Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity-modulated proton therapy treatment planning.
Incorporating deliverable monitor unit constraints into spot intensity optimization in intensity-modulated proton therapy treatment planning.
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DOI：
10.1088/0031-9155/58/15/5113
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发表时间：
2013-08-07
影响因子：
3.5
通讯作者：
Zhang X
中科院分区：
文献类型：
--
作者：
Cao W;Lim G;Li X;Li Y;Zhu XR;Zhang X
本研究的目的是探讨在调强质子治疗（IMPT）治疗计划中将可交付监测单元（MU）约束纳入点强度优化的可行性和影响。当前的IMPT治疗计划系统（TPS）忽视了斑点强度优化（SIO）程序中的可交付MU约束。它对优化计划执行后处理程序，以强制执行点扫描质子输送系统所需的可输送MU值。该过程可能在优化的和后处理的可交付计划之间产生显著的剂量分布偏差，特别是当使用小光斑间距时。在这项研究中，我们引入了两阶段线性规划（LP）方法来优化光斑强度并同时约束可交付的MU值，即，可交付光斑强度优化（DSIO）模型。因此，消除了后处理过程，并且可以避免相关联的优化计划劣化。在我们的机构中选择了四个前列腺癌病例进行研究，并计划对所有病例进行两个平行相对的射束角度。基于二次规划（QP）的模型，没有MU约束，即，一个传统的光斑强度优化（CSIO）模型，也被实现来模拟商业TPS。由DSIO和CSIO模型优化的计划进行了评估，为5个不同的设置，从3毫米到7毫米的光斑间距。对于所有的光斑间距，DSIO优化的计划产生了更好的均匀性的目标剂量覆盖范围和关键结构的保留比CSIO优化的计划。随着光斑间距的减小，在DSIO中观察到的靶剂量均匀性和临界结构保留比CSIO优化计划中的改善更显著。此外，更好地保留直肠和膀胱时，减少间距用于DSIO优化计划。建议的DSIO方法，确保交付的优化IMPT计划，考虑到MU的限制。这消除了TPS所需的后处理程序以及对最终剂量分布产生的恶化影响。因此，这种方法允许IMPT计划最佳地采用所有可能的光斑间距。此外，剂量测定的好处，可以实现使用较小的斑点间距。
The purpose of this study is to investigate the feasibility and impact of incorporating deliverable monitor unit (MU) constraints into spot intensity optimization in intensity modulated proton therapy (IMPT) treatment planning. The current treatment planning system (TPS) for IMPT disregards deliverable MU constraints in the spot intensity optimization (SIO) routine. It performs a post-processing procedure on an optimized plan to enforce deliverable MU values that are required by the spot scanning proton delivery system. This procedure can create a significant dose distribution deviation between the optimized and post-processed deliverable plans, especially when small spot spacings are used. In this study, we introduce a two-stage linear programming (LP) approach to optimize spot intensities and constrain deliverable MU values simultaneously, i.e., a deliverable spot intensity optimization (DSIO) model. Thus, the post-processing procedure is eliminated and the associated optimized plan deterioration can be avoided. Four prostate cancer cases at our institution were selected for study and two parallel opposed beam angles were planned for all cases. A quadratic programming (QP) based model without MU constraints, i.e., a conventional spot intensity optimization (CSIO) model, was also implemented to emulate the commercial TPS. Plans optimized by both the DSIO and CSIO models were evaluated for five different settings of spot spacing from 3 mm to 7 mm. For all spot spacings, the DSIO-optimized plans yielded better uniformity for the target dose coverage and critical structure sparing than did the CSIO-optimized plans. With reduced spot spacings, more significant improvements in target dose uniformity and critical structure sparing were observed in the DSIO- than in the CSIO-optimized plans. Additionally, better sparing of the rectum and bladder was achieved when reduced spacings were used for the DSIO-optimized plans. The proposed DSIO approach ensures the deliverability of optimized IMPT plans that take into account MU constraints. This eliminates the post-processing procedure required by the TPS as well as the resultant deteriorating effect on ultimate dose distributions. This approach therefore allows IMPT plans to adopt all possible spot spacings optimally. Moreover, dosimetric benefits can be achieved using smaller spot spacings.
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