Linked Life Data

12164584

Source:http://linkedlifedata.com/resource/pubmed/id/12164584

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
13
pubmed:dateCreated
2002-8-7
pubmed:abstractText
Complex intensity patterns generated by traditional beamlet-based inverse treatment plans are often very difficult to deliver. In the approach presented in this work the intensity maps are controlled by pre-defining field segments to be used for dose optimization. A set of simple rules was used to define a pool of allowable delivery segments and the mixed-integer programming (MIP) method was used to optimize segment weights. The optimization problem was formulated by combining real variables describing segment, weights with a set of binary variables, used to enumerate voxels in targets and critical structures. The MIP method was compared to the previously used Cimmino projection algorithm. The field segmentation approach was compared to an inverse planning system with a traditional beamlet-based beam intensity optimization. In four complex cases of oropharyngeal cancer the segmental inverse planning produced treatment plans, which competed with traditional beamlet-based IMRT plans. The mixed-integer programming provided mechanism for imposition of dose-volume constraints and allowed for identification of the optimal solution for feasible problems. Additional advantages of the segmental technique presented here are: simplified dosimetry, quality assurance and treatment delivery.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
0031-9155
pubmed:author
pubmed:issnType
Print
pubmed:day
7
pubmed:volume
47
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2235-45
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
The use of mixed-integer programming for inverse treatment planning with pre-defined field segments.
pubmed:affiliation
Department of Radiation Oncology, Kimmel Cancer Center of the Jefferson Medical College, Thomas Jefferson University, Philadelphia, PA 19107, USA. Greg.Bednarz@mail.tju.edu
pubmed:publicationType
Journal Article, Comparative Study, Evaluation Studies