The Initial Area Under the Curve Derived from Dynamic Contrast-Enhanced MRI Improves Prognosis Prediction in Glioblastoma with Unmethylated MGMT Promoter

BACKGROUND AND PURPOSE:Although perfusion and permeability MR parameters have known to have prognostic value, they have reproducibility issues. Our aim was to evaluate whether the initial area under the time-to-signal intensity curve (IAUC) derived from dynamic contrast-enhanced MR imaging can improve prognosis prediction in patients with glioblastoma with known MGMT status.MATERIALS AND METHODS:We retrospectively examined 88 patients with glioblastoma who underwent preoperative dynamic contrast-enhanced MR imaging. The means of IAUC values at 30 and 60 seconds (IAUC30_mean and IAUC60_mean) were extracted from enhancing tumors. The prognostic values of IAUC parameters for overall survival and progression-free survival were assessed with log-rank tests, according to the MGMT status. Multivariate overall survival and progression-free survival models before and after adding the IAUC parameters as covariates were explored by net reclassification improvement after receiver operating characteristic analysis for 1.5-year overall survival and 1-year progression-free survival and by random survival forest.RESULTS:High IAUC parameters were associated with worse overall survival and progression-free survival in the unmethylated MGMT group, but not in the methylated group. In the unmethylated MGMT group, 1.5-year overall survival and 1-year progression-free survival prediction improved significantly after adding IAUC parameters (overall survival area under the receiver operating characteristic curve, 0.86; progression-free survival area under the receiver operating characteristic curve, 0.74–0.76) to the model with other prognostic factors (overall survival area under the receiver operating characteristic curve, 0.81; progression-free survival area under the receiver operating characteristic curve, 0.69; P < .05 for all) except in the case of IAUC60_mean for 1-year progression-free survival prediction (P = .059). Random survival forest models indicated that the IAUC parameters were the second or most important predictors in the unmethylated MGMT group, except in the case of the IAUC60_mean for progression-free survival.CONCLUSIONS:IAUC can be a useful prognostic imaging biomarker in patients with glioblastoma with known MGMT status, improving prediction of glioblastoma prognosis with the unmethylated MGMT promoter status.

Glioblastoma (GBM) is the most common primary malignant tumor in the adult brain. Although its prognosis remains poor (median survival, ∼14.7 months),¹ some patients with GBM show a distinct prognosis and response to chemoradiation. Previous studies have investigated the prognostic factors of GBM, including MR imaging^2–4 and molecular biomarkers (O⁶-methylguanine-DNA methyltransferase [MGMT] promoter methylation).⁵Previous studies have shown that high relative cerebral blood volume (rCBV; derived via dynamic susceptibility contrast-enhanced MR imaging) and high volume transfer constant (K^trans; derived via dynamic contrast-enhanced [DCE] MR imaging) are associated with poor survival outcomes.^6–8 However, rCBV and K^trans measurements have reproducibility issues related to postprocessing techniques, including normalization, model-based calculation, arterial input function, and software.^9–13 In contrast, the initial area under the time-to–signal intensity curve (IAUC), derived via DCE MR imaging, is a model-free parameter that does not require an arterial input function or a complicated model-based calculation and is highly reproducible.^10,14 Because IAUC reflects both tumor perfusion and permeability,^9,10,15 we hypothesized that IAUC might be useful for predicting the survival outcome in GBM. In this study, we used automatically calculated IAUC parameters to maximize reproducibility.MGMT removes alkyl groups from the alkylation site of temozolomide. Methylation of the MGMT promoter inhibits MGMT activity and yields a better response to temozolomide and improved prognosis.⁵ Because the MGMT status is available after surgery in most patients with GBM, the predictive ability of IAUC for prognosis in patients with GBM with known MGMT status is clinically relevant. Here, we aimed to assess whether IAUC can improve prognosis prediction in patients with GBM with known MGMT status.