Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1999-6-21
pubmed:abstractText
Radioactive decay during measurement can be accounted for by either a decay correction of the measured data before modeling (DbM) or by direct implementation of decay into the pharmacokinetic model (DiM). The purpose of this study was to quantify the influence of the type of decay correction on the calculated parameters for the example of a three-compartment model used for the calculation of myocardial perfusion with 13N ammonia and positron emission tomography (PET). For a given input function [Ca(t)infinity t exp(-kt), k= 1.72/min] the tissue uptake for two parameter sets of K1, k2, k3, TBV were calculated for 20 frames (12 x 10 s, 4 x 30 s, 3 x 120 s, 1 x 300 s). These values were mathematically deteriorated by various noise levels according to Poisson statistics and fitted by a Levenberg-Marquardt algorithm. Estimated parameter means and coefficients of variation of the fitted parameters were calculated for the DbM and DiM case. The estimated parameter means for both decay correction methods were of comparable quality. The important measure for a single fit is the relative variability of the fitted parameters. This value is up to a factor 1.15 smaller for K1 obtained with DiM and a reasonable noise level of 10%. Therefore, decay correction should be taken into account during modeling to reduce the variability in the fitted parameters.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0094-2405
pubmed:author
pubmed:issnType
Print
pubmed:volume
26
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
616-21
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Treatment of radioactive decay in pharmacokinetic modeling: influence on parameter estimation in cardiac 13N-PET.
pubmed:affiliation
Abteilung Nuklearmedizin, Universität Ulm, Germany. gerhard.glatting@medizin.uni-ulm.de
pubmed:publicationType
Journal Article