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3D variable‐density SPARKLING trajectories for high‐resolution T2*‐weighted magnetic resonance imaging
Author(s) -
Lazarus Carole,
Weiss Pierre,
El Gueddari Loubna,
Mauconduit Franck,
Massire Aurélien,
Ripart Mathilde,
Vignaud Alexandre,
Ciuciu Philippe
Publication year - 2020
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.4349
Subject(s) - k space , physics , isotropy , sampling (signal processing) , nuclear magnetic resonance , image resolution , stack (abstract data type) , magnetic resonance imaging , projection (relational algebra) , compressed sensing , computer science , resolution (logic) , algorithm , optics , artificial intelligence , detector , quantum mechanics , fourier transform , medicine , radiology , programming language
We have recently proposed a new optimization algorithm called SPARKLING (Spreading Projection Algorithm for Rapid K‐space sampLING) to design efficient compressive sampling patterns for magnetic resonance imaging (MRI). This method has a few advantages over conventional non‐Cartesian trajectories such as radial lines or spirals: i) it allows to sample the k‐space along any arbitrary density while the other two are restricted to radial densities and ii) it optimizes the gradient waveforms for a given readout time. Here, we introduce an extension of the SPARKLING method for 3D imaging by considering both stacks‐of‐SPARKLING and fully 3D SPARKLING trajectories. Our method allowed to achieve an isotropic resolution of 600 μ m in just 45 seconds for T 2∗ ‐weighted ex vivo brain imaging at 7 Tesla over a field‐of‐view of 200 × 200 × 140 m m 3 . Preliminary in vivo human brain data shows that a stack‐of‐SPARKLING is less subject to off‐resonance artifacts than a stack‐of‐spirals.