Interior point algorithms: guaranteed optimality for fluence map optimization in IMRT
Interior point algorithms: guaranteed optimality for fluence map optimization in IMRT
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DOI：
10.1088/0031-9155/55/18/013
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发表时间：
2010-09-21
影响因子：
3.5
通讯作者：
Dempsey, James F.
中科院分区：
文献类型：
--
作者：
Aleman, Dionne M.;Glaser, Daniel;Dempsey, James F.
调强放射治疗(IMRT)治疗计划问题中研究最广泛的问题之一是注量图优化(FMO)问题，即确定每个射束中每个束流的辐射强度或注量的问题。对于一组给定的束流，束流的注量会极大地影响治疗计划的质量，因此获得良好的辐射传输注量图是至关重要的。虽然已经证明有几种方法可以很好地解决FMO问题，但这些解决方案并不能保证是最优的。这一缺点可以归因于优化模型的复杂性或用于求解优化模型的算法的特性。我们提出了凸FMO公式和内点算法，在几秒钟内就能产生最优治疗计划，使其成为临床应用的可行选择。
One of the most widely studied problems of the intensity-modulated radiation therapy (IMRT) treatment planning problem is the fluence map optimization (FMO) problem, the problem of determining the amount of radiation intensity, or fluence, of each beamlet in each beam. For a given set of beams, the fluences of the beamlets can drastically affect the quality of the treatment plan, and thus it is critical to obtain good fluence maps for radiation delivery. Although several approaches have been shown to yield good solutions to the FMO problem, these solutions are not guaranteed to be optimal. This shortcoming can be attributed to either optimization model complexity or properties of the algorithms used to solve the optimization model. We present a convex FMO formulation and an interior point algorithm that yields an optimal treatment plan in seconds, making it a viable option for clinical applications.