Apparent diffusion coefficient and tumor volume measurements help stratify progression

The aim of this study was to determine whether apparent diffusion coefficient (ADC) bi-component curve-fitting histogram analysis and volume percentage change (VPC) prior to bevacizumab treatment can stratify progression-free survival (PFS) and overall survival (OS) in patients with glioblastoma multiforme (GBM) on first recurrence. We retrospectively evaluated 17 patients with recurrent GBM who received bevacizumab and fotemustine (n？=？13) or only bevacizumab (n？=？4) on first recurrence at our institution between December 2009 and July 2015. Both T2/FLAIR abnormalities and enhancing tumor on T1 images were mapped to the ADC images. ADC-L and ADC-M values were obtained trough bi-Gaussian curve fitting histogram analysis. Furthermore, the study population was dichotomized into two subgroups: patients displaying a reduction in enhancing tumor volume of either >55% or <55% between the mean value calculated at baseline and first follow-up. Subsequently, a second dichotomization was performed according to a reduction in the T2 / FLAIR volume >41% or <41% at first check after treatment. OS and PFS were assessed using volume parameters in a Cox regression model adjusted for significant clinical parameters. In univariate analysis, contrast-enhanced (CE)-ADC-L was significantly predictive of PFS (p？=？0.01) and OS (p？=？0.03). When we dichotomized our sample using the 55% cut-off for enhancing tumor volume, CE-VPC was able to predict PFS (p？=？0.01) but not OS (p？=？0.08). In multivariate analysis, only the CE-ADC-L was predictive of PFS (p？=？0.01), albeit not predictive of OS (p？=？0.14). CE-ADC-M, T2/FLAIR-ADC-L, T2/FLAIR-ADC, and T2/FLAIR VPC were not significantly predictive of PFS and OS (p？>？0.05) in both univariate and multivariate analysis. CE-ADC and CE-VPC can stratify PFS for patients with recurrent glioblastoma prior to bevacizumab treatment