Dixon Techniques in Spiral Trajectories With Off-Resonance Correction: A New Approach for Fat Signal Suppression Without Spatial-Spectral RF Pulses

Hisamoto Moriguchi, Jonathan S. Lewin, Jeffrey L. Duerk

Research output: Contribution to journalArticle

Abstract

Spiral imaging has recently gained acceptance in MR applications requiring rapid data acquisition. One of the main disadvantages of spiral imaging, however, is blurring artifacts that result from off-resonance effects. Spatial-spectral (SPSP) pulses are commonly used to suppress those spins that are chemically shifted from water and lead to off-resonance artifacts. However, SPSP pulses may produce nonuniform fat signal suppression or unwanted water signal suppression when applied in the presence of B0 field inhomogeneities. Dixon techniques have been developed as methods for water-fat signal decomposition in rectilinear sampling schemes since they can produce unequivocal water-fat signal decomposition even in the presence of B 0 inhomogeneities. This article demonstrates that three-point and two-point Dixon techniques can be extended to conventional spiral and variable-density spiral data acquisitions for unambiguous water-fat decomposition with off-resonance blurring correction. In the spiral three-point Dixon technique, water-fat signal decomposition and image deblurring are performed based on the frequency maps that are directly derived from the acquired images. In the spiral two-point Dixon technique, several predetermined frequencies are tested to create a frequency map. The newly proposed techniques can achieve more effective and more uniform fat signal suppression when compared to the conventional spiral acquisition method with SPSP pulses.

Original languageEnglish (US)
Pages (from-to)915-924
Number of pages10
JournalMagnetic resonance in medicine
Volume50
Issue number5
DOIs
StatePublished - Nov 1 2003

Keywords

  • Dixon
  • Fat suppression
  • Off-resonance correction
  • Spiral

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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