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Combinatorial optimisation in radiotherapy treatment planning

Authors :
Emma Altobelli
Maurizio Amichetti
Alessio Langiu
Francesca Marzi
Filippo Mignosi
Pietro Pisciotta
Giuseppe Placidi
Fabrizio Rossi
Giorgio Russo
Marco Schwarz
Stefano Smriglio
Sabina Vennarini
Source :
AIMS Medical Science, Vol 5, Iss 3, Pp 204-223 (2018)
Publication Year :
2018
Publisher :
AIMS Press, 2018.

Abstract

The goal of radiotherapy is to cover a target area with a desired radiation dose while keeping the exposition of non-target areas as low as possible in order to reduce radiation side effects. In the case of Intensity Modulated Proton Therapy (IMPT), the dose distribution is typically designed via a treatment planning optimisation process based on classical optimisation algorithms on some objective functions.We investigate the planning optimisation problem under the point of view of the Theory of Complexity in general and, in particular, of the Combinatorial Optimisation Theory. We firstly give a formal definition of a simplified version of the problem that is in the complexity class NPO.We prove that above version is computationally hard, i.e. it belongs to the class NPO$\setminus$PTAS if $\mathbb{NP}\neq \mathbb{P}$.We show how Combinatorial Optimisation Theory can give valuable tools, both conceptual and practical, in treatment plan definition, opening the way for new deterministic algorithms with bounded time complexity which have to support the technological evolution up to adaptive plans exploiting near real time solutions.

Details

Language :
English
ISSN :
23751576
Volume :
5
Issue :
3
Database :
Directory of Open Access Journals
Journal :
AIMS Medical Science
Publication Type :
Academic Journal
Accession number :
edsdoj.f05ef5c55c740e6966748539a9f71ce
Document Type :
article
Full Text :
https://doi.org/10.3934/medsci.2018.3.204