Diffusion-Weighted MRI as a Biomarker of Tumor Radiation Treatment Response Heterogeneity: A Comparative Study of Whole-Volume Histogram Analysis versus Voxel-Based Functional Diffusion Map Analysis

AbstractRATIONALE: Treatment of glioblastoma (GBM) remains challenging due in part to its histologic intratumoral heterogeneity that contributes to its overall poor treatment response. Our goal was to evaluate a voxel-based biomarker, the functional diffusion map (fDM), as an imaging biomarker to detect heterogeneity of tumor response in a radiation dose escalation protocol using a genetically engineered murine GBM model. EXPERIMENTAL DESIGN: Twenty-four genetically engineered murine GBM models [Ink4a-Arf-/-/Ptenloxp/loxp/Ntv-a RCAS/PDGF(+)/Cre(+)] were randomized in four treatment groups (n = 6 per group) consisting of daily doses of 0, 1, 2, and 4 Gy delivered for 5 days. Contrast-enhanced T1-weighted and diffusion-weighted magnetic resonance imaging (MRI) scans were acquired for tumor delineation and quantification of apparent diffusion coefficient (ADC) maps, respectively. MRI experiments were performed daily for a week and every 2 days thereafter. For each animal, the area under the curve (AUC) of the percentage change of the ADC (AUCADC) and that of the increase in fDM values (AUCfDM+) were determined within the first 5 days following therapy initiation. RESULTS: Animal survival increased with increasing radiation dose. Treatment induced a dose-dependent increase in tumor ADC values. The strongest correlation between survival and ADC measurements was observed using the AUCfDM+ metric (R2 = 0.88). CONCLUSION: This study showed that the efficacy of a voxel-based imaging biomarker (fDM) was able to detect spatially varying changes in tumors, which were determined to be a more sensitive predictor of overall response versus whole-volume tumor measurements (AUCADC). Finally, fDM provided for visualization of treatment-associated spatial heterogeneity within the tumor