Gadolinium-enhanced fat-suppressed T1-weighted imaging of the head and neck: Comparison of gradient and conventional SE sequences

Joshua A. Hirsch, Laurie A. Loevner, David M. Yousem, Evan S. Siegelman, Mark D. Keiper, Robert P. Marquis, Robert I. Grossman

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Purpose: The purpose of this study was to compare contrast-enhanced GRE and conventional SE (CSE) fat-suppressed T1-weighted techniques in the evaluation of head and neck lesions. A hybrid, opposed phase, frequency- selective, fat-suppressed fast multiplanar spoiled GRE (FMPSPGR) sequence was compared with a fat-suppressed CSE sequence. Method: Thirty-two patients with head and neck pathology were evaluated With both fat-suppressed CSE and FMPSPGR sequences. Regions of interest obtained by two viewers in consensus were used to establish contrast-to-noise (CNR) and signal-to-noise ratios for both sequences. Three neuroradiologists also independently reviewed the images for quality of fat suppression, lesion conspicuity, and potential pitfalls. Results: The CNR of the FMPSPGR sequence was superior to that of the fat-suppressed CSE sequence. Subjectively, all three reviewers rated the FMPSPGR sequence as having fat suppression equal to or better than that in the CSE sequence in 94% of cases. Imaging times for the FMPSPGR sequence were 60-75% faster than those for the CSE sequence. Conclusion: Enhanced imaging of the head and neck region using an Opposed phase, fat-suppressed GRE sequence results in improved fat suppression compared with the CSE technique, with substantial savings in imaging time.

Original languageEnglish (US)
Pages (from-to)771-776
Number of pages6
JournalJournal of Computer Assisted Tomography
Volume22
Issue number5
DOIs
StatePublished - 1998

Keywords

  • Chemical shift imaging
  • Fat suppression
  • Gradient echo imaging-Head, abnormalities
  • Magnetic resonance imaging
  • Neck, abnormalities

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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