LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

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

Photo from wikipedia

PURPOSE Non-Cartesian MRI with long arbitrary readout directions are susceptible to off-resonance artifacts due to patient induced B 0 $$ {B}_0 $$ inhomogeneities. This results in degraded image quality with… Click to show full abstract

PURPOSE Non-Cartesian MRI with long arbitrary readout directions are susceptible to off-resonance artifacts due to patient induced B 0 $$ {B}_0 $$ 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. THEORY The recently developed SPARKLING algorithm is extended to drastically diminish off-resonance artifacts by generating temporally smooth k-space sampling patterns. For doing so, the cost function which is optimized in SPARKLING is modified using a temporal weighting factor. Additionally, oversampling of the center of k-space beyond the Nyquist criteria is prevented through the use of gridded sampling in the region, enforced with affine constraints. METHODS Prospective k-space data was acquired at 3 T on new trajectories, and we show robustness to B 0 $$ {\mathrm{B}}_0 $$ inhomogeneities through in silico experiments by adding Δ B 0 $$ \Delta {\mathrm{B}}_0 $$  through artificial degradation of system B 0 $$ {\mathrm{B}}_0 $$ shimming. Later on, in vivo experiments were carried out to optimize parameters of the new improvements and benchmark the gain in performance. RESULTS The improved trajectories allowed for the recovery of signal dropouts observed on original SPARKLING acquisitions at larger B 0 $$ {\mathrm{B}}_0 $$ field inhomogeneities. Furthermore, imposing gridded sampling at the center of k-space provided improved reconstructed image quality with limited artifacts. CONCLUSION These advancements allowed us for nearly 4 . 62 × $$ 4.62\times $$ shorter scan time compared to GRAPPA-p4x1, allowing us to reach 600 µm isotropic resolution in 3D T 2 ∗ $$ {\mathrm{T}}_2^{\ast } $$ -w imaging in just 3.3 min at 3 T with negligible degradation in image quality.

Keywords: space sampling; space; algorithm; resonance artifacts; resonance; image

Journal Title: Magnetic resonance in medicine
Year Published: 2023

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.