The application of distance transformation on parameter optimization of inverse planning in intensity-modulated radiation therapy.

Abstract

In inverse planning for intensity-modulated radiation therapy (IMRT), the dose specification and related weighting factor of an objective function for involved organs is usually predefined by a single value and then iteratively optimized, subject to a set of dose-volume constraints. Because the actual dose distribution is essentially non-uniform and considerably affected by the geometric shape and distribution of the anatomic structures involved, the spatial information regarding those structures should be incorporated such that the predefined parameter distribution is made to approach the clinically expected distribution. Ideally, these parameter distributions should be predefined on a voxel basis in a manual method. However, such an approach is too time-consuming to be feasible in routine use. In the present study, we developed a computer-aided method to achieve the goal described above, producing a non-uniform parameter distribution based on spatial information about the anatomic structures involved. The method consists of two steps: Use distance transformation technique to calculate the distance distribution of the structures. Based on the distance distribution, produce the parameter distribution via a function guided by prior knowledge. We use two simulated cases to examine the effectiveness of the method. The results indicate that application of a non-uniform parameter distribution produced by distance transformation clearly improves dose-sparing of critical organs without compromising dose coverage of the planning target.