Commissioning and validation of RayStation treatment planning system for CyberKnife M6
JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS(2022)
摘要
Background RaySearch (AB, Stockholm) has released a module for CyberKnife (CK) planning within its RayStation (RS) treatment planning system (TPS). Purpose To create and validate beam models of fixed, Iris, and multileaf collimators (MLC) of the CK M6 for Monte Carlo (MC) and collapsed cone (CC) algorithms in the RS TPS. Methods Measurements needed for the creation of the beam models were performed in a water tank with a stereotactic PTW 60018 diode. Both CC and MC models were optimized in RS by minimizing the differences between the measured and computed profiles and percentage depth doses. The models were then validated by comparing dose from the plans created in RS with both single and multiple beams in different phantom conditions with the corresponding measured dose. Irregular field shapes and off-axis beams were also tested for the MLC. Validation measurements were performed using an A1SL ionization chamber, EBT3 Gafchromic films, and a PTW 1000 SRS detector. Finally, patient-specific QAs with gamma criteria of 3%/1 mm were performed for each model. Results The models were created in a straightforward manner with efficient tools available in RS. The differences between computed and measured doses were within +/- 1% for most of the configurations tested and reached a maximum of 3.2% for measurements at a depth of 19.5-cm. With respect to all collimators and algorithms, the maximum averaged dose difference was 0.8% when considering absolute dose measurements on the central axis. The patient-specific QAs led to a mean result of 98% of points fulfilling gamma criteria. Conclusions We created both CC and MC models for fixed, Iris, and MLC collimators in RS. The dose differences for all collimators and algorithms were within +/- 1%, except for depths larger than 9 cm. This allowed us to validate both models for clinical use.
更多查看译文
关键词
collapsed cone,commissioning,CyberKnife,Monte Carlo,treatment planning system,validation measurements
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要