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•A dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory was developed to accelerate the acquisition for fast simultaneous three-dimensional (3D) multiparametric mapping of whole brain myelin water fraction (MWF), T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+).•A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation (JMSE) algorithm was proposed to improve the quantification of MWF by correcting for the T1 saturation effect and B1+/B1− inhomogeneities.•By integrating the DFA-mGRE SOS sequence, the JMSE algorithm, the tissue-prior-based B1+ estimation algorithm, and the subspace-based reconstruction, our technique can provide robust multiparametric mapping of 3D whole brain MWF, T1, PD, R2*, QSM, and B1+ with a two-minute scan. A new MRI technique is presented for three-dimensional fast simultaneous whole brain mapping of myelin water fraction (MWF), T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+). Phantom and human (N = 9) datasets were acquired using a dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory. Images were reconstructed using a subspace-based algorithm with a locally low-rank constraint. A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation (JMSE) algorithm is proposed to correct for the T1 saturation effect and B1+/B1− inhomogeneities in the quantification of MWF. A tissue-prior-based B1+ estimation algorithm was adapted for B1 correction in the mapping of T1 and PD. In the phantom study, measurements obtained at an acceleration factor (R) of 12 using prospectively under-sampled SOS showed good consistency (R2 > 0.997) with Cartesian reference for R2*/T1app/M0app. In the in vivo study, results of retrospectively under-sampled SOS with R = 6, 12, 18, showed good quality (structure similarity index measure > 0.95) compared with those of fully-sampled SOS. Besides, results of prospectively under-sampled SOS with R = 12 showed good consistency (intraclass correlation coefficient > 0.91) with Cartesian reference for T1/PD/B1+/MWF/QSM/R2*, and good reproducibility (coefficient of variation < 7.0 %) in the test-retest analysis for T1/PD/B1+/MWF/R2*. This study has demonstrated the feasibility of simultaneous whole brain multiparametric mapping with a two-minute scan using the DFA-mGRE SOS sequence, which may overcome a major obstacle for neurological applications of multiparametric MRI.

To address the issue of steering vector mismatch, a robust adaptive beamforming design via steering vector optimization is proposed in this paper. Different from conventional studies, this paper resolves the exact desired signal (DS) steering vector through formulating an array output power maximization problem subjected to noise subspace (NS) based and interference subspace (IS) based constraints. Under the condition that the NS is ready to be attained while the IS is hard to be got, two efficient interference-plus-noise covariance matrix (INCM) reconstruction means, i.e. direct DS matrix removal from sample covariance matrix and indirect DS blocking from training data and matrix transition, are derived to estimate the IS with high accuracy. Herein, after resolving DS steering vector, the weight vectors are thereby extracted with orthogonal projection (OP) criterion. Numerical simulations verify that the devised methods can outperform the existing ones and obtain almost optimal performance across a wide range of DS power.