to categorise the patient with an incidental meningioma into one of three risk groups: low, medium and high risk with a proposed active monitoring strategy based on the risk and temporal trajectory of progression, accounting for actuarial life expectancy. The primary aim of this study is to assess the external validity of this model.

METHODS AND ANALYSIS

IMPACT is a retrospective multicentre study which will aim to include 1500 patients with an incidental intracranial meningioma, powered to detect a 10% progression risk. Adult patients ≥16 years diagnosed with an incidental meningioma between 1 January 2009 and 31 December 2010 will be included. Clinical and radiological data will be collected longitudinally until the patient reaches one of the study endpoints: intervention (surgery, stereotactic radiosurgery or fractionated radiotherapy), mortality or last date of follow-up. Data will be uploaded to an online Research Electronic Data Capture database with no unique identifiers. External validity of IMPACT will be tested using established statistical methods.

ETHICS AND DISSEMINATION

Local institutional approval at each participating centre will be required. Results of the study will be reported through peer-reviewed articles and conferences and disseminated to participating centres, patients and the public using social media.

Is Contrast Medium Really Needed for Follow-up MRI of Untreated Intracranial Meningiomas?

BACKGROUND AND PURPOSE

Recent concerns relating to tissue deposition of gadolinium are favoring the use of noncontrast MR imaging whenever possible. The purpose of this study was to assess the necessity of gadolinium contrast for follow-up MR imaging of untreated intracranial meningiomas.

MATERIALS AND METHODS

One-hundred twenty-two patients (35 men, 87 women) with meningiomas who underwent brain MR imaging between May 2007 and May 2019 in our institution were included in this retrospective cohort study. We analyzed 132 meningiomas: 73 non-skull base (55%) versus 59 skull base (45%), 93 symptomatic (70%) versus 39 asymptomatic (30%). Fifty-nine meningiomas underwent an operation: 54 World Health Organization grade I (92%) and 5 World Health Organization grade II (8%). All meningiomas were segmented on T1 3D-gadolinium and 2D-T2WI. Agreement between T1 3D-gadolinium and 2D-T2WI segmentations was assessed by the intraclass correlation coefficient.

RESULTS

The mean time between MR images was 1485 days (range, 760-3810 days). There was excellent agreement between T1 3D-gadolinium and T2WI segmentations (P < .001): mean tumor volume (T1 3D-gadolinium: 9012.15 [SD, 19,223.03] mm³; T2WI: 8528.45 [SD, 18,368.18 ] mm³; intraclass correlation coefficient = 0.996), surface area (intraclass correlation coefficient = 0.989), surface/volume ratio (intraclass correlation coefficient = 0.924), maximum 3D diameter (intraclass correlation coefficient = 0.986), maximum 2D diameter in the axial (intraclass correlation coefficient = 0.990), coronal (intraclass correlation coefficient = 0.982), and sagittal planes (intraclass correlation coefficient = 0.985), major axis length (intraclass correlation coefficient = 0.989), minor axis length (intraclass correlation coefficient = 0.992), and least axis length (intraclass correlation coefficient = 0.988). Tumor growth also showed good agreement (P < .001), estimated as a mean of 461.87 [SD, 2704.1] mm³/year on T1 3D-gadolinium and 556.64 [SD, 2624.02 ] mm³/year on T2WI.

CONCLUSIONS

Our results show excellent agreement between the size and growth of meningiomas derived from T1 3D-gadolinium and 2D-T2WI, suggesting that the use of noncontrast MR imaging may be appropriate for the follow-up of untreated meningiomas, which would be cost-effective and avert risks associated with contrast media.

An International Multicenter Matched Cohort Analysis of Incidental Meningioma Progression During Active Surveillance or After Stereotactic Radiosurgery: The IMPASSE Study

BACKGROUND

The optimal management of patients with an incidental meningiomas remains unclear. The aim of this study was to characterize the radiologic and neurological outcomes of expectant and SRS management of asymptomatic meningioma patients.

METHODS

Using data from 14 centers across 10 countries, the study compares SRS outcomes to active surveillance of asymptomatic meningiomas. Local tumor control of asymptomatic meningiomas and development of new neurological deficits attributable to the tumor were evaluated in the SRS and conservatively managed groups.

RESULTS

In unmatched cohorts, 727 meningioma patients underwent SRS and were followed for a mean of 57.2 months. In the conservatively managed cohort, 388 patients were followed for a mean of 43.5 months. Tumor control was 99.0% of SRS and 64.2% of conservatively managed patients (p<0.001; OR 56.860 (95%CI 26.253-123.150))). New neurological deficits were 2.5% in the SRS and 2.8% of conservatively managed patients (p=0.764; OR 0.890 (95% CI 0.416-1.904)). After 1:1 propensity matching for patient age, tumor volume, location, and imaging follow-up, tumor control in the SRS and conservatively managed cohorts was 99.4% and 62.1%, respectively (p<0.001; OR 94.461 (95% CI 23.082-386.568)). In matched cohorts, new neurological deficits were noted in 2.3% of SRS treated and 3.2% of conservatively managed patients (p=0.475; OR 0.700 (95% CI 0.263-1.863)).

