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  1. Home
  3. Laterally Oscillating Trajectory For Undersampling Slices: Lotus.
  1. Home
  3. Laterally Oscillating Trajectory For Undersampling Slices: Lotus.

Related Experiment Video

Modified Roller Tube Method for Precisely Localized and Repetitive Intermittent Imaging During Long-term Culture of Brain Slices in an Enclosed System
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Modified Roller Tube Method for Precisely Localized and Repetitive Intermittent Imaging During Long-term Culture of Brain Slices in an Enclosed System

Published on: December 28, 2017

Laterally Oscillating Trajectory for Undersampling Slices: LOTUS.

Mayuri Sothynathan1,2, Paul I Dubovan3,4, Corey A Baron1,5

  • 1Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, Western University, London, Ontario, Canada.

Magnetic Resonance in Medicine
|June 10, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

A new diffusion MRI technique, Laterally Oscillating Trajectory for Undersampling Slices (LOTUS), improves image quality and reduces scan time by enabling faster simultaneous multislice imaging. This method minimizes g-factor for better diffusion MRI data acquisition.

Keywords:
diffusion MRIg‐factornon‐Cartesiansimultaneous multislicespiral

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Area of Science:

  • Medical Imaging
  • Magnetic Resonance Imaging (MRI)
  • Diffusion MRI

Background:

  • Spiral sampling in diffusion MRI offers signal-to-noise ratio (SNR) benefits.
  • Simultaneous multislice (SMS) acceleration in diffusion MRI is crucial for reducing scan times.
  • Exploration of SMS acceleration with spiral trajectories remains limited.

Purpose of the Study:

  • Introduce Laterally Oscillating Trajectory for Undersampling Slices (LOTUS), a novel 3D spiral-like k-space trajectory.
  • Minimize g-factor through controlled incoherent aliasing for improved image reconstruction.
  • Develop a constrained reconstruction approach for robust g-factor estimation in non-Cartesian reconstructions.

Main Methods:

  • Simulated data acquisition using LOTUS and other trajectories on a numerical phantom.
  • In vivo diffusion-weighted brain MRI acquisition in two subjects with varying acceleration factors (in-plane and slice).
  • Quantitative and qualitative comparison of trajectory performance using g-factor maps and fractional anisotropy (FA) maps, with and without compressed sensing.

    • Main Results:

    • Simulations demonstrated reduced g-factor (20%-31%) and improved reconstruction accuracy with LOTUS compared to other trajectories.
    • In vivo acquisitions showed g-factor benefits and qualitative image quality improvements consistent with simulations.
    • LOTUS performance improvements increased with higher numbers of simultaneous slices in both simulations and in vivo data.

    Conclusions:

    • LOTUS enables higher rates of slice acceleration in diffusion MRI.
    • This acceleration capability has the potential to significantly decrease overall scan time.
    • The findings highlight LOTUS as a promising technique for efficient diffusion MRI acquisition.