LiU Electronic Press
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Author:
Holm, Åsa (Linköping University, Department of Mathematics) (Linköping University, The Institute of Technology)
Carlsson Tedgren, Åsa (Linköping University, Department of Medical and Health Sciences, Radiation Physics) (Linköping University, Faculty of Health Sciences) (Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL)
Larsson, Torbjörn (Linköping University, Department of Mathematics, Optimization ) (Linköping University, The Institute of Technology)
Title:
Integrated Optimization of Catheter Positioning and Dwell Time Distribution in Prostate HDR Brachytherapy
Department:
Linköping University, Faculty of Health Sciences
Linköping University, Department of Mathematics
Linköping University, Department of Medical and Health Sciences, Radiation Physics
Linköping University, Department of Mathematics, Optimization
Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL
Linköping University, The Institute of Technology
Publication type:
Manuscript (preprint) (Other academic)
Language:
English
URI:
urn:nbn:se:liu:diva-67788
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-67788
Subject category:
Mathematics
SVEP category:
MATHEMATICS
Abstract(en) :

High dose-rate (HDR) brachytherapy is a kind of radiotherapy used to treat, among others, prostate cancer. When applied to prostate cancer a radioactive source is moved through catheters implanted into the prostate. For each patient a treatment plan is constructed that decide for example catheter placement and dwell time distribution, that is where to stop the radioactive source and for how long.

Mathematical optimization methods has been used to find quality plans with respect to dwell time distribution, however few optimization approaches regarding catheter placement have been studied. In this article we present an integrated optimization model that optimize catheter placement and dwell time distribution simultaneously. Our results show that integrating the two decisions yields greatly improved plans, from 15% to 94% improvement.

Since the presented model is computationally demanding to solve we also present three heuristics: tabu search, variable neighbourhood search and genetic algorithm. Of these variable neighbourhood search is clearly the best, outperforming a state-of-the-art optimization software (CPLEX) and the two other heuristics.

Available from:
2011-04-26
Created:
2011-04-26
Last updated:
2011-04-26
Statistics:
30 hits