Linked Life Data

17627422

Source:http://linkedlifedata.com/resource/pubmed/id/17627422

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2007-7-13
pubmed:abstractText
Activity quantification in nuclear medicine imaging is highly desirable, particularly for dosimetry and biodistribution studies of radiopharmaceuticals. Quantitative (111)In imaging is increasingly important with the current interest in therapy using (90)Y radiolabeled antibodies. One of the major problems in quantification is scatter in the images, which leads to degradation of image quality. The aim of this study was to optimize the energy-window settings for quantitative (111)In imaging with a camera that enabled acquisition in three energy windows. Experimental measurements and Monte Carlo simulations, using the SI-MIND code, were conducted to investigate parameters such as sensitivity, image contrast, and image resolution. Estimated scatter-to-total ratios and distributions, as obtained by the different window settings, were compared with corresponding simulations. Results showed positive agreement between experimental measurements and results from simulations, both quantitatively and qualitatively. We conclude that of the investigated methods, the optimal energy-window setting was two windows centered at 171 and 245 keV, together with a broad scatter window located between the photopeaks.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1084-9785
pubmed:author
pubmed:issnType
Print
pubmed:volume
22
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
136-42
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Optimization of energy-window settings for scatter correction in quantitative (111)In imaging: comparison of measurements and Monte Carlo simulations.
pubmed:affiliation
Joint Department of Physics, Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK. maria.holstensson@icr.ac.uk
pubmed:publicationType
Journal Article, Comparative Study