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A fast optimization approach for treatment planning of volumetric modulated arc therapy

机译:体积调制弧疗法治疗计划的快速优化方法

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摘要

Abstract Background Volumetric modulated arc therapy (VMAT) is widely used in clinical practice. It not only significantly reduces treatment time, but also produces high-quality treatment plans. Current optimization approaches heavily rely on stochastic algorithms which are time-consuming and less repeatable. In this study, a novel approach is proposed to provide a high-efficient optimization algorithm for VMAT treatment planning. Methods A progressive sampling strategy is employed for beam arrangement of VMAT planning. The initial beams with equal-space are added to the plan in a coarse sampling resolution. Fluence-map optimization and leaf-sequencing are performed for these beams. Then, the coefficients of fluence-maps optimization algorithm are adjusted according to the known fluence maps of these beams. In the next round the sampling resolution is doubled and more beams are added. This process continues until the total number of beams arrived. The performance of VMAT optimization algorithm was evaluated using three clinical cases and compared to those of a commercial planning system. Results The dosimetric quality of VMAT plans is equal to or better than the corresponding IMRT plans for three clinical cases. The maximum dose to critical organs is reduced considerably for VMAT plans comparing to those of IMRT plans, especially in the head and neck case. The total number of segments and monitor units are reduced for VMAT plans. For three clinical cases, VMAT optimization takes < 5 min accomplished using proposed approach and is 3–4 times less than that of the commercial system. Conclusions The proposed VMAT optimization algorithm is able to produce high-quality VMAT plans efficiently and consistently. It presents a new way to accelerate current optimization process of VMAT planning.
机译:摘要背景体积调制电弧疗法(VMAT)广泛用于临床实践。它不仅显着降低了治疗时间,而且还产生了高质量的治疗计划。目前的优化依赖于随机算法依赖于耗时且可重复的随机算法。在这项研究中,提出了一种新的方法,为VMAT治疗计划提供了一种高效的优化算法。方法采用渐进采样策略用于VMAT规划的梁排列。具有等空间的初始光束以粗略采样分辨率添加到平面中。对这些光束进行流量映射优化和叶排序。然后,根据这些光束的已知的光线映射来调整流量映射优化算法的系数。在下一轮中,采样分辨率加倍,并添加更多的光束。该过程继续,直到光束总数到达。使用三种临床病例进行了评估VMAT优化算法的性能,并与商业规划系统相比。结果VMAT计划的数据质量等于或优于三种临床病例的相应IMRT计划。对于与IMRT计划的计划相比,临界器官的最大剂量显着降低,特别是在头部和颈部壳体中。为VMAT计划减少了段的总数和监控单元。对于三种临床病例,使用所提出的方法完成VMAT优化需要<5分钟,比商业系统的3-4倍。结论所提出的VMAT优化算法能够有效且始终如一地生产高质量的VMAT计划。它提出了一种加速VMAT规划的当前优化过程的新方法。

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