Direct optimization of 3D dose distributions using collimator rotation
The primary goal of this thesis is to improve the precision and efficiency of radiation therapy treatment. This goal is achieved by developing and implementing a direct aperture optimization (DAO) platform where the multileaf collimator (MLC) is rotated between each aperture. The approach is referre...
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Format: | Others |
Language: | en |
Published: |
University of British Columbia
2008
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Online Access: | http://hdl.handle.net/2429/274 |
Summary: | The primary goal of this thesis is to improve the precision and efficiency of radiation therapy treatment. This goal is achieved by developing and implementing a direct aperture optimization (DAO) platform where the multileaf collimator (MLC) is rotated between each aperture. The approach is referred to as rotating aperture optimization (RAO).
A series of tests is performed to evaluate how a final optimized plan depends on MLC parameters. Imposing constraints on the leaf
sequence results in increased efficiency and a simplification of the treatment plan without compromising the quality of the dose
distribution. It is also shown that an arrangement of equispaced collimator angles takes full advantage of the flexibility associated with collimator rotation.
A study including ten recurring nasopharynx cancer patients is used to evaluate the capabilities of RAO compared to other optimization techniques. It is shown that RAO plans require significantly less
linac radiation output (monitor units or MU) while maintaining equivalent dose distribution quality compared to plans generated with the conventional fluence based approach. Furthermore with an
improved collimator rotation speed, the RAO plans should be executable in the same or less time than plans generated with the
fluence-based approach. For the second part of the study it is shown that plans generated with RAO are as good as or better than plans generated with standard fixed collimator DAO. Film and ion chamber
measurements indicate that RAO plans can be delivered more accurately than DAO plans.
Additional applications of DAO were investigated through collaboration with two PhD students. First, Monte Carlo was used to
generate pencil beam dose distributions for DAO inverse treatment planning (MC-DAO). The MC-DAO technique correctly models
traditionally difficult treatment geometries such as small fields and tissue inhomogeneities. The MC-DAO also takes advantage of the improved MU efficiency associated with the DAO technique. Secondly
DAO is proposed for adaptive radiation therapy. The results show that plan re-adaptation can be performed more quickly than complete plan regeneration thereby minimizing the time the patient has to
spend in the treatment room and reducing the potential for geometric errors in treatment delivery. |
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