Optimization of proton therapy ballistics using a genetic algorithm

François Smekens 1 Jean-Michel Létang 1 Nicolas Freud 1 Bruno Sixou 1 Guillaume Beslon 2, 3
1 Imagerie Tomographique et Radiothérapie
CREATIS - Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé
3 BEAGLE - Artificial Evolution and Computational Biology
LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558, Inria Grenoble - Rhône-Alpes, LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : New treatment planning systems adapted to proton spot scanningtechniques have been recently proposed to simultaneouslyoptimize several fields and thus improve dose delivery.The only parameters usually optimized are the field fluenceswhereas other parameters (e.g. beam directions) are chosenby medical physicists and are limited by technological constraints.We investigate a genetic algorithm approach designed tooptimize the number of beams, target points and irradiationdirections at the same time. This tool is intended to pave theway towards optimal treatment ballistics. The optimizationframework is designed to be versatile and to account formany degrees of freedom, without any a priori technologicalconstraint.
Document type :
Poster communications
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  • HAL Id : hal-01354428, version 1


François Smekens, Jean-Michel Létang, Nicolas Freud, Bruno Sixou, Guillaume Beslon. Optimization of proton therapy ballistics using a genetic algorithm. Particle Therapy Co-Operative Group, PTCOG, May 2011, Philadelphia (US), United States. 2011. ⟨hal-01354428⟩



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