The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques
(2009) 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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1311627
- author
- Ottosson, Rickard
; Engström, Per
LU
; Sjostrom, David
; Behrens, Claus F.
; Karlsson, Anna
; Knöös, Tommy
LU
and Ceberg, Crister LU
- organization
- publishing date
- 2009
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Acta Oncologica
- volume
- 48
- issue
- 2
- pages
- 233 - 237
- publisher
- Taylor & Francis
- external identifiers
-
- wos:000262909000011
- scopus:60549110084
- pmid:18752085
- 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
- 2016-04-01 15:00:14
- date last changed
- 2025-04-04 14:52:10
@article{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}}, issn = {{0284-186X}}, language = {{eng}}, number = {{2}}, pages = {{233--237}}, publisher = {{Taylor & Francis}}, series = {{Acta Oncologica}}, title = {{The feasibility of using Pareto fronts for comparison of treatment planning systems and delivery techniques}}, url = {{http://dx.doi.org/10.1080/02841860802251559}}, doi = {{10.1080/02841860802251559}}, volume = {{48}}, year = {{2009}}, }