CONCLUSIONS

SRS affords superior radiologic tumor control compared to active surveillance without increasing the risk of neurological deficits in asymptomatic meningioma patients. While SRS and active surveillance are reasonable options, SRS appears to alter the natural history of asymptomatic meningiomas including tumor progression in the majority of patients treated.

Petroclival meningiomas: update of current treatment and consensus by the EANS skull base section

BACKGROUND

The optimal management of petroclival meningiomas (PCMs) continues to be debated along with several controversies that persist.

METHODS

A task force was created by the EANS skull base section along with its members and other renowned experts in the field to generate recommendations for the management of these tumors. To achieve this, the task force reviewed in detail the literature in this field and had formal discussions within the group.

RESULTS

The constituted task force dealt with the existing definitions and classifications, pre-operative radiological investigations, management of small and asymptomatic PCMs, radiosurgery, optimal surgical strategies, multimodal treatment, decision-making, and patient's counselling.

CONCLUSION

This article represents the consensually derived opinion of the task force with respect to the management of PCMs.

The Impact of 5-Year Tumor Doubling Time to Predict the Subsequent Long-Term Natural History of Asymptomatic Meningiomas

OBJECTIVE

Meningiomas are the most frequent primary brain tumors. The long-term natural history of asymptomatic meningiomas remains unclear and difficult to predict accurately, however. The purpose of this study was to determine the subsequent course of asymptomatic meningiomas preceded by 5 years of no treatment.

METHODS

We retrospectively studied patients with radiologically suspected intracranial asymptomatic meningiomas preceded by 5 years of no treatment. We volumetrically measured the lesions' chronological changes during the initial 5 years to obtain the 5-year tumor doubling time (5y-TdT).

RESULTS

A total of 201 cases met the inclusion criteria. They were further divided into 3 subgroups: those who remained asymptomatic (group A; 174 cases), those who developed neurological symptoms and underwent treatment (group B; 8 cases), and those who received intentional intervention for a preventative reason (group C; 19 cases). 5y-TdT of group B (median: 46.5 months) was significantly shorter than that of group A (median: 216.3 months) (P < 0.001). Progression-free survival (PFS) was significantly different between tumors that exhibited 5y-TdT ≥ 98.8 months and <98.8 months (P < 0.001). When we combined groups B and C and set the PFS endpoint as either disease progression or treatment, we found that more than 20% of patients would require treatment within 15 years.

CONCLUSIONS

The present study revealed the subsequent course of asymptomatic meningiomas after 5 years of no treatment and demonstrated that 5y-TdT is useful to detect patients who may require treatment.

A prognostic model to personalize monitoring regimes for patients with incidental asymptomatic meningiomas

BACKGROUND

Asymptomatic meningioma is a common incidental finding with no consensus on the optimal management strategy. We aimed to develop a prognostic model to guide personalized monitoring of incidental meningioma patients.

METHODS

A prognostic model of disease progression was developed in a retrospective cohort (2007-2015), defined as: symptom development, meningioma-specific mortality, meningioma growth or loss of window of curability. Secondary endpoints included non-meningioma-specific mortality and intervention.

RESULTS

Included were 441 patients (459 meningiomas). Over a median of 55 months (interquartile range, 37-80), 44 patients had meningioma progression and 57 died (non-meningioma-specific). Forty-four had intervention (at presentation, n = 6; progression, n = 20; nonprogression, n = 18). Model parameters were based on statistical and clinical considerations and included: increasing meningioma volume (hazard ratio [HR] 2.17; 95% CI: 1.53-3.09), meningioma hyperintensity (HR 10.6; 95% CI: 5.39-21.0), peritumoral signal change (HR 1.58; 95% CI: 0.65-3.85), and proximity to critical neurovascular structures (HR 1.38; 95% CI: 0.74-2.56). Patients were stratified based on these imaging parameters into low-, medium- and high-risk groups and 5-year disease progression rates were 3%, 28%, and 75%, respectively. After 5 years of follow-up, the risk of disease progression plateaued in all groups. Patients with an age-adjusted Charlson comorbidity index ≥6 (eg, an 80-year-old with chronic kidney disease) were 15 times more likely to die of other causes than to receive intervention at 5 years following diagnosis, regardless of risk group.

CONCLUSIONS

The model shows that there is little benefit to rigorous monitoring in low-risk and older patients with comorbidities. Risk-stratified follow-up has the potential to reduce patient anxiety and associated health care costs.

