Simultaneous navigation of multiple Pareto surfaces, with an application to multicriteria IMRT planning with multiple beam angle configurations

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Abstract

Purpose: To introduce a method to simultaneously explore a collection of Pareto surfaces. The method will allow radiotherapy treatment planners to interactively explore treatment plans for different beam angle configurations as well as different treatment modalities. Methods: The authors assume a convex optimization setting and represent the Pareto surface for each modality or given beam set by a set of discrete points on the surface. Weighted averages of these discrete points produce a continuous representation of each Pareto surface. The authors calculate a set of Pareto surfaces and use linear programming to navigate across the individual surfaces, allowing switches between surfaces. The switches are organized such that the plan profits in the requested way, while trying to keep the change in dose as small as possible. Results: The system is demonstrated on a phantom pancreas IMRT case using 100 different five beam configurations and a multicriteria formulation with six objectives. The system has intuitive behavior and is easy to control. Also, because the underlying linear programs are small, the system is fast enough to offer real-time exploration for the Pareto surfaces of the given beam configurations. Conclusions: The system presented offers a sound starting point for building clinical systems for multicriteria exploration of different modalities and offers a controllable way to explore hundreds of beam angle configurations in IMRT planning, allowing the users to focus their attention on the dose distribution and treatment planning objectives instead of spending excessive time on the technicalities of delivery. © 2010 American Association of Physicists in Medicine.

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APA

Craft, D., & Monz, M. (2010). Simultaneous navigation of multiple Pareto surfaces, with an application to multicriteria IMRT planning with multiple beam angle configurations. Medical Physics, 37(2), 736–741. https://doi.org/10.1118/1.3292636

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