An evolutionary approach to coplanar radiotherapy inverse planning is proposed. It consists of a genetic algorithm-based framework that solves with little modification treatment planning for three different kinds of radiation therapy: conformal, so-called aperture-based and intensity modulated. Thanks to evolutionary optimisation technique we have been able to search for full beam configurations, that is beam intensity, beam shape and especially beam orientation. Our dose distribution model has been validated through comparison with commercial system, then we have tested the optimisation algorithm with real clinical cases. These involved both simple (convex target, far OARs) and complex (concave target, close OARs) ones. As stated by physician and by simulation with the same commercial system, our tools found good solutions in both cases using corresponding correct therapy.

Full Beam Configuration for Coplanar Radiotherapy Inverse Planning: a Genetic Algorithm-based Framework

BEVILACQUA, Vitoantonio;MASTRONARDI, Giuseppe;
2003

Abstract

An evolutionary approach to coplanar radiotherapy inverse planning is proposed. It consists of a genetic algorithm-based framework that solves with little modification treatment planning for three different kinds of radiation therapy: conformal, so-called aperture-based and intensity modulated. Thanks to evolutionary optimisation technique we have been able to search for full beam configurations, that is beam intensity, beam shape and especially beam orientation. Our dose distribution model has been validated through comparison with commercial system, then we have tested the optimisation algorithm with real clinical cases. These involved both simple (convex target, far OARs) and complex (concave target, close OARs) ones. As stated by physician and by simulation with the same commercial system, our tools found good solutions in both cases using corresponding correct therapy.
AIA 2003
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11589/20662
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