How should we manage incidental meningiomas?

See the article by Islim et al. in this issue, pp. 278–289. Meningiomas are the most common primary intracranial neoplasm. The incidence of meningiomas rises with increasing age, in particular after 60 years.1 With the general population slowly aging, we can expect that meningioma will remain at the forefront of the tumors that will be dealt with in neuro-oncology. Despite their prevalence, very few studies have focused on meningiomas. Over the last decade we have learned that meningiomas can harbor neurofibromatosis type 2 (NF2) or mutually exclusive non-NF2 mutations, with the latter being enriched in benign meningiomas.2–4 More recently, we have learned that epigenome-wide DNA methylation signatures are associated with subgroups of tumors with distinct clinical outcomes.5–7 These studies, of course, relied on tumor tissue that was resected as part of clinical care for the patients but where tissue was subsequently used for genomic profiling in research. For the most part, the management strategy for patients with large and symptomatic meningiomas is straightforward, with almost all patients requiring surgery for treatment. Recent guidelines suggest that patients with smaller tumors that are asymptomatic—so-called incidental meningiomas—should be managed conservatively with serial imaging.8 However, small size and asymptomaticity at diagnosis do not always translate into indolent disease course. It is known that the majority of meningiomas are benign; however, a small subset of approximately 20–25% of tumors demonstrate aggressive behavior with faster than expected growth and early tumor recurrence after surgery.9 Therefore, it’s possible that some incidental meningiomas in fact will harbor aggressive behavior, and finding features that help predict behavior in this population can help with management. With increasing availability and use of brain imaging and the general aging population, the management of incidental meningiomas will become a greater burden to our system. In this issue, Islim et al used routine clinical and brain imaging factors from 441 patients at a single institution with median follow-up of 55 months to develop a prognostic model of tumor progression for patients with incidental meningiomas.10 Progression was a composite endpoint of clinical (symptom development, meningioma-specific mortality) and radiographic outcomes (peritumoral hyperintensity on T2/fluid attenuated inversion recovery [FLAIR], evidence of venous sinus invasion, or meningioma volume exceeding 10 cm3). The authors selected these radiographic outcomes because each had the potential to increase the likelihood of failure of treatment—peritumoral hyperintensity being suggestive of brain invasion, venous sinus invasion potentially precluding complete total resection of tumor without additive risk, and meningioma volume exceeding 10 cm3 precluding use of radiosurgery as a treatment option. Using feature selection methods, the authors identify tumor T2/FLAIR hyperintensity (suggestive of calcification), peritumoral T2/FLAIR hyperintensity, increasing meningioma volumetrics, and proximity to neurovascular structures to be predictive of tumor progression within the first 10 years following diagnosis. With the exception of proximity to neurovascular structures, the features included in this model have previously been suggested to be correlated with tumor growth in incidental meningiomas.11,12 Visual inspection of the data revealed two thresholds that could identify increasing risk groups for progression (low, medium, and high risk). Based on these results, the authors propose active monitoring strategies that can be used for patients with differing risk scores in correlation with patient characteristics (World Health Organization performance status and comorbidity indices) and provide their risk calculator available for public use. Although traditionally thought to be a minor issue, meningiomas are in fact the most commonly identified incidental brain tumor and can in fact be identified in almost 1% of the healthy population.13 Greater attention is needed for these tumors, and the report by Islim et al comprehensively details outcomes of the largest series of incidental meningiomas that we are aware of. Approximately 11% of patients in this study experienced disease progression, which is similar to the rates of symptom development reported from a meta-analysis of published studies conducted by the same authors.14 The model that the authors present could help with decision making regarding management. However, it is important to note that this model was developed using data and reporting from a single center. A more exhaustive validation using independent and international datasets similar to other machine-learning models developed for classification and prognostication of brain tumors5,15 will be a key factor that governs the utility of this model. Additionally, investigating how exogenous factors, such as use of hormonal therapies which have been linked with meningioma development and growth, can influence model performance may help with further refinement.

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