Literature DB >> 12033562

Acceleration of intensity-modulated radiotherapy dose calculation by importance sampling of the calculation matrices.

Christian Thieke1, Simeon Nill, Uwe Oelfke, Thomas Bortfeld.   

Abstract

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.

Mesh:

Year:  2002        PMID: 12033562     DOI: 10.1118/1.1469633

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  4 in total

1.  Motion management with phase-adapted 4D-optimization.

Authors:  Omid Nohadani; Joao Seco; Thomas Bortfeld
Journal:  Phys Med Biol       Date:  2010-08-16       Impact factor: 3.609

2.  A two-stage sequential linear programming approach to IMRT dose optimization.

Authors:  Hao H Zhang; Robert R Meyer; Jianzhou Wu; Shahid A Naqvi; Leyuan Shi; Warren D D'Souza
Journal:  Phys Med Biol       Date:  2010-01-14       Impact factor: 3.609

3.  Worst case optimization for interfractional motion mitigation in carbon ion therapy of pancreatic cancer.

Authors:  Julian Steitz; Patrick Naumann; Silke Ulrich; Matthias F Haefner; Florian Sterzing; Uwe Oelfke; Mark Bangert
Journal:  Radiat Oncol       Date:  2016-10-07       Impact factor: 3.481

4.  A linear programming approach to inverse planning in Gamma Knife radiosurgery.

Authors:  J Sjölund; S Riad; M Hennix; H Nordström
Journal:  Med Phys       Date:  2019-03-08       Impact factor: 4.071

  4 in total

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