Comparative analysis of Pareto surfaces in multi-criteria IMRT planning.

In the multi-criteria optimization approach to IMRT planning, a given dose distribution is evaluated by a number of convex objective functions that measure tumor coverage and sparing of the different organs at risk. Within this context optimizing the intensity profiles for any fixed set of beams yields a convex Pareto set in the objective space. However, if the number of beam directions and irradiation angles are included as free parameters in the formulation of the optimization problem, the resulting Pareto set becomes more intricate.

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

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.

Trade-off bounds for the Pareto surface approximation in multi-criteria IMRT planning.

One approach to multi-criteria IMRT planning is to automatically calculate a data set of Pareto-optimal plans for a given planning problem in a first phase, and then interactively explore the solution space and decide on the clinically best treatment plan in a second phase. The challenge of computing the plan data set is to ensure that all clinically meaningful plans are covered and that as many clinically irrelevant plans as possible are excluded to keep computation times within reasonable limits. In this work, we focus on the approximation of the clinically relevant part of the Pareto surface, the process that constitutes the first phase.

Pareto navigation: algorithmic foundation of interactive multi-criteria IMRT planning.

Inherently, IMRT treatment planning involves compromising between different planning goals. Multi-criteria IMRT planning directly addresses this compromising and thus makes it more systematic. Usually, several plans are computed from which the planner selects the most promising following a certain procedure.

A new concept for interactive radiotherapy planning with multicriteria optimization: first clinical evaluation.

Background And Purpose: Currently, inverse planning for intensity-modulated radiotherapy (IMRT) can be a time-consuming trial and error process. This is because many planning objectives are inherently contradictory and cannot reach their individual optimum all at the same time. Therefore in clinical practice the potential of IMRT cannot be fully exploited for all patients.