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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.

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Brain metastases are common and are usually detected by MRI. Diffusion tensor imaging (DTI) is a derivative MRI technique that can detect disruption of white matter tracts in the brain. We have matched preoperative DTI with image-guided sampling of the brain-tumor interface in 26 patients during resection of a brain metastasis and assessed mean diffusivity and fractional anisotropy (FA). The tissue samples were analyzed for vascularity, inflammatory cell infiltration, growth pattern, and tumor expression of proteins associated with growth or local invasion such as Ki67, S100A4, and MMP2, 9, and 13. A lower FA in the peritumoral region indicated more white matter tract disruption and independently predicted longer overall survival times (HR for death = 0.21; 95% confidence interval, 0.06-0.82; = 0.024). Of all the biological markers studied, only increased density of CD3 lymphocytes in the same region correlated with decreased FA (Mann-Whitney = 0.037) as well as confounding completely the effect of FA on multivariate survival analyses. We conclude that the T-cell response to brain metastases is not a surrogate of local tumor invasion, primary cancer type, or aggressive phenotype and is associated with patient survival time regardless of these biological factors. Furthermore, it can be assayed by DTI, potentially offering a quick, noninvasive, clinically available method to detect an active immune microenvironment and, in principle, to measure susceptibility to immunotherapy. These findings show that white matter tract integrity is degraded in areas where T-cell infiltration is highest, providing a noninvasive method to identify immunologically active microenvironments in secondary brain tumors. .

Background:Understanding the factors that drive recurrence and radiosensitivity in brain metastases would improve prediction of outcomes, treatment planning and development of therapeutics. We investigated the expression of known metastasis-inducing proteins in human brain metastases.Methods:Immunohistochemistry on metastases removed at neurosurgery from 138 patients to determine the degree and pattern of expression of the proteins S100A4, S100P, AGR2, osteopontin (OPN) and the DNA repair marker FANCD2. Validation of significant findings in a separate prospective series with the investigation of intra-tumoral heterogeneity using image-guided sampling. Assessment of S100A4 expression in brain metastatic and non-metastatic primary breast carcinomas.Results:There was widespread staining for OPN, S100A4, S100P and AGR2 in human brain metastases. Positive staining for S100A4 was independently associated with a shorter time to intracranial progression after resection in multivariate analysis (hazard ratio for negative over positive staining=0.17, 95% CI: 0.04–0.74, P=0.018). S100A4 was expressed at the leading edge of brain metastases in image guided sampling and overexpressed in brain metastatic vs non-brain metastatic primary breast carcinomas. Staining for OPN was associated with a significant increase in survival time after post-operative whole-brain radiotherapy in retrospective (OPN negative 3.43 months, 95% CI: 1.36–5.51 vs OPN positive, 11.20 months 95% CI: 7.68–14.72, Log rank test, P<0.001) and validation populations.Conclusions:Proteins known to be involved in cellular adhesion and migration in vitro, and metastasis in vivo are significantly expressed in human brain metastases and may be useful biomarkers of intracranial progression and radiosensitivity.