Spatial mechanistic modeling for prediction of the growth of asymptomatic meningiomas

BACKGROUND AND OBJECTIVE

Mathematical modeling of tumor growth draws interest from the medical community as they have the potential to improve patients' care and the use of public health resources. The main objectives of this work are to model the growth of meningiomas - slow-growing benign tumors requiring extended imaging follow-up - and to predict tumor volume and shape at a later desired time using only two times examinations.

METHODS

We develop two variants of a 3D partial differential system of equations (PDE) which yield after a spatial integration systems of ordinary differential equations (ODE) that relate tumor volume with time. Estimation of models parameters is a crucial step to obtain a personalized model for a patient that can be used for descriptive or predictive purposes. As PDE and ODE systems share the same parameters, they are both estimated by fitting the ODE systems to the tumor volumes obtained from MRI examinations acquired at different times. A population approach allows to compensate for sparse sampling times and measurement uncertainties by constraining the variability of the parameters in the population.

RESULTS

Description capabilities of the models are investigated in 39 patients with benign asymptomatic meningiomas who had had at least three surveillance MRI examinations. The two models can fit to the data accurately and more realistically than a naive linear regression. Prediction performances are validated for 33 patients using a population approach. Mean relative errors in volume predictions are less than 10% with ODE systems versus 12.5% with the naive linear model using only two times examinations. Concerning the shape, the mean Sørensen-Dice coefficients are 85% with the PDE systems in a subset of 10 representative patients.

CONCLUSIONS

Our strategy - based on personalization of mathematical model - provides a good insight on meningioma growth and may help decide whether to extend the follow-up or to treat the tumor.

DNA repair and cell synthesis proteins: immunohistochemical expression and correlation with recurrence-regrowth in meningiomas

Meningiomas are considered the second most common neoplasm of the central nervous system in adults. Most of them are benign with slow growth, frequent in women and with a high recurrence rate. In tumors, DNA error repair processes lose efficacy, providing mutagenesis and genomic instability. This work evaluated the expression of proteins involved in cell synthesis (cyclin D1) and DNA errors repair (MUTYH, XPF, XPG) in meningiomas, relating them to clinical, tumor and survival variables. The study included 85 patients, with a mean age of 52 ± 13.3 years and most of them women (2:1 ratio). Sixty-seven cases were grade I (79%). Grade II tumors were independent predictors of recurrence-regrowth (HR: 2.8; p = 0.038). The high expression of cyclin D1 was associated with grade II (p = 0.001) and low MUTYH expression with grade I (p = 0.04). Strong expression of XPF and XPG was associated with grade II (p = 0.002; p < 0.001) and with recurrence-regrowth (p = 0.04; p = 0.003). Strong XPF expression was significantly related to large tumors (p = 0.03). An association of cyclin D1, MUTYH and XPF were found. Survival was not associated with the expression of any of the proteins studied. To know the role of DNA repair proteins and cell synthesis is important for understanding the processes of origin and tumor development. Grade II meningiomas and strong expression of XPF and XPG were predictors of recurrence or regrowth and may assist in clinical management, considering the high recurrence of meningiomas and the absence of consensus regarding treatment.

Treatment Outcomes of Incidental Intracranial Meningiomas: Results from the IMPACT Cohort

BACKGROUND

Incidental findings such as meningioma are becoming increasingly prevalent. There is no consensus on the optimal management of these patients. The aim of this study was to examine the outcomes of patients diagnosed with an incidental meningioma who were treated with surgery or radiotherapy.

METHODS

Single-center retrospective cohort study of adult patients diagnosed with an incidental intracranial meningioma (2007-2015). Outcomes recorded were postintervention morbidity, histopathologic diagnosis, and treatment response.

RESULTS

Out of 441 patients, 44 underwent treatment. Median age at intervention was 56.1 years (interquartile range [IQR], 49.6-66.5); patients included 35 women and 9 men. The main indication for imaging was headache (25.9%). Median meningioma volume was 4.55 cm³ (IQR, 1.91-8.61), and the commonest location was convexity (47.7%). Six patients underwent surgery at initial diagnosis. Thirty-eight had intervention (34 with surgery and 4 with radiotherapy) after a median active monitoring duration of 24 months (IQR, 11.8-42.0). Indications for treatment were radiologic progression (n = 26), symptom development (n = 6), and patient preference (n = 12). Pathology revealed World Health Organization (WHO) grade 1 meningioma in 36 patients and WHO grade 2 in 4 patients. The risk of postoperative surgical and medical morbidity requiring treatment was 25%. Early and late moderate adverse events limiting activities of daily living occurred in 28.6% of patients treated with radiotherapy. Recurrence rate after surgery was 2.5%. All meningiomas regressed or remained radiologically stable after radiotherapy.

