Abstract
The purpose of this work was to develop a hybrid column generation (CG) and simulated annealing (SA) algorithm for direct aperture optimization (H-DAO) and to show its effectiveness in generating high quality treatment plans for intensity modulated radiation therapy (IMRT) and mixed photon-electron beam radiotherapy (MBRT). The H-DAO overcomes limitations of the CG-DAO with two features improving aperture selection (branch-feature) and enabling aperture shape changes during optimization (SA-feature). The H-DAO algorithm iteratively adds apertures to the plan. At each iteration, a branch is created for each field provided. First, each branch determines the most promising aperture of its assigned field and adds it to a copy of the current apertures. Afterwards, the apertures of each branch undergo an MU-weight optimization followed by an SA-based simultaneous shape and MU-weight optimization and a second MU-weight optimization. The next H-DAO iteration continues the branch with the lowest objective function value. IMRT and MBRT treatment plans for an academic, a brain and a head and neck case generated using the CG-DAO and H-DAO were compared. For every investigated case and both IMRT and MBRT, the H-DAO leads to a faster convergence of the objective function value with number of apertures compared to the CG-DAO. In particular, the H-DAO needs about half the apertures to reach the same objective function value as the CG-DAO. The average aperture areas are 27% smaller for H-DAO than for CG-DAO leading to a slightly larger discrepancy between optimized and final dose. However, a dosimetric benefit remains. The H-DAO was successfully developed and applied to IMRT and MBRT. The faster convergence with number of apertures of the H-DAO compared to the CG-DAO allows to select a better compromise between plan quality and number of apertures.
Highlights
Treatment plans are generated and delivered in photon intensity modulated radiation therapy (IMRT)cri pt (Bortfeld 2006) to achieve a highly conformal dose distribution to the target volume
It is visible that for each combination of case and treatment technique (IMRT or mixed photonelectron beam radiotherapy (MBRT)), the fastest convergence is always given by H-direct aperture optimization (DAO), followed by column generation (CG)-DAO_SA, CG-DAO_Branch and CG-DAO
All the DAO algorithms do not pte converge to the value given by the fluence map optimization (FMO), because all the DAO algorithms consider transmission through the multileaf collimator (MLC) in case of photon apertures in contrast to FMO
Summary
Treatment plans are generated and delivered in photon intensity modulated radiation therapy (IMRT). DAO deals with MU weighted mechanically deliverable apertures that describe which beamlets are covered by the MLC leaves This leads to a difficult large-scale non-convex optimization problem which cannot be solved efficiently. In contrast to the us CG-DAO algorithm, the number of apertures per field is pre-defined These approaches start with arbitrary aperture shapes such as conformal to the target or closed. (Cassioli and Unkelbach 2013) typically start with an initial aperture set generated through pte CG-DAO (Carlsson 2008, Cassioli and Unkelbach 2013) or FMO and leaf-sequencing They refine the leaf positions locally within the current beamlet using a linear function of the leaf positions approximating the dose distribution.
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