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This review explores non-Cartesian magnetic resonance imaging (MRI) trajectories for faster imaging. It details their implementation and evaluates performance, offering insights for rapid prototyping in MRI applications.

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Computer-Aided Diagnosis

Background:

  • Magnetic resonance imaging (MRI) is crucial for diagnosing diseases.
  • Cartesian k-space trajectories are standard but less time-efficient.
  • Non-Cartesian trajectories offer speed improvements but require complex reconstruction.

Purpose of the Study:

  • To review non-Cartesian k-space trajectories for rapid prototyping and implementation.
  • To provide practical examples and implementation guidance for 2D and 3D trajectories.
  • To assess the performance of different non-Cartesian trajectories in MRI.

Main Methods:

  • Survey of 2D and 3D non-Cartesian k-space trajectories with analytical equations.
  • Implementation of radial and spiral trajectories (standard, golden angle, tiny golden angle) using open-source software (Pulseq).
  • Acquisition of phantom and in-vivo brain data, followed by reconstruction and signal-to-noise ratio assessment.

Main Results:

  • Demonstrated implementation of various non-Cartesian trajectories.
  • Quantified and assessed signal-to-noise ratios for different reconstruction methods.
  • Provided a practical framework for rapid prototyping of advanced MRI sequences.

Conclusions:

  • Non-Cartesian trajectories are viable for efficient MRI acquisition and prototyping.
  • Open-source tools facilitate the implementation and evaluation of these advanced techniques.
  • This work supports the development of faster and potentially more effective MRI diagnostics.