Purpose This study aimed to develop a new 3D dual‐echo rosette k‐space trajectory, specifically designed for UTE MRI applications. The imaging of the ultra‐short transverse relaxation time (uT2) of brain was acquired to test the performance of the proposed UTE sequence. Theory and Methods The rosette trajectory was developed based on rotations of a “petal‐like” pattern in the kx–ky plane, with oscillated extensions in the kz‐direction for 3D coverage. Five healthy volunteers underwent 10 dual‐echo 3D rosette UTE scans with various TEs. Dual‐exponential complex model fitting was performed on the magnitude data to separate uT2 signals, with the output of uT2 fraction, uT2 value, and long‐T2 value. Results The 3D rosette dual‐echo UTE sequence showed better performance than a 3D radial UTE acquisition. More significant signal intensity decay in white matter than gray matter was observed along with the TEs. The white matter regions had higher uT2 fraction values than gray matter (10.9% ± 1.9% vs. 5.7% ± 2.4%). The uT2 value was approximately 0.10 ms in white matter . Conclusion The higher uT2 fraction value in white matter compared to gray matter demonstrated the ability of the proposed sequence to capture rapidly decaying signals.

Magnetic particle imaging (MPI) is a relatively new medical imaging modality, which detects the nonlinear response of magnetic nanoparticles (MNPs) that are exposed to external magnetic fields. The system matrix (SM) method for MPI image reconstruction requires a time consuming system calibration scan prior to image acquisition, where a single MNP sample is measured at each voxel position in the field-of-view (FOV). The scanned sample has the maximum size of a voxel so that the calibration measurements have relatively poor signal-to-noise ratio (SNR). In this paper, we present the coded calibration scene (CCS) framework, where we place multiple MNP samples inside the FOV in a random or pseudo-random fashion. Taking advantage of the sparsity of the SM, we reconstruct the SM by solving a convex optimization problem with alternating direction method of multipliers using CCS measurements. We analyze the effects of filling rate, number of measurements, and SNR on the SM reconstruction using simulations and demonstrate different implementations of CCS for practical realization. We also compare the imaging performance of the proposed framework with that of a standard compressed sensing SM reconstruction that utilizes a subset of calibration measurements from a single MNP sample. The results show that CCS significantly reduces calibration time while increasing both the SM reconstruction and image reconstruction performances.

The proposed setup is suitable for FFL MPI imaging with an open bore configuration without the need for mechanical rotation, which is preferable for clinical usage in terms of imaging time and patient access. Further studies are necessary to determine the limitations imposed by peripheral nerve stimulation, and to optimize the system parameters and the sequence design.

Magnetic particle imaging (MPI) is a relatively new imaging modality that images the spatial distribution of superparamagnetic iron oxide nanoparticles administered to the body. In this study, we use a new method based on Alternating Direction Method of Multipliers (a subset of Augmented Lagrangian Methods, ADMM) with total variation and l1 norm minimization, to reconstruct MPI images. We demonstrate this method on data simulated for a field free line MPI system, and compare its performance against the conventional Algebraic Reconstruction Technique. The ADMM improves image quality as indicated by a higher structural similarity, for low signal-to-noise ratio datasets, and it significantly reduces computation time. Index Terms-Magnetic particle imaging, field free line, augmented Lagrangian method, algebraic reconstruction technique, alternating direction method of multipliers.