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SU‐EE‐A1‐05: Trade‐Off between Treatment Plan Quality and Beam‐On‐Time in IMRT Using Direct Aperture Optimization
Author(s) -
Salari E,
Romeijn E
Publication year - 2010
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3468010
Subject(s) - beam (structure) , aperture (computer memory) , multi objective optimization , computer science , pareto principle , mathematical optimization , set (abstract data type) , quality (philosophy) , medical physics , mathematics , optics , medicine , engineering , physics , mechanical engineering , quantum mechanics , programming language
Purpose : Beam‐on‐time is an important aspect of IMRT treatment efficiency, but optimization of this is usually postponed until the leaf sequencing phase of treatment planning. However, there exists a trade‐off between treatment plan quality and beam‐on‐time. The aim of this study is to incorporate the beam‐on‐time into a direct aperture optimization model to explicitly quantify that trade‐off. Method and Material : A direct aperture optimization problem is formulated that includes a composite measure of treatment plan quality as well as a penalty for beam‐on‐time. An efficient method is developed to then obtain all treatment plans on the entire corresponding Pareto‐efficient frontier. Starting with a very large beam‐on‐time penalty for which it is optimal not to treat, the beam‐on‐time penalty is reduced while simultaneously adding high‐quality deliverable apertures while ensuring that the treatment plan remains Pareto efficient. The method can account for several MLC delivery constraints (row‐convexity, interdigitation, connectedness, jaws‐only). Using the set of Pareto‐optimal treatment plans, gains in different measures of treatment plan quality that can be obtained when beam‐on‐time is increased are quantified. The analysis also identifies the range of beam‐on‐times for which a clinically acceptable treatment plan is obtained Results : For a set of ten clinical head‐and‐neck cases, the trade‐offs between the treatment plan quality and beam‐on‐time are quantified. The impact of allowing for longer beam‐on‐times on the DVH criteria was investigated. Conclusion : This work provides a direct aperture optimization model that explicitly incorporates beam‐on‐time. The model allows for studying the effect of beam‐on‐time on the treatment plan quality.