Non-Cartesian 3D-SPARKLING vs Cartesian 3D-EPI encoding schemes for functional Magnetic Resonance Imaging at 7 Tesla.

The quest for higher spatial and/or temporal resolution in functional MRI (fMRI) while preserving a sufficient temporal signal-to-noise ratio (tSNR) has generated a tremendous amount of methodological contributions in the last decade ranging from Cartesian vs. non-Cartesian readouts, 2D vs. 3D acquisition strategies, parallel imaging and/or compressed sensing (CS) accelerations and simultaneous multi-slice acquisitions to cite a few.

Impact of field imperfections correction on BOLD sensitivity in 3D-SPARKLING fMRI data.

Purpose: Static and dynamic field imperfections are detrimental to functional MRI (fMRI) applications, especially at ultra-high magnetic fields (UHF). In this work, a field camera is used to assess the benefits of retrospectively correcting field perturbations on Blood Oxygen Level Dependent (BOLD) sensitivity in non-Cartesian three-dimensional (3D)-SPARKLING fMRI acquisitions.

Methods: fMRI data were acquired at 1 mm and for a 2.

Deep learning-assisted model-based off-resonance correction for non-Cartesian SWI.

Purpose: Patient-induced inhomogeneities in the static magnetic field cause distortions and blurring (off-resonance artifacts) during acquisitions with long readouts such as in SWI. Conventional versatile correction methods based on extended Fourier models are too slow for clinical practice in computationally demanding cases such as 3D high-resolution non-Cartesian multi-coil acquisitions.

Theory: Most reconstruction methods can be accelerated when performing off-resonance correction by reducing the number of iterations, compressed coils, and correction components.

Improving spreading projection algorithm for rapid k-space sampling trajectories through minimized off-resonance effects and gridding of low frequencies.

Purpose: Non-Cartesian MRI with long arbitrary readout directions are susceptible to off-resonance artifacts due to patient induced inhomogeneities. This results in degraded image quality with strong signal losses and blurring. Current solutions to address this issue involve correcting the off-resonance artifacts during image reconstruction or reducing inhomogeneities through improved shimming.

Iterative static field map estimation for off-resonance correction in non-Cartesian susceptibility weighted imaging.

Purpose: Patient-induced inhomogeneities in the magnetic field cause distortions and blurring during acquisitions with long readouts such as in susceptibility-weighted imaging (SWI). Most correction methods require collecting an additional field map to remove these artifacts.

Theory: The static field map can be approximated with an acceptable error directly from a single echo acquisition in SWI.

Optimizing Full 3D SPARKLING Trajectories for High-Resolution Magnetic Resonance Imaging.

The Spreading Projection Algorithm for Rapid K-space sampLING, or SPARKLING, is an optimization-driven method that has been recently introduced for accelerated 2D MRI using compressed sensing. It has then been extended to address 3D imaging using either stacks of 2D sampling patterns or a local 3D strategy that optimizes a single sampling trajectory at a time. 2D SPARKLING actually performs variable density sampling (VDS) along a prescribed target density while maximizing sampling efficiency and meeting the gradient-based hardware constraints.