Direct Monte-Carlo optimization (DMCO) with biological, physical and hybrid objective functions

Abstract

The biological effects of an applied dose can be taken into account by using biological objective functions with IMRT. A commonly used concept is the generalized equivalent uniform dose (gEUD) developed by Niemierko. Unlike the equivalent uniform dose (EUD) which is defined for the tumor only, the gEUD can be used for both, target volume and organs at risk. In this study, the gEUD has been integrated in our inhouse inverse treatment planning system DMCO (direct Monte-Carlo optimization). DMCO is based on an inverse kernel concept and is maintaining full Monte-Carlo precision. The system uses direct aperture optimization by means of a simulated annealing algorithm. Via simulated annealing, it is more likely to find a global minimum than with gradient-based methods. In this work, we are performing a ‘pseudo’ Pareto study with different gEUD parameters on a prostate case. The best plan is then compared to a conventional plan, which is based on dose-volume constraints. Furthermore, a hybrid objective function (OF) was developed. It consists of both, a biologic OF in the OARs and a physical OF in the target. A plan comparison is performed by means of target coverage OAR sparing.