Retrospective quantification pharmacokinetics of clinical breast DCE-MRI using deep learning

Standard-of-care DCE-MRI suffers from a limited number of contrast phases and low temporal resolution, preventing the quantification of pharmacokinetic parameters. Quantitative DCE-MRI techniques have not yet been widely applied in the clinic due to the limited availability of specialized sequences and image reconstruction. To tackle this problem, we proposed to improve the temporal resolution of multi-phasic DCE-MRI by deep learning post-processing and demonstrated promising results in tumor delineation in the Duke-Breast-Cancer-MRI dataset.