Dynamic contrast enhanced MRI (DCE MRI) for assessment of effects of anti-angiogenic therapy: Comparison of the transfer constant (Ktrans) to blood flow and permeability derived by a distributed parameters model

Abstract

14109 Background: Transfer constant (Ktrans) and IAUC60 normalized with arterial input function are commonly used dynamic contrast enhanced magnetic resonance imaging (DCE MRI) parameters. The distributed parameters model (DP) is a DCE MRI model that enables derivation of blood flow and capillary permeability-surface area product (PS). We aim to study the distributed parameters model as an alternative method of angiogenesis assessment and correlate the above parameters to drug exposure and patient outcome in a Phase I anti- angiogenic trial. Methods: Fifteen evaluable patients from an on-going Phase I trial (ABT 869) with 3 dose escalations formed the study population. Pharmacokinetic study was performed on Day 1 and the area under the concentration time curve extrapolated to infinity (AUCinfinity) was used as an indicator of drug exposure. All patients underwent DCE MRI at baseline, Day 3 and Day 15 with temporal resolution of 4 seconds. Gadolinium concentrations were estimated using a dual flip angle method. Patients demonstrating progressive disease in first 2 evaluation scans (cycle 2 or 4) based on RECIST criteria were considered progressors and all other patients non-progressors. Receiver operating curve (ROC) analysis was performed. Correlation with AUCinfinity was analyzed. Results: There is good correlation (Spearman’s coefficient -0.67, p = 0.008) between AUCinfinity and DP derived PS and less strong correlation with normalized IAUC60 (Spearman’s coefficient -0.57, p = 0.03). There is no correlation for Ktrans (Spearman’s coefficient 0.04). ROC analysis for predicting progressors versus non-progressors showed a higher ROC area for PS compared to Ktrans (0.83 versus 0.47, p = 0.037). Normalized IAUC60 showed a slightly lower area compared to PS (0.77 versus 0.83) but the difference is not significant (p = 0.58). Conclusions: PS derived from DP model shows better correlation with drug exposure and may predict patient outcome better than Ktrans. [Table: see text]