Nonsurgical treatment options in the management of intracranial meningiomas

Emerging Medical Treatments for Meningioma in the Molecular Era

Meningiomas are the most common type of primary central nervous system tumors. Approximately, 80% of meningiomas are classified by the World Health Organization (WHO) as grade I, and 20% of these tumors are grade II and III, considered high-grade meningiomas (HGMs). Clinical control of HGMs, as well as meningiomas that relapse after surgery, and radiation therapy is difficult, and novel therapeutic approaches are necessary. However, traditional chemotherapies, interferons, hormonal therapies, and other targeted therapies have so far failed to provide clinical benefit. During the last several years, next generation sequencing has dissected the genetic heterogeneity of meningioma and enriched our knowledge about distinct oncogenic pathways driving different subtypes of meningiomas, opening up a door to new personalized targeted therapies. Molecular classification of meningioma allows a new design of clinical trials that assign patients to corresponding targeted agents based on the tumor genetic subtypes. In this review, we will shed light on emerging medical treatments of meningiomas with a particular focus on the new targets identified with genomic sequencing that have led to clinical trials testing novel compounds. Moreover, we present recent development of patient-derived preclinical models that provide platforms for assessing targeted therapies as well as strategies with novel mechanism of action such as oncolytic viruses.

The diagnostic value of using combined MR diffusion tensor imaging parameters to differentiate between low- and high-grade meningioma

OBJECTIVE

The purpose of this study was to examine whether the combined use of MR diffusion tensor imaging (DTI) parameters [DTI-apparent diffusion coefficient (ADC), fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD)] could provide a more accurate diagnosis in differentiating between low-grade and atypical/anaplastic (high-grade) meningioma.

METHODS

Pathologically proven 45 meningioma patients [32 low-grade, 13 high-grade (11 atypical and 2 anaplastic)] who had received DTI before surgery were assessed retrospectively by 2 independent observers. For each lesion, MR DTI parameters (ADCmin, ADCmax, ADCmean, FA, AD, and RD) and ratios (rADCmin, rADCmax, rADCmean, rFA, rAD, and rRD) were calculated. When differentiating between low- and high-grade meningioma, the optimum cutoff values of all MR DTI parameters were determined by using receiver operating characteristic (ROC) analysis. Area under the curve (AUC) was measured with combined ROC analysis for different combinations of MR DTI parameters in order to identify the model combination with the best diagnostic accuracy in differentiation between low and high-grade meningioma.

RESULTS

Although the ADCmin, ADCmax, ADCmean, AD, RD, rADCmin, rADCmax, rADCmean, rAD, and rRD values of high-grade meningioma were significantly low (p = 0.007, p = 0.045, p = 0.035, p = 0.045, p = 0.003, p = 0.02, p = 0.03, p = 0.03, p = 0.045, and p = 0.01, respectively), when compared with low-grade meningioma, their FA and rFA values were significantly high (p = 0.007 and p = 0.01, respectively). For all MR DTI parameters, the highest individual distinctive power was RD with AUC of 0.778. The best diagnostic accuracy in differentiating between low- and high-grade meningioma was obtained by combining the ADCmin, RD, and FA parameters with 0.962 AUC.

CONCLUSION

This study shows that combined MR DTI parameters consisting of ADCmin, RD, and FA can differentiate high-grade from low-grade meningioma with a diagnostic accuracy of 96.2%. Advances in knowledge: To the best of our knowledge, this is the first study reporting that a combined use of all MR DTI parameters provides higher diagnostic accuracy for the differentiation of low- from high-grade meningioma. Our study shows that any of the model combinations was superior to use of any individual MR DTI parameters for differentiation between low and high-grade meningioma. A combination of ADCmin, RD, and FA was found to be the best model for differentiating low-grade from high-grade meningioma and sensitivity, specificity, and AUC values were found to be 92.3%, 100%, and 0.96, respectively. Thus, a combination of MR DTI parameters can provide more accurate diagnostic information when differentiation between low and high-grade meningioma.

Treatment of unresectable skull base meningiomas with somatostatin analogs

OBJECT

The standard surgical treatment for meningiomas is total resection, but the complete removal of skull base meningiomas can be difficult for several reasons. Thus, the management of certain meningiomas of the skull base--for example, those involving basal vessels and cranial nerves--remains a challenge. In recent reports it has been suggested that somatostatin (SST) administration can cause growth inhibition of unresectable and recurrent meningiomas. The application of SST and its analogs is not routinely integrated into standard treatment strategies for meningiomas, and clinical studies proving growth-inhibiting effects do not exist. The authors report on their experience using octreotide in patients with recurrent or unresectable meningiomas of the skull base.

METHODS

Between January 1996 and December 2010, 13 patients harboring a progressive residual meningioma (as indicated by MR imaging criteria) following operative therapy were treated with a monthly injection of the SST analog octreotide (Sandostatin LAR [long-acting repeatable] 30 mg, Novartis). Eight of 13 patients had a meningioma of the skull base and were analyzed in the present study. Postoperative tumor enlargement was documented in all patients on MR images obtained before the initiation of SST therapy. All tumors were benign. No patient received radiation or chemotherapy before treatment with SST. The growth of residual tumor was monitored by MR imaging every 12 months.

RESULTS

Three of the 8 patients had undergone surgical treatment once; 3, 2 times; and 2, 3 times. The mean time after the last meningioma operation (before starting SST treatment) and tumor enlargement as indicated by MR imaging criteria was 24 months. A total of 643 monthly cycles of Sandostatin LAR were administered. Five of the 8 patients were on SST continuously and stabilized disease was documented on MR images obtained in these patients during treatment (median 115 months, range 48-180 months). Three of the 8 patients interrupted treatment: after 60 months in 1 case because of tumor progression, after 36 months in 1 case because of side effects, and after 36 months in 1 case because the health insurance company denied cost absorption.

CONCLUSIONS

Although no case of tumor regression was detected on MR imaging, the study results indicated that SST analogs can arrest the progression of unresectable or recurrent benign meningiomas of the skull base in some patients. It remains to be determined whether a controlled prospective clinical trial would be useful.

Medical therapies for meningiomas

Meningiomas are the most common primary brain tumor in adults. Although the majority of these tumors can be effectively treated with surgery and radiation therapy, an important subset of patients have inoperable tumors, or develop recurrent disease after surgery and radiotherapy, and require some form of medical therapy. There are increasing numbers of studies evaluating various medical therapies but the results remain disappointing. Chemotherapies and hormonal therapies have been generally ineffective, although somatostatin analogues may have therapeutic potential. There is also increasing interest in targeted molecular therapies. Agents inhibiting platelet derived growth factor receptors and epidermal growth factor receptors have shown little efficacy, but molecular agents inhibiting vascular endothelial growth factor receptors appear to have some promise. As with other tumors, advances in the medical therapies for meningiomas will require improved understanding of the molecular pathogenesis of these tumors, more predictive preclinical models, and efficient mechanisms for conducting clinical trials, given the small population of eligible patients.