Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2000-5-16
pubmed:abstractText
In this study a semi-automated and observer-independent algorithm for quantifying post-stenotic signal loss (PSL) in 3D phase-contrast (PC) magnetic resonance angiography (MRA) of patients with renal artery stenosis is presented. This algorithm was developed on MRA datasets of stenotic phantoms, which were included in a flow circuit with stationary flows. The length and the severity of the PSL (incorporating both length and degree of PSL) in the maximum intensity projections (MIPs) of MRA datasets were proposed for quantifying stenoses. The algorithm was tested in renal arteries of ten patients with renal artery stenosis and seven healthy volunteers. Digital subtraction angiography (DSA) was performed in the patients and served as the gold standard. Stenosis severity showed better correlation with the severity of the PSL than with the length, both for in vitro as in vivo. Spearman correlation coefficients (rS) showed statistically significant correlations between the severity of the PSL and parameters determined by DSA, i.e. percent diameter stenosis (rS = 0.90). The length of the PSL showed no correlation with the diameter stenosis (rS = 0.37).
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0167-9899
pubmed:author
pubmed:issnType
Print
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
483-93
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Stenosis quantification from post-stenotic signal loss in phase-contrast MRA datasets of flow phantoms and renal arteries.
pubmed:affiliation
Division of Image Processing, Leiden University Medical Center, The Netherlands.
pubmed:publicationType
Journal Article, Clinical Trial, Comparative Study