Vascular change measured with independent component analysis of dynamic susceptibility contrast MRI predicts bevacizumab response in high-grade glioma

Glioblastoma (GBM) is one of the most deadly cancers in adults. GBM accounts for 52% of all parenchymal brain tumor cases and 20% of all intracranial tumors.1 The current standard of care, which includes surgery followed by radiation therapy and chemotherapy, is associated with a survival of ∼14.6 months.2 The anti–vascular endothelial growth factor (VEGF) antibody bevacizumab was approved by the Food and Drug Administration for the treatment of patients with recurrent GBM in 2009. This neoplastic angiogenesis-targeting drug3 demonstrated an improvement in progression-free survival (PFS) from the 15% historical control rate to 42.6% and 29% in separate phase II clinical trials.4,5 Although bevacizumab is quickly becoming standard treatment for recurrent GBM, it has become increasingly clear that standard pre- and postcontrast anatomical imaging methods, which have been used to measure tumor volumes and, thus, treatment responses, are no longer adequate.6,7 Bevacizumab decreases vessel permeability,8 which results in diminished contrast agent extravasation.9 This decreases the enhancing tumor volume. Unfortunately, this does not necessarily reflect a tumor's true biological response.10 Therefore, alternative imaging methods beyond blood-brain barrier disruption are being explored as more direct indicators of tumoral responses to anti-angiogenic treatments. In a recent article, the change in T2w signal was shown to be associated with greater survival,11 and another study showed that histogram-based changes in apparent diffusion coefficient (ADC) correlated with response and, subsequently, longer PFS.12 In addition, single-threshold and graded functional diffusion maps derived from serial changes in ADC have shown sensitivity to treatment response.13,14 Additionally, researchers have noticed that the presence of bevacizumab-induced calcification predicts overall survival (OS).15 Although these methods have proven to be effective for predicting response to treatment, they are insensitive to vascular change, which is the mechanistic target of bevacizumab treatment. Measures of relative cerebral blood volume (rCBV) have been shown to be sensitive to tumor grade,16–18 predictive of survival,19 and able to distinguish regions of contrast agent enhancement resulting from treatment effects (particularly postradiation changes) from those due to recurrent or residual tumor.20,21 More recently, MRI perfusion parameters, which include rCBV, contrast agent volume transfer coefficient (Ktrans), and vessel size index, have demonstrated the potential to reflect a condition termed vascular normalization.22,23 Although physiologic angiogenesis, such as that which occurs with wound healing, results in the formation of well-ordered, mature vessels, pathologic angiogenesis results in the formation of chaotic and immature arterioles and venules.24 Vascular normalization is thought to occur when a tumor's chaotic vasculature becomes more ordered and efficient, such as that of normal vasculature, resulting in more efficient delivery of oxygen and cytotoxic drugs to tumor.25 Imaging biomarkers sensitive to these vascular changes may provide an additional measure of biologic response. In this study, we used independent component analysis (ICA) to measure the temporal characteristics of contrast agent perfusing through brain tumor and normal vasculature. ICA is an emerging technique in functional MRI (fMRI) data processing that takes a data-driven, multivariate approach to categorize voxel time series by examining voxels exhibiting the same temporal response patterns. After its first use in fMRI,26 ICA has been used in many fMRI and EEG applications studying brain activation. ICA applied to dynamic susceptibility contrast (DSC) MRI in patients with brain tumors has shown the ability to separate tumor from normal vasculature and distinguish perfusion patterns in GBM from those in meningioma.27 This study uses ICA to classify voxels on the basis of stage delays of contrast agent perfusion through different vessel types.28 We hypothesized that abnormal vasculature classified in both venous and arterial ICA components (ie, arterio-venous overlap [AVOL]) exists in greater proportions in contrast-enhancing tumor, compared with normal brain vasculature. We additionally hypothesized that vessels of this nature may benefit from treatment with bevacizumab and that effective treatment would be characterized by an overall decrease in the volume of AVOL. To address these hypotheses, we applied ICA to DSC-MRI data collected in untreated patients with GBM (dataset A) to determine the proportion of AVOL in ICA-classified normal and tumor vasculature. An additional mutually exclusive dataset (dataset B) was processed before and after bevacizumab treatment in patients with recurrent grades III and IV glioma to determine whether changes in AVOL are predictive of OS.