A unified mixed-integer programming model for simultaneous fluence weight and aperture optimization in VMAT, Tomotherapy, and Cyberknife
Akartunali, Kerem and Mak-Hau, Vicky and Tran, Thu (2015) A unified mixed-integer programming model for simultaneous fluence weight and aperture optimization in VMAT, Tomotherapy, and Cyberknife. Computers & Operations Research, 56. pp. 134-150. ISSN 0305-0548 (https://doi.org/10.1016/j.cor.2014.11.009)
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Abstract
In this paper, we propose and study a unified mixed-integer programming model that simultaneously optimizes fluence weights and multi-leaf collimator (MLC) apertures in the treatment planning optimization of VMAT, Tomotherapy, and CyberKnife. The contribution of our model is threefold: i. Our model optimizes the fluence and MLC apertures simultaneously for a given set of control points. ii. Our model can incorporate all volume limits or dose upper bounds for organs at risk (OAR) and dose lower bound limits for planning target volumes (PTV) as hard constraints, but it can also relax either of these constraint sets in a Lagrangian fashion and keep the other set as hard constraints. iii. For faster solutions, we propose several heuristic methods based on the MIP model, as well as a meta-heuristic approach. The meta-heuristic is very efficient in practice, being able to generate dose- and machinery-feasible solutions for problem instances of clinical scale, e.g., obtaining feasible treatment plans to cases with 180 control points, 6,750 sample voxels and 18,000 beamlets in 470 seconds, or cases with 72 control points, 8,000 sample voxels and 28,800 beamlets in 352 seconds. With discretization and down-sampling of voxels, our method is capable of tackling a treatment field of 8000cm3∼64000cm3, depending on the ratio of critical structure versus unspecified tissues.
ORCID iDs
Akartunali, Kerem ORCID: https://orcid.org/0000-0003-0169-3833, Mak-Hau, Vicky and Tran, Thu;-
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Item type: Article ID code: 50513 Dates: DateEventApril 2015Published22 November 2014Published Online13 November 2014AcceptedNotes: NOTICE: this is the author’s version of a work that was accepted for publication in Computers & Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Operations Research, [VOL#, ISSUE#, (22/11/2014)] DOI:10.1016/j.cor.2014.11.009 Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management Department: Strathclyde Business School > Management Science Depositing user: Pure Administrator Date deposited: 25 Nov 2014 11:23 Last modified: 11 Nov 2024 10:52 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/50513