Yi Guo1, Sajan Goud Lingala1, Yinghua Zhu1, R. Marc Lebel2, and Krishna S Nayak1
1Electrical Engineering, University of Southern California, Los Angeles, CA, United States, 2GE Healthcare, Calgary, AB, Canada
parameter maps derived from DCE-MRI provide quantitative physiological
information that aids in cancer diagnosis and assessment of treatment response.
Recently, direct reconstruction of PK maps from under-sampled k,t-space has
shown great potential to provide optimal detection of kinetic parameter maps
from an information theoretic perspective. We build on prior work (using the
Patlak model) and demonstrate direct reconstruction of kinetic parameter maps
using the extended-Tofts model, which is a more appropriate model in brain
tumor. We demonstrate convergence behavior, computational efficiency, and
application to brain DCE-MRI.