Mixed-Effects Modeling of Clinical DCE-MRI Data: Application to Colorectal Liver Metastases Treated With Bevacizumab

PurposeMost dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data are evaluated for individual patients with cohorts analyzed to detect significant changes from baseline values, repeating the process at each posttreatment timepoint. Our study aimed to develop a statistically valid model for the complete time course of DCE-MRI data in a patient cohort. Materials and MethodsData from 10 patients with colorectal cancer liver metastases were analyzed, including two baseline scans and four post-bevacizumab scans. Apparent changes in tumor median K-trans were adjusted for changes in observed enhancing tumor fraction (EnF) by multiplying K-trans by EnF (KEnF). A mixed-effects model (MEM) was defined to describe the KEnF time course for all patients simultaneously by assuming a three-parameter indirect response model with model parameters lognormally distributed across patients. ResultsThe typical cohort time course showed a KEnF reduction to 59% of baseline at 24 hours, returning to 65% of baseline values by day 12. Interpatient variability of model parameters ranged from 11% to 307%. ConclusionThe MEM approach has potential for comparing responses at a group level in clinical trials with different doses, schedules, or combination regimens. Furthermore, the KEnF biomarker successfully resolved confounds in interpreting K-trans arising from therapy induced changes in the volume of enhancing tumor. J. Magn. Reson. Imaging 2015;41:132-141. (c) 2014 Wiley Periodicals, Inc.