Linked Life Data

17290132

Source:http://linkedlifedata.com/resource/pubmed/id/17290132

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2007-2-9
pubmed:abstractText
Ultrasound perfusion imaging of the human brain is a bedside technique based on the detection of ultrasound contrast agent (UCA) in the cerebral microcirculation. In the last decade, ultrasound technology improved from single-pulse harmonic imaging to multiple-pulse technologies (pulse inversion or power modulation harmonic imaging as well as contrast pulse sequencing), with a further dramatic increase of the contrast-agent-to-tissue ratio. Different kinetic models for the qualitative assessment of brain perfusion have been evaluated so far in healthy subjects as well as in patients suffering from acute ischemic stroke. The analysis of the contrast bolus kinetics yields robust time-intensity curve parameters, which qualitatively describe regional brain perfusion. In the acute phase of ischemic stroke, the peak signal increase and the time-to-peak intensity are the most valuable curve parameters to predict the area of definite infarction and the outcome of the patient. Color-coded parametric imaging of these parameters facilitates the interpretation of contrast kinetics in analyzing brain perfusion. UCA-specific kinetic models, such as replenishment and diminution kinetics, are new modalities for the qualitative visualization of brain perfusion. The latter is more promising for acute ischemic stroke patients because of the faster imaging and processing time, leading to a lower vulnerability to movement artifacts.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1660-4431
pubmed:author
pubmed:issnType
Print
pubmed:volume
21
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
127-39
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Acute stroke: perfusion imaging.
pubmed:affiliation
Neurologische Universitätsklinik, Lübeck, Germany. guenter.seidel@neuro.uni-luebeck.de
pubmed:publicationType
Journal Article, Review