| Yan Hui,Li Yexiong,Dai Jianrong.Fast gradient descent based VMAT optimization algorithm[J].Chinese Journal of Radiological Medicine and Protection,2017,37(12):933-937 |
| Fast gradient descent based VMAT optimization algorithm |
| Received:April 24, 2017 |
| DOI：10.3760/cma.j.issn.0254-5098.2017.12.011 |
| KeyWords:Volumetric modulated arc therapy Intensity modulated radiation therapy Gradient descent Leaf sequencing |
| FundProject:国家重点研发计划项目（2016YFC0904600） |
| Author Name | Affiliation | E-mail | | Yan Hui | National Cancer Center, Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100021, China | | | Li Yexiong | National Cancer Center, Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100021, China | | | Dai Jianrong | National Cancer Center, Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100021, China | dai_jianrong@163.com |
|
| Hits: 2682 |
| Download times: 1577 |
| Abstract:: |
| Objective To explore a new gradient descent based optimization algorithm in order to improve the efficiency and unrepeatability of current VMAT planning systems. Methods Firstly, fast monotonic descent method was used to generate intensity maps of a simple IMRT plan consisting of few static fields. Then, leaf sequencing algorithm was employed to determine the best segments (aperture shape and weight) of these fields. The segments of the existing beams were fixed, and the new beams were continuously added to the plan and optimized until the maximal number of beams arrived. The performance of this algorithm was evaluated with clinical cases. Results For the head-and-neck case, the computation time was about 5 min while the time for those commercial planning systems was 10-20 min. Due to the nature of gradient-based algorithm, the repeatability of optimization result was guaranteed. The conformity and homogeneity of VMAT plan was better than that of IMRT plan. For most of critical organs, the dose sparing of VMAT plan was better than that of IMRT plan. Conclusions Compared to existing VMAT optimization algorithms, the computation time of our algorithm is significantly reduced and the optimization result is repeatable. |
| HTML View Full Text View/Add Comment Download reader |
| Close |
|
|
|
