Quantifying the Trade‐off Between IMRT Treatment Plan Quality and Delivery Efficiency Using Direct Aperture Optimization

Quantifying the Trade‐off Between IMRT Treatment Plan Quality and Delivery Efficiency Using Direct Aperture Optimization

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Article ID: iaor20126816
Volume: 24
Issue: 4
Start Page Number: 518
End Page Number: 533
Publication Date: Sep 2012
Journal: INFORMS Journal on Computing
Authors: ,
Keywords: medicine, programming: convex
Abstract:

Beam‐on time is an important measure of the delivery efficiency in intensity‐modulated radiation therapy (IMRT). Traditionally, minimizing beam‐on time has been postponed until the leaf sequencing stage, where the treatment plan quality is already determined and fixed. However, there is a trade‐off between the beam‐on time and the treatment plan quality. The aim of this study is to incorporate the beam‐on time into the treatment plan optimization stage using a direct aperture optimization approach that allows for explicitly quantifying the trade‐off. The proposed approach can provide clinicians with valuable information for each patient case so that they can design clinically attractive yet efficient treatment plans. Using the special structure of the problem, we propose an exact solution approach that sequentially characterizes segments of the Pareto‐efficient frontier. In addition, an approximate solution technique that is applicable to more classes of evaluation criteria is developed. Our approximate technique is tested on clinical cancer cases, and its performance is compared with the general approximation techniques that are available for convex bicriteria optimization problems. The results of our experiments validate that our approach can achieve a more accurate representation of the Pareto‐efficient frontier with less computational effort.

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