Xia Li1, Lori R. Arlinghaus1, A. Bapsi chakravarthy1, E. Brian Welch1, Jaime Farley1, Ingrid A. Mayer1, Vandana G. Abramson1, Mark C. Kelley1, Ingrid M. Meszoely1, Julie A. Means-Powell1, Ana M. Grau1, Sandeep Bhave1, Thomas E. Yankeelov1
1Vanderbilt University Institute of Imaging Science, Nashville, TN, United States
To monitor tumor response to neoadjuvant chemotherapy, investigators have begun to employ the quantitative physiological parameters available from dynamic contrast enhanced MRI (DCE-MRI). However, most studies track the changes in average parameter values obtained from the whole tumor region of interest, thereby discarding all spatial information on tumor heterogeneity. In this study, we applied a novel registration algorithm to longitudinal DCE-MRI data and performed a voxel-by-voxel analysis. The results indicate that voxel-based analysis, after longitudinal registration, may improve the ability of DCE-MRI to separate pathologic complete responders from non-responders after one cycle of therapy when using the fast exchange regime model.