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Three‐dimensional Yarnball k‐space acquisition for accelerated MRI
Author(s) -
Stobbe Robert W.,
Beaulieu Christian
Publication year - 2021
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.28536
Subject(s) - undersampling , artifact (error) , voxel , sampling (signal processing) , trajectory , computer science , projection (relational algebra) , mathematics , deconvolution , human head , point (geometry) , function (biology) , physics , artificial intelligence , algorithm , computer vision , geometry , optics , filter (signal processing) , astronomy , evolutionary biology , absorption (acoustics) , biology
Purpose To introduce an efficient sampling technique named Yarnball, which may serve as a direct alternative to 3D Cones. Methods Yarnball evolves through 3D k‐space with increasing loop size, and the differential equations defining this flexible trajectory are presented in detail. The sampling efficiencies of Yarnball and 3D Cones were compared through point spread function analysis and simulated imaging (which highlights undersampling in the absence of other scanning effects). The feasibility of Yarnball implementation was demonstrated for fully sampled T 1 ‐weighted images of the human head at 3 T. Results The mostly large 3D loops of the Yarnball trajectory facilitate rapid sampling under peripheral nerve stimulation constraint, an advantage that increases with readout duration (T RO ). Point spread function analysis yielded 89% (T RO = 2 ms) and 77% (T RO = 10 ms) of Yarnball voxels with magnitude less than 0.01% of the point spread function peak. For 3D Cones, these values were only 52% and 29%. The 3D‐Cones technique required 1.4 times (T RO = 2 ms) and 1.8 times (T RO = 10 ms) more trajectories than Yarnball to produce simulated images of a sphere free from undersampling artifact. For a prolate spheroidal (head‐like) object, 1.75 times and 2.6 times more trajectories were required for 3D Cones. Yarnball produced 0.72 mm (1/2k max ) isotropic T 1 ‐weighted human brain images free from undersampling artifact in only 98 seconds at 3 T. Conclusion Yarnball demonstrated greater k‐space sampling efficiency than directly comparable 3D Cones, and may have value wherever 3D Cones has been considered. Yarnball may also have value in the context of rapid T 1 ‐weighted brain imaging.