CONCLUSIONS

The morbidity after treatment of incidental intracranial meningioma is not negligible. Considering most operated tumors are WHO grade 1, treatment should be reserved for those manifesting symptoms or demonstrating substantial growth on radiologic surveillance.

Natural History of Meningiomas: Review with Meta-analyses

Observation has been a mainstay in asymptomatic meningiomas, but it may increase the risk associated with treatment due to tumor enlargement and the aging of patients. Understanding the natural course of meningiomas is important to provide appropriate treatment. The majority of previous studies investigated factors related to their growth, but failed to demonstrate their relationship with symptomatic progression (sympP) because of its rarity. We reviewed and meta-analyzed 27 studies that investigated natural courses in asymptomatic or untreated meningiomas to find clinico-radiological factors predictive of radiological progression (radioP), growth speed, and sympP. In results of time-growth analysis, two-thirds of meningiomas showed radioP defined by a volume criterion and the rate approached a plateau at 4-5 years. In growth curve analyses, about half of incidental meningiomas presented decelerating or no growth, while less than one-quarter of them grew exponentially. RadioP, growth speed [annual volume change (AVC) or relative growth rate], and sympP each had different factors related to them. Younger age, non-calcification, and high intensity on T2-weighted image were related to radioP and rapid growth speed, but not to sympP. Tumors in males and those of larger size were likely to be symptomatic in the meta-analysis. AVC (≥2.1 cm³/year) was the strongest indicator of sympP. Apart from perifocal edema, radiological features at up-front imaging may not be useful for predicting sympP. This may be due to dynamic changes of those radiological markers in the long term. Quantified tumor size and growth speed, especially AVC, are important markers for deciding on treatment.

A practical predictor of the growth potential of benign meningiomas: Hypointensity of surface layer in T2-weighted magnetic resonance imaging

BACKGROUND

Accurate evaluation of proliferative potential is particularly important in the clinical management of individual patients with meningiomas. We introduce a new feature in the parenchyma of meningioma, namely, hypointensity of the surface layer (HSL), on T2-weighted MR images and compare it with a cellular proliferation index and growth speed.

MATERIALS AND METHODS

We retrospectively analyzed the records of consecutive patients with WHO grade I meningiomas in two institutes: an operated group with 124 meningiomas resected in one institute, and an observed group with 89 meningiomas monitored without surgery in the other. Proliferative potential was evaluated using the MIB-1 labeling index (MIB-1 LI) for the operated group and using the relative growth rate on serial MR images for the observed group.

RESULTS

In the operated group, 60 (48.4%) meningiomas exhibited HSL. HSL-positive meningiomas were significantly smaller in size and more often calcified than HSL-negative ones. Univariate analysis showed that HSL negativity, large size, no calcification, and surrounding brain edema were significantly associated with high MIB-1 LI (p < 0.05). Multivariate analysis demonstrated that only HSL was significantly related to MIB-1 LI (p = 0.001). HSL did not correlate with tumor recurrence after resection. In the observed group, 43 (48.3%) meningiomas exhibited HSL and they presented a significantly slow relative growth rate.

CONCLUSIONS

HSL is a simple and new radiological feature indicative of low proliferative potential and a low risk of enlargement of meningiomas. The presence or absence of HSL may serve as a key parameter for the selection of aggressive treatment or active observation.

A prospective study of the natural history of incidental meningioma-Hold your horses!

Background

The number of incidental meningiomas has increased because of the increased availability of neuroimaging. Lack of prospective data on the natural history makes the optimal management unclear. We conducted a 5-year prospective study of incidental meningiomas to identify risk factors for tumor growth.

Methods

Sixty-four of 70 consecutive patients with incidental meningioma were included. Clinical and radiological status was obtained at 0, 0.5, 1, 1.5, 2, 3, 4, and 5 years. GammaPlan and mixed linear regression modeling were utilized for volumetric analysis with primary endpoint tumor growth.

Results

None of the patients developed tumor-related symptoms during the study period, although 48 (75%) tumors increased (>15%), 13 (20.3%) remained unchanged, and 3 (4.7%) decreased (>15%) in volume. Mean time to growth was 2.2 years (range, 0.5-5.0 years).The growth pattern was quasi-exponential in 26%, linear in 17%, sigmoidal in 35%, parabolic in 17%, and continuous reduction in 5%. There was significant correlation among growth rate, larger baseline tumor volume (P < .001), and age in years (<55 y: 0.10 cm³/y, 55-75 y: 0.24 cm³/y, and >75 y: 0.85 cm³/y).

Conclusion

The majority of meningiomas will eventually grow. However, more than 60% display a self-limiting growth pattern. Our study provides level-2 evidence that asymptomatic tumors can be safely managed utilizing serial imaging until persistent radiological and/or symptomatic growth.