Linked Life Data

16896702

Source:http://linkedlifedata.com/resource/pubmed/id/16896702

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2006-11-24
pubmed:abstractText
Our aim was to evaluate quantitative parametric analysis for characterization of breast lesions in contrast-enhanced magnetic resonance (MR) mammography. In 62 patients, contrast-enhanced MR mammography revealed 75 suspicious lesions, of which 18 were benign and 57 were malignant. The quantitative parametric analysis delineates signal intensity changes of contrast-enhanced lesions on a pixel-by-pixel basis. The initial rate of enhancement is coded by color intensity: a slow rate is coded to dark; a fast rate, bright. The postinitial enhancement change is coded by color hue: blue for increasing signal intensity, green for plateau, and red for decrease in signal intensity. Malignant lesions showed a significantly higher number of bright-red (P = 0.004) and medium-red (P < 0.001) pixels than benign lesions. Benign lesions showed significantly more blue pixels than did malignant lesions (P = 0.010). Of the 75 lesions, 72 (96%) showed heterogeneous distribution of pixel color hue. Quantitative parametric analysis of contrast kinetics in lesions can replace the subjective manual region of interest (ROI) method and makes a step toward standardization of MR mammography. It allows quantitative evaluation of different contrast kinetics parameters in contrast-enhanced breast lesions.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0938-7994
pubmed:author
pubmed:issnType
Print
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2834-41
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Evaluation of quantitative parametric analysis for characterization of breast lesions in contrast-enhanced MR mammography.
pubmed:affiliation
Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Hufelandstr 55, 45122 Essen, Germany. elke.hauth@uni-essen.de
pubmed:publicationType
Journal Article