Dose optimization via index-dose gradient minimization.

This paper presents an iterative optimization algorithm based on gradient minimization of index dose, defined as the product of physical dose and a numerical index. Acting as a template the index distribution is designed to represent the dosimetry that meets the dose volume histogram-based optimization objectives. The treatment dosimetry is optimized when the uniformity of the index-dose distribution is maximized. Prior to optimization the user can select all or only some of the beams to be intensity modulated. The remaining unmodulated beams can be either open or wedged photon beams, electron beams, or beams of previous treatments. The optimization result and treatment delivery efficiency can often be enhanced by including not only the IM photon beams but also all suitable fixed-beams available on the linac in the treatment plan. In addition, the doses from previous treatments can also be considered in the optimization of current treatment. Five clinical examples with different complexities in optimization objective are presented. The effects of two nonoptimization variables, beam setup and initial beam weights, on the quality of the dose optimization are also presented. The results are analyzed in terms of isodose distribution, dose volume histograms, and a dose optimization quality factor. The optimization algorithm, implemented in our in-house TPS PLanUNC, has been used in clinical application since 1996. The primary advantages of our optimization algorithm include computational efficiency, intensity modulation selection choice, and performance reliability for a wide range of clinical beam setups and optimization objectives.