Introduction: The aim of this study was to develop a weighted scoring system that estimates the risk of rapid growth of intracranial meningiomas (IMs) to aid treatment decision making.
Methods: A retrospective analysis of 232 patients with presumed IM who had been followed up from 1997 to 2013. Volumetric tumor measurement at each follow-up visit. The growth rate was determined by regression analysis. Predictors of rapid tumor growth (defined as = 2 cm3/year) were identified using a logistic regression model; each factor was awarded a score based on its own coefficient value. The probability (P) of rapid tumor growth was estimated using the following formula: [1/(1+e^(-(intercept+b1×total score) ) )]×100(%)
Results: Fifty-nine tumors (25.4%) showed rapid growth. Tumor size , absence of calcification, peritumoral edema, and hyperintense or isointense signal on T2-
weighted MRI were predictors of tumor growth rate. In the scoring system, tumor size was categorized into 3 groups of < 2.5 cm, = 2.5 to < 4.0 cm, and = 4.0 cm in diameter and awarded a score of 0, 3, and 6, respectively; the parameters of calcification and peritumoral edema were categorized into 2 groups based on their presence or absence and given a score of 0 or 2 and 1 or 0, respectively; and the signal on T2-weighted MRI was categorized into 2 groups of hypointense and hyperintense/isointense and given a score of 0 or 2, respectively. The risk of rapid tumor growth was estimated to be < 10% when the total score was 0–2, 10%–50% when the total score was 3–6, and = 50% when the total score was 7–11.
Conclusions: The authors suggest a weighted scoring system that predicts the specific probability of rapid tumor growth for patients with untreated IM. This scoring system will aid to screen out patients at high risk for rapid tumor growth.
Patient Care: Our scoring system will help clinicians to screen patients with IMs who may require early treatment and thus facilitate optimal and timely treatment in these patients.
Learning Objectives: By the conclusion of this session, participants should be able to 1) Describe the natural history of intracranial meningiomas, 2) Estimate the overall risk of rapid growth in individual meningioma, and 3) Identify and usefulness of AIMSS in screening the patients at risk