No abstract

BACKGROUND AND PURPOSE:A subset of patients with malignant glioma develops conspicuous lesions characterized by persistent restricted diffusion during treatment with bevacizumab. The purpose of the current study was to characterize the evolution of these lesions and to determine their relationship to patient outcome.

Purpose: To compare ''standardization,'' ''Gaussian normalization,'' and ''Z-score normalization'' intensity transformation techniques in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) estimates of cerebral blood volume (CBV) in human gliomas. DSC-MRI is a well-established biomarker for CBV in brain tumors; however, DSC-MRI estimates of CBV are semiquantitative. The use of image intensity transformation algorithms provides a mechanism for obtaining quantitatively similar CBV maps with the same intensity scaling. Materials and Methods:The coefficient of variance (CV) in normal-appearing white matter and relative contrast between tumor regions and normal tissue was compared between the three CBV transformations across five different MR scanners in 96 patients with gliomas. Results:The results suggest all normalization techniques improved variability and relative tumor contrast of CBV measurements compared with nonnormalized CBV maps. The results suggest Gaussian normalization of CBV maps provided slightly lower CV in normal white matter and provided slightly higher tumor contrast for glioblastomas (WHO grade IV) compared with other techniques. Conclusion:The results suggest Gaussian normalization of leakage-corrected CBV maps may be the best choice for image intensity correction for use in large-scale, multicenter clinical trials where MR scanners and protocols vary widely due to ease of implementation, lowest variability, and highest tumor to normal tissue contrast.

Functional diffusion mapping (fDM) has shown promise as a sensitive imaging biomarker for predicting survival in initial studies consisting of a small number of patients, mixed tumor grades, and before routine use of anti-angiogenic therapy. The current study tested whether fDM performed before and after radiochemotherapy could predict progression-free and overall survival in 143 patients with newly diagnosed glioblastoma from 2007 through 2010, many treated with anti-angiogenic therapy after recurrence. Diffusion and conventional MRI scans were obtained before and 4 weeks after completion of radiotherapy and concurrent temozolomide treatment. FDM was created by coregistering pre- and posttreatment apparent diffusion coefficient (ADC) maps and then performing voxel-wise subtraction. FDMs were categorized according to the degree of change in ADC in pre- and posttreatment fluid-attenuated inversion recovery (FLAIR) and contrast-enhancing regions. The volume fraction of fDM-classified increasing ADC(+), decreasing ADC(-), and change in ADC(+/-) were tested to determine whether they were predictive of survival. Both Bonferroni-corrected univariate log-rank analysis and Cox proportional hazards modeling demonstrated that patients with decreasing ADC in a large volume fraction of pretreatment FLAIR or contrast-enhancing regions were statistically more likely to progress earlier and expire sooner than in patients with a lower volume fraction. The current study supports the hypothesis that fDM is a sensitive imaging biomarker for predicting survival in glioblastoma.

The current study examined the use of voxel-wise changes in (18)F-FDOPA and (18)F-FLT PET uptake, referred to as parametric response maps (PRMs), to determine whether they were predictive of response to bevacizumab in patients with recurrent malignant gliomas. Twenty-four patients with recurrent malignant gliomas who underwent bevacizumab treatment were analyzed. Patients had MR and PET images acquired before and at 2 time points after bevacizumab treatment. PRMs were created by examining the percentage change in tracer uptake between time points in each image voxel. Voxel-wise increase in PET uptake in areas of pretreatment contrast enhancement defined by MRI stratified 3-month progression-free survival (PFS) and 6-month overall survival (OS) according to receiver-operating characteristic curve analysis. A decrease in PET tracer uptake was associated with longer PFS and OS, whereas an increase in PET uptake was associated with short PFS and OS. The volume fraction of increased (18)F-FDOPA PET uptake between the 2 posttreatment time points also stratified long- and short-term PFS and OS (log-rank, P < .05); however, (18)F-FLT uptake did not stratify OS. This study suggests that an increase in FDOPA or FLT PET uptake on PRMs after bevacizumab treatment may be a useful biomarker for predicting PFS and that FDOPA PET PRMs are also predictive of OS in recurrent gliomas treated with bevacizumab.