Litcius/Paper detail

3D variable‐density SPARKLING trajectories for high‐resolution T2*‐weighted magnetic resonance imaging

Carole Lazarus, Pierre Weiss, Loubna El Gueddari, Franck Mauconduit, Aurélien Massire, Mathilde Ripart, Alexandre Vignaud, Philippe Ciuciu

2020NMR in Biomedicine24 citationsDOI

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 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.

Topics & Concepts

PhysicsSampling (signal processing)Isotropyk-spaceImage resolutionStack (abstract data type)Nuclear magnetic resonanceMagnetic resonance imagingResolution (logic)Projection (relational algebra)Compressed sensingComputer scienceOpticsAlgorithmArtificial intelligenceDetectorProgramming languageQuantum mechanicsFourier transformMedicineRadiologyAdvanced MRI Techniques and ApplicationsMedical Imaging Techniques and ApplicationsSparse and Compressive Sensing Techniques