Journal
MEDICAL PHYSICS
Volume 42, Issue 3, Pages 1367-1377Publisher
WILEY
DOI: 10.1118/1.4908224
Keywords
radiotherapy; treatment plan optimization; VMAT
Funding
- Cancer Research UK [19727] Funding Source: researchfish
- NCI NIH HHS [R01 CA176553] Funding Source: Medline
- Direct For Computer & Info Scie & Enginr
- Division of Computing and Communication Foundations [1217906] Funding Source: National Science Foundation
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Volumetric modulated arc therapy (VMAT) has found widespread clinical application in recent years. A large number of treatment planning studies have evaluated the potential for VMAT for different disease sites based on the currently available commercial implementations of VMAT planning. In contrast, literature on the underlying mathematical optimization methods used in treatment planning is scarce. VMAT planning represents a challenging large scale optimization problem. In contrast to fluence map optimization in intensity-modulated radiotherapy planning for static beams, VMAT planning represents a nonconvex optimization problem. In this paper, the authors review the state-of-the-art in VMAT planning from an algorithmic perspective. Different approaches to VMAT optimization, including arc sequencing methods, extensions of direct aperture optimization, and direct optimization of leaf trajectories are reviewed. Their advantages and limitations are outlined and recommendations for improvements are discussed. (C) 2015 American Association of Physicists in Medicine.
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