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The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques

Ottosson, Rickard; Engström, Per LU ; Sjostrom, David; Behrens, Claus F.; Karlsson, Anna; Knöös, Tommy LU and Ceberg, Crister LU (2009) Symposium of the Nordic-Association-of-Clinical-Physics In Acta Oncologica 48(2). p.233-237
Abstract
Pareto optimality is a concept that formalises the trade-off between a given set of mutually contradicting objectives. A solution is said to be Pareto optimal when it is not possible to improve one objective without deteriorating at least one of the other. A set of Pareto optimal solutions constitute the Pareto front. The Pareto concept applies well to the inverse planning process, which involves inherently contradictory objectives, high and uniform target dose on one hand, and sparing of surrounding tissue and nearby organs at risk (OAR) on the other. Due to the specific characteristics of a treatment planning system (TPS), treatment strategy or delivery technique, Pareto fronts for a given case are likely to differ. The aim of this study... (More)
Pareto optimality is a concept that formalises the trade-off between a given set of mutually contradicting objectives. A solution is said to be Pareto optimal when it is not possible to improve one objective without deteriorating at least one of the other. A set of Pareto optimal solutions constitute the Pareto front. The Pareto concept applies well to the inverse planning process, which involves inherently contradictory objectives, high and uniform target dose on one hand, and sparing of surrounding tissue and nearby organs at risk (OAR) on the other. Due to the specific characteristics of a treatment planning system (TPS), treatment strategy or delivery technique, Pareto fronts for a given case are likely to differ. The aim of this study was to investigate the feasibility of using Pareto fronts as a comparative tool for TPSs, treatment strategies and delivery techniques. In order to sample Pareto fronts, multiple treatment plans with varying target conformity and dose sparing of OAR were created for a number of prostate and head neck IMRT cases. The DVHs of each plan were evaluated with respect to target coverage and dose to relevant OAR. Pareto fronts were successfully created for all studied cases. The results did indeed follow the definition of the Pareto concept, i.e. dose sparing of the OAR could not be improved without target coverage being impaired or vice versa. Furthermore, various treatment techniques resulted in distinguished and well separated Pareto fronts. Pareto fronts may be used to evaluate a number of parameters within radiotherapy. Examples are TPS optimization algorithms, the variation between accelerators or delivery techniques and the degradation of a plan during the treatment planning process. The issue of designing a model for unbiased comparison of parameters with such large inherent discrepancies, e.g. different TPSs, is problematic and should be carefully considered. fc. (Less)
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Acta Oncologica
volume
48
issue
2
pages
233 - 237
publisher
Taylor & Francis
conference name
Symposium of the Nordic-Association-of-Clinical-Physics
external identifiers
  • wos:000262909000011
  • scopus:60549110084
ISSN
0284-186X
DOI
10.1080/02841860802251559
language
English
LU publication?
yes
id
b7c3b8b1-8059-430c-a843-49fb33013ff3 (old id 1311627)
date added to LUP
2009-03-17 09:09:38
date last changed
2017-01-01 06:33:03
@inproceedings{b7c3b8b1-8059-430c-a843-49fb33013ff3,
  abstract     = {Pareto optimality is a concept that formalises the trade-off between a given set of mutually contradicting objectives. A solution is said to be Pareto optimal when it is not possible to improve one objective without deteriorating at least one of the other. A set of Pareto optimal solutions constitute the Pareto front. The Pareto concept applies well to the inverse planning process, which involves inherently contradictory objectives, high and uniform target dose on one hand, and sparing of surrounding tissue and nearby organs at risk (OAR) on the other. Due to the specific characteristics of a treatment planning system (TPS), treatment strategy or delivery technique, Pareto fronts for a given case are likely to differ. The aim of this study was to investigate the feasibility of using Pareto fronts as a comparative tool for TPSs, treatment strategies and delivery techniques. In order to sample Pareto fronts, multiple treatment plans with varying target conformity and dose sparing of OAR were created for a number of prostate and head neck IMRT cases. The DVHs of each plan were evaluated with respect to target coverage and dose to relevant OAR. Pareto fronts were successfully created for all studied cases. The results did indeed follow the definition of the Pareto concept, i.e. dose sparing of the OAR could not be improved without target coverage being impaired or vice versa. Furthermore, various treatment techniques resulted in distinguished and well separated Pareto fronts. Pareto fronts may be used to evaluate a number of parameters within radiotherapy. Examples are TPS optimization algorithms, the variation between accelerators or delivery techniques and the degradation of a plan during the treatment planning process. The issue of designing a model for unbiased comparison of parameters with such large inherent discrepancies, e.g. different TPSs, is problematic and should be carefully considered. fc.},
  author       = {Ottosson, Rickard and Engström, Per and Sjostrom, David and Behrens, Claus F. and Karlsson, Anna and Knöös, Tommy and Ceberg, Crister},
  booktitle    = {Acta Oncologica},
  issn         = {0284-186X},
  language     = {eng},
  number       = {2},
  pages        = {233--237},
  publisher    = {Taylor & Francis},
  title        = {The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques},
  url          = {http://dx.doi.org/10.1080/02841860802251559},
  volume       = {48},
  year         = {2009},
}