Acceleration of intensity-modulated radiotherapy dose calculation by importance sampling of the calculation matrices.
In inverse planning for intensity-modulated radiotherapy, the dose calculation is a crucial element limiting both the maximum achievable plan quality and the speed of the optimization process. One way to integrate accurate dose calculation algorithms into inverse planning is to precalculate the dose contribution of each beam element to each voxel for unit fluence. These precalculated values are stored in a big dose calculation matrix. Then the dose calculation during the iterative optimization process consists merely of matrix look-up and multiplication with the actual fluence values. However, because the dose calculation matrix can become very large, this ansatz requires a lot of computer memory and is still very time consuming, making it not practical for clinical routine without further modifications. In this work we present a new method to significantly reduce the number of entries in the dose calculation matrix. The method utilizes the fact that a photon pencil beam has a rapid radial dose falloff, and has very small dose values for the most part. In this low-dose part of the pencil beam, the dose contribution to a voxel is only integrated into the dose calculation matrix with a certain probability. Normalization with the reciprocal of this probability preserves the total energy, even though many matrix elements are omitted. Three probability distributions were tested to find the most accurate one for a given memory size. The sampling method is compared with the use of a fully filled matrix and with the well-known method of just cutting off the pencil beam at a certain lateral distance. A clinical example of a head and neck case is presented. It turns out that a sampled dose calculation matrix with only 1/3 of the entries of the fully filled matrix does not sacrifice the quality of the resulting plans, whereby the cutoff method results in a suboptimal treatment plan.
Thieke
Christian
C
Department of Medical Physics, Deutsches Krebsforschungszentrum, Heidelberg, Germany.
Nill
Simeon
S
Oelfke
Uwe
U
Bortfeld
Thomas
T
D000465:Algorithms; D055592:Biophysical Phenomena; D001703:Biophysics; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy; D006801:Humans; D017785:Photons / Q000627:therapeutic use; D011859:Radiography; D011874:Radiometry / Q000706:statistics & numerical data; D011880:Radiotherapy Planning, Computer-Assisted / Q000706:statistics & numerical data; D011882:Radiotherapy, High-Energy / Q000706:statistics & numerical data; D012984:Software