Improving efficiency in the radiation management of multiple brain metastases using a knowledge-based planning solution for single-isocentre volumetric modulated arc therapy (VMAT) technique

利用基于知识的单中心容积调强弧形治疗(VMAT)计划方案提高多发性脑转移瘤放射治疗的效率

阅读:1

Abstract

INTRODUCTION: This study aimed to develop a single-isocentre volumetric modulated arc therapy (si-VMAT) technique for multiple brain metastases using knowledge-based planning software, comparing it with a multiple-isocentre stereotactic radiosurgery (mi-SRS) planning approach. METHODS: Twenty-six si-VMAT plans were created and uploaded into RapidPlan(TM) (RP) to create a si-VMAT model. Ten patients, with 2 to 6 metastases (mets), were planned with a si-VMAT technique utilising RP, and a mi-SRS technique on Brainlab iPlan. Paddick Conformity Index (PCI) was used to compare conformity. The volumes of the brain receiving 15Gy, 12Gy, 10Gy, 7.5Gy and 3Gy were also compared. Retrospective treatment times from the last eight patients treated were averaged for pre-imaging and beam on time to calculate treatment times for both techniques. RESULTS: There was a significant difference in the PCI scores for the mi-SRS plans (M = 0.667, SD = 0.114) and si-VMAT plans (M = 0.728, SD = 0.088), with PCI values suggesting better prescription dose conformity with the si-VMAT technique (P = 0.014). Percentage of total brain volume receiving low-dose wash at four of the five different dose levels was significantly less (P < 0.05) with mi-SRS. Average time to treat a single met with current mi-SRS technique is 25.7 min, with each additional met requiring this same amount of time. The average time to treat 2-3 mets using si-VMAT would be 25.3 min and 4+ metastases 33.5 min. CONCLUSION: A knowledge-based si-VMAT approach was efficient in planning and treating multi metastases while achieving clinically acceptable dosimetry with respect to dose conformity and low-dose fall off.

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。