Linked Life Data

19785020

Source:http://linkedlifedata.com/resource/pubmed/id/19785020

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2009-11-30
pubmed:abstractText
Gliomas are the most common primary brain tumors and the majority are highly malignant, with one of the worst prognoses for patients. Gliomas are characterized by invasive growth into normal brain tissue that makes complete surgical resection and accurate radiotherapy planning extremely difficult. We have performed independent component analysis of magnetic resonance spectroscopy imaging data from human gliomas to segment brain tissue into tumor core, tumor infiltration, and normal brain, with confirmation by diffusion tensor imaging analysis. Our data are consistent with previous studies that compared anomalies in isotropic and anisotropic diffusion images to determine regions of potential glioma infiltration. We show that coefficients of independent components can be used to create colored images for easy visual identification of regions of infiltrative tumor growth.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1522-2594
pubmed:author
pubmed:copyrightInfo
(c) 2009 Wiley-Liss, Inc.
pubmed:issnType
Electronic
pubmed:volume
62
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1646-51
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Pattern recognition of MRSI data shows regions of glioma growth that agree with DTI markers of brain tumor infiltration.
pubmed:affiliation
Division of Basic Medical Sciences, St George's University of London, London, England. awright@sgul.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Evaluation Studies