线性规划在伽玛刀放射外科中的逆向规划方法。

PURPOSE

Leksell Gamma Knife 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.

METHODS

We 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.

RESULTS

The beam-on time penalization reduces the beam-on time by a factor 2-3 compared with the naïve 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 26 s with a median time of 5.7 s.

CONCLUSION

We present a combination of techniques that enables sector-duration optimization in a clinically feasible time frame.

目的

Leksell Gamma Knife 是一种立体定向放射外科系统，可实现对所给予剂量分布的精细控制。我们描述了一种新的逆向规划方法，该方法既解决了早期方法的缺点，又开辟了新的功能。

方法

我们固定等中心点位置，并使用线性规划进行扇区-持续时间优化，并研究了束流开启时间惩罚对束流开启时间和计划质量之间权衡的影响。我们还描述了两种可减小问题规模从而进一步缩短解决方案时间的技术：对偶化和代表性抽样。

结果

与简单的替代方案相比，束流开启时间惩罚可将束流开启时间减少 2-3 倍。对偶化和代表性抽样分别使优化时间节省了 5-20 倍。总体而言，我们在与 75 个临床计划的比较中发现，我们始终可以找到具有相似覆盖率和更好选择性以及束流开启时间的计划。在其中的 44 个计划中，我们甚至可以找到一个具有更好梯度指数的计划。在标准的 GammaPlan 工作站上，优化时间范围为 2.3 到 26 秒，中位数时间为 5.7 秒。