Linked Life Data

10436196

Source:http://linkedlifedata.com/resource/pubmed/id/10436196

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
1999-10-7
pubmed:abstractText
The aim of the study was to examine the physiological relevance of factors produced by a modified procedure for factor analysis of dynamic renal studies. Factor analysis has been applied locally to subsets of dynamic renal data which were well defined in both space and time domains. Optimised factor images resulting from different subsets were used as fuzzy regions of interest (ROIs) for the extraction of time-activity curves corresponding to renal parenchyma, renal pelvis, vascular and spatially homogeneous background. The original procedure employed the factor images of renal parenchyma and pelvis resulting from an analysis of the interval between the peaks of parenchymal and pelvic curves. In an attempt to improve the separation of renal parenchyma and pelvis, new fuzzy ROIs were used. They correspond to the factor image of renal uptake obtained from the analysis of the early phase of the study, and to the factor image of the renal pelvis obtained from the outflow phase. The curves generated with the new fuzzy ROIs were compared with those of the original procedure and tested for the presence of known artefacts inconsistent with the expected physiological behaviour. Unlike with the original procedure, no such artefacts were found. The most striking difference was that the pelvic factor curves did not start from zero time of the study but exhibited a physiologically correct initial horizontal zero segment the length of which correlated closely with the minimum parenchymal transit time (r=0.79, n=46, P<0.001). The new method permits easy and reliable application of factor analysis to dynamic renal studies. Problems which remain to be solved are user-independent identification of the optimum factors and suboptimal performance of the method under extreme conditions. Our results provide additional evidence that factor analysis can extract physiologically relevant information quantitatively from dynamic scintigraphic data.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0340-6997
pubmed:author
pubmed:issnType
Print
pubmed:volume
26
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
837-43
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Improved automatic separation of renal parenchyma and pelvis in dynamic renal scintigraphy using fuzzy regions of interest.
pubmed:affiliation
Ludwig Boltzmann Institute of Nuclear Medicine, Vienna, Austria.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't