A method to improve dose gradient for robotic radiosurgery

一种改善机器人放射外科手术剂量梯度的方法

阅读:1

Abstract

For targets with substantial volume, collimators of relatively large size are usually selected to minimize the treatment time in robotic radiosurgery. Their large penumbrae may adversely affect the dose gradient around the target. In this study, we implement and evaluate an inner-shell planning method to increase the dose gradient and reduce dose to normal tissues. Ten patients previously treated with CyberKnife M6 system were randomly selected with the only criterion being that PTV be larger than 2 cm(3). A new plan was generated for each patient in which the PTV was split into two regions: a 5 mm inner shell and a core, and a 7.5 mm Iris collimator was exclusively applied to the shell, with other appropriate collimators applied to the core depending on its size. The optimization objective, functions, and constraints were the same as in the corresponding clinical plan. The results were analyzed for V12 Gy, V9 Gy, V5 Gy, and gradient index (GI). Volume reduction was found for the inner-shell method at all studied dose levels as compared to the clinical plans. The absolute dose-volume reduction ranged from 0.05 cm(3) to 18.5 cm(3) with a mean of 5.6 cm(3) for 12 Gy, from 0.2 cm(3) to 38.1 cm(3) with a mean of 9.8 cm(3) for 9 Gy, and from 1.5 cm(3) to 115.7 cm(3) with a mean of 24.8 cm(3) for 5 Gy, respectively. The GI reduction ranged from 3.2% to 23.6%, with a mean of 12.6%. Paired t-test for GI has a p-value of 0.0014. The range for treatment time increase is from -3 min to 20 min, with a mean of 7.0 min. We conclude that irradiating the PTV periphery exclusively with the 7.5 mm Iris collimator, rather than applying mixed collimators to the whole PTV, can substantially improve the dose gradient, while maintaining good coverage, conformity, and reasonable treatment time.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。