Fast non-coplanar beam orientation optimization based on group sparsity

The selection of beam orientations, which is a key step in radiation treatment planning, is particularly challenging for non-coplanar radiotherapy systems due to the large number of candidate beams. In this paper, we report progress on the group sparsity approach to beam orientation optimization, wherein beam angles are selected by solving a large scale fluence map optimization problem with an additional group sparsity penalty term that encourages most candidate beams to be inactive. The optimization problem is solved using an accelerated proximal gradient method, the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). We derive a closed-form expression for a relevant proximal operator which enables the application of FISTA. The proposed algorithm is used to create non-coplanar treatment plans for four cases (including head and neck, lung, and prostate cases), and the resulting plans are compared with clinical plans. The dosimetric quality of the group sparsity treatment plans is superior to that of the clinical plans. Moreover, the runtime for the group sparsity approach is typically about 5 minutes. Problems of this size could not be handled using the previous group sparsity method for beam orientation optimization, which was slow to solve much smaller coplanar cases. This work demonstrates for the first time that the group sparsity approach, when combined with an accelerated proximal gradient method such as FISTA, works effectively for non-coplanar cases with 500-800 candidate beams.

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