Fluence optimization

The goal of the fluence optimization is to find a set of bixel/spot weights which yield the best possible dose distribution according to the clinical objectives and constraints underlying the radiation treatment.

For mathematical optimization, these clinical objectives and constraints have to be translated into mathematical objectives and constraints. matRad supports the mathematical optimization of a weighted sum of objetives to help finding an optimal trade-off between adequate target coverage and normal tissue sparing for an individual patent as well as the formulation of constraints. The individual objectives and constraints are defined per structure and can be chosen by the user and include, among others:

• squared overdosage objective,
• squared underdosage objective,
• squared dose deviation objective,
• mean dose objective,
• equivalent uniform dose objective,
• min/max dose constraints,
• DVH point objectives and constraints.

The overall fluence optimization process is coordinated by the matRad function matRad_fluenceOptimization.m. The objectives and constraints are stored as an dose objective struct within the cst cell array. The objectives and constraints can be set including all necessary parameters via the matRad GUI. All functions involved in the optimization process are located in a subfolder "optimization" within the matRad root folder. matRad relies on the IPOPT package for large scale non-linear optimization which is included via a MEX file. IPOPT requires call back functions for objective function, gradient, constraint, and jacobian evaluation. We use the wrapper functions matRad_objFuncWrapper, matRad_gradFuncWrapper, matRad_constFuncWrapper, and matRad_jacobFuncWrapper to coordinate the evaluation of all defined objectives and constraints.

All optimization functionalities work equally for optimization processes based on physical dose as well as biological effect Wilkens & Oelfke (2006) and RBE-weighted dose dose according to Krämer & Scholz (2006). The biological effect and the RBE-weighted dose are calculated with α and β base data that has been calculated according to the local effect model IV. α and β tables are available as part of the base data set carbon_Generic.mat which is provided with the matRad release.

For photons, matRad also features an experimental direct aperture optimization that largely follows the implementation described in Wild et al. (2015) which is based on Bzdusek et al. (2009) and (with some modification) Unkelbach & Cassioli (2012).