Rapid mono and biexponential 3D-T_1ρ mapping of knee cartilage using variational networks.

ABSTRACT: In this study we use undersampled MRI acquisition methods to obtain accelerated 3D mono and biexponential spin-lattice relaxation time in the rotating frame (T_1ρ) mapping of knee cartilage, reducing the usual long scan time. We compare the accelerated T_1ρ maps obtained by deep learning-based variational network (VN) and compressed sensing (CS). Both methods were compared with spatial (S) and spatio-temporal (ST) filters. Complex-valued fitting was used for T_1ρ parameters estimation. We tested with seven in vivo and six synthetic datasets, with acceleration factors (AF) from 2 to 10. Median normalized absolute deviation (MNAD), analysis of variance (ANOVA), and coefficient of variation (CV) were used for analysis. The methods CS-ST, VN-S, and VN-ST performed

SUBMITTER: Zibetti MVW 

PROVIDER: S-EPMC7645759 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature