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This is a Quantitative Study study.

September 17, 2025

Density optimization of low-discrepancy k-space trajectories for accelerated 2D single-point imaging

Key Points

Optimized k-space trajectories reduced scanning time significantly and enhanced imaging efficiency for clinical applications.
The simulation results indicate a promising reduction in acquisition times while maintaining image quality and coherence.
The method entails a 2D quasi-random sampling approach merged with a novel PSF optimization for artifact behavior reduction.
Faster imaging could expand the use of single-point imaging in clinical settings, addressing limitations presented by long acquisition times.

Abstract

Motivation: Single-point imaging (SPI) is highly effective for imaging short T2(*) relaxation times and regions of susceptibility, but suffers from long acquisition times. Goal(s): SPI methods inherently allow for versatile sampling and are therefore well suited for integration with reconstruction-based image acceleration methods. Approach: We present a 2D realization of a previously introduced 3D quasi-random sampling scheme with enhanced PSF optimization algorithm for coherent artifact behavior reduction. Results: The method was validated through simulations and phantom studies, showing promising results for faster and more efficient imaging. Impact: The clinical application of pure phase encoding methods as SPI and CSI is limited by the related long acquisition times. The presented optimized trajectories enable high undersampling and related reduction of scan time for broader clinical applications.

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Density optimization of low-discrepancy k-space trajectories for accelerated 2D single-point imaging

Key Points

Abstract

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