TU-D-207B-07: Radiomic Response Assessment for Recurrent Glioblastoma Treated with Bevacizumab in the BRAIN Trial

Authors


Abstract

Purpose:

To develop radiomic biomarkers for non-invasive response assessment of Bevacizumab (Avastin; Genentech) treatment in recurrent glioblastoma multiforme (GBM).

Methods:

We analyzed prospectively acquired data from the BRAIN trial. For 167 patients, we extracted 71 radiomic features each from normalized post-contrast T1-weighted and fluid attenuation inversion recovery (FLAIR) sequences at baseline (pretreatment), and at follow-ups of six and twelve weeks (post-treatment), respectively, where available. For every imaging modality and time point, we selected 10 comprehensive features using an unsupervised feature selection approach that did not take clinical outcomes into account to limit overfitting. We investigated these features in terms of their prognostic value for overall survival (OS), progression-free survival (PFS), as well as early and late progressors.

Results:

T1 and FLAIR features showed only low correlation at baseline (mean positive and negative Pearson correlation of - 0.13 and 0.3) indicating complementary effects of imaging modalities at the radiomic level. We identified a textural-heterogeneity feature (large area emphasis) that had higher prognostic value of OS at baseline as compared to conventional tumor volume (C-index 0.71 vs 0.52, p = 0.006). Highest prognostic value was observed for the delta difference between baseline and six week follow-up values for short-run lengths of image intensities (Cindex 0.86, p = 2×10−8). Radiomic features generally showed similar or lower performances for PFS. Comparing radiomic feature values of early and late progressors directly showed significant differences in tumor surface and textural features after correcting for multiple-testing (Wilcoxon rank sum test, p < 0.05).

Conclusion:

For the first time, our study allows the definition of radiomic response phenotypes of Bevacizumab treatment in recurrent GBM by leveraging high-quality prospective trial data. Importantly, our data suggests the increased benefit of measuring radiomic patient profiles longitudinally after treatment has been initiated to monitor progression and resistance for immediate intervention and treatment adaptation.

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