Neighborhood search approaches to non-coplanar beam orientation optimization for total marrow irradiation using IMRT

We consider the beam orientation optimization (BOO) problem for total marrow irradiation (TMI) treatment planning using intensity modulated radiation therapy (IMRT). Currently, IMRT is not widely used in TMI treatment delivery; furthermore, the effect of using non-coplanar beam orientations is not known. We propose and implement several variations of a single neighborhood search algorithm that solves the BOO problem effectively when gantry angles and couch translations are considered. Our work shows that the BOO problem for TMI cases can be solved in a clinically acceptable amount of time and leads to treatment plans that are more effective than the conventional approach to TMI.     

Mathematical optimization in intensity modulated radiation therapy

The design of an intensity modulated radiotherapy treatment includes the selection of beam angles (geometry problem), the computation of an intensity map for each selected beam angle (intensity problem), and finding a sequence of configurations of a multileaf collimator to deliver the treatment (realization problem). Until the end of the last century research on radiotherapy treatment design has been published almost exclusively in the medical physics literature. However, since then, the attention of researchers in mathematical optimization has been drawn to the area and important progress has been made. In this paper we survey the use of optimization models, methods, and theories in intensity modulated radiotherapy treatment design.     

A collaboratory for radiation therapy treatment planning optimization research

Intensity modulated radiation therapy treatment planning (IMRTP) is a challenging application of optimization technology. We present software tools to facilitate IMRTP research by computational scientists who may not have convenient access to radiotherapy treatment planning systems. The tools, developed within Matlab and CERR (computational environment for radiotherapy research), allow convenient access, visualization, programmable manipulation, and sharing of patient treatment planning data, as well as convenient generation of dosimetric data needed as input for treatment plan optimization research. CERR/Matlab also provides a common framework for storing, reviewing, sharing, and comparing optimized dose distributions from multiple researchers.