Linked Life Data

11105046

Source:http://linkedlifedata.com/resource/pubmed/id/11105046

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2001-2-2
pubmed:abstractText
The purpose of this study was to assess heterogeneity of tumor microcirculation determined by dynamic contrast-enhanced magnetic resonance (MR) imaging and its prognostic value for tumor radiosensitivity and long-term tumor control using pixel-by-pixel analysis of the dynamic contrast enhancement. Sixteen patients with advanced cervical cancer were examined with dynamic contrast-enhanced MR imaging at the time of radiation therapy. Pixel-by-pixel statistical analysis of the ratio of post- to precontrast relative signal intensity (RSI) values in the tumor region was performed to generate pixel RSI distributions of dynamic enhancement patterns. Histogram parameters were correlated with subsequent tumor control based on long-term cancer follow-up (median follow-up 4.6 years; range 3.8-5.2 years). The RSI distribution histograms showed a wide spectrum of heterogeneity in the dynamic enhancement pattern within the tumor. The quantity of low-enhancement regions (10th percentile RSI < 2.5) significantly predicted subsequent tumor recurrence (88% vs. 0%, P = 0.0004). Discriminant analysis based on both 10th percentile RSI and pixel number (reflective of tumor size) further improved the prediction rate (100% correct prediction of subsequent tumor control vs. recurrence). These preliminary results suggest that quantification of the extent of poor vascularity regions within the tumor may be useful in predicting long-term tumor control and treatment outcome in cervical cancer. J. Magn. Reson. Imaging 2000;12:1027-1033.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1053-1807
pubmed:author
pubmed:copyrightInfo
Copyright 2000 Wiley-Liss, Inc.
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1027-33
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Pixel analysis of MR perfusion imaging in predicting radiation therapy outcome in cervical cancer.
pubmed:affiliation
Division of Radiation Oncology, Department of Radiology, The University of Iowa College of Medicine, Iowa City, Iowa 52242, USA. nina-mayr@uiowa.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.