  Magnetic Resonance Spin Tomography in Time-Domain (MR-STAT) is a
multiparametric quantitative MR framework, which allows for simultaneously
acquiring quantitative tissue parameters such as T1, T2 and proton density from
one single short scan. A typical 2D MR-STAT acquisition uses a
gradient-spoiled, gradient-echo sequence with a slowly varying RF flip-angle
train and Cartesian readouts, and the quantitative tissue maps are
reconstructed by an iterative, model-based optimization algorithm. In this
work, we design a 3D MR-STAT framework based on previous 2D work, in order to
achieve better image SNR, higher though-plan resolution and better tissue
characterization. Specifically, we design a 7-minute, high-resolution 3D
MR-STAT sequence, and the corresponding two-step reconstruction algorithm for
the large-scale dataset. To reduce the long acquisition time, Cartesian
undersampling strategies such as SENSE are adopted in our transient-state
quantitative framework. To reduce the computational burden, a data splitting
scheme is designed for decoupling the 3D reconstruction problem into
independent 2D reconstructions. The proposed 3D framework is validated by
numerical simulations, phantom experiments and in-vivo experiments.
High-quality knee quantitative maps with 0.8 x 0.8 x 1.5mm3 resolution and
bilateral lower leg maps with 1.6mm isotropic resolution can be acquired using
the proposed 7-minute acquisition sequence and the 3-minute-per-slice decoupled
reconstruction algorithm. The proposed 3D MR-STAT framework could have wide
clinical applications in the future.
