Laterally Oscillating Trajectory for Undersampling Slices: LOTUS
Mayuri Sothynathan, Paul I. Dubovan, Corey. A. Baron

TL;DR
LOTUS is a novel 3D spiral-like trajectory for diffusion MRI that reduces g-factor noise amplification and improves image quality at high slice acceleration rates, enabling faster scans.
Contribution
This paper introduces LOTUS, a new trajectory design that minimizes g-factor in undersampled diffusion MRI, with a robust g-factor estimation method for non-Cartesian reconstructions.
Findings
LOTUS reduces g-factor by 20-31% at high undersampling rates.
LOTUS improves image quality metrics like SSIM and entropy.
Higher slice acceleration enhances LOTUS's benefits.
Abstract
Purpose: While spiral sampling offers SNR advantages for diffusion MRI, its acceleration with simultaneous multislice remains relatively unexplored. This study introduces Laterally Oscillating Trajectory for Undersampling Slices (LOTUS), which is a 3D spiral-like k-space trajectory that aims to minimize g-factor via controlled incoherent aliasing. To aid in validation, we also introduce a robust method to estimate g-factor for iterative non-Cartesian reconstructions. Methods: Simulated data sampling of a numerical phantom was performed using LOTUS and several acquisition schemes proposed by others to quantitatively compare the resulting image quality when compared to a known ground truth. Diffusion-weighted in vivo brain data from two subjects was acquired with two in-plane acceleration factors (2x and 4x), and two slice acceleration factors (2x and 4x). Estimated g-factor maps and…
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Taxonomy
TopicsAdvanced Neuroimaging Techniques and Applications · Advanced MRI Techniques and Applications · MRI in cancer diagnosis
