3D variable‐density SPARKLING trajectories for high‐resolution T2*‐weighted magnetic resonance imaging. (1st July 2020)

• Record Type: Journal Article
• Authors: Lazarus, Carole; Weiss, Pierre; El Gueddari, Loubna; Mauconduit, Franck; Massire, Aurélien; Ripart, Mathilde; Vignaud, Alexandre; Ciuciu, Philippe
• Is Part Of: NMR in biomedicine. Volume 33:Number 9(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-07-01
• Subjects: acceleration -- compressed sensing -- non‐Cartesian -- optimization -- SWI -- 3D MRI; Nuclear magnetic resonance -- Periodicals; Magnetic Resonance Spectroscopy -- Periodicals; 574
• DOI: 10.1002/nbm.4349
• Languages: English
• ISSNs: 0952-3480

Abstract

Abstract : 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 T2∗‐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. Abstract : In this work, we show the extension of the non‐Cartesian SPARKLING (Spreading Projection Algorithm for Rapid K‐space sampLING) sampling method to 3D MR imaging. We use both stack‐of‐SPARKLING and fully 3D SPARKLING trajectories to acquire T2∗‐weighted high‐resolution 3D images at 7 Tesla. We show that our method preserves the image quality even for short scan times and compare it to conventional non‐Cartesian variable‐density 3D sampling.