Meningioma is by far the most common primary intracranial tumor in adults. Treatment of meningioma is complex due to a tremendous amount of variability in tumor behavior. Many patients are incidentally found to have tumors that will remain asymptomatic throughout their lives. It is important to identify these patients so that they can be spared from potentially morbid interventions. On the other end of the spectrum, high-grade meningiomas can behave very aggressively. When treatment is necessary, surgical resection is the cornerstone of meningioma therapy. Studies spanning decades have demonstrated that extent of resection correlates with prognosis. Radiation therapy, either in the form of external beam radiation therapy or stereotactic radiosurgery, represents another important therapeutic tool that can be used in place of or as a supplement to surgery. There are no chemotherapeutic agents of proven efficacy against meningioma, and chemotherapy treatment is generally reserved for patients who have exhausted surgical and radiotherapy options. Ongoing and future studies will help to answer unresolved questions such as the optimum use of radiation in resected WHO grade II meningiomas and the efficacy of additional chemotherapy agents.

Background and purpose

Relative cerebral blood volume, as measured by T2*-weighted dynamic susceptibility-weighted contrast-enhanced MRI, represents the most robust and widely used perfusion MR imaging metric in neuro-oncology. Our aim was to determine whether differences in modeling implementation will impact the correction of leakage effects (from blood-brain barrier disruption) and the accuracy of relative CBV calculations as measured on T2*-weighted dynamic susceptibility-weighted contrast-enhanced MR imaging at 3T field strength.

Materials and methods

This study included 52 patients with glioma undergoing DSC MR imaging. Thirty-six patients underwent both non-preload dose- and preload dose-corrected DSC acquisitions, with 16 patients undergoing preload dose-corrected acquisitions only. For each acquisition, we generated 2 sets of relative CBV metrics by using 2 separate, widely published, FDA-approved commercial software packages: IB Neuro and nordicICE. We calculated 4 relative CBV metrics within tumor volumes: mean relative CBV, mode relative CBV, percentage of voxels with relative CBV > 1.75, and percentage of voxels with relative CBV > 1.0 (fractional tumor burden). We determined Pearson (r) and Spearman (ρ) correlations between non-preload dose- and preload dose-corrected metrics. In a subset of patients with recurrent glioblastoma (n = 25), we determined receiver operating characteristic area under the curve for fractional tumor burden accuracy to predict the tissue diagnosis of tumor recurrence versus posttreatment effect. We also determined correlations between rCBV and microvessel area from stereotactic biopsies (n = 29) in 12 patients.

Results

With IB Neuro, relative CBV metrics correlated highly between non-preload dose- and preload dose-corrected conditions for fractional tumor burden (r = 0.96, ρ = 0.94), percentage > 1.75 (r = 0.93, ρ = 0.91), mean (r = 0.87, ρ = 0.86), and mode (r = 0.78, ρ = 0.76). These correlations dropped substantially with nordicICE. With fractional tumor burden, IB Neuro was more accurate than nordicICE in diagnosing tumor versus posttreatment effect (area under the curve = 0.85 versus 0.67) (P < .01). The highest relative CBV-microvessel area correlations required preload dose and IB Neuro (r = 0.64, ρ = 0.58, P = .001).

Conclusions

Different implementations of perfusion MR imaging software modeling can impact the accuracy of leakage correction, relative CBV calculation, and correlations with histologic benchmarks.