Linked Life Data

15690517

Source:http://linkedlifedata.com/resource/pubmed/id/15690517

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-2-3
pubmed:abstractText
Sensitivity encoding (SENSE) with a receiver coil array is typically used as a means of reducing the scan time in MRI. The speed benefit usually comes at some expense in terms of the signal-to-noise ratio (SNR) efficiency, which has been notorious as the main downside of SENSE and parallel MRI in general. In this work it is shown that in steady-state gradient-echo imaging the parallel approach may as well be used to increase the SNR efficiency. The basic idea is to balance reduced phase encoding by increasing the repetition time. In this fashion both the acquisition duty cycle and the steady-state magnetization can be enhanced, resulting in considerable net gains in SNR yield. It is argued that the reduction factor in parallel imaging is essentially an additional degree of freedom in optimizing the SNR. The optimal SENSE factor depends on scan, tissue, and hardware parameters, assuming values up to 3.0 and higher. The achievable SNR benefit also depends on the spoiling regime and is most pronounced for RF-spoiled techniques. The proposed mechanism is demonstrated by simulations and phantom experiments, as well as by contrast-enhanced angiography in vivo, achieving an approximate doubling of the SNR efficiency.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0740-3194
pubmed:author
pubmed:copyrightInfo
Copyright 2004 Wiley-Liss, Inc.
pubmed:issnType
Print
pubmed:volume
53
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
177-85
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Sensitivity encoding as a means of enhancing the SNR efficiency in steady-state MRI.
pubmed:affiliation
Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology Zurich, 8092 Zurich, Switzerland.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't