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Fast spin‐echo MR imaging of the abdomen: Contrast optimization and artifact reduction
Author(s) -
Low Russell N.,
Hinks R. Scott,
Alzate Gregg D.,
Shimakawa Ann
Publication year - 1994
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.1880040502
Subject(s) - ghosting , image quality , artifact (error) , magnetic resonance imaging , echo time , nuclear medicine , contrast (vision) , k space , fast spin echo , spin echo , medicine , radiology , computer science , artificial intelligence , image (mathematics)
The effects of various fast spin‐echo (FSE) magnetic resonance (MR) imaging parameters and artifact reduction techniques on FSE image contrast and quality were studied. The authors performed 139 abdominal MR examinations, comparing standard FSE images (echo train length [ETL] = 8, echo space [E‐space] = 17 msec, bandwidth = ±16‐kHz) with FSE images with an ETL of 16 ( n = 22) or FSE images with a ±32‐kHz bandwidth and an E‐space of 11‐14 msec ( n = 22). FSE artifact reduction techniques were evaluated with spectral fat saturation ( n = 40) or with a new flow compensation FSE sequence ( n = 55). Images of liver lesions were reviewed qualitatively and with contrast‐to‐noise ratio (C/N) measurements. Decreasing the time of echo train sampling produced superior image quality, with increased anatomic sharpness, less image artifact, and improved liver‐lesion C/N. Images obtained with an ETL of 16 showed more image blurring and a 23% decrease in relative contrast and 28% decrease in relative C/N for liver tumors. Increasing the bandwidth reduced E‐space, producing a 12% decrease in background noise. Artifact reduction with fat saturation or flow compensation produced images with less ghosting artifact and superior overall image quality, with 39% and 20% increases in liver‐tumor C/N, respectively. FSE image quality and contrast in the depiction of hepatic disease can be optimized with careful selection of imaging parameters and the use of artifact reduction techniques.