ESTRO 37 Abstract book

S1027

ESTRO 37

of objective functions with a clear connection to plan quality indices qualifies as being trial-and-error eliminating and thereby automating. The potential then depends on the ability to generate plans of at least equivalent quality as the conventional formulation. Initial investigation of such potential of a specific formulation was the subject of our recent preliminary study. The purpose of the current study is to examine this formulation in a more clinical setting, where, e.g., deliverability of plans is accounted for. Material and Methods The plan quality indices involved are dose levels in the dose-volume histogram (doses-at-volume). To achieve a clear connection to plan quality, the proposed objective functions abandon the penalty-function paradigm. The intractable dose-at-volume functions are explicitly approximated using mean-tail-dose objective functions, resulting in a convex optimization problem. The formulation is extended with deliverability constraints for sliding window (DMLC) delivery, which preserves convexity. Results We examined the plan quality obtained among Pareto optimal DMLC treatment plans, which result from using the proposed objective functions in a multicriteria optimization (MCO) framework. As a reference, DMLC treatment plans were generated using the penalty- function based MCO module in RayStation (RaySearch Laboratories). Two patient cases were considered. For each case, three plan quality indices were chosen as tradeoff objectives, and the remaining clinical criteria were imposed using hard constraints. After a final accurate dose computation step, all generated plans were evaluated based on the three plan quality indices. The distribution of these indices is graphically visualized in a three-dimensional coordinate system.

Figure 1. Distribution of plan quality indices for a prostate (top) and lung (bottom) case. Blue points correspond to treatment plans generated using the proposed formulation; the blue surface is the convex hull. Red and green points correspond to plans generated using penalty-based functions; red points violate clinical criteria. The magenta circle marks the corner of all best values. Top: The PTV conformity index (CI) is here defined as the average dose of a 1 cm ring around the PTV. Conclusion For the two studied patient cases, the plan quality indices obtained using the proposed formulation are deemed equivalent to those obtained using penalty-based functions. When disregarding plans that violate clinical criteria, the quality indices of plans obtained using the proposed formulation are superior. This outcome confirms our previous preliminary results. We conclude that the proposed formulation has an automating potential when applied to DMLC planning. EP-1894 Genetic algorithm based script for automation of head and neck VMAT treatment planning E. Gallio 1 , A. Alparone 2 , C. Fiandra 3 , C. Vecchi 2 , G. Balestra 4 , R. Ragona 3 , U. Ricardi 3 1 A.S.O.U. S. Giovanni Battista di Torino - Molinette, S.C. Fisica Sanitaria, Torino, Italy 2 Tecnologie Avanzate s.r.l, Electronics, Torino, Italy 3 University of Torino, Radiation Oncology, Torino, Italy 4 Politecnico di Torino, Electronics and Telecomunication, Torino, Italy