Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, ON M5S 3G8, Canada.
Phys Med Biol. 2010 Sep 21;55(18):5467-82. doi: 10.1088/0031-9155/55/18/013. Epub 2010 Aug 27.
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.
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通量图优化（FMO）问题，即确定每个射束中的每个射束的辐射强度或通量的问题。对于给定的射束集，射束的通量会极大地影响治疗计划的质量，因此获得良好的辐射输送通量图至关重要。尽管已经有几种方法被证明可以很好地解决 FMO 问题，但这些解决方案并不一定是最优的。这一缺点可以归因于优化模型的复杂性或用于解决优化模型的算法的性质。我们提出了一种凸 FMO 公式和一种内点算法，该算法可以在几秒钟内生成最佳治疗计划，使其成为临床应用的可行选择。
