445The effect of altered anatomy due to implants on MRI based 3D interstitial brachytherapy treatment planning

Kovács, G.; Schultze, Jürgen; Kampf, R.; Hebbinghaus, D; Kohr, P.; Wilhelm, R.; Kimmig, B.

doi:10.1016/s0167-8140(96)80454-3

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“…Image-based treatment planning in interstitial high dose rate (HDR) brachytherapy using the modalities of computed tomography (CT) (Kovacs et al 1996, Vicini et al 1998, Kolotas et al 1999, Martinez et al 2000, Polgar et al 2000, Koutrouvelis et al 2001, magnetic resonance (MR) (Di Biase et al 2002) and ultrasound (US) (Kini et al 1999) has been around for several years, and is nowadays well established in a variety of localizations such as prostate, breast and gynaecological tumours. The use of imaging makes it possible to accurately define the target volume and the organs at risk (OAR) in three dimensions, and at the same time to determine the position of the HDR applicators relative to these structures (Milickovic et al 2000(Milickovic et al , 2001.…”

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confidence: 99%

Multiobjective anatomy-based dose optimization for HDR-brachytherapy with constraint free deterministic algorithms

et al. 2002

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In high dose rate (HDR) brachytherapy, conventional dose optimization algorithms consider multiple objectives in the form of an aggregate function that transforms the multiobjective problem into a single-objective problem. As a result, there is a loss of information on the available alternative possible solutions. This method assumes that the treatment planner exactly understands the correlation between competing objectives and knows the physical constraints. This knowledge is provided by the Pareto trade-off set obtained by single-objective optimization algorithms with a repeated optimization with different importance vectors. A mapping technique avoids non-feasible solutions with negative dwell weights and allows the use of constraint free gradient-based deterministic algorithms. We compare various such algorithms and methods which could improve their performance. This finally allows us to generate a large number of solutions in a few minutes. We use objectives expressed in terms of dose variances obtained from a few hundred sampling points in the planning target volume (PTV) and in organs at risk (OAR). We compare two- to four-dimensional Pareto fronts obtained with the deterministic algorithms and with a fast-simulated annealing algorithm. For PTV-based objectives, due to the convex objective functions, the obtained solutions are global optimal. If OARs are included, then the solutions found are also global optimal, although local minima may be present as suggested.

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