%0 Dataset
%T IAGA Based Spot Scanning Path Optimization for Intensity Modulated Proton Therapy
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/74ed9652-733b-4efc-9a4e-72de71c4f90e
%W NCDC
%R 10.12072/ncdc.imp.db4139.2023
%A Xiao Guoqing
%K Point scan;proton intensity modulated radiotherapy;adaptive genetic algorithm;path optimization
%X In this paper, an adaptive genetic algorithm based scanning path optimization method for proton intensity modulated radiation therapy (IMRT) is studied and developed. The self-adaptive genetic algorithm (AGA) is used to develop the point scan proton intensity-modulated radiation path optimization module, which has strong fault tolerance and full space optimal search ability, and is integrated into the self-developed radiotherapy planning system. AAPM tg-119 head and neck tumor and prostate tumor simulation examples and two clinical cases are selected for testing, The scanning path length of proton radiotherapy plan before and after scanning path optimization was compared. For aapmtg-119 head and neck tumor and prostate tumor simulation cases, the total scanning path length was reduced by 27.17% and 18.72% respectively. The total scanning path length of clinical head and neck tumor and prostate tumor cases was reduced by 25.36% and 32.95% respectively. The reduction ratio of path length before and after optimization was related to zero weight scanning points and tumor anatomical structure. The scanning path optimization method based on adaptive genetic algorithm can reduce the scanning time of proton intensity modulated radiotherapy plan, thus shorten the treatment time of patients, which can be widely used in clinical technology of proton re scanning.