T1-mapping from Variable Flip Angle Data Utilizing Constrained Model-based Reconstruction

Quantitative imaging techniques are a main topic of ongoing research in Magnetic Res-
onance Imaging (MRI). Current challenges involve the speed up of acquisition as well
as maintaining good accuracy. The present work describes a new accelerated T1 map-
ping method on the basis of model-based reconstruction for Variable Flip Angle (VFA)
data. The reconstruction problem is solved with an Iterative Regularized Gauss-Newton
(IRGN)-Total-Generalized-Variation (TGV) algorithm. Reconstructed parameter maps
for numerical, phantom, and in vivo knee data were in reasonable agreement with ref-
erence values up to a 12 fold acceleration. In order to minimize systematic errors it is
crucial to have knowledge of the exact flip angle distribution. The blurring at sharp
NMR-parameter changes provides an area for future improvements. In this context the
influence of the regularization functional could be subject of further investigations.