Linked Life Data

20171508

Source:http://linkedlifedata.com/resource/pubmed/id/20171508

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3 Suppl
pubmed:dateCreated
2010-2-22
pubmed:abstractText
The actual distribution of radiation dose accumulated in normal tissues over the complete course of radiation therapy is, in general, poorly quantified. Differences in the patient anatomy between planning and treatment can occur gradually (e.g., tumor regression, resolution of edema) or relatively rapidly (e.g., bladder filling, breathing motion) and these undermine the accuracy of the planned dose distribution. Current efforts to maximize the therapeutic ratio require models that relate the true accumulated dose to clinical outcome. The needed accuracy can only be achieved through the development of robust methods that track the accumulation of dose within the various tissues in the body. Specific needs include the development of segmentation methods, tissue-mapping algorithms, uncertainty estimation, optimal schedules for image-based monitoring, and the development of informatics tools to support subsequent analysis. These developments will not only improve radiation outcomes modeling but will address the technical demands of the adaptive radiotherapy paradigm. The next 5 years need to see academia and industry bring these tools into the hands of the clinician and the clinical scientist.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1879-355X
pubmed:author
pubmed:copyrightInfo
Copyright 2010 Elsevier Inc. All rights reserved.
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
76
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S135-9
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Accurate accumulation of dose for improved understanding of radiation effects in normal tissue.
pubmed:affiliation
Princess Margaret Hospital, Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada. david.jaffray@rmp.uhn.on.ca
pubmed:publicationType
Journal Article, Review, Meta-Analysis