ADC quantification to classify patients candidate to receive bevacizumab treatment for recurrent glioblastoma

Abstract

Background

Recurrent high-grade gliomas progressing after surgery and temozolomide plus radiation therapy have traditionally been treated using antiangiogenic drugs as the first-line therapy. Since the phase 3 EORTC 26101 trial showed no significant benefit of administering antiangiogenic drugs, the need to identify a biomarker to classify subgroups of potential responders has increased.

Purpose

To investigate the feasibility of using apparent diffusion coefficient as a predictor of the response of recurrent high-grade gliomas to bevacizumab or classifier for patients showing better response.

Material and Methods

This retrospective study analyzed magnetic resonance images obtained from 39 patients at the time of high-grade glioma progression who were treated using bevacizumab. The apparent diffusion coefficient maps were quantified and modelled as a mixture of Gaussian functions. The correlation of their descriptors and the time to second progression was studied. Log-rank tests were performed to determine the power of these descriptors as the classifiers for patients exhibiting better survival.

Results

None of the descriptors showed correlation with time to second progression (r < 0.35) but several of them stratified subgroups showing a better time to second progression passing log-rank tests (P < 0.02).

Conclusion

Apparent diffusion coefficient cannot be used to predict the time to second progression of recurrent high-grade gliomas treated with bevacizumab, but it can stratify groups with better time to second progression distributions.