A linear programming approach to inverse planning in Gamma Knife radiosurgery
A linear programming approach to inverse planning in Gamma Knife radiosurgery
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DOI：
10.1002/mp.13440
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发表时间：
2019-04-01
期刊：
影响因子：
3.8
通讯作者：
Nordstrom, H.
中科院分区：
文献类型：
--
作者：
Sjolund, J.;Riad, S.;Nordstrom, H.
Leksell伽玛刀(R)是一种立体定向放射外科系统，可对输送剂量分布进行精细控制。提出了一种新的逆向规划方法，既解决了已有方法的不足，又释放了新的能力。方法利用线性规划确定等中心位置，进行扇区持续时间优化，并研究了加束时间惩罚对加束时间和计划质量之间权衡的影响。我们还描述了两种减少问题规模从而进一步减少求解时间的技术：对偶化和代表性亚抽样。结果束上时间惩罚比朴素方案减少了束上时间2-3倍。对偶化和代表性二次抽样均可将优化时间节省5-20倍。总体而言，我们发现，在与75个临床计划的比较中，我们总是可以找到覆盖相似、选择性和束流时间更好的计划。在其中的44个方案中，我们甚至可以找到一个同样具有更好的梯度指数的方案。在标准GammaPlan工作站上，优化时间范围为2.3到26秒，中位时间为5.7秒。结论我们提出了一种技术组合，可以在临床可行的时间范围内实现扇区持续时间的优化。
PurposeLeksell Gamma Knife (R) is a stereotactic radiosurgery system that allows fine-grained control of the delivered dose distribution. We describe a new inverse planning approach that both resolves shortcomings of earlier approaches and unlocks new capabilities.MethodsWe fix the isocenter positions and perform sector-duration optimization using linear programming, and study the effect of beam-on time penalization on the trade-off between beam-on time and plan quality. We also describe two techniques that reduce the problem size and thus further reduce the solution time: dualization and representative subsampling.ResultsThe beam-on time penalization reduces the beam-on time by a factor 2-3 compared with the naive alternative. Dualization and representative subsampling each leads to optimization time-savings by a factor 5-20. Overall, we find in a comparison with 75 clinical plans that we can always find plans with similar coverage and better selectivity and beam-on time. In 44 of these, we can even find a plan that also has better gradient index. On a standard GammaPlan workstation, the optimization times ranged from 2.3 to 26s with a median time of 5.7s.ConclusionWe present a combination of techniques that enables sector-duration optimization in a clinically feasible time frame.