Model-based iterative reconstruction for single-shot EPI at 7T

Magn Reson Med. 2017 Dec;78(6):2250-2264. doi: 10.1002/mrm.26633. Epub 2017 Feb 10.

Abstract

Purpose: To describe a model-based reconstruction strategy for single-shot echo planar imaging (EPI) that intrinsically accounts for k-space nonuniformity, Nyquist ghosting, and geometric distortions during rather than before or after image reconstruction.

Methods: Ramp sampling and inhomogeneous B0 field-induced distortion cause the EPI samples to lie on a non-Cartesian grid, thus requiring the nonuniform fast Fourier transform. Additionally, a 2D Nyquist ghost phase correction without the need for extra navigator acquisition is included in the proposed reconstruction. Coil compression is also incorporated to reduce the computational load. The proposed method is applied to phantom and human brain MRI data.

Results: The results demonstrate that Nyquist ghosting and geometric distortions are reduced by the proposed reconstruction. The proposed 2D phase correction is superior to a conventional 1D correction. The reductions of both artifacts lead to improved temporal signal-to-noise ratio (tSNR). The virtual coil results suggest that the processing time can be reduced by up to 75%, with a mean tSNR loss of only 3.2% when using 8-virtual instead of 32-physical coils for twofold undersampled data.

Conclusion: The proposed reconstruction improves the quality (ghosting, geometry, and tSNR) of EPI without requiring calibration data for Nyquist ghost correction. Magn Reson Med 78:2250-2264, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Keywords: Nyquist ghost; geometric distortion; model-based reconstruction; single-shot EPI.

MeSH terms

  • Adult
  • Algorithms
  • Artifacts
  • Brain / diagnostic imaging
  • Calibration
  • Computer Simulation
  • Echo-Planar Imaging / methods*
  • Equipment Design
  • Female
  • Fourier Analysis
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging
  • Male
  • Models, Statistical
  • Phantoms, Imaging
  • Signal Transduction
  • Signal-To-Noise Ratio
  